TUW-ASE-Summer 2015: Advanced Services Engineering - Introduction

Advanced Services Engineering-
Introduction
Hong-Linh Truong
Distributed Systems Group,
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://dsg.tuwien.ac.at/staff/truong
1ASE Summer 2015
Advanced Services Engineering,
Summer 2015
Advanced Services Engineering,
Summer 2015

Outline
 Why do we need a course on advanced services
engineering?
 What is the course about?
 Course administrative information
ASE Summer 2015 2

ASE – current trends (1)
 „Big“ and „small“ data
 High performance, scalable data analytics at data centers
 Hybrid data analytics
 Data marketplaces
 Cloud and service computing models
 Enable dynamic and flexible data and service
provisioning/integration
 Human computation
 Human services for complex computation and analytics
 Crowdsouring and collective adaptive systems
ASE Summer 2015 3

ASE – current trends (2)
 Internet of Things (IoT)/cyber-physical systems
 Integration and virtualization of sensors/actuators, edge
networks
 Dependability, performane, security and privacy issues
 IoT and cloud integration  IoT cloud systems
 Dealing with sensors/actuators and gateways integration
with cloud data centers
 Social-physical clouds
 Core elements: software, people and things
 Systems: human computation platforms+ IoT platforms +
cloud systems
ASE Summer 2015 4

ASE – complex requirements (1)
 Big and near real-time data must be handled in a timely
manner to extract insightful information
 Cross-boundary, Internet-scale computational, data and
network services integration must be done
 Complex applications/sytems executed atop multiple, diverse
computing environments
 Data centers/cloud infrastructures, IoT systems, human
computation environments, etc.
 Multiple concerns wrt quality, regulation and cost/benefits
must be assured.
 Flexible and dynamic management, e.g., software-defined
and elastic capabilities
ASE Summer 2015 5

ASE – complex requirements (2)
ASE Summer 2015 6
 We want to have a coherent, uniform view
of diverse types of resources and platforms
 We want to coordinate capabilities of these
resources and platforms
 Engineering Internet-scale service-based
systems for these requirements is very
challenging

ASE -- application examples (1)
ASE Summer 2015 7
Equipment Operation
and Maintenance
Equipment Operation
and Maintenance
Civil protectionCivil protection
Building Operation
Optimization
Building Operation
Optimization
Cities, e.g. including:
10000+ buildings
1000000+ sensors
Near
realtime
analytics
Near
realtime
analytics
Predictive
data
analytics
Visual
Analytics
Enterprise
Resource
Planning
Enterprise
Resource
Planning
Emergency
Management
Emergency
Management
Internet/public cloud
boundary
Organization-specific
boundary
Tracking/Log
istics
Tracking/Log
istics
Infrastructure
Monitoring
Infrastructure
Monitoring
Infrastructure/Internet of Things
......

ASE – application examples -
2012 (2)
ASE Summer 2015 8
A lot of input data (L0):
~2.7 TB per day
A lot of results (L1, L2):
e.g., L1 has ~140 MB per
day for a grid of
1kmx1km
Soil
moisture
analysis for
Sentinel-1
Michael Hornacek,Wolfgang Wagner, Daniel Sabel, Hong-Linh Truong, Paul Snoeij, Thomas Hahmann, Erhard Diedrich, Marcela Doubkova,
Potential for High Resolution Systematic Global Surface Soil Moisture Retrieval Via Change Detection Using Sentinel-1, IEEE Journal of
Selected Topics in Applied Earth Observations and Remote Sensing, April, 2012
Data-as-a-Service
and Platform-as-a-
Service in clouds
Data-as-a-Service
and Platform-as-a-
Service in clouds

ASE – application examples - 2015
(3)
ASE Summer 2015 9
See: https://www.eodc.eu/

ASE – application examples (4)
ASE Summer 2015 10
Source: http://www.undata-api.org/
Source:
http://www.strikeiron.com/Catalog/StrikeIronServices.aspx
Source: http://docs.gnip.com/w/page/23722723/Introduction-
to-Gnip

ASE – complex, diverse and elastic
properties
 Different platforms and multiple services from multiple
providers for multiple stakeholders
 Complex service-based systems
 Not just big data in a single organization which can be dealt by
using, e.g., MapReduce/Hadoop
 Not just take the data and do the computation: how to guarantee
multitude of data/service concerns
 Not just things and software: we need human services
 Not just local actions: we need coordination-aware techniques
 Quality of analytics results are elastic: they are not
fixed and dependent on specific contexts!
ASE Summer 2015 11

ASE – relevant courses
 Existing courses provide foundations
 Advanced Internet Computing
 Give you some advanced technologies about SOC, Cloud
Computing and (business) processes/workflows
 Distributed Systems
 Give you fundamental distributed system concepts and
technologies
 Distributed Systems Technologies:
 Give you fundamental technologies and how to use them
 But they do not deal with engineering such large-scale,
complex service-based systems
 Big, near-realtime data and complex service integration are the
driving force!
ASE Summer 2015 13

ARE YOU WORKING ON SUCH
SYSTEMS? ARE YOU
CONVINCED THAT THIS
COURSE IS SUITABLE FOR
YOU?
Questions
ASE Summer 2015 14

What is the course about? (1)
 Discuss new concepts and techniques for engineering
advanced, Internet-scale, elastic service-based
systems
 Focus on service systems for complex data analytics,
programming elasticity, and principles for engineering
IoT cloud systems and for social-physical cloud systems
 Consider a wide range of applications for real-world
problems in machine-to-machine (M2M), science and
engineering, and social media
ASE Summer 2015 15
We research and explore emerging techniques!We research and explore emerging techniques!

What is the course about? (2)
ASE Summer 2015 16
Big/realtime
Data
Big/realtime
Data
Data
Provisioning
Data
Provisioning
Data
Analytics
Data
Analytics
Quality of data -/Quality of Result - aware workflow design and optimizationQuality of data -/Quality of Result - aware workflow design and optimization
Service engineering and integration in multiple cloud environmentsService engineering and integration in multiple cloud environments
Hybrid software-based and human-based service systems engineeringHybrid software-based and human-based service systems engineering
•IoT cloud platforms
•Data concerns,
•Data concern monitoring
and evaluation
•IoT cloud platforms
•Data concerns,
•Data concern monitoring
and evaluation
•Data-as-a-service
(DaaS)
•Data Marketplaces
•Data Elasticity
•Data-as-a-service
(DaaS)
•Data Marketplaces
•Data Elasticity
•Principles of big data
analytics
•Hybrid software and human-
based services
•Multi-cloud analytics
services
•Principles of big data
analytics
•Hybrid software and human-
based services
•Multi-cloud analytics
services
Focus
Topics
Science, social, business, machine-to-machine and open dataScience, social, business, machine-to-machine and open data

References for the course
 No text book designed for this course
 Some references from recent scientific papers
 Relevant research in big data
 But not very much on data management or individual
data processing framework (e.g.,
MapReduce/Hadoop)
 Relevant work in Internet of Things, People and
Software integration
 Distributed and Cloud Computing
ASE Summer 2015 17

Course administration (1)
 Lectures are held through the whole semester
 But not every week – check the course website!
 Technical assistants when using COMOT/iCOMOT:
 Daniel Moldovan (d.moldovan@dsg.tuwien.ac.at)
 Duc-Hung Le (d.le@dsg.tuwien.ac.at)
 http://tuwiendsg.github.io/
ASE Summer 2015 18

 Who could participate?
 Master students in advanced stages (e.g., seeking for
master thesis) in informatics and business informatics
 PhD students: PhD School of Informatics, Doctoral
College of Adaptive Systems
 Students should have knowledge about fundamental
distributed systems, internet computing and
distributed computing technologies
ASE Summer 2015 19

 Learning methods
 Discussion, individual and team work, design,
engineering and evaluation actions
 Evaluation methods
 Assignments, a mini project and a final examination
 Assignments
 4 home assignments resulting in some
design/deployment and analysis summaries
 Mini project
 One mini project resulting in a small
prototype/conceptual design
 Oral final exam
ASE Summer 2015 20

Grades
 Participations + discussions: 10 points
 Assignments: 40 points
 Mini project: 20 points
 Final oral examination: 30 points
ASE Summer 2015 21
Point Final mark
90-100 1 (sehr gut)
75-89 2 (gut)
56-74 3 (befriedigend)
40-55 4 (genügend)
0-39 5 (nicht genügend)
Failed ?  retake the final oral examination part!

THANKS! ANY QUESTION?
ASE Summer 2015 22

23
Thanks for
your attention
Hong-Linh Truong
Distributed Systems Group
Vienna University of Technology
truong@dsg.tuwien.ac.at
http://dsg.tuwien.ac.at/staff/truong
ASE Summer 2015

TUW-ASE-Summer 2015: Advanced Services Engineering - Introduction

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TUW-ASE-Summer 2015: Advanced Services Engineering - Introduction