![Big Data in Cloud Today: A
Comprehensive Survey
K. Umapathy, S. Omkumar, S. Chandramohan, D. Muthukumaran,
and Wasana Boonsong
1 Introduction
Big data refers to a great collection of data which cannot be stored or processed
by any means of data storage or processing units at traditional level. It is produced
at a larger scale and employed by various companies for processing and analyzing
in view of improving their business activities [1]. Moreover, it is also meant for
uncovering the insights relevant to those companies. Big data is a blend of organized
and unorganized data collected by various organizations, meant for mining and used
for applications such as predictive modeling, projects relevant of machine learning,
and data analytics. As a typical example, the application of amazon – “Elastic
Map Reduce” – illustrates how the power of cloud elastic computers is employed
for the processing of big data [2]. Cloud is a blend of servers with each server
having a unique function. It is not a physical entity, but a very wide network that
comprises remote servers all over the world. These servers are integrated together
in order to operate as a single entity. They are meant to store and manage data,
execute applications, and provide services such as video streaming, electronic e-
mail, and software for productivity. Data or information can be accessed anywhere
from online rather than retrieving from the local computing system. Hence, cloud
computing can be referred to as utility computing or on-demand computing [3].
K. Umapathy () · S. Omkumar · S. Chandramohan · D. Muthukumaran
Department of ECE, SCSVMV Deemed University, Kanchipuram, India
e-mail: chandramohan@kanchiuniv.ac.in
W. Boonsong
Department of EE, Rajamangala University of Technology, Songkhla, Thailand
e-mail: wasana.b@rmutsv.ac.th
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
R. Sharma et al. (eds.), Data Analytics for Internet of Things Infrastructure,
Internet of Things, https://doi.org/10.1007/978-3-031-33808-3_1
1](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-19-320.jpg)
![2 K. Umapathy et al.
Fig. 1 V’s of big data
2 Characteristics of Big Data
Data management architectures in various companies include systems to process
and manage big data integrated with relevant tools for analytics. Figure 1 shows the
various types of V’s connected with big data [4]. Big data is usually characterized
by the following three V’s:
• Large volume of data in many environments
• Wide variety of data types stored in big data systems
• Velocity at which data is produced, collected, and processed
The above three characteristics were resolved in the year 2001 by Doug Lancy,
an analyst who belonged to a consulting company – Meta Group Incorporation.
Recently, in addition to the existing V’s, other V’s were included to explain big data
[5].
Figure 2 shows the six V’s of big data. There is no specific volume to equate with
big data but applications generally involve terabytes, petabytes, and even exabytes
of data generated and collected with respect to time. Big data is a blend of organized
and unorganized data collected by various institutions and is subject to mining for
information [6].
• Organized data such as documents and transactions linked with finance
• Unorganized data such as text, records, and multimedia files
• Semi-structured data such as web logs and data streaming
Hence big data is voluminous and more complex sets of data especially from new
sources of data. The voluminous of data makes it very difficult for processing using
suitable traditional software. But big data can be employed to sort out problems in
business which would have been not possible in the past earlier [7]. Figure 3 shows
the five key characteristics of big data.](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-20-320.jpg)
![4 K. Umapathy et al.
• Data source: The source of data – media, machines, and/or human beings.
• Data consumers: The relevant consumers and applications integrated with pro-
cessed data
4 Importance of Big Data
Various organizations use big data to enhance typical operations, provide good
customer services, generate sales strategies, and implement other activities for
increasing profit. The business activities with and without application of big data
matter a lot for taking faster and better decisions in business [8]. Activities such as
sales, advertising, and production can be refined appropriately by the companies if
big data is handled properly. Hence, handling of big data gives a clear insight for the
customers by which customer engagement and rate of conversion can be enhanced
easily. In this context, both real time and traditional data can be subject to analysis.
Medical professionals also use employ big data for identifying health complications
and risk factors, making a diagnosis, and establishing the medical history of patients.
Moreover, the data available from various sources of media and internet will guide
them appropriately regarding infections of diseases and pandemic. The following
are some typical illustrations for employment of big data by certain organizations.
• Identification of the locations of potential drilling and operations of pipeline by
oil manufacturing companies
• Management of risks and real-time computation of data by financial companies
• Management of supply and demand chains with appropriated routes of delivery
by transportation and cargo companies
• Other applications or services such as prevention of crime, initiatives for smart
city, and fulfilment of any response on demand.
The following are the list of activities connected with business ranging from
consumer experience to statistical analytics:
• Development of products
• Maintenance of predictive services
• Experience of the customers
• Machine learning
• Efficiency in operations
• Innovative activities
Big data provides an opportunity for all business models, which includes the
following vital actions:
• Integrate
• Manage
• Analyze](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-22-320.jpg)
![Big Data in Cloud Today: A Comprehensive Survey 5
Fig. 4 Services of big data
Fig. 5 Examples of big data
5 Examples for Big Data
Figure 4 shows the services of big data – data sources, ingest, storage, processing,
and servicing. Big data comes from different forms of sources. The typical
illustrations are processing systems, databases of consumers, files, electronic mails,
medical histories, etc. [9]. It also comprises data generated from log files of server
and from sensors connected with manufacturing and industrial equipments and IoT
devices. Figure 5 shows the various examples for big data usage.
Apart from the availability of internal data from the concerned systems, the
environments of big data also include external information from consumers,
open markets, traffic conditions, weather conditions, information connected with
geographical locations, research, etc. The different forms of big data are images,
videos, audios, and various applications that represent streaming to data subject to
processing and collection on a regular arrangement [10].
6 Tools and Techniques
The big data applications include various tools and methodologies for processing
and analysis of the data. Table 1 shows few relevant tools and techniques [11].
Table 1 shows that Hadoop Map Reduce is a technique for distributed processing
framework, which is meant for preparing applications that handle huge volume of
data with hardware resources in an efficient way with minimum number of errors.
The task of Map Reduce work is to decompose the given information into small
pieces which are handled by it in parallel manner. The values resulting from these
mapping by the above framework are provided as inputs for the reduction of tasks.](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-23-320.jpg)
![6 K. Umapathy et al.
Table 1 Tools and techniques used for Big Data
Tools/techniques Description Developed by Written in
HDFS Reliable storage of data Google Java
Map reduce Framework for distributed processing Google Java
YARN Framework for resource management Apache Java
Spark Parallelism of data Berkeley Scala
Pig Framework for Pig Latin Yahoo Java
Fig. 6 Data processing
There is storage in the file system for preserving both the inputs and outputs.
Scheduling of tasks, tracking, and executing of unsuccessful tasks are managed by
the framework [12].
HDFS is another technique that covers all the nodes in the form of cluster for the
purpose of storing data. It integrates all file systems of the network connected with
local nodes to construct a larger system of file. This tool enhances the reliability
by duplicating the data across various relevant sources for overcoming failures in
nodes.
7 Big Data Analytics and Its Benefits
Big data analytics is one among the analytic techniques at advanced level for
diversifying great volume of big data in terms of sets, which involve both organized
and unorganized forms of data from various sources in different sizes ranging
from terabytes to zettabytes [13]. The following are the advantages of Big Data
Analytics:
• Speeder and comparatively better decision-making
• Economical and efficient in operation
• Enhanced driving of data with respect to market (Fig. 6)](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-24-320.jpg)
![Big Data in Cloud Today: A Comprehensive Survey 7
Fig. 7 Concept of cloud computing
8 Cloud Computing
A cloud can belong to either private or public party. A cloud in public provides
services to the concerned with the help of internet. A cloud in private is an owned
data center of a person, which provides hosted services to certain people with
specific settings of permissions. However, the objective of cloud computing is to
give easy means of access to specific resources of computing and services of IT [14,
21]. Figure 7 shows the concept of cloud computing.
9 Working of Cloud Computing
The concept of front end comprises client device usage, type of browsing software,
and applications connected with cloud software. The concept of back end comprises
databases and server computers that operate as repository for storage of data used
by the front end. A server at the center manages the communication between the
front and back ends of cloud computing. This server depends on certain protocols
to implement the data exchange [15, 22]. It employs both software and middleware
to establish connection between various devices and servers in the cloud. Figure 8
shows the features and characteristics of cloud.
Cloud computing mainly depends on the virtual concept and technologies of
automation. By the concept of virtualization, customers can access services of cloud](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-25-320.jpg)
![8 K. Umapathy et al.
Fig. 8 Cloud features and
characteristics
Fig. 9 Key features of a public cloud
and utilize them appropriately. The customers can access the relevant resources,
integrate services, and employ workloads without any sort of disturbance from the
IT staff of cloud provider [16, 23]. Figure 9 shows the key features of a public cloud.
The following are the characteristics and benefits of cloud computing.
• Reliability
• Flexibility
• Reduction of cost
• Global deployment in shorter time
• Payment based on usage
• Resilience in workload
• Provision of self services
• Broad Access in Network
• Pooling of available resources
• Management of cost toward essential services
• Mobility in data and job](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-26-320.jpg)
![10 K. Umapathy et al.
Fig. 11 Cloud service providers
The list of other companies who excel in cloud computing are as follows:
• Apple
• Citrix
• IBM
• Salesforce
• Alibaba
• Oracle
• VMware
• SAP
• Joyent
• Rackspace
Factors Influencing Companies to Become Cloud Computing Providers
• Money factor: Most of the large datacenters used to buy hardware, bandwidth
of network, and computing power for one-fifth of the cost provided to middle-
level datacenter [17]. Moreover, the money spent for the development of software
and deployment can be extended to any number of computers. Hence, there is a
possibility for a large company to make a huge profit with less investment spent
as such for that of a small company.
• Existing investment: If the services of a cloud computing are concatenated to the
existing network, then it will provide a stream of revenue system with less cost
and investments. The web techniques prepared by Amazon are well applicable
for the internal operations of Amazon.
• Defend a franchise: Since the server and applications at traditional level are able
to embrace the technique of cloud computing, vendors having interest in building
franchise will be encouraged to provide the choice of cloud. As a typical example,
Microsoft Azure gives a migrating way for the existing users to cope with a cloud
environment [18, 24].
• Attack an incumbent: If a company has sufficient resources and proper datacenter,
it may be able to build a path for deployment of cloud leading to automation with
respect to features in scalability and balancing of load.
• Customer relationships: The relationship with the customers can be build by
providing service in the name of branded cloud computing which leads to totally
free pathway for both the companies and the customers.](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-28-320.jpg)
![Big Data in Cloud Today: A Comprehensive Survey 11
Fig. 12 Big data in the cloud
• Become a platform: If the application like plug-in facility is introduced by a
company, then that company will become a good provider in cloud.
Typical Successful Example
The web service provided by Amazon known as Elastic Compute Cloud (EC2)
markets ISA “slices” at a frequency of 1 GHz for 10 cents per hour, and new
additions can be done within a time period of 2 minutes. Amazon’s Scalable Storage
Service (S3) costs about $0.12 to $0.15 per gigabyte per month to send data in and
out of AWS over the Internet [19, 25, 26]. If many instances are multiplexed with
a single box, then lot of profit can be earned without any interference among the
customers. Three factors are essential for an organization to become a provider in
cloud computing – minimum investments on data centre, software infrastructure,
and operational cost (Fig. 12).
Big Data and Cloud Computing Relationship
Both the techniques – big data and cloud computing – have their own unique
advantages. Many companies across the globe are planning to integrate these two
methodologies for earning huge profit in their business. Their objective is to improve
the income of the company, thereby reducing the cost of investment in parallel.
Cloud and big data help them in the management of software and decision-making,
respectively. Big data is concerned with collection, storage, and processing of huge
data either in organized or in unorganized manner. The five aspects of big data are
already described under Sect. 2 And are as follows:
• Volume – amount of data
• Variety – types of data
• Velocity – rate at which data flows
• Value – depends upon the content of data
• Veracity – confidentiality present in data](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-29-320.jpg)
![12 K. Umapathy et al.
Fig. 13 Corrleation between
big data and cloud computing
Figure 13 shows the correlation between big data and cloud computing. Cloud
computing provides services based on the concept of paying capacity of the
customers, which provides three types of services and are as follows.
• Infrastructure as a Service (IAAS)
This service provides the infrastructure on an entire basis in parallel with tasks
related with maintenance.
• Platform as a Service (PAAS)
This service provides a set of resources like storage of objects, execution time,
process of queuing, databases, etc. The consumer is totally responsible for the
configuration and implementation of connected tasks.
• Software as a Service (SAAS)
This service provides a list of essential settings against the platform and
infrastructure.
Figure 14 shows the architecture of big data, cloud computing, and data analytics.
Hence from the above explanation, it is seen that cloud can be thought of “As-a-
Service” indication by which challenges are abstracted by means of flexible services
[20, 27, 28]. Big data also satisfies the same requirement but the end customers
abstract the processing of huge data in a distributed manner. The following are the
various advantages of big data analysis with respect to cloud:
• Improved analysis: The analysis of big data has got better with the integration
of cloud. Hence most of the organizations show interest to analyze big data with
respect to cloud. Additionally, cloud helps to concatenate the data from various
types of sources.
• Simplified infrastructure: The analysis of big data is a good task on the part of
infrastructure since the data arrives in huge level with changing speed. Since the
infrastructure provided by the cloud is flexible, it is very easier to handle any sort
of workloads with appropriate scaling.
• Lowering the cost: These two techniques reduce weightage of ownership by
providing appropriate values to the companies. Cloud enables customers to
process big data without the need for larger resources. Hence these techniques
help the companies to reduce the cost factor for their objectives and add values
to them.](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-30-320.jpg)
![Cloud of Things Platform for a Water
Meter Network
Biswaranjan Bhola, Raghvendra Kumar, and Ahmed Alkhayyat
1 Introduction
With the steep rise in the population on Earth, there is an exponential decline in
the availability of essential commodities such as electricity, water, and food. For
the proper management and maintenance of essential things, different types of
devices have been designed. In order to maintain all the devices properly and gather
information and facts to generate knowledge so that the devices are interconnected
with each other is called the Internet of Things (IoT). The implementation of
systems such as traffic management on the roads, medical services, streetlight
systems, and educational systems should be managed in a systematic manner. Some
examples of contributions of the IoT system to the technical world are described in
the following. Home appliances are monitored by the IoT system to avoid the abuse
of electricity [1]. When people are absent from home, this technology can be used
to monitor and provide security to the home [2]. It can also be used for monitoring
and controlling the office [3]. In medical services, the IoT is used to provide patients
with a better service as well as to warn the management regarding fire and leakage of
different gases, which are harmful to patients [4]. Using the IoT, traffic systems and
street lights can be controlled efficiently in localized urban areas [5–7]. It can also
be applied for monitoring water distribution in a centralized manner in townships
[8]. In agriculture, the system is in use for providing video surveillance over the land
and for operating the machinery remotely [9].
B. Bhola · R. Kumar ()
Department of Computer Science and Engineering, GIET University, Kharling, Gunupur, Odisha,
India
e-mail: biswaranjan.bhola@giet.edu; raghvendra@giet.edu
A. Alkhayyat
College of Technical Engineering, The Islamic University, Najaf, Iraq
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
R. Sharma et al. (eds.), Data Analytics for Internet of Things Infrastructure,
Internet of Things, https://doi.org/10.1007/978-3-031-33808-3_2
17](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-35-320.jpg)
![18 B. Bhola et al.
Fig. 1 Traditional internet of things (IoT) architecture
To develop the IoT, different types of communication technologies are used,
such as the Global System for Mobile Communications (GSM), Bluetooth, Zigbee,
etc. [10]. Here, we analyze the architecture of the traditional IoT system. Figure 1
describes the architecture of the IoT system. In this system, the main components
of the IoT architecture are:
• IoT Hub
• Sensors
• Switch
• Smart Device
• Connectivity
IoT Hub
The IoT hub is an interface between the Internet and the Controlling and Monitoring
Components (CMCs). The user monitors the CMCs using the Internet and an IoT
hub. The IoT hub controls and monitors CMC components such as sensors and
switches. Moreover, it uses a separate network to communicate with sensors and
switches present within a CMC.
Sensors
Using sensors, the IoT hub detects the location of a particular place. For example, a
gas sensor is used to identify the leakage of gas.
Switch
Using a switch, the IoT hub switches the electrical and electronics components on
or off.](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-36-320.jpg)
![20 B. Bhola et al.
This article is further described in the following order. The next section discusses
the methodology of components, followed by the working structure, results, and
conclusion.
2 Related Work and Problem Motivation
This section focuses on the present success and challenges of the IoT. Moreover, we
discuss a few challenges of the existing IoT system and the problem motivation for
our research background.
2.1 Related Work
According to a survey, trillions of devices have converted to the IoT, which indicates
the popularity of the IoT. However, certain limitations exist in the traditional system.
In Yakoub et al. [11], the authors have stated that the increased requirement of
the IoT formed a complex network structure, which is caused by the creation of
various kinds of problems such as inter-operability, flexibility, scalability, energy
efficiency, and security. For example, owing to the increased population, motor
vehicles, and industries, the pollution of the cities is increasing day by day. To
monitor the pollution, Kaur et al. proposed an IoT architecture named green IoT
architecture [12]. To improve the efficiency of above-mentioned architecture needs
a distributed platform.
Chien et al. [13] proposed an IoT architecture in which the sensors and actuators
of devices are interconnected with each other using private networks and the
Internet. Each device uses its own network, which is heterogeneous in nature, and
every sensor also has a different technology. An improvised architecture is essential
for handling interoperability and heterogeneity in a seamless way. In [14], the
authors used a Software-Defined Network (SDN) to secure IoT devices. However,
it does not meet the other inherent challenges. Table 1 discusses a few important
forms of IoT architecture used in the literature. From the above literature survey,
we observed that the IoT hub is an essential part of the architecture, which may
lead to high maintenance cost, network, and architecture dependency. However,
in the proposed architecture, the smart switch and the smart sensor have been
introduced, which connect directly to the network. This architecture can pave the
way for various challenges faced by the current IoT system. The methodology
and experimentations are discussed in the following chapters. It is an integrational
physical, computational, and electronic environment. Liu et al. describe the same
concept in the form of a Cyber Physical System (CPS) [15]. An organization such as
the European Telecommunications Standards InstituteETSI explains it as an M2M](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-38-320.jpg)
![Cloud of Things Platform for a Water Meter Network 21
Table 1 Existing IoT architecture
References Year Short analysis
[17] 2008 A four-layer architecture for the IoT system. The lower layer consists of
an electronic controller to connect with the sensor and relay and
contains the control information. The second layer contains the
executable program. The third layer is the interface with higher-level
languages and the task- and actor-oriented level is present in the fourth
layer
[18] 2008 A prototype architecture defined by Tan et al. that in the physical
architecture of an embedded system in lower layer the outer
environment information is sensed by the sensor in the form of a
electrical signal and the control system converts it into the high-level
information that is required by the user or operational system
[19] 2015 To access the physical world through the IoT is dependent on the
control network connected with sensors and actuators
[14] 2016 The IoT devices can be secured using advanced IoT security
architecture, which supports Software-Defined Network (SDN)
architecture
[20] 2017 To make the IoT device comparable and light weight it should be
scalable. The proposed architecture solves the scalable problem created
in the IoT device
[21] 2017 IoT resources can be properly managed using multiagent distributed
architecture. But the shortcoming of this idea is that each agent is an
independent module. If there is any dependency this type of architecture
may not function properly
[12] 2018 To monitor the pollution, green IoT architecture has been proposed. To
improve the efficiency of this type of architecture, it should be
converted to a distributed platform, which can be solved using the
proposed architecture
[22] 2018 Much research work has been done on architecture and the protocol of
the IoT, but some problems remain
[13] 2019 Each IoT device uses its own network and Internet technology, which is
heterogeneous is nature. Every sensor also uses different technology
[23] 2020 The shortcoming of this work is that it communicates with the user
using a GSM module through SMS communication. Hence, the user
only knows the device information by using SMS, and there is a
maximum than can be communicated with the 24 sensors, because the
controller has only 24 I/O ports
[24] 2020 A revised architecture is presented to add scalability and dynamism
through the application layer
communication system [16]. Hence, in such a type of ambiguous scenario the real
fact that is discussed by most technical reports is that physical objects around the
world try to communicate with others using a common virtual platform to improve
the performance and take decisions on a real-time basis or for the future called the
IoT platform.](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-39-320.jpg)
![22 B. Bhola et al.
Fig. 2 Functional unit of the IoT
2.2 IoT Paradigm
The survey by Tran-Dang et al. [25] defines the services of the IoT into four
categories:
1. Things Oriented (physical and virtual entities are the focus)
2. Internet Oriented (development of an IP-based network that enables the things)
3. Semantic Oriented (handles a huge amount of data in communication)
4. Service Oriented (developing the IoT intelligent service and application based on
the above three perspectives)
and all the services are processed using four functional units explained in the Fig. 2.
In the above, all the pi-nodes are the end-to-end and intermediate components
such as the control unit, edge server, cloud server, client smart devices, etc. pi-
containers are the data packets, which are transmitted and the pi-movers are the
technology that describes how pi-containers are transmitted from one pi-node to
another pi-node. pi-protocols explain which protocols (http, tcp/ip, oli, etc.) are
used for communication. One computing platform has been designed by Kondo
et al. for dynamic module (pi-nodes) configuration for the IoT [26]. Ranganathan
et al. explain the data communication in the IoT and an SDN switch, which can
reduce the distributed denial of service attack. Using the proposed architecture and
implemented module the above-mentioned things can be achieved and some of the
problems defined below can be minimized.
2.3 Problem Motivation
In the present IoT system, to communicate between end users and sensors or
switches to dissimilar networks (e.g., the Internet, an IoT hub network) two basic
intermediate heterogeneous application layers are used. One is an Internet web](https://image.slidesharecdn.com/26203783-250606011742-8b6d5c72/85/Data-Analytics-For-Internet-Of-Things-Infrastructure-Rohit-Sharma-40-320.jpg)
Data Analytics For Internet Of Things Infrastructure Rohit Sharma
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- 5. Internet ofThings Rohit Sharma Gwanggil Jeon Yan Zhang Editors Data Analytics for Internet ofThings Infrastructure
- 6. Internet of Things Technology, Communications and Computing Series Editors Giancarlo Fortino, Rende (CS), Italy Antonio Liotta, Edinburgh Napier University, School of Computing, Edinburgh, UK
- 7. The series Internet of Things - Technologies, Communications and Computing publishes new developments and advances in the various areas of the different facets of the Internet of Things. The intent is to cover technology (smart devices, wireless sensors, systems), communications (networks and protocols) and computing (the- ory, middleware and applications) of the Internet of Things, as embedded in the fields of engineering, computer science, life sciences, as well as the methodologies behind them. The series contains monographs, lecture notes and edited volumes in the Internet of Things research and development area, spanning the areas of wireless sensor networks, autonomic networking, network protocol, agent-based computing, artificial intelligence, self organizing systems, multi-sensor data fusion, smart objects, and hybrid intelligent systems. Indexing: Internet of Things is covered by Scopus and Ei-Compendex **
- 8. Rohit Sharma • Gwanggil Jeon • Yan Zhang Editors Data Analytics for Internet of Things Infrastructure
- 9. Editors Rohit Sharma SRM Institute of Science and Technology, Delhi NCR Campus Ghaziabad, Uttar Pradesh, India Yan Zhang Xi’an Shiyou University Xi’An, China Gwanggil Jeon Incheon National University Incheon, Korea (Republic of) ISSN 2199-1073 ISSN 2199-1081 (electronic) Internet of Things ISBN 978-3-031-33807-6 ISBN 978-3-031-33808-3 (eBook) https://doi.org/10.1007/978-3-031-33808-3 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.
- 10. Preface The edited book aims to bring together leading academic scientists, researchers, and scholars to exchange and share their experiences and results on all aspects of IoT and big data analytics. It also provides a premier interdisciplinary platform for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, and concerns as well as practical challenges encountered and solutions adopted in IoT and data analytics. Ghaziabad, Uttar Pradesh, India Rohit Sharma Incheon, Korea (Republic of) Gwanggil Jeon Xi’An, China Yan Zhang v
- 11. Organization of the Book The book is organized into 17 chapters. A brief description of each of the chapters is as follows: Chapter “Big Data in Cloud Today: A Comprehensive Survey” enunciates big data’s importance, characteristics, and classification with relevant examples. It also presents the tools and techniques used for processing of big data. In addition, the concept, working, characteristics, and key features of cloud computing are discussed. Ultimately, this chapter correlates the technologies – big data and cloud computing – in the today’s scenario with a case study. Chapter “Cloud of Things Platform for a Water Meter Network” analyzes and modifies the IoT architecture for designing an autonomous and distributed IoT module. The module enabled M2M (machine-to-machine) communication to reduce the problem and add scalability to IoT devices. The designed module can be built on IoT devices to directly connect with the network through Ethernet or Wi-Fi and provide an interface to the user (cloud server, person, device) to communicate with each other. Chapter “Online Newspaper Development within the Internet of Things Environ- ment: The Role of Computer-Mediated Communication” includes a social approach to developing online newspapers within IOT environment and discusses how CMC plays a significant role in online journalism. CMC in journalism also enables the readers to put their thoughts and views in comments under the provided section of online newspapers. Communication within IOT environmental online newspapers has three inherent characteristics. Chapter “FATS (Fuzzy Authentication to Provide Trust-Based Security) in VANET to Mitigate Black Hole Attack”, In this chapter, Fuzzy Authentication is used to provide trust-based Security to find a Black Hole node and block the node from communication. FATS system uses Trust factor as the significant parameter to estimate a genuine node from a malicious node. The simulation is carried out in MATLAB for parameter estimation and implemented using Network Simulator 2.28 software. Chapter “AI-Based Chatbot Agents as Drivers of Purchase Intentions: An Interdisciplinary Study” aims to determine the impact of chatbots on customers’ vii
- 12. viii Organization of the Book purchase intentions. An empirical study was carried out on the impact of chat- bot agent’s informational support, emotional credibility, and trust on purchasing intentions. The data was collected through an online survey from 223 Delhi-NCR customers who use chatbots while making online purchases. PLS-SEM was used to analyze the data that was collected. The results of structural equation modelling (SEM) showed a significant impact of informational support, emotional credibility, and trust of chatbots on purchase intentions of customers. Chapter “An Intelligent Model for Identifying Fluctuations in the Stock Market and Predicting Investment Policies with Guaranteed Returns” analyzes the current and market tendencies’ shortcomings and constructs a time-series version for mitigating most of them by imposing more efficient algorithms. An expert machine is proposed to predict the marketplace risk’s uncertainty and the assured return amount. Fuzzy Inference is deployed to deal with the uncertainty and make a prediction for the same. Chapter “Sandwiched Metasurface Antenna for Small Spacecrafts in IoT Infras- tructure” the main targets of this study is the use of an optimized sandwiched metasurface for increasing return loss and peak gain of the proposed antenna at the X-band. Moreover, the sandwiched metasurface is used for minimizing levels of generated back lobes and so interferences with electronic components inside the spacecraft box. Chapter “Development of Laser-Beam Cutting-Edge Technology and IOT-Based Race Car Lapse Time Computational System” proposes a system that uses a laser beam transmitter and receiver to detect laps crossing. The ATMEGA 328 controller continuously triggers the laser transceiver. This system provides the solution for the time delay in lapse calculation for racing. The detection of the vehicle is based on beam cutting. Chapter “A Study of Cloud-Based Solution for Data Analytics” studies the provisioning and usage of the cloud-based architecture of AWS and GCP for building a data analytics platform. With the introduction of big data technologies, cloud computing, and different types of data analytics technique, it now became easier to combine real world data and data generated from scientific experiments to extract meaningful insights and use them in real-world scenarios. Chapter “An Intelligent Model for Optimizing Sparsity Problem Toward Movie Recommendation Paradigm Using Machine Learning” proposes a system that uses a laser beam transmitter and receiver to detect laps crossing. The ATMEGA 328 controller continuously triggers the laser transceiver. This system provides the solution for time delay in lapse calculation for racing. The detection of the vehicle is based on beam cutting. Chapter “Techniques to Identify Image Objects Under Adverse Environmental Conditions: A Systematic Literature Review” references all the research articles published between 2011 and 2022 in various IEEE Xplore, ScienceDirect confer- ences, and journals for the systematic review on identifying different objects from images and videos taken in adverse environmental conditions. We used different tags and keywords to search papers about the topic under study.
- 13. Organization of the Book ix Chapter “Technology-Enhanced Teaching and Learning During the COVID- 19 Pandemic Using IoT Infrastructure” reviews learning during the COVID-19 pandemic-related studies and perspectives on technology-assisted language teaching and learning to make recommendations for administrators, teachers, and learners. It first reviews current perspectives on technology-assisted teaching and learning. Then, it critically examines second language acquisition theories aligning with computer-mediated communication. Chapter “The Symbiotic Relation of IoT and AI for Applications in Various Domains: Trends and Future Directions” aims to showcase the current trend of IoT with artificial intelligence and future directions. Many domains have been analyzed and showcased in the tabular format where the methodology advantages and future scope with respect with AI-assisted IoT technologies are identified. Chapter “Text Summarization for Big Data Analytics: A Comprehensive Review of GPT 2 and BERT Approaches” looks at extensive data methodologies and methods such as Bidirectional Encoder Representations (BERT) and Generative Pre-trained Transformer 2 (GPT 2) transformers for multi-document summarization. In transformers, the BERT and GPT 2 models in-text summarization give very close results in terms of accuracy, and they need to be compared to give a model that performs better. Chapter “Leveraging Secured E-Voting Using Decentralized Blockchain Tech- nology” provides detailed information on the blockchain concept, features, and types. The chapter also discusses a few major consensus algorithms frequently utilized in different blockchain networks. Further, the major challenges faced by existing voting methodologies are addressed and the chapter explains how integrating the e-voting systems with blockchain technology can help overcome most of these challenges. Chapter “Multilayer Security and Privacy Provision in Internet of Things Net- works: Challenges and Future Trends” demonstrates security challenges and coun- termeasures. Moreover, the chapter also gives the existing security models and solutions. The chapter concludes with future trends in IoT. Chapter “A Methodology for the Development of Soft Sensors with Kafka-ML” presents a methodology to support soft sensor development based on Kafka-ML, an open-source framework to manage ML pipelines. Kafka-ML will allow researchers to develop, train, and validate ML models, and visualize real-time predictions using streaming data. Key Features • This book will help generate interest in new trends in low-voltage circuit design for IoT applications. • This book addresses the challenges in designing low power architectures for IoT applications.
- 14. x Organization of the Book • This book provides a comparative analysis of different techniques used for designing low power architectures. • This book contains an analysis of different low power architectures. • This book provides a practical understanding of the uses of semantic technology in designing, so the readers can improve their strengths in making better decisions.
- 15. About the Book This book focuses on the use of the Internet of Things (IoT) and big data in business intelligence, data management, Hadoop, machine learning, cloud, smart cities, etc. IoT and big data emerged from the early 2000’s data boom, driven forward by many of the early Internet and technology companies. The Internet of Things (IoT) is an interconnection of several devices, networks, technologies, and human resources to achieve a common goal. A variety of IoT-based applications being used in different sectors have succeeded in providing huge benefits to users. The generation of big data by IoT has ruptured the existing data processing capacity of IoT and recommends adopting data analytics to strengthen solutions. The success of IoT depends upon the influential association of big data analytics. New technologies like search engines, mobile devices, and industrial machines provided as much data as companies could handle—and the scale continues to grow. In a study by IDC, the Market Intelligence firm estimated that global data production would grow 10x between 2015 and 2020. So, the proposed book will cover all the aspects discussed in the field above. xi
- 16. Contents Big Data in Cloud Today: A Comprehensive Survey......................... 1 K. Umapathy, S. Omkumar, S. Chandramohan, D. Muthukumaran, and Wasana Boonsong Cloud of Things Platform for a Water Meter Network ...................... 17 Biswaranjan Bhola, Raghvendra Kumar, and Ahmed Alkhayyat Online Newspaper Development within the Internet of Things Environment: The Role of Computer-Mediated Communication .......... 39 Pham Chien Thang and Ta Thi Nguyet Trang FATS (Fuzzy Authentication to Provide Trust-Based Security) in VANET to Mitigate Black Hole Attack ..................................... 55 M. Gayathri and C. Gomathy AI-Based Chatbot Agents as Drivers of Purchase Intentions: An Interdisciplinary Study .......................................................... 77 Priyanka Tyagi and Ajay Jain An Intelligent Model for Identifying Fluctuations in the Stock Market and Predicting Investment Policies with Guaranteed Returns .... 91 Manash Sarkar, M. N. Pratima, R. Darshan, Debkanta Chakraborty, and Maroi Agrebi Sandwiched Metasurface Antenna for Small Spacecrafts in IoT Infrastructure .................................................................... 117 Boutaina Benhmimou, Niamat Hussain, Nancy Gupta, Rachid Ahl Laamara, Sandeep Kumar Arora, Josep M. Guerrero, and Mohamed El Bakkali Development of Laser-Beam Cutting-Edge Technology and IOT-Based Race Car Lapse Time Computational System.............. 129 B. Thiyaneswaran, E. Ganasri, A. H. Hariharasudan, S. Kumarganesh, K. Martin Sagayam, and Ahmed Alkhayyat xiii
- 17. xiv Contents A Study of Cloud-Based Solution for Data Analytics ........................ 145 Urvashi Gupta and Rohit Sharma An Intelligent Model for Optimizing Sparsity Problem Toward Movie Recommendation Paradigm Using Machine Learning .............. 163 Manash Sarkar, Shiwangi Singh, V. L. Soundarya, Maroi Agrebi, and Ahmed Alkhayyat Techniques to Identify Image Objects Under Adverse Environmental Conditions: A Systematic Literature Review ............... 187 Navjot Kaur, Kalpana Sharma, and Anuj Jain Technology-Enhanced Teaching and Learning During the COVID-19 Pandemic ........................................................ 203 Hung Phu Bui, Tra Thu Dao, Thuy Thanh Dao, and Van Huong Vi The Symbiotic Relation of IoT and AI for Applications in Various Domains: Trends and Future Directions ...................................... 219 Aman Jolly, Vikas Pandey, Praveen Kumar Malik, and Turki Alsuwian Text Summarization for Big Data Analytics: A Comprehensive Review of GPT 2 and BERT Approaches ..................................... 247 G. Bharathi Mohan, R. Prasanna Kumar, Srinivasan Parathasarathy, S. Aravind, K. B. Hanish, and G. Pavithria Leveraging Secured E-Voting Using Decentralized Blockchain Technology ........................................................................ 265 Anushka Chaubey, Anubhav Kumar, Vikalp Pandey, Bharat Bhushan, and Priyambada Purohit Multilayer Security and Privacy Provision in Internet of Things Networks: Challenges and Future Trends..................................... 291 Kashif Naseer Qureshi, Thomas Newe, Rosheen Qazi, and Gwanggil Jeon A Methodology for the Development of Soft Sensors with Kafka-ML ..... 307 Antonio Jesús Chaves, Cristian Martín, Luis Llopis Torres, Enrique Soler, and Manuel Díaz Index............................................................................... 325
- 18. About the Editors Rohit Sharma is currently an Associate Professor in the Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi NCR Campus Ghaziabad, India. He is an active member of ISTE, IEEE, ICS, IAENG, and IACSIT. He is an editorial board member and reviewer of more than 22 international journals and conferences, including the topmost journal IEEE Access and IEEE Internet of Things Journal. He serves as a book editor for 24 different titles. Gwanggil Jeon received the B.S., M.S., and Ph.D. (summa cum laude) degrees from the Department of Electronics and Computer Engineering, Hanyang Uni- versity, Seoul, Korea, in 2003, 2005, and 2008, respectively. He was with the Department of Electronics and Computer Engineering, Hanyang University, from 2008 to 2009. He was with the School of Information Technology and Engineering, University of Ottawa, Ottawa, ON, Canada, as a Post-Doctoral Fellow, from 2009 to 2011. He was with the Graduate School of Science and Technology, Niigata University, Niigata, Japan, as an Assistant Professor, from 2011 to 2012. He is currently an Assistant Professor with the Department of Embedded Systems Engineering, Incheon National University, Incheon, Korea. His current research interests include image processing, particularly image compression, motion estima- tion, demosaicking, and image enhancement, and computational intelligence, such as fuzzy and rough sets theories. Dr. Jeon was a recipient of the IEEE Chester Sall Award in 2007 and the ETRI Journal Paper Award in 2008. Yan Zhang received the Ph.D. degree from the School of Physics and Opto- electronic Engineering, Xi’dian University, China. The main research directions are optical communication, quantum communication, nonlinear optics, and device reliability. xv
- 19. Big Data in Cloud Today: A Comprehensive Survey K. Umapathy, S. Omkumar, S. Chandramohan, D. Muthukumaran, and Wasana Boonsong 1 Introduction Big data refers to a great collection of data which cannot be stored or processed by any means of data storage or processing units at traditional level. It is produced at a larger scale and employed by various companies for processing and analyzing in view of improving their business activities [1]. Moreover, it is also meant for uncovering the insights relevant to those companies. Big data is a blend of organized and unorganized data collected by various organizations, meant for mining and used for applications such as predictive modeling, projects relevant of machine learning, and data analytics. As a typical example, the application of amazon – “Elastic Map Reduce” – illustrates how the power of cloud elastic computers is employed for the processing of big data [2]. Cloud is a blend of servers with each server having a unique function. It is not a physical entity, but a very wide network that comprises remote servers all over the world. These servers are integrated together in order to operate as a single entity. They are meant to store and manage data, execute applications, and provide services such as video streaming, electronic e- mail, and software for productivity. Data or information can be accessed anywhere from online rather than retrieving from the local computing system. Hence, cloud computing can be referred to as utility computing or on-demand computing [3]. K. Umapathy () · S. Omkumar · S. Chandramohan · D. Muthukumaran Department of ECE, SCSVMV Deemed University, Kanchipuram, India e-mail: chandramohan@kanchiuniv.ac.in W. Boonsong Department of EE, Rajamangala University of Technology, Songkhla, Thailand e-mail: wasana.b@rmutsv.ac.th © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 R. Sharma et al. (eds.), Data Analytics for Internet of Things Infrastructure, Internet of Things, https://doi.org/10.1007/978-3-031-33808-3_1 1
- 20. 2 K. Umapathy et al. Fig. 1 V’s of big data 2 Characteristics of Big Data Data management architectures in various companies include systems to process and manage big data integrated with relevant tools for analytics. Figure 1 shows the various types of V’s connected with big data [4]. Big data is usually characterized by the following three V’s: • Large volume of data in many environments • Wide variety of data types stored in big data systems • Velocity at which data is produced, collected, and processed The above three characteristics were resolved in the year 2001 by Doug Lancy, an analyst who belonged to a consulting company – Meta Group Incorporation. Recently, in addition to the existing V’s, other V’s were included to explain big data [5]. Figure 2 shows the six V’s of big data. There is no specific volume to equate with big data but applications generally involve terabytes, petabytes, and even exabytes of data generated and collected with respect to time. Big data is a blend of organized and unorganized data collected by various institutions and is subject to mining for information [6]. • Organized data such as documents and transactions linked with finance • Unorganized data such as text, records, and multimedia files • Semi-structured data such as web logs and data streaming Hence big data is voluminous and more complex sets of data especially from new sources of data. The voluminous of data makes it very difficult for processing using suitable traditional software. But big data can be employed to sort out problems in business which would have been not possible in the past earlier [7]. Figure 3 shows the five key characteristics of big data.
- 21. Big Data in Cloud Today: A Comprehensive Survey 3 Fig. 2 Six V’s of big data Fig. 3 Five characteristics of big data 3 Classification of Big Data Big data is classified into the following types: • Analysis type: The type in which data is analyzed either in real time or processed in batch. Typical examples for real time and batch process are fraud detection in banking and strategic decisions in business, respectively. • Processing methodology: The business requirements have to decide the method- ology for processing of data – either predictive or ad-hoc in nature. • Data frequency: Indicates the frequency of data being ingested and arrived. The nature of data shall be either continuous or time dependent. • Data type: Indicates the stream of data – transactions, history, or real time. • Data format: The type of format used for data –structured, unstructured, or semi- structured. The format type decides the type of data for storage and processing.
- 22. 4 K. Umapathy et al. • Data source: The source of data – media, machines, and/or human beings. • Data consumers: The relevant consumers and applications integrated with pro- cessed data 4 Importance of Big Data Various organizations use big data to enhance typical operations, provide good customer services, generate sales strategies, and implement other activities for increasing profit. The business activities with and without application of big data matter a lot for taking faster and better decisions in business [8]. Activities such as sales, advertising, and production can be refined appropriately by the companies if big data is handled properly. Hence, handling of big data gives a clear insight for the customers by which customer engagement and rate of conversion can be enhanced easily. In this context, both real time and traditional data can be subject to analysis. Medical professionals also use employ big data for identifying health complications and risk factors, making a diagnosis, and establishing the medical history of patients. Moreover, the data available from various sources of media and internet will guide them appropriately regarding infections of diseases and pandemic. The following are some typical illustrations for employment of big data by certain organizations. • Identification of the locations of potential drilling and operations of pipeline by oil manufacturing companies • Management of risks and real-time computation of data by financial companies • Management of supply and demand chains with appropriated routes of delivery by transportation and cargo companies • Other applications or services such as prevention of crime, initiatives for smart city, and fulfilment of any response on demand. The following are the list of activities connected with business ranging from consumer experience to statistical analytics: • Development of products • Maintenance of predictive services • Experience of the customers • Machine learning • Efficiency in operations • Innovative activities Big data provides an opportunity for all business models, which includes the following vital actions: • Integrate • Manage • Analyze
- 23. Big Data in Cloud Today: A Comprehensive Survey 5 Fig. 4 Services of big data Fig. 5 Examples of big data 5 Examples for Big Data Figure 4 shows the services of big data – data sources, ingest, storage, processing, and servicing. Big data comes from different forms of sources. The typical illustrations are processing systems, databases of consumers, files, electronic mails, medical histories, etc. [9]. It also comprises data generated from log files of server and from sensors connected with manufacturing and industrial equipments and IoT devices. Figure 5 shows the various examples for big data usage. Apart from the availability of internal data from the concerned systems, the environments of big data also include external information from consumers, open markets, traffic conditions, weather conditions, information connected with geographical locations, research, etc. The different forms of big data are images, videos, audios, and various applications that represent streaming to data subject to processing and collection on a regular arrangement [10]. 6 Tools and Techniques The big data applications include various tools and methodologies for processing and analysis of the data. Table 1 shows few relevant tools and techniques [11]. Table 1 shows that Hadoop Map Reduce is a technique for distributed processing framework, which is meant for preparing applications that handle huge volume of data with hardware resources in an efficient way with minimum number of errors. The task of Map Reduce work is to decompose the given information into small pieces which are handled by it in parallel manner. The values resulting from these mapping by the above framework are provided as inputs for the reduction of tasks.
- 24. 6 K. Umapathy et al. Table 1 Tools and techniques used for Big Data Tools/techniques Description Developed by Written in HDFS Reliable storage of data Google Java Map reduce Framework for distributed processing Google Java YARN Framework for resource management Apache Java Spark Parallelism of data Berkeley Scala Pig Framework for Pig Latin Yahoo Java Fig. 6 Data processing There is storage in the file system for preserving both the inputs and outputs. Scheduling of tasks, tracking, and executing of unsuccessful tasks are managed by the framework [12]. HDFS is another technique that covers all the nodes in the form of cluster for the purpose of storing data. It integrates all file systems of the network connected with local nodes to construct a larger system of file. This tool enhances the reliability by duplicating the data across various relevant sources for overcoming failures in nodes. 7 Big Data Analytics and Its Benefits Big data analytics is one among the analytic techniques at advanced level for diversifying great volume of big data in terms of sets, which involve both organized and unorganized forms of data from various sources in different sizes ranging from terabytes to zettabytes [13]. The following are the advantages of Big Data Analytics: • Speeder and comparatively better decision-making • Economical and efficient in operation • Enhanced driving of data with respect to market (Fig. 6)
- 25. Big Data in Cloud Today: A Comprehensive Survey 7 Fig. 7 Concept of cloud computing 8 Cloud Computing A cloud can belong to either private or public party. A cloud in public provides services to the concerned with the help of internet. A cloud in private is an owned data center of a person, which provides hosted services to certain people with specific settings of permissions. However, the objective of cloud computing is to give easy means of access to specific resources of computing and services of IT [14, 21]. Figure 7 shows the concept of cloud computing. 9 Working of Cloud Computing The concept of front end comprises client device usage, type of browsing software, and applications connected with cloud software. The concept of back end comprises databases and server computers that operate as repository for storage of data used by the front end. A server at the center manages the communication between the front and back ends of cloud computing. This server depends on certain protocols to implement the data exchange [15, 22]. It employs both software and middleware to establish connection between various devices and servers in the cloud. Figure 8 shows the features and characteristics of cloud. Cloud computing mainly depends on the virtual concept and technologies of automation. By the concept of virtualization, customers can access services of cloud
- 26. 8 K. Umapathy et al. Fig. 8 Cloud features and characteristics Fig. 9 Key features of a public cloud and utilize them appropriately. The customers can access the relevant resources, integrate services, and employ workloads without any sort of disturbance from the IT staff of cloud provider [16, 23]. Figure 9 shows the key features of a public cloud. The following are the characteristics and benefits of cloud computing. • Reliability • Flexibility • Reduction of cost • Global deployment in shorter time • Payment based on usage • Resilience in workload • Provision of self services • Broad Access in Network • Pooling of available resources • Management of cost toward essential services • Mobility in data and job
- 27. Big Data in Cloud Today: A Comprehensive Survey 9 Fig. 10 Service categories of cloud computing Disadvantages of Cloud Computing The following are the demerits of cloud computing: • No Security in the cloud • Unpredictability in cost factor • No expertise in specific domain • Mismatch of governance in IT • Non-compliance with laws in the industry • Cloud management is hard to implement as every cloud is unique • No optimum performance in cloud • Hard to construct a private cloud • Migration in cloud Cloud Computing Versus Traditional Web Hosting The characteristics of a cloud are totally different from that of traditional web hosting for the following reasons: 1. Huge volume of power computing can be accessed by the consumers on the basis of demand. Hence, it is sold at that particular minute or hour of demand. 2. It is totally flexible – service is provided to the users as much as they want with respect to capacity and time interval. 3. Management of all services will be done by the provider completely except for a computing system and internet connectivity. The interest in cloud computing increased due to better innovations in computing and virtualization. Cloud Service Providers Figure 10 shows the service categories of cloud computing. There is no shortage of providers in the market of cloud computing. Figure 11 shows the major service providers in this field. Following are the companies who are experts the industry: • Amazon Web Services (AWS) • Google Cloud Projects (GCP) • Microsoft Azure
- 28. 10 K. Umapathy et al. Fig. 11 Cloud service providers The list of other companies who excel in cloud computing are as follows: • Apple • Citrix • IBM • Salesforce • Alibaba • Oracle • VMware • SAP • Joyent • Rackspace Factors Influencing Companies to Become Cloud Computing Providers • Money factor: Most of the large datacenters used to buy hardware, bandwidth of network, and computing power for one-fifth of the cost provided to middle- level datacenter [17]. Moreover, the money spent for the development of software and deployment can be extended to any number of computers. Hence, there is a possibility for a large company to make a huge profit with less investment spent as such for that of a small company. • Existing investment: If the services of a cloud computing are concatenated to the existing network, then it will provide a stream of revenue system with less cost and investments. The web techniques prepared by Amazon are well applicable for the internal operations of Amazon. • Defend a franchise: Since the server and applications at traditional level are able to embrace the technique of cloud computing, vendors having interest in building franchise will be encouraged to provide the choice of cloud. As a typical example, Microsoft Azure gives a migrating way for the existing users to cope with a cloud environment [18, 24]. • Attack an incumbent: If a company has sufficient resources and proper datacenter, it may be able to build a path for deployment of cloud leading to automation with respect to features in scalability and balancing of load. • Customer relationships: The relationship with the customers can be build by providing service in the name of branded cloud computing which leads to totally free pathway for both the companies and the customers.
- 29. Big Data in Cloud Today: A Comprehensive Survey 11 Fig. 12 Big data in the cloud • Become a platform: If the application like plug-in facility is introduced by a company, then that company will become a good provider in cloud. Typical Successful Example The web service provided by Amazon known as Elastic Compute Cloud (EC2) markets ISA “slices” at a frequency of 1 GHz for 10 cents per hour, and new additions can be done within a time period of 2 minutes. Amazon’s Scalable Storage Service (S3) costs about $0.12 to $0.15 per gigabyte per month to send data in and out of AWS over the Internet [19, 25, 26]. If many instances are multiplexed with a single box, then lot of profit can be earned without any interference among the customers. Three factors are essential for an organization to become a provider in cloud computing – minimum investments on data centre, software infrastructure, and operational cost (Fig. 12). Big Data and Cloud Computing Relationship Both the techniques – big data and cloud computing – have their own unique advantages. Many companies across the globe are planning to integrate these two methodologies for earning huge profit in their business. Their objective is to improve the income of the company, thereby reducing the cost of investment in parallel. Cloud and big data help them in the management of software and decision-making, respectively. Big data is concerned with collection, storage, and processing of huge data either in organized or in unorganized manner. The five aspects of big data are already described under Sect. 2 And are as follows: • Volume – amount of data • Variety – types of data • Velocity – rate at which data flows • Value – depends upon the content of data • Veracity – confidentiality present in data
- 30. 12 K. Umapathy et al. Fig. 13 Corrleation between big data and cloud computing Figure 13 shows the correlation between big data and cloud computing. Cloud computing provides services based on the concept of paying capacity of the customers, which provides three types of services and are as follows. • Infrastructure as a Service (IAAS) This service provides the infrastructure on an entire basis in parallel with tasks related with maintenance. • Platform as a Service (PAAS) This service provides a set of resources like storage of objects, execution time, process of queuing, databases, etc. The consumer is totally responsible for the configuration and implementation of connected tasks. • Software as a Service (SAAS) This service provides a list of essential settings against the platform and infrastructure. Figure 14 shows the architecture of big data, cloud computing, and data analytics. Hence from the above explanation, it is seen that cloud can be thought of “As-a- Service” indication by which challenges are abstracted by means of flexible services [20, 27, 28]. Big data also satisfies the same requirement but the end customers abstract the processing of huge data in a distributed manner. The following are the various advantages of big data analysis with respect to cloud: • Improved analysis: The analysis of big data has got better with the integration of cloud. Hence most of the organizations show interest to analyze big data with respect to cloud. Additionally, cloud helps to concatenate the data from various types of sources. • Simplified infrastructure: The analysis of big data is a good task on the part of infrastructure since the data arrives in huge level with changing speed. Since the infrastructure provided by the cloud is flexible, it is very easier to handle any sort of workloads with appropriate scaling. • Lowering the cost: These two techniques reduce weightage of ownership by providing appropriate values to the companies. Cloud enables customers to process big data without the need for larger resources. Hence these techniques help the companies to reduce the cost factor for their objectives and add values to them.
- 31. Big Data in Cloud Today: A Comprehensive Survey 13 Fig. 14 Architecture of big data, cloud computing, and data analytics • Security and privacy: The security of data is a major concern while connecting with data of an enterprise. The security will become a bothering factor if any application is executed in the platform of cloud because of its open access. Solutions of big data like hadoop employ services of a third party and its relevant infrastructure. These days, solutions for private cloud are available with flexibility and extendibility. In addition, processing of data is done in a distributed and scalable manner. Generally, there will be a common location called cloud storage server used to store and process the data of cloud. The service agreement has to be signed by the service provider then after identifying the cloud server for gaining the confidence. If it is needed, the level of security will also be leveraged by the service provider. Following are the rules connected with the agreement of service for data protection: • Big data protection from threats • Maintenance of storage and data The following issues are covered by the factor of security in big data with the aid of cloud computing: • Data • Capacity • Scalability • Security • Privacy • Storage and growth of data
- 32. 14 K. Umapathy et al. Fig. 15 Logo of redBus The analytics in big data is employed to identify and avoid online threats and hackers. Case Study redBus is an online travel agency and is widely used in India for booking tickets. In order to enhance the booking system and to increase its sales, redBus decided to employ infrastructure of Google data. One such application is Google BigQuery. This application is meant for handling huge amounts of booking and data within a short span of time. By this application, consistent streaming of data is available with respect to location of customers, information about seats, and booking. These data will be centralized in a common place. This data shall be provided to BigQuery for answering any sort of queries within seconds. Figure 15 shows the logo of redBus. This complete arrangement of big data integrated with cloud helps redBus application to identify the glitches in a speedy manner and reduce the marketing losses, thereby enhancing customer service. 10 Conclusion The integration of big data and cloud computing is a perfect choice to improve the efficiencies of organizations. Even though certain constraints like storage of data and accession in open environment do persist, they are negligible when compared to net benefits provided by this blend of big data and cloud computing. Management of data in cloud-based environment will help companies to integrate both master and big data in all respects. This chapter clearly presents the importance, characteristics, and classification of big data with appropriate examples. It also explains the tools and techniques used for the processing of big data. Moreover, the concept, working, characteristics, and key features of cloud computing are discussed in a detailed manner. Ultimately, this chapter correlates both the technologies – big data and cloud computing – in today’s scenario with a case study. Both the techniques significantly modified the path, in which companies handle their data and promote it for their business activities. Additionally, these techniques improve the success
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- 35. Cloud of Things Platform for a Water Meter Network Biswaranjan Bhola, Raghvendra Kumar, and Ahmed Alkhayyat 1 Introduction With the steep rise in the population on Earth, there is an exponential decline in the availability of essential commodities such as electricity, water, and food. For the proper management and maintenance of essential things, different types of devices have been designed. In order to maintain all the devices properly and gather information and facts to generate knowledge so that the devices are interconnected with each other is called the Internet of Things (IoT). The implementation of systems such as traffic management on the roads, medical services, streetlight systems, and educational systems should be managed in a systematic manner. Some examples of contributions of the IoT system to the technical world are described in the following. Home appliances are monitored by the IoT system to avoid the abuse of electricity [1]. When people are absent from home, this technology can be used to monitor and provide security to the home [2]. It can also be used for monitoring and controlling the office [3]. In medical services, the IoT is used to provide patients with a better service as well as to warn the management regarding fire and leakage of different gases, which are harmful to patients [4]. Using the IoT, traffic systems and street lights can be controlled efficiently in localized urban areas [5–7]. It can also be applied for monitoring water distribution in a centralized manner in townships [8]. In agriculture, the system is in use for providing video surveillance over the land and for operating the machinery remotely [9]. B. Bhola · R. Kumar () Department of Computer Science and Engineering, GIET University, Kharling, Gunupur, Odisha, India e-mail: biswaranjan.bhola@giet.edu; raghvendra@giet.edu A. Alkhayyat College of Technical Engineering, The Islamic University, Najaf, Iraq © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 R. Sharma et al. (eds.), Data Analytics for Internet of Things Infrastructure, Internet of Things, https://doi.org/10.1007/978-3-031-33808-3_2 17
- 36. 18 B. Bhola et al. Fig. 1 Traditional internet of things (IoT) architecture To develop the IoT, different types of communication technologies are used, such as the Global System for Mobile Communications (GSM), Bluetooth, Zigbee, etc. [10]. Here, we analyze the architecture of the traditional IoT system. Figure 1 describes the architecture of the IoT system. In this system, the main components of the IoT architecture are: • IoT Hub • Sensors • Switch • Smart Device • Connectivity IoT Hub The IoT hub is an interface between the Internet and the Controlling and Monitoring Components (CMCs). The user monitors the CMCs using the Internet and an IoT hub. The IoT hub controls and monitors CMC components such as sensors and switches. Moreover, it uses a separate network to communicate with sensors and switches present within a CMC. Sensors Using sensors, the IoT hub detects the location of a particular place. For example, a gas sensor is used to identify the leakage of gas. Switch Using a switch, the IoT hub switches the electrical and electronics components on or off.
- 37. Cloud of Things Platform for a Water Meter Network 19 Smart Device Using a smart device (Android-based mobile phone, computer) end users com- municate with the IoT hub through the internet to monitor and control the device remotely. Connectivity The Internet is the public network through which a user’s smart device can communicate with the IoT hub present in any part of the world. The discovery of the IoT has been exceptionally beneficial to human lives. For instance, the IoT facilitates Machine to Machine (M2M) communication. Owing to M2M, physical devices can stay connected. With the introduction of the IoT, physical devices are connected digitally within a wireless infrastructure. Without much human interaction, devices can communicate seamlessly, which leads to more automation. Generating a variety of information through IoT-enabled devices assists in making better decisions. Another major advantage of the IoT is in monitoring the environment. This monitoring capability helps to make our lives easier. For instance, air-quality monitoring, milk-density monitoring, gas-leakage monitoring, an IoT monitoring system can improve safety. Moreover, the development and innovation of the IoT play a key role in the continuously changing lifestyle of modern society. In other words, the amount of time saved by this technology is huge. Although it has many advantages, the IoT still faces a variety of challenges. To utilize its fullest potential, it is essential to solve some grave issues. For instance, there is no standard of compatibility for monitoring the devices. The compatibility issue is obvious because devices from different manufacturing companies are being interconnected. The risk of losing privacy and security is always high in the IoT system. Moreover, existing IoT architecture is more complex. Although a lot of research is going on, it is still in its infancy. Hence, in this article we have proposed a new modified IoT architecture, which has certain advantages over the existing system. Some of the advantages of the proposed system are described below. • Low maintenance cost • Network independence • Architecture independence • Scalability The prime contributions of this paper are highlighted as follows. • With the idea of an IoT-hubless infrastructure, a novel architecture has been explored. By doing so, this work introduces the concept of a smart switch module. It first verifies the user, then it switches on the device and sends information to the user. • This work also introduces another smart module called a smart sensor. The smart sensor reads the environmental information, and sends information to the smart switch and user for the necessary action. • Further, the proposed architecture has been tested within a physical test-bed.
- 38. 20 B. Bhola et al. This article is further described in the following order. The next section discusses the methodology of components, followed by the working structure, results, and conclusion. 2 Related Work and Problem Motivation This section focuses on the present success and challenges of the IoT. Moreover, we discuss a few challenges of the existing IoT system and the problem motivation for our research background. 2.1 Related Work According to a survey, trillions of devices have converted to the IoT, which indicates the popularity of the IoT. However, certain limitations exist in the traditional system. In Yakoub et al. [11], the authors have stated that the increased requirement of the IoT formed a complex network structure, which is caused by the creation of various kinds of problems such as inter-operability, flexibility, scalability, energy efficiency, and security. For example, owing to the increased population, motor vehicles, and industries, the pollution of the cities is increasing day by day. To monitor the pollution, Kaur et al. proposed an IoT architecture named green IoT architecture [12]. To improve the efficiency of above-mentioned architecture needs a distributed platform. Chien et al. [13] proposed an IoT architecture in which the sensors and actuators of devices are interconnected with each other using private networks and the Internet. Each device uses its own network, which is heterogeneous in nature, and every sensor also has a different technology. An improvised architecture is essential for handling interoperability and heterogeneity in a seamless way. In [14], the authors used a Software-Defined Network (SDN) to secure IoT devices. However, it does not meet the other inherent challenges. Table 1 discusses a few important forms of IoT architecture used in the literature. From the above literature survey, we observed that the IoT hub is an essential part of the architecture, which may lead to high maintenance cost, network, and architecture dependency. However, in the proposed architecture, the smart switch and the smart sensor have been introduced, which connect directly to the network. This architecture can pave the way for various challenges faced by the current IoT system. The methodology and experimentations are discussed in the following chapters. It is an integrational physical, computational, and electronic environment. Liu et al. describe the same concept in the form of a Cyber Physical System (CPS) [15]. An organization such as the European Telecommunications Standards InstituteETSI explains it as an M2M
- 39. Cloud of Things Platform for a Water Meter Network 21 Table 1 Existing IoT architecture References Year Short analysis [17] 2008 A four-layer architecture for the IoT system. The lower layer consists of an electronic controller to connect with the sensor and relay and contains the control information. The second layer contains the executable program. The third layer is the interface with higher-level languages and the task- and actor-oriented level is present in the fourth layer [18] 2008 A prototype architecture defined by Tan et al. that in the physical architecture of an embedded system in lower layer the outer environment information is sensed by the sensor in the form of a electrical signal and the control system converts it into the high-level information that is required by the user or operational system [19] 2015 To access the physical world through the IoT is dependent on the control network connected with sensors and actuators [14] 2016 The IoT devices can be secured using advanced IoT security architecture, which supports Software-Defined Network (SDN) architecture [20] 2017 To make the IoT device comparable and light weight it should be scalable. The proposed architecture solves the scalable problem created in the IoT device [21] 2017 IoT resources can be properly managed using multiagent distributed architecture. But the shortcoming of this idea is that each agent is an independent module. If there is any dependency this type of architecture may not function properly [12] 2018 To monitor the pollution, green IoT architecture has been proposed. To improve the efficiency of this type of architecture, it should be converted to a distributed platform, which can be solved using the proposed architecture [22] 2018 Much research work has been done on architecture and the protocol of the IoT, but some problems remain [13] 2019 Each IoT device uses its own network and Internet technology, which is heterogeneous is nature. Every sensor also uses different technology [23] 2020 The shortcoming of this work is that it communicates with the user using a GSM module through SMS communication. Hence, the user only knows the device information by using SMS, and there is a maximum than can be communicated with the 24 sensors, because the controller has only 24 I/O ports [24] 2020 A revised architecture is presented to add scalability and dynamism through the application layer communication system [16]. Hence, in such a type of ambiguous scenario the real fact that is discussed by most technical reports is that physical objects around the world try to communicate with others using a common virtual platform to improve the performance and take decisions on a real-time basis or for the future called the IoT platform.
- 40. 22 B. Bhola et al. Fig. 2 Functional unit of the IoT 2.2 IoT Paradigm The survey by Tran-Dang et al. [25] defines the services of the IoT into four categories: 1. Things Oriented (physical and virtual entities are the focus) 2. Internet Oriented (development of an IP-based network that enables the things) 3. Semantic Oriented (handles a huge amount of data in communication) 4. Service Oriented (developing the IoT intelligent service and application based on the above three perspectives) and all the services are processed using four functional units explained in the Fig. 2. In the above, all the pi-nodes are the end-to-end and intermediate components such as the control unit, edge server, cloud server, client smart devices, etc. pi- containers are the data packets, which are transmitted and the pi-movers are the technology that describes how pi-containers are transmitted from one pi-node to another pi-node. pi-protocols explain which protocols (http, tcp/ip, oli, etc.) are used for communication. One computing platform has been designed by Kondo et al. for dynamic module (pi-nodes) configuration for the IoT [26]. Ranganathan et al. explain the data communication in the IoT and an SDN switch, which can reduce the distributed denial of service attack. Using the proposed architecture and implemented module the above-mentioned things can be achieved and some of the problems defined below can be minimized. 2.3 Problem Motivation In the present IoT system, to communicate between end users and sensors or switches to dissimilar networks (e.g., the Internet, an IoT hub network) two basic intermediate heterogeneous application layers are used. One is an Internet web
- 41. Cloud of Things Platform for a Water Meter Network 23 server and the other an IoT hub. However, certain limitations persist in this type of architecture, which are listed below. • High maintenance cost • Network dependency • Architecture dependent • Unscalable Hence, considering the above limitations, in this article, we propose a novel architecture, in which the switches and the sensors are directly connected to the Internet. In turn, the intermediate layer, i.e., the IoT hub, is not required. These are the main motivations for this work. 3 Proposed IoT Architecture In this section, we describe the system model and functionality of the proposed scheme followed by analysis. 3.1 System Model In the present IoT system Fig. 1, the switches (also called Relay) are used to switch the devices on and off. The sensors are used to read the current environmental information of a particular location. In this system we cannot directly access the switches or sensors. They can be accessed through the IoT hub. Hence, switches and sensors are tightly coupled with the IoT hub. Such tight coupling makes it difficult to add new sensors or switches to the IoT hub. The IoT hub will be reprogrammed to add new sensors or switches. Figure 3 describes the architecture of the proposed IoT system The proposed smart switch or smart sensor can be used to design any IoT application. Let, in an IoT system .I there be n smart switches and n smart sensors. It can directly connect through the network, either using Wi-Fi or Ethernet. Each smart switch or sensor can be configured with one IP address, which is used to identify it in the network uniquely. Figure 4 describes the architecture of a smart switch, and Fig. 5 describes the architecture of a smart sensor. 3.2 Methodology The traditional switch is a passive component in the IoT. It connects to the IoT hub. Only the IoT hub can change the state of the switch, which is on/off according to the user request or as the information is received by the sensor. It is also connected to the IoT hub. The IoT hub reads the information from the sensor, analyzes it, and
- 42. 24 B. Bhola et al. Fig. 3 Architecture of the proposed internet of things (IoT) system Fig. 4 Architecture of a smart switch then sends the control information to the switch. The clear definition between the smart switch and smart sensor is defined below. Definition 1 A smart switch directly receives the data packet from the user or sensor to switch on/off under its secure control and resends the confirmation or acknowledgment. Definition 2 A smart sensor is an active component. It is directly connected to the network or Internet, analyzes the environment situation, and then transmits the information to the user as well as the smart switch for action.
- 43. Cloud of Things Platform for a Water Meter Network 25 Fig. 5 Architecture of a smart sensor Both the smart switch and the smart sensor are the active and intelligent modules. They can communicate with each other through networks or the Internet and can also take decisions if required. The basic function of the smart switch is that it first verifies the user, then switches the device on or off, and also sends the information to the user, sensor, or both, regarding the state of the switch. The step-by-step process of the switched-off mode processed by the smart switch is shown in Fig. 6. The flowchart depicted in Fig. 6 describes when the switch OFF mode is processed by the smart switch module. In a similar fashion, the switched ON mode is processed by the smart switch module. Worldwide, the authenticated sensor or user can access the smart switch to switch ON/OFF directly through the Internet. The smart sensor reads the situation of the environment. For example, using a light sensor, we can find out the brightness of light present at a particular time or using a temperature sensor we can find out the temperature of the environment at a specific time. The smart sensor reads the environmental information and then sends it to the user and sends a control message to the particular switch to switch ON/OFF. The flowchart illustrated in Fig. 7, describes the smart sensor sending process. When the user wants to know about the situation of the environment from the smart sensor, it works like the previous process. 3.3 Development of Active Switch The electronic name of the switch is Relay. It is used to make a device switch ON or OFF. There are five pins of Relay. Two pins, let us say A and B, are used to connect to the power source; one pin let us say C, is used as a Pole; and the remaining two pins, let us say D and E, are used as a Terminal, as shown in Fig. 8. Initially, the pole is connected with Normally Closed (NC), that is, pin E. When the current flow is available in pin A and pin B, the pole is shifted to Normally Opened (NO), that is,
- 44. 26 B. Bhola et al. Fig. 6 Flowchart for switched OFF mode processed by the smart switch module the pin D. Hence, pins D and E can be used for ON and OFF. Using Relay, transistor, diode, and resistor, one Relay module can be designed that has six pins. The pins numbered 1, 2, and 3 can be used as input pins and 4, 5, and 6, can be used as output pins. Using this module the relay can be triggered to ON or OFF by providing the signal in to pin 1 of the Relay module, as depicted in Fig. 9. Active relay is a relay module that can directly connect with the Internet through an Network Interface Card (NIC). To convert a Relay module to Active Relay, the components are Ethernet, Wi-Fi gateway, Memory, Processor, Relay module. The interconnection structure is depicted in Fig. 10. This module can be triggered directly using the Internet and can be monitored remotely to discover whether it is in ON/OFF state. Algorithm 1 describes the message passing technology between the user and the active switch. The user may be a person, device, or server that can directly communicate with the Active Switch using the httpRequest() and httpResponse() method. Before sending data packets the active switch initializes all the parameters of the Ethernet controller/Wi-Fi controller, MAC address, and the Service Set Identifier (SSID). Further, it initializes the IP address automatically if the Dynamic Host Configuration Protocol (DHCP)-enabled router is there; otherwise, it initializes to
- 45. Cloud of Things Platform for a Water Meter Network 27 Fig. 7 The sensor sends the information to the switch and the user Fig. 8 Basic diagram of a Relay. COM .= common, NC .= normally closed, NO .= normally open the user-provided IP address. Next, it initializes the port as an output to operate the relay. After that, it reads the packet until the program receives a valid packet. Upon receiving an authenticated request, it sends the switch information in the form of a httpResponse() format. In the case of an unauthenticated request, it discards all the previous operations. Further, it starts to read the new packet, as discussed in step 1. The Algorithm 1 discusses the active switch interaction through the Internet.
- 46. 28 B. Bhola et al. Fig. 9 Schematic diagram of a Relay module Fig. 10 Active Relay interconnection structure 3.4 Development of an Active Sensor With the existing technology, an active sensor module can be designed with its own SSID, MAC Address, and IP address. That module can directly connect to the Internet using Wi-Fi/Ethernet. It also communicates the message to the user (person, server, device) using the httpRequest(), or httpResponse() method. The block diagram of an active sensor is shown in Fig. 11. The operation of the sensor is described using the Algorithm 2. In Algorithm 2, the processor initializes all the parameters of the Ethernet controller/Wi-Fi controller, MAC, SSID, DHCP, etc., similar to Algorithm 1. Next,
- 47. Cloud of Things Platform for a Water Meter Network 29 Algorithm 1 Sending data packets by an active switch Input: Ethernet Controller or Wi-Fi controller Output: Get Details Initialization : 1: Initialize MAC/SSID 2: Initialize IP and Port Optimization Loop : 3: while 1 do 4: Read TCP packets 5: if Valid GET then 6: if Valid REQ then 7: Get Details 8: else 9: Unauthorized 10: end if 11: end if 12: end while Fig. 11 Block diagram of an active sensor it initializes the port as an input port and enables Analogue to Digital Converter (ADC) to read the information of the environment from the sensor. If the program finds that the read packet is valid, then it checks the request (REQ). If the request is authenticated, then it reads data from the sensor and sends it in the form of an httpResponse() format; otherwise, it discards all the previous operations and again reads the new packet.
- 48. 30 B. Bhola et al. Algorithm 2 Sending data packets by active sensor through the internet Input: Ethernet Controller Output: Send Status Initialization : 1: Initialize MAC/SSID 2: Initialize IP and Port Optimization Loop : 3: while 1 do 4: Read TCP packets 5: if Valid GET then 6: if Valid REQ then 7: Read Environmental Status 8: Send Status 9: else 10: Unauthorized 11: end if 12: end if 13: end while 3.5 Integration The integration of an active sensor and active switch is discussed below. Each active sensor and active switch can directly connect to the local router, either through an Ethernet port or Wi-Fi. Further, each local router is directly connected to the Internet. Users can remotely monitor and control the device via the LAN or Internet. Each active module can communicate with each other because each module is uniquely identified using an IP address, and a MAC address. The web browser is used to access the data and to send the control message to the module. The whole integration concept is demonstrated in Fig. 3. 4 Simulation and Result In this section, the performance of the proposed architecture is evaluated by comparing the results with the existing architecture. 4.1 Setup Process The proposed device (Fig. 12) is directly connected with the network through Ethernet (ENC28J60) or wireless module (ESP8266). The packets are processed using a microcontroller (Atmega32). The magnetic switch (Relay) or sensor is connected with the microcontroller. Through the web browser, the user can directly send instructions to the relay for the switch on or switch off instruction. The
- 49. Cloud of Things Platform for a Water Meter Network 31 Fig. 12 Setup process and initialization sensor information is also directly accessed through the web browser. The control information is transmitted in the form of an HTTP request or HTTP response using the GET method. It is described using the datasheet of ENC28J60 Ethernet controller. To set up the proposed IoT architecture certain steps have to be followed. These steps are discussed below. • Configure the IP address of the smart switch or smart sensor. • Connect with the network using Wi-Fi or Ethernet. • Access using any web browser. This module can easily interface with any web application or stand-alone appli- cation. Moreover, owing to the absence of an IoT hub, it is purely platform independent, network independent, and provides a faster response. Figure 12, shows the setup for the implementation of the proposed architecture. Figure 13 illustrates the initial process and Figs. 12, 13 show the remotely received stated details using a web browser. The Relay ON or OFF state has been experi- mented with in Figs. 14 and 15 respectively. 4.2 Analysis One of the basic functions of IoT devices is to read all the information of the environment using the sensors and transmit it to the cloud for analysis and monitoring purposes. This section discusses and analyzes the shortest job first
- 50. 32 B. Bhola et al. Fig. 13 Accessing the switch using an IP address Fig. 14 Remotely operate Relay ON state
- 51. Cloud of Things Platform for a Water Meter Network 33 Fig. 15 Remotely operate the Relay OFF state Fig. 16 Waiting time of different sensors (SJF) scheduling algorithm on the proposed architecture. Further, it compares the waiting time, average waiting time, turnaround time, and average turnaround time required to upload the data to the cloud by traditional IoT devices with the proposed IoT module (Fig. 16). The analysis was done using a hypothetical IoT device. For experimentation, IoT device is connected with four sensors named Sensor1, Sensor2, Sensor3, and Sensor4. The time taken by these sensors to read the data from the environment is 5, 7, 6, and 3 units of time (ms) respectively. The basic function of the particular device is to repeatedly upload the sensor information onto the cloud. The time taken by the device, using the traditional sensor and switch, to upload one instance of data is given in Table 2. If we observe the total waiting time it will be, Total waiting time .= 0 .+ 3 .+ 8 .+ 14 .= 25 unit Here, the .waiting time = Service time–Arrival time.
- 52. 34 B. Bhola et al. Table 2 Time taken by the devices to upload data using the existing architecture Resources Arrival time Execution time Service time Waiting time (Service time .− Arrival time) Sensor 1 0 5 3 3 Sensor 2 0 7 14 14 Sensor 3 0 6 8 8 Sensor 4 0 3 0 0 Table 3 Time taken by the devices to upload data in the proposed architecture Resources Arrival time Execution time Service time Waiting time Sensor 1 0 5 0 0 Sensor 2 0 7 0 0 Sensor 3 0 6 0 0 Sensor 4 0 3 0 0 .Average waiting time = T otal waiting time No. of Resources (1) The waiting times of different sensors are shown in Fig. 16. So, .Average waiting .time = 25/4 = 6.25 unit .T otal T urnAround T ime = 3+8+14+21 = 46 unit .Average T urnaround time = T otal T urnaround time No of Sensors .= 46 4 .= 11.5 unit To upload one instance of data, the time taken by the devices using the proposed architecture is given in Table 3. The graph presented in Fig. 17 shows that although one sensor starts reading the data, other sensors have to wait. The waiting time is rather due to the IoT hub present in the system. The hub acts as the interface between the Internet and the CMC. However, using the proposed architecture, smart sensors can simultaneously read and send the data to the cloud. Hence, the overall waiting time has been reduced. In Fig. 18, we can observe that at 1 ms, all sensors have executed their task. The advantages of this integrated architecture are listed below. • Each module connects with the network through the Ethernet/Wi-Fi; hence, interfacing with the modules is very easy. • It is scalable because each module contains its own program for operation • The module can communicate using the browser for which it supports being platform independent. • Different setup networks are not required to communicate with sensor and switch. • There is no intermediate device such as an IoT hub between the user and the sensor; as a result, it can provide the user with a good-quality service. • Interoperability is possible owing to the implementation of the httpRequest() and HTTPresponse() method for message communication.
- 53. Cloud of Things Platform for a Water Meter Network 35 Fig. 17 Sensing time and waiting time using the existing architecture Fig. 18 Sensing and waiting time using the proposed architecture 5 Conclusion Today, the Internet is the world’s powerful communication system for interaction in any part of the world. This article is about a smart switch and smart sensor that help users of every IoT automation system such as smart home automation systems, smart traffic automation systems, smart street light automation systems, etc. The proposed architecture is platform independent and does not require an
- 54. 36 B. Bhola et al. extra network to be created for monitoring. Owing to its cost-effectiveness, it may overcome potential problems such as scalability and security. In addition, it is very convenient to use in any centralized controlling system as well as a distributive environment to reduce the human resources and for the efficient management of other resources. The switch can communicate directly with a sensor and vice versa. The smart sensor can make a decision to switch on or off directly, without an IoT hub. As there is no intermediate layer required for the IoT system the performance of the IoT system can be increased. It is very helpful for the designer in terms of easy deployment of the sensor/switch without frequently rewriting the code. mds August 26, 2015 References 1. Motlagh, N. H., Khajavi, S. H., Jaribion, A., Holmstrom, J. (2018). An IoT-based automation system for older homes: A use case for lighting system. In 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA) (pp. 1–6). IEEE. 2. Quadri, S. A. I., Sathish, P. (2017). IoT based home automation and surveillance system. In 2017 International Conference on Intelligent Computing and Control Systems (ICICCS) (pp. 861–866). IEEE. 3. Shaikh, S. A., Kapare, A. S. (2017). Intelligent office area monitoring and control using internet of things. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 6, 4705–4711. 4. Baker, S. B., Xiang, W., Atkinson, I. (2017). Internet of things for smart healthcare: Technologies, challenges, and opportunities. IEEE Access, 5, 26521–26544. 5. Javaid, S., Sufian, A., Pervaiz, S., Tanveer, M. (2018). Smart traffic management system using internet of things. In 2018 20th International Conference on Advanced Communication Technology (ICACT) (pp. 393–398). IEEE. 6. Dheena, P. F., Raj, G. S., Dutt, G., Jinny, S. V. (2017). IOT based smart street light management system. In 2017 IEEE International Conference on Circuits and Systems (ICCS) (pp. 368–371). IEEE. 7. Sahoo, K. S., et al. (2019). ESMLB: Efficient switch migration-based load balancing for multi- controller SDN in IoT. IEEE Internet of Things Journal, 7, 5852–5860. 8. Srihari, M. M. (2018). Intelligent water distribution and management system using internet of things. In 2018 International Conference on Inventive Research in Computing Applications (ICIRCA) (pp. 785–789). IEEE. 9. Sushanth, G., Sujatha, S. (2018). IOT based smart agriculture system. In 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE. 10. Vaidya, V. D., Vishwakarma, P. (2018). A comparative analysis on smart home system to control, monitor and secure home, based on technologies like GSM, IOT, Bluetooth and PIC microcontroller with ZigBee modulation. In 2018 International Conference on Smart City and Emerging Technology (ICSCET) (pp. 1–4). IEEE. 11. Yaqoob, I., Ahmed, E., Hashem, I. A. T., Ahmed, A. I. A., Gani, A., Imran, M., Guizani, M. (2017). Internet of things architecture: Recent advances, taxonomy, requirements, and open challenges. IEEE Wireless Communications, 24(3), 10–16. 12. Kaur, G., Tomar, P., Singh, P. (2018). Design of cloud-based green IoT architecture for smart cities. In Internet of Things and Big Data Analytics Toward Next-Generation Intelligence (pp. 315–333). Cham: Springer.
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- 56. revealed unto me that Bahman will sit upon the throne that hath been denied unto me.” Alas! having thus spoken, behold, Isfendiyar sighed, and the sun of his life was set, and great was the lamentation for the brave young hero lost unto Iran. As for Rustem, sorrowfully he made ready for Isfendiyar a coffin of gold, causing it to be lined with silken stuffs and perfumed with amber. Then he laid therein the valiant hero- prince of the Heft-Khan, and all beholding him wept with bitter sorrow. Tenderly then the coffin of gold was placed upon the back of a slow-moving dromedary, forty others following in its wake. And lo! there followed after them the brave army of the Prince, clad in robes of mourning, while Bashutan marched at the head of the sorrowful train, leading Isfendiyar’s horse, whose saddle was reversed and whose mane and tail were shorn, while from its sides hung the armor of the vanquished one. Now thus it was that they brought brave Isfendiyar back unto the palace of his fathers, and behold! all the world mourned this great loss unto Iran. But while Iran sorrowed for Isfendiyar, behold, Bahman grew up in the courts of Rustem, the Pehliva loving him as a son. For in his heart he grieved bitterly that by his hand brave Isfendiyar had fallen. Yea, and he gloried not in his last great fight, even though he knew that now his star would shine on undimmed unto the end, and that the children of Ormuzd would sing his praises through all the ages as the one great unconquered hero of the Persians.
- 57. THE DEATH OF RUSTEM Lo! it is chronicled by Firdusi, who, in his great epic poem, hath made immortal the heroes and kings of Persia, that Zal in his old age had born unto him a son of remarkable beauty. But alas! when the astrologers cast the horoscope of this beautiful babe, they read therein that few and evil would be the days of Shughad; that he would be the ruin of the house of his fathers, also bringing destruction upon the land of Iran. Now Zal was overwhelmed with dismay when this message of the stars was communicated unto him, and he prayed continually unto Ormuzd that he would avert this terrible fate from the head of his boy. Yea, and he reared him carefully, sparing no pains to inculcate in the youth the principles of truth, honor, loyalty unto his house and unto the King. Then, when Shughad was come unto man’s estate, Zal sent him unto the King of Kabul, who, when he saw that he was tall and handsome, and fit in every way to sit upon the throne, showed unto him great kindness, even giving unto him his daughter in marriage, and providing for him bountifully. Now the King of Kabul paid tribute unto Rustem, every year being required to send unto the Hero of Seistan a bull’s hide as a token of sovereignty. And alas! this was a great grievance unto his soul, for he was proud in his spirit and desired to be bondsman unto none. So it was not alone kindness which prompted him to take Shughad unto him as his son, for in his heart he hoped thus to have the tribute remitted.
- 58. But behold! when the proper time came, Rustem sent his messenger as usual to demand the bull’s hide, which made the King very angry. So, in his disappointment, he hesitated not to express his opinion of Rustem’s conduct unto Shughad, stirring up his mind against his brother. Then Shughad, becoming angry and discontented also, said unto the King: “Verily, since my elder brother hath behaved unto me thus unkindly, in my heart he shall be unto me no more than a stranger. Let us consider, therefore, how we may ensnare him.” So all night the King and Shughad talked and pondered how they might rid the world of Rustem, and at last they decided upon a scheme. Consequently, it came to pass that presently the King of Kabul gave a great feast, and when all had become excited with wine, behold, Shughad, the son of Zal, began to boast of his lineage, saying: “Verily, Shughad alone of all this great company should be toasted! Yea, and I except not even the King, our host! For is not the Mighty Rustem my brother? And do I not come from a long line of heroes, extending from Husheng the Shah even unto Zal of the white hair?” Now hearing this, lo, the King sprang up in pretended wrath, saying: “Upstart! Thinkest thou to lord it over me, the King of Kabul? Verily, nay! For thou art really no brother unto Rustem, since thy mother was but a slave in thy father’s household. Therefore, boast not so loudly.” Then Shughad, feigning great anger, hastily left the banqueting- halls, threatening to call forth Rustem to avenge the insulting words of the King. So, with guile in his heart, the Prince rode forth unto the palace of his brother. And behold! after they had exchanged greetings, Rustem said: “And how fares it with thee at Kabul, O my brother? Art thou still happy and contented in the King’s palace?” Then Shughad, rejoicing at the opening thus given him, said:
- 59. “I pray thee do not speak unto me of Kabul, for the word is hateful unto mine ears. For verily this night hath the King insulted me beyond bearing. Yea, and thee, too, and my father! So I came away in a rage, and never will I return until the vile words which he spake of my family are avenged.” Now when Rustem learned what had been spoken by the King of Kabul, he said unto Shughad: “O my brother, trouble not thyself concerning this matter, for verily it shall bring thee naught but gain. Alas! ever hath the King of Kabul been vain and arrogant of spirit, but for this he shall be humbled unto the dust, for no longer shall he reign in Kabul, since his crown shall henceforth grace thine own fair brow.” So, at once Rustem set forth to avenge the wrongs of his brother, but lo! when they were yet far from Kabul, they were met by the King, who, bowing himself low in the dust, said unto Rustem: “O Lord of the World! Thou beholdest before thee, with uncovered head and bare feet, the proud King of Kabul. Pardon, therefore— thou who art gracious as the River Nile—the foolish words of thy slave, spoken when his head was troubled with wine. For lo! his mouth is filled with dust and his soul with sorrow and repentance.” Now hearing these words of humility, Rustem’s anger was appeased. Granting unto the King forgiveness, therefore, he graciously consented to be his guest. So a great banquet was made ready to celebrate the reconciliation, and as they feasted the King lauded his wondrous hunting-grounds, wherein the deer and the wild ass furnished such excellent sport, and he invited Rustem to hunt therein for a day before returning unto Seistan. So Rustem, who loved the chase almost as well as the field of battle, consented to remain the King’s guest for yet another day, for he suspected not that poison lurked in the honey of the monarch’s words. But alas! in a certain part of these beautiful hunting-grounds, the schemers had caused to be dug treacherous pits, lined thickly
- 60. with swords and lances and hunting-spears, yet no man would have suspected their existence, so cleverly were they covered over. On the following day, therefore, the King directed the hunt unto the place in the forest where the pits were hidden. And behold! Shughad ran beside the horse of Rustem to show unto him the path. But when they were come unto the place of peril, Rakush, smelling the newly-turned earth, reared high in the air, refusing to advance. Then Rustem, thinking he was afraid, commanded him to go forward; but Rakush, backing, refused to give ear unto his master’s voice. Now this made Rustem angry so that lightly he struck him with his whip, though never before in all their long wanderings together had he done so. Then, alas! surprised and maddened by the stroke, Rakush sprang forward, but only to fall into one of the treacherous pits. Now sinking into the midst of this cruel bed of pointed weapons, many a ghastly stab and many a cut in limb and body received Rustem and his gallant steed. Yet from this awful grave, at one prodigious spring, Rakush escaped with his master still upon his back. But alas! what availed that mighty effort? For, down again into another pit, yet deeper, both fell together. And though again they rose, and yet again, it was only to be engulfed once more, and yet again. Yea, seven times down prostrate, seven times bruised and maimed, did Rakush struggle on, until mounting up the edge of the seventh pit, all covered with deep wounds, both horse and rider lay exhausted, Rustem swooning in his agony. But when once more the mighty Hero opened his horror-stricken eyes upon the world, lo, he beheld Shughad his brother, smiling in triumph at his side. Then knew he unto whom he owed this infamous treachery, and he said: “Thou Wicked One! Is it possible that thou, the son of Zal, hast contrived and wrought this evil deed against thy brother? Verily thy heart is as black as thy shadow, which shall not long darken the earth.”
- 61. Then the treacherous Shughad, trying to justify his cruel deed, said sternly unto the dying Hero: “Verily, God hath decreed this awful vengeance to recompense thee for all the blood that thou hast shed in thy long life as a warrior. Not I, but He, hath determined thy fate.” Now at this moment the King of Kabul drew near, feigning great anger and sorrow when he beheld the dying one. And he wailed: “Alas the day! That the Mighty Rustem should perish so ignobly, and as my guest! Quick, bring the matchless balm for Rustem’s cure, for the great Champion of Iran must not be allowed to die a death so wretched!” But Rustem, smiling scornfully, said unto the treacherous King: “O Man of Wile! Right well thou knowest that Death, that cometh unto all men in their turn, is the only physician that now can heal the great Rustem of his wounds. But why should the mighty son of Zal complain of Fate? For verily, many a mighty King hath died and left me still triumphant, still in power unconquerable. And behold! yet there liveth valiant Feramurz, who will be revenged upon thee for his father’s death.” And now the Mighty Rustem sighed, saying unto Shughad in a weak and mournful voice: “Verily, my spirit will soon be free! But alas! it grieveth me sore that my faithful body may this night be food unto the wolves and lions. String, therefore, my bow, and place it in my hands that I may appear unto the wild beasts that would devour me, even as a live warrior, ready to defend his life. For our father’s sake, O Shughad, refuse not thy brother this last request.” So, suspecting naught, Shughad drew the great bow from its case, and placed it in Rustem’s hands, smiling with satisfaction to think that his brother’s end was so nigh. But verily he smiled not but a moment, for noting the strength with which Rustem gripped his bow, and the peculiar look of his eye, shuddering with terror, quickly
- 62. Shughad dodged behind a plane-tree close at hand. But useless was the shelter, for though the dimness of death was come over the eyes of the Hero, he yet spied Shughad where he hid, and whiz! went an arrow, straight through the tree and the wicked Shughad, transfixing them together. And Rustem, when he saw the fate of his brother, was content, knowing that he could do no more harm unto his house. But alas! of all that mighty hunting-party not a knightly follower escaped. For Zuara and all the others perished in the treacherous pits of the traitor King, save only one, who quickly fled with the dire news unto Seistan. Then Zal, in agony, tore his white hair and rent his garments, lamenting bitterly for Rustem, crying again and again: “Why was I not present, fighting at his side? Why could I not die for him? Wherefore, alas, am I left alone to mourn his memory?” But behold! though bowed to the earth with grief, quickly the white- haired old warrior sent Feramurz forth with a great army to avenge the death of his father. And verily the work of the Hero was complete. For not only did he make of Kabul a desert, but he laid low the head of the treacherous King and all his race. Then the work of vengeance finished, lo, he sought out the body of Rustem, and of Rakush his gallant steed, and bare them back in sorrow unto Seistan, where they were placed in a noble tomb. And alas! never was there such wailing in the land of Iran as for Rustem the Mighty. Nay, not even for the glorious Shahs of Old! And well might it be so, for never again did Persia rejoice in such an unbroken line of heroes, and never did she achieve such telling victories, for with Rustem her glory departed; yea, for many long years!
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