Resource Consideration in Internet of Things A Perspective View

International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume: 3 | Issue: 4 | May-Jun 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 - 6470
@ IJTSRD | Unique Paper ID - IJTSRD23694 | Volume – 3 | Issue – 4 | May-Jun 2019 Page: 223
Resource Consideration in Internet of Things:
A Perspective View
Rishikesh Sahani1, Prof. Avinash Sharma2
1PG Scholar, 2Assistant Professor
1,2Department of CSE, MITS, Bhopal, Madhya Pradesh, India
How to cite this paper: Rishikesh
Sahani | Prof. Avinash Sharma
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ABSTRACT
The ubiquitous computing and its applications at different levels of abstraction
are possible mainly by virtualization. Most of its applications are becoming
pervasive with each passing day and with the growing trend of embedding
computational and networking capabilities in everyday objects of use by a
common man. Virtualization provides many opportunities for research in IoT
since most of the IoT applications are resource constrained. Therefore, thereisa
need for an approach that shall manage the resources of the IoT ecosystem.
Virtualization is one such approach that can play an important role in
maximizing resource utilization and managing the resourcesofIoT applications.
This paper presents a survey of Virtualization and the Internet of Things. The
paper also discusses the role of virtualization in IoT resource management.
Keywords: Virtual Machine, Virtualization, Internet of Things, Fog Computing,
Resource Management
1. INTRODUCTION
Virtualization is the replication of a device or its resources in virtual form.
Multiple processes from different applications run at the same time, thereby
increasing the efficiency and decreasing the maintenance overhead.IBM
developed the concept of virtualization, but as the cost of hardware decreased
with time, the concept of virtualization became less prominent [1, 2].
With the advent of the Internet, the concept of virtualization
came into existence again. Nowadays, data centers use
virtualization techniques to abstract physical hardware and
create multiple logical resources, available to users on-
demand. Thus, virtualization users can instantly access
computing resources and it leads to improved resource
utilization and better application performance [3, 4].
Applications of virtualization are manifoldwhenweconsider
the computing as a service at different levels of abstraction.
Nowadays, virtualization has become diversified in its
applications especially in the field of Internet of Things.
Virtualization is a powerful technique which can be used in a
wide variety of IoT applications. These may include server
consolidation, access to a variety of hardware and software
resources at the device level andenhancementsinthequality
of service, etc.
With the advent of the Internet of Things, the number of
devices connected to the Internet increases. In most of the
IoT applications, thesedevicesareresourcelimitedregarding
computation and communication which include storage,
processing power, energy, and bandwidth. To manage these
limited resources in IoT devices, a resource management
approach is required.Virtualizationisonesuchapproachthat
leads to better resource optimization and efficient resource
management. In addition to this, the surplus amount of data
generated by the IoT devices imposes further constraints on
IoT resources, and this becomes a major challenge in such
application environments. Virtualization acts as a key
enabling technology for various resource constrained IoT
applications.
This paper presents an overview of virtualization and its
type. It further discusses theInternetof Things along withits
applications and architectures. This paper also gives the
overview of various resources in IoT along with their
limitations. It then discusses the role of virtualization in IoT
resourcemanagement and the challengesencounteredinIoT
virtualization.
The paper is organized as Section 2 discusses virtualization,
Section 3focuses ontheInternetofThings,Section4presents
virtualization for IoT resource management, Section 5
discusses the challenges, and Section 6gives conclusions.
2. RELATED WORK
It is expected that billions of objects will be connected
through sensors and embedded devices for pervasive
intelligence in the coming era of Internet of Things (IoTs).
However, the performance of such ubiquitous
interconnection highly depends on the supply of network
resources in terms of both energy and spectrum. Librating
IoT devices from the resource deficiency, we consider a
green IoT network in which the IoT devices transmit data to
a fusion node over multi-hop relaying. To achieve
IJTSRD23694

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
sustainable operation, IoT devices obtain energy from both
ambient energy sources and power grid, while
opportunistically access the licensed spectrum for data
transmission. We formulate astochasticproblemto optimize
the Network utility minus the cost on on-grid energy
purchasing. (Deyu Zhang, Ying Qiao, Liang She, Ruyin
Shen, Ju Ren; 2019)
In this paper, we study sustainable resource allocation for
cloud radio access networks (CRANs) powered by hybrid
energy supplies (HES). Specifically, the central unit (CU) in
the CRANs distributes data to a set of radio units (RUs)
powered by both on-grid energy and energy harvested from
green sources, and allocates channels to the selected RUs for
downlink transmissions. We formulate an optimization
problem to maximize the net gain of the system which is the
difference between the user utility gain and on-grid energy
costs, taking into consideration the stochastic nature of
energy harvesting process, time-varying on-grid energy
price, and dynamic wireless channel conditions. A resource
allocation framework is developed to decompose the
formulated problem into three sub problems, i.e., the hybrid
energy management, data requesting, and channel and
power allocation. Based on the solutions of the sub
problems, we propose a netgain-optimalresource allocation
(GRA) algorithm to maximize the net gain while stabilizing
the data buffers and ensuring the sustainability of batteries.
Performance analysis demonstrates that the GRA algorithm
can achieve close-to optimal net gain with bounded data
buffer and battery capacity. Extensive simulations validate
the analysis and demonstrate that GRA algorithm
outperforms other algorithms in terms of the net gain and
delay performance.(Deyu Zhang, Zhigang Chen, Lin X.Cai,
Haibo Zhou,Sijing Duan,JuRen,Xuemin (Sherman) Shen
and Yaoxue Zhang; 2018)
Non-Orthogonal Multiple Access (NOMA) exhibits
superiority in spectrum efficiency and device connectionsin
comparison with the traditional orthogonal multiple access
technologies. However, the non-orthogonality of NOMA also
introduces intra-cell interference that has become the
bottleneck limiting the performance to be furtherimproved.
To coordinate the intra cell interference, we investigate the
dynamic user scheduling and power allocation problem in
this paper. Specifically, we formulate this problem as a
stochastic optimization problem with the objective to
minimize the total power consumptionofthewholenetwork
under the constraint of all users’ long term rate
requirements. To tackle this challenging problem, we first
transform it into a series of static optimization problems
based on the stochastic optimization theory. (Daosen Zhai,
Ruonan Zhang, Lin Cai, Bin Li and Yi Jiang; 2018)
Established approaches to data aggregation in wireless
sensor networks (WSNs) do not cover the varietyofnew use
cases developing with the advent of the Internet of Things
(IoT). In particular, the current push toward fog computing,
in which control, computation, and storage are moved to
nodes close to the network edge, induces a need to collect
data at multiple sinks, rather than the single sink typically
considered in WSN aggregation algorithms. Moreover, for
machine-to-machine communication scenarios, actuators
subscribing to sensor measurements may also bepresent, in
which case data should be not only aggregated and
processed in-network but also disseminated to actuator
nodes. In this paper,wepresentmixed-integerprogramming
formulations and algorithms for the problem of energy-
optimal routing and multiple-sink aggregation, as well as
joint aggregation and dissemination,of sensormeasurement
data in IoT edgenetworks.(EmmaFitzgerald,Michał Pióro
and Artur Tomaszewski; 2018)
With the development of wireless communications and the
intellectualization of machines, the Internet of things (IoT)
has been of interest to both industry and academia.Multihop
routing and relaying are key technologies that will underpin
IoT mesh networks in the future. This paper investigates
optimal routing based on the trusted connectivity
probability (T-CP) for multi-hop, underlay, device-to-device
(D2D) communications with decode-and-forward (DF)
relaying. Both random and fixed locations for base stations
(BSs) are considered, where the former case assumes that
the locations of the BSs are modeled as a Poisson point
process (PPP). First, we derive two expressions for the
connectivity probability (CP): a tight lower bound and an
exact closed-form. Analysis is carried outforthecaseswhere
the channel state information (CSI) between BSs and the
D2D transmitter is known (CSI-aware) and unknown (no-
CSI). Interference from active cellular users (CUEs) is
characterized by modeling CUE locations as a PPP. (Gaojie
Chen, Jinchuan Tang and Justin P. Coon; 2018)
3. VIRTUALIZATION
Virtualization is the replication of a device or its resources
such that multiple processes from different applicationsrun
at the same time to increase the efficiency and decrease the
maintenance overhead. It attempts to reducethecomplexity
by abstracting underlying hardware and software. This
allows efficient interaction with the various hardware and
softwareresourcesalongwith improved resourceutilization.
Figure 1 depicts the IT infrastructure before virtualization,
and Figure 2 depicts the IT infrastructure after
virtualization.
Figure 1 Before Virtualization
Figure 2 After Virtualization

There are different types of virtualization in different
computing environments. Some of which includes
virtualization at the desktoplevel, network level, application
level and storage level. The virtualization may differ in
approach and implementation depending on the application
requirements. Accordingly, virtualization can be categorized
as follows:
System Virtualization
Infrastructure Virtualization
Software Virtualization
System Virtualization
System Virtualization adds a layer on top of the bare
hardware to provide an interface to some virtual machines
(VMs) that is functionally equivalent to the actual hardware
[5]. There are three techniques of system virtualization: full
virtualization, para-virtualization, and hardware-assisted
virtualization techniques [6].In full system virtualization, a
virtual replica of the system’s hardware is created so that
operating system and softwaremayrunonthevirtualformof
device as they would run on the actualhardware.Someofthe
advantages of full system virtualization include good
isolation,better portability, and enhancedsecurityforvirtual
machines. But the disadvantageoffullsystemvirtualizationis
the very poor performance of virtual machines. Para
virtualization, also known as operating system assisted
virtualization, decreases the above problem of full system
virtualization by modifying the procedure of operating
system by using a virtual machine instead of CPU to perform
the protected tasks. Hardware-assisted virtualization also
known as accelerated virtualizationisplatformvirtualization
where the modified guestoperatingsystemisunnecessaryto
enable virtualization because virtual machine manager
manages privilege instructions at a root mode without
affecting the guest operating system while in CPUs like x86
do not have virtualization extensions which are not included
in hardware Assisted virtualization.
Figure 3 gives the summary of types of system virtualization.
Figure 3 Types of System Virtualization
System virtualization is of two types - server virtualization
and desktop virtualization. In server virtualization, one
physical machine is divided into multiplevirtualserverswith
the help hypervisor, a software virtualization layer.
Hypervisors are classified into two types: Type 1and Type 2.
The Type-1 hypervisor runs directly on the hardware while
as the Type-2 hypervisor runs on the top of an operating
system [7, 8]. Development of server virtualization
technology started from a single server to multiple servers
having common instruction set and manual management to
multiple servers with the diverse instruction set and
automated management. A single server system consists of a
dedicated server with a hypervisor supporting one or more
dedicated services. Multiple server systems comprises
multiple servers with the common instruction set and a
hypervisor that allows services from one physical server to
another server manually. Here, the server-service
relationship is dedicated. Multiple servers with the diverse
instruction set and automated management contain virtual
resources extended across someunderlyingserverhardware
with diverse instruction sets, and flow of services is done
automatically.
The server virtualizationwasconceptuallydevelopedfordata
centers todynamically control and share available resources
on-demand. Services runningon aserver areinteractingwith
available server hardware resources such as CPU, memory,
network interfacing card, etc. These available resources can
become invisible to the service and can also be shared if the
virtualization layer is placed on the top of hardware. The
virtualization can help to create different virtual machines
and share the available resources between these virtual
machines. Each virtual machine can have its resources
depending on the service defined for it [9, 10, 11]. Some of
the server virtualization software solutions include those by
VMware, Citrix, and Microsoft.
As the range of users increases in an IT organization, it
becomes a challengefor IT todelivertherightkindofdesktop
view in the right way for each user type. Desktop
virtualization provides a solution by separating the physical
location of a client device from its logical interface [12, 13].
The desktop virtualization is a server-centric computing
model. In this model, each end user can get the desktop
experience remotely while the desktop virtual machines can
be hosted and managed centrally in the data center [14].
There are many benefits of desktop virtualization which
include high availability, a lower total cost of ownership
(TCO), increased security, reduced energy costs and
centralized management. Limitations of desktop
virtualization include difficult GUI, increased downtime,
security risks, etc.
Desktop virtualization can be done on user data and settings
(user state virtualization), application and tools (application
virtualization) and the operating system itself. Theuserstate
virtualization (USV) separates the data of user and settings
from the physical device and replicates it centrally. It allows
independence of the user profile from the client. Since the
data is stored on a central machine, the user can log in
anytime and can get immediate personalized experience. In
case a device gets lost, the user can recover his data
immediately, e.g., VDI Suite allows access to windows
environment by connecting to host desktop running in the
data center. In Application Virtualization, applications are
isolated from other applications. It allows applications
written for OS version to happily execute in another
environment; this environmentcanbeanewOSversionoran
entirely different OS, e.g., App-V from Microsoft provides
application virtualization. Operating system virtualization
allows access to the whole desktop environment, e.g.,
MicrosoftEnterpriseVirtualizationprovidesOSvirtualization
and mitigates applicationincompatibility.
Desktop virtualization is of two types: server-side desktop
virtualization (hosted desktop virtualization) andclient-side
desktopvirtualization.With server-side virtualization,auser
will keep the OS, applications, and data within the data
center, wherea user can execute thoseprimarilyusingserver
resources. The advantage is low cost, low maintenance, and
easy to manage client devices. The disadvantage ofserver-
side virtualization is it requires additional server

infrastructure. Server-side desktop virtualization is of two
types - server- based computing and virtual desktop
infrastructure.Withserver-basedcomputing,applicationsare
implemented, controlled, supported on the server instead of
the client. While as in desktop infrastructure, all the profile
settings, installed applicationsandpatchesaremanageablein
a central location. In client-side virtualization, user access
applications that are streamed on-demand from central
servers to client devicesand these applications are isolated
from the restof the clientsystem byavirtualizationlayerthat
is between the application and the local operating system.
Client-side virtualization offers better central management
with proper local execution than server-side virtualization.
Advantages of client-sidevirtualizationincludenoneedofbig
server infrastructure, better user experience due to local
execution of applications, lower costs because images are
managed centrally on the server, security to the data and
virtualized images, and full PC performance while reducing
the need for additional server investments.
Infrastructure Virtualization
Infrastructure virtualization refers to the virtualization of
infrastructure resources such as network and storage.
Accordingly, there are two types of Infrastructure
virtualization viz., network virtualization and storage
virtualization as shown in Figure 4.
Network virtualizationcombinesthenetworkresourcessuch
as hosts, switches, adapters, routers, bridges virtual
machines, etc. into a single platform that appear as a single
pool of resources. Hence, network virtualization increases
resource utilizationbysharingnetworkresources.Benefitsof
network virtualization are improved efficiency, scalability,
reduced operational costs and complexity,easymaintenance
and provisioning tasks [15, 16]. Network virtualization is of
two types- device level virtualization and network level
virtualization. Device level virtualizationreducesthenumber
of physical devices in a network; while network-level
virtualization creates multiple logical networks from a
physical network.
Storage Virtualization abstractslogicalstoragefromphysical
storage. As per Storage Networking Industry Association
(SNIA), storage virtualization is defined as follows: "The act
of hiding, abstracting or isolating the internal functions of a
storage (sub)system or service from applications, host
computers or general network resources to enable
application and network independent management of
storage or data."
Figure 4 Types of Infrastructure Virtualization
Benefits of storage virtualization include easy migration of
data between storage locations, better utilization of storage,
improved SAN management, and decreased complexity in
overall storage networking, faster and easier backup,
archivingand recovery, etc.Someofthedemeritsincludelack
of standards, lack of interoperability, the overhead of
mapping between local and physical locations, etc. [17, 18].
Storage Virtualization can be done at the block level and file
level. Block Virtualization refers to the separation of logical
storage from physical storagetogive greater flexibilitytouse
the storage irrespective of the physical storage. The File
Virtualization eliminates the dependencies betweenthedata
accessed and the physical location of the file to optimize
storage utilization.
Software Virtualization
Figure 5 Types of Software Virtualization
Software virtualizationcreatesvirtualsoftwareinstallations.
Benefits of software virtualization include easy client
deployments, easy updating of software and easy software
migration, security, centralized management of virtualized
software, etc. The disadvantage of software virtualization is
the extra overhead of packaging software; virtual software’s
may require more resources regarding storage and CPU, etc.
Software virtualization is of two types - high-level language
virtualization and application virtualization as shown in
Figure 5.
The high-level virtualization solves themigrationproblemof
executable programs between different architectures, while
as application virtualization improves themanageabilityand
compatibility of applications.
From the above discussions, it is evident that virtualization
can be applied to a wide range of devices and resources
starting from servers to desktopstotinydevicesand storage,
network resources, and applications; the main goal is the
management of resources.
4. INTERNET OF THINGS
Internet of Things is the interconnection of billions of
physical objects that are connected to the Internet [19]. The
“objects” deployed in IoT systemsincludeRFIDtags,sensors,
actuators, etc. These objects (devices) sense and aggregate
the data to provide services to the end user. SinceInternet of
Things aims to embed higher level of Intelligence to the
objects which otherwise are dumb, therefore it is evident
from that IoT is transforming a physical world into a virtual
world where anything can communicateintelligently.Figure
6 depicts an environment of the Internet of Things.
Figure 6 IoT Environment
According to the Gartner Report, the number of
interconnected things in IoT is likely to reach 20 billion by
2020. Figure 7 shows the number of devices estimated and
expected in the Internet of Things [20].

Other aspects of the Internet of Things have been discussed
in the following subsections:
IoT Applications
IoT Architectures
Resources on the Internet of Things
Virtual IoT
Figure 7 Number of Devices Connected Globally Versus a
Year
IoT Applications
Internet of Things provides a number of applications that
covers several domains such as healthcare, automotive,
security, smart environment, road monitoring, etc. as
discussed in Table 1.
IoT
Applications
Techniques
Smart
Agriculture
IoT sensors can be deployed across
multiple areas to facilitate remote
monitoring of soil parameters and
perform other agriculture-related
tasks.
Smart
HealthCare
Wearable IoT sensors can also be
used to monitor patients remotely.
Smart
Education
Internet of Things can also help in
optimal learning in the education
sector.
Environment
Monitoring
IoT devices can be used in the
remote monitoring of
environmental parameters such as
temperature, humidity, etc.
Smart Energy
Internet of Things also finds its
applicability in energy management.
Water Quality
and Dam Water
Monitoring
Real-time monitoring of water
quality with IoT sensors can also be
done.
Disaster
Mitigation
Multiple sensors can be deployed to
reduce the influence of disasters on
our ecosystem.
Road
Monitoring
Roads can be monitored by various
built-in IoT sensors in the vehicles.
Traffic
Monitoring
IoT can also find its applicability in
monitoring traffic in smart cities.
Table 1 IoT based Applications
IoT Architectures
A lot of research has been done on the IoT architectures to
find one reference architecture for all applications, but IoT
encompasses an extremely wide range of technologies,
therefore, a universal architecture cannot be used as a
blueprintfor all possible IoT implementations.Generally,IoT
architectures can be classified on the basis of layers present
in a particular architecture. Table 2 presents an overview of
layered architectures used in various IoT implementations.
IoT
Architecture
Layers
Three-layer
Architecture
Perception Layer interacts with IoT
nodes to collect,processandtransmit
the processed data into the upper
layer,
Network Layer determines the
routes to transmit the data to IoT
applications,
Application Layer receives the data
transmitted from the network layer
and uses the data to providerequired
functions.
Four-layer
Architecture
Perception layer,
Network layer,
Service layer,
Application layer,
The extra layer being service layer aims
at the discovery, composition, and
management of services.
Five-layer
Architecture
Perception layer,
Network layer,
Processing layer,
Application layer,
Business layer,
The role of perception, network and
application layers is the same, but the
additional layers add more functionality
such as the processing layer stores,
analyzes, and processes huge amounts of
data. The business layer manages the
applications, business, and privacy of
users.
Six-Layer
Architecture
Coding Layer,
Perception Layer,
Network Layer,
Middleware/ Processing Layer,
Application Layer,
Business Layer,
The five layers perform the same
functions as in five layered architecture;
the role of the coding layer is to provide
identification to the IoT objects.
Table 2 Layered Architectures of IoT
Figure 8 shows a general architecture of the Internet of
Things.
Figure 8 General Architecture of IoT

Resources in Internet of Things
With the advancements in embedded technology, the
processingpower of IoT devices is increasingday by day.For
any IoT device to process the collected data without relying
on any powerful infrastructure, it needs storage space for
data processing algorithms [21], which is limited in case of
IoT devices. Further, the processing capability and
networking is dependent upon the availability of energy,
which is also limited in IoT devices. Inadditiontothis,theIoT
devices have limited bandwidth; therefore inefficient
management of bandwidth imposes more constraint on
energy, storage, and processing requirements in IoT
environments [22]. Thus, it is evident that IoT devices are
constrained in terms ofresources.
According to RFC7228, constrained nodes are classified into
Class 0, Class 1 and Class 2 (See Table 3).
Class Memory
Flash
Processing
Battery Examples
0 10kb <100kb Yes
Push
button
1 10kb 100kb Yes
Environ-
mental
sensors
2 50kb 250kb Yes
Power
Meter
Table 3 Class of Constrained Nodes
A typical IoT device is equipped with 8/16 microcontrollers,
a very little storage, and an IEEE 802.15.4 radio that enables
wireless networks [23].
Virtual IoT
Nowadays, the Internet of Things is growing at an enormous
rate, and its accessibilitytothecommonmanisincreasing.As
such it enables more and more data to be collected for
processing and analysis. To support various intelligent
applications, IoT utilize sits physical resources such as
storage, processing, energy, and communication. Since these
resources are limited, itposes manychallengesinapplication
environments which in turn demands management of these
scare resources in Internet of Things. Virtualization is
considered as one of the possible means that can take care of
resources in IoT environments. The idea is to integrate the
real world with the virtual one to increase the access to new
possibilities in Internet of Things that could forecast past,
present and future. Research in this area is in progress.
5. VIRTUALIZATIONFORIoT RESOURCEMANAGEMENT
Internet of Things is a novel paradigm that has gained
momentum in the past few years. It is actually a worldwide
network of interconnected things that are characterized by
high degree autonomous activities such as data sensing,
storage, and communication. The devices in Internet of
Things can be classified into resourceful and resource
constrained devices depending on the resourcesavailable in
a particular device. The limited resources with
heterogeneous characteristics of IoT devices becomes a
major challenge, as such, there is a need of need of special
attention towards on how to manage the resources. IoT
presents the biggest challenge to network designers on how
to manage the number of devices and their connections, the
surplus amount of data generated by IoT devices, and
resource consumption such as memory, processing,
bandwidth, and power consumption [24]. Virtualization
plays a dominant role to manage resources in such
environments and is considered to be one of the approaches
to addresses such limitations especially resourcelimitations
in IoT. Thus, virtualization provides a better solution for
networks to deliver the resources necessary for IoT to
eliminate the need for network infrastructures.
There has been recent work on virtualization in Internet of
Things to optimize its resources and improve its network
design. Work has been done to standardize and virtualize
IoT devices and its resources through OpenFlowtechnology
[25]. Lightweight virtualization has been carried out to take
the limited resources in IoT, the most common being the
container-based virtualization which includes Docker and
LXC containers. Container-based virtualization iscommonly
adopted on IoT devices and benefits include fast creation
and initiation of virtualized instances, high density of
applications, reduced costs, improved software quality,
decreased design time, and reduced overhead as compared
to hypervisor-based approach (See Figure 9).
Figure 9 Container-Based Virtualization and Hypervisor-
Based Virtualization Architectures
IoT is a complex paradigm consisting of interconnected
heterogeneous devices ranging from servers to desktop to
tiny devices which includes wireless sensor motes, fog
devices, mobile devices, etc. Like IoT devices, WSN nodes,
mobile devices, and edge/fog devices are resource
constrained in task-intensive applications that demand
deployment of a hugenumber of devices andgeneratealarge
volume of data. And resource management is an essential
step that needs to be explored in such devices as well.
Considerable work has been done on resource management
in Mobile Computing, Wireless Sensor Networks, and Fog
devices. Resource managementisanessentialstepthatneeds
to be explored in such devices as well.
Mobile devices are an integral part of many IoT applications
that deal with the transmission of data, without having to be
connected to a fixed physical link. Since mobile devices are
resource limited in applications and generate an enormous
amount of data, an offloading mechanismisrequiredthatwill
send the computations to the remote server or cloud to
balance the resource-constrainednatureofsuchdeviceswith
application requirements (see Figure 10).
Figure 10 Offloading in Mobile Devices

Many virtualization approaches play an important role in
offloading tasks to manage the resources of mobile devices,
and these include Cuckoo, Cloudlet, Think Air, etc.
WSN devices are an integral part of IoT applications capable
of sensing, computing and communicating data to monitor
the environment (see Figure 11).
Figure 11 Wireless Sensor Network Architecture
However, there are limitations in WSNs devices such as
limited computation, memory and communication
capabilities that affect the performance of the system.
Adoption of virtualizationtechnologyinWSNshaseliminated
these drawbacks.Virtualizationabstractsphysicalcomputing
resources into logical units to have efficient utilization of
deployments in WSN [30]. WSN devices and networkscanbe
virtualized to enable multiple applications to run their tasks
concurrently on a single sensor node or a single network so
that it becomes multi-purpose. Software Defined Networks
(SDN) is one of the platforms for network virtualization in
WSNs and provides benefits such as reduced deployment
costs, scalability, versatility, andotherresourcemanagement
benefits.
There has been a recent trend towards virtualization in fog
platforms to manage the limited resources in Internet of
Things. Fog computing extends cloud servicestothenetwork
edge. Figure 12 shows the architecture of Fog Computing.
Computational offloading is one technique that takes care of
constrained resources in IoT at the node level and network
level by pushing the computation towards the Fog devices.
Benefits include high data accuracy, improved Quality of
Service, reduced latency, etc., buttherearevariousissueslike
security, privacy, trust, and service migration in Fog
platforms. Virtualization can play a dominant role in Fog
computing to resolve some of these issues.
Figure 12 Fog Computing Architecture
Since, various operations such as storing and processing of
data between the cloud and enddevicesareperformedbythe
fog, therefore, itautomaticallyhelpsinresourcemanagement
of IoT. Many approaches can be used toperformoffloadingin
Fog computing and virtualization is one of them. By
incorporating virtualization at the network edge, there is an
option to push computation to the network edge. Using
virtualization, Fog platforms get multiple functions into a
single device that enables various virtualized devices to co-
existon multiplemachines and this, in turn,helpsinresource
management in Internet of Things.
6. CHALLENGES
Internet of Things consists of resource-constrained IoT
devices such as storage, computational power,
communication, etc. To make optimal use of the resources,
virtualization can play a key role. However, the distributed
and ad hoc nature of the IoT systems poses many challenges
to virtualization as discussed below: Identification of IoT
devices in a Network: In virtualization of IoT devices, proper
identification, naming, and addressing of these virtualized
devices is a major challenge, since the number of devices in
an IoT environment is huge.
Heterogeneity: IoT environment is a very complicated
heterogeneous network platform, and management of
such a high level of heterogeneity at both architectural
and a protocol level is also a major challenge.
Performance issues: Virtualization in IoT devices
causes saturation of the network that affects
performance, bandwidth, and latency.
Managing huge number of IoT devices in a network: As
the number of devices increases in a network, the
number of virtual devices increases in multiples of an
actual number, as a result, unified information
infrastructure is required to manage such number.
Manage Complex Data: A huge number of connected
virtual devices in the IoT environment produce data in
a variety of form. Managing this IoT data is a major
challenge in virtualization.
Standardization: Standardization in virtualization is
another challenge; standards need to be evolved with
the emergence of virtualization while designing other
technologies at a horizontal pace.
Security: The larger number of virtual devices in the
IoT application increases the attack surface, with the
result the need for security becomes a major concern.
7. CONCLUSIONS
The increased role of the IoT devices in our daily life leads to
data explosion and demands improved processing,
connectivity, and analysis of the data generated. The huge
number of IoT devices and the surplus amount of data
generated by these devices becomes the major concerns in
such environments. Virtualization in different forms can be
applied tosuch IoT environments todealwithalargeamount
of data generated by these devices. The voluminous data in
IoT applications has forced the offloading of computations
from IoT devices to the Fog devices or cloud platforms. The
offloading of the computational load from the IoT devices to
edge devices or fog is possible by virtualization.
Virtualization in different forms can also be applied to IoT
devices to deal with the huge amount of data generated by
them. Network virtualization also plays a key role in dealing
with such inherent complexity in Internet of Things.
Virtualization increasestheefficiencyofcomplexIoTsystems
to optimize their limited resources. It reduces the number of
physical IoT devices by making virtual images of devices,
which intern reduces the cost and improves hardware
utilization, hence leads to better management of limited
resource in IoT environments.

IoT environments have adopted virtualization to meet
various challenges such as a large amount of data, a huge
number of devices,deviceheterogeneity,performanceissues,
and resource management. The volume of heterogeneous
data is growing rapidly and handling such data requires the
managementofmultipledatastoresincomputation-intensive
IoT applications. Virtualization provides an added level of
efficiency to make low-cost IoT application services in our
day-to-day life, a reality.
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