Robert van der Drift
Call for Proposals: Big Software
Software in the Big Data era
Programme
13:00
Registration
13:30
Introduction Big Software
Robert van der Drift, Head of Computer Science (NWO)
13:45
Michiel van Genuchten (COO Vital Health Software)
‘The Impact of Software’
Jurgen Vinju (Professor Technische Universiteit Eindhoven
and group leader Centrum Wiskunde & Informatica) –
’
Challenges and Opportunities of Big Software-based
Innovation’
14:15
Start Pitch & Match sessions
Introduction Big Software
Robert van der Drift
NWO’s role in research funding
Ministry of Education, Culture and Science Ministry of Economic Affairs, Agriculture and Innovation other ministries(e.g. Health, Foreign Affairs, Infrastructure & Environment)
private sector and public organisations
direct government funding
indirect government funding
universities
(incl. medical centres)
NWO institutes
other knowledge
institutes
2,3 Bn€ 500 M€ 4The Challenges of Big Software
•
Individual systems have grown to millions of lines of code built from
many different technologies. Such systems have come to be known as
'legacy systems' -- systems that resist change.
•
Systems have become more and more inter-dependent, relying strongly
on third party components and services, giving rise to systems-of-
systems.
•
The operational context and actual use of software systems has become
increasingly complex and unpredictable.
•
In combination, it is increasingly hard to develop software that is
reliable, efficient, secure, and evolvable in a timely and cost-effective
manner.
Big Software welcomes ground-breaking research addressing these
challenges.
Who can apply
•
Professors, associate professors and assistant professors as well as
other senior researchers can apply if they:
– are employed at a Dutch University or a research institute
recognised by NWO, and
– have at least a master’s degree in science or engineering or an
equivalent qualification, and
– have an employment contract for at least the duration of the
application procedure and the duration of the research the grant
is applied for.
Role industrial partner(s):
•
In the project application the industrial and/or public partner(s) must
be listed as a co-applicant.
Business value for industrial partner(s)
•
Be involved in innovation projects as your part of innovation strategy
•
Gain access to state-of-the-art research and excellent research
groups, knowledge and results to be used in product development
•
Meet potential future employees who are the top talents in their
Type of project
Project team
Funded by
Contribution
Appointed through
2 researchers
(PhD-students or
postdocs)
1 funded by industrial
and/or public parties
1 funded by NWO
In cash
University
2 researchers
(PhD-students or
postdocs)
1 funded by NWO
1 fte – max 2
employees by
industrial and/or public
parties
In kind
University and
participating partner(s)
1 PhD-student or
postdoc
50% funded by
industrial and/or public
parties
50% funded by NWO
What can be applied for
a)
Hiring PhD’s and/or 2-year or 3-year postdocs based on fulltime position,
(incl. bench fee of € 5,000).
b)
Project-related equipment/software provided the costs are more than €
5,000.
c)
Other project activities, such as knowledge transfer, valorisation, and
costs to cover non-scientific personnel, travel/accommodation guest
lecturers and organisation of meetings/symposia.
Maximum budget for project-related equipment (b) and other project
activities (c) is no more than 10% of the total project costs, which will be
covered for half of the budget – 50%- by NWO. The other half – 50% -
should be covered by the partner(s)
Not eligible for funding:
•
Costs for computers, standard software and other costs which are
standard facilities of research institutes
When can be applied
•
The closing date for the submission of application to NWO is
Tuesday, 15 September 2015
,
14.00 hours
(CET + 01:00).
Application consists of:
•
Fact sheet (available at Iris system)
•
Application form – in English
•
Letter(s) of Commitment (LoC) – a pledge of financial support
Criteria
•
Scientific quality
•
Quality of the consortium
•
Knowledge utilisation
More information can be found in Call for Proposals (chapter 4.2).
Timeline procedure
Submission
Full Proposal
Peer
Review
applicant
Rebuttal
Assess-
ment
Decision
15 Sept,
Contact
Robert van der Drift
Head of Computer Science
Tel. +31 (0)70 – 344 07 75
[email protected]
Rosemarie van der Veen-Oei
Programme manager
Tel. +31 (0)70 – 344 05 87
[email protected]
More information?
Programme
13:00
Registration
13:30
Introduction Big Software
Robert van der Drift, Head of Computer Science (NWO)
13:45
Michiel van Genuchten (COO Vital Health Software)
‘The Impact of Software’
Jurgen Vinju (Professor Technische Universiteit Eindhoven
and group leader Centrum Wiskunde & Informatica) –
’
Challenges and Opportunities of Big Software-based
Innovation’
14:15
Start Pitch & Match sessions
Michiel van Genuchten
09/07/2015
30 columns in 2010-15
ASML, Bosch, RealNetworks
Philips, Honeywell
Hitachi, Uni of Queensland
Tomtom, Fujixerox
Microsoft, Shell
CERN, Oracle, Airbus, JPL,
Lint, Bayesian networks,
Vodafone India
09/07/2015
“To date, no significant
anomalies have revealed
themselves
LINT
Mobile
apps
Mars
Cabin swairplane kernel
l
lander
09/07/2015Tokyo
railway
CERN
boson
MM
player
1
100
10k
1M
100M
Volume or
unique users
in #/year
100M
10M
100K
1M
10K
Size of sw
in LOC
ECU
CAR
MR
scanner
Airplane FMS
Workflow
engine
Car
Navigation
ASML
Oil
exploration
Solaris
Bayesian
Tanzania
Compound Annual Growth Rate for sw
•
Software seems to be growing with about 18 % a year
•
Irrespective of application, technology a.s.o.
•
Analysed 50 MLOC closed and 500 MLOC open source
–
No statistical difference in CAGR between the two
•
Relevant for both theory and practice
Genuchten, Hatton, IEEE Software, 2012, IEEE Computer 2013
Genuchten, Hatton, Spinellis, to appear, 2016
09/07/2015
sales volume and software size
14000000
12000000
10000000
8000000
6000000
4000000
2000000
0
2004 2005 2006 2007 2008 2009 2010 2011
year
sales volume
lines of code
sa
les
v
o
lu
m
e
14000000
12000000
10000000
8000000
6000000
4000000
2000000
0
li
n
e
s
o
f
c
od
e
Suggestions for research
To be falsified
•
Defect free ‘rocket science’ software exists
•
Software grows with about 18 percent a year
•
It’s software economics, stupid!
Also to be investigated
•
'legacy-systemen' - ongevoelig voor veranderingen - No
•
Quantifying the benefits of next gen sw technology
•
Explain the 1.18 growth rate (we have some ideas)
Jurgen Vinju
Center for Mathematics and
Computer Science
S
oftware Analysis And Transformation
Challenges and Opportunities of
Big Software-based Innovation
Jurgen J. Vinju
Centrum Wiskunde & Informatica
TU Eindhoven
INRIA Lille
Big Software Matchmaking Day
July 1st, 2015
Go Big Software!
The Software Medium
Erasmus
The Software Medium
The Software Medium
Internet
Tim
Berners-Lee
The Software Medium
yesterday’s ICT inventions
+
more and better software
=
Software
The Innovation Engine
•
from risky products to exploitable services
•
cost-of-development -> cost-of-ownership
•
big bang release -> incremental update
•
from pricy consultants to valuable experts
•
outsourcing -> core business
•
from quantity & complexity to quality & fl exibility
•
constraining people -> supporting people
Netherlands = Software
•
Programming
Languages
•
Formal Methods
•
Components &
Modules
•
Agile Processes
•
Operating Systems
•
Distributed Computing
•
Domain Specifi c
Languages
•
Model Driven
Engineering
•
Software Architecture
•
Database technology
•
Software Analytics
•
Software Testing
The Netherlands:
a global leader in
software and software
engineering
Big Software
•
Big Code
•
Big Process
•
Big Logs
•
Better Code
•
Better Process
•
Better Products
Research
Complexity => Opportunity
[
http://comphacker.org/comp/engl338/2015/01/28/visuals-of-wicked-problems/
]
Contextual Software Research
•
Great software and software research is contextual, tailor-made
•
Expert, local, domain knowledge is key to success
•
“Premature [generalization] is the root of all evil”
•
Focus on local urgency and local success factors
[Escher]
collaborate
for the
Contextual Software
Research
•
Building up general SE theory & methods as we go
•
The goal is incremental, but defi nite, improvement in SE
•
Disruptive innovation is
enabled
by better software engineering
•
Back to common sense;
stop following the hype
•
Use yesterday’s and today’s assets and experience
what if?
•
time-to-market one month sooner?
•
20% fewer bugs after initial release?
•
50% of the unused features not even
developed?
•
developers working on features, not bugs?
•
legacy code an asset instead of a risk?
how?
research!
Cross-cutting Contexts
•
Software Contexts are not silo’ed in industrial or public sectors
•
Example
: High-end Financial Services and Embedded Systems
•
High effi ciency
•
High integration complexity (third-party)
•
High product/service variability
•
Example
: Distributed (Big) Data and Meta Programming Systems
•
Intermediate formats
•
Marshalling and transformation
Software for Software
•
Research methods built as (re)usable software
•
automated data collection, analysis, reporting
•
code, process, trace analyses
•
questionnaires & monitors
•
Proof-of-concepts built as software
•
analyzing, transforming, generating, visualizing
•
integrated into existing environments & processes
•
There is no fi eld like ours where knowledge transfer {c,sh,w}ould be
organized so directly and faithfully, in either direction
•
only if research has
access
to the real code, real processes and real logs
•
only if industry has
access
to full and automated methods and experiments
CWI SWAT
•
Preventing and curing software complexity to enable higher quality
software systems, using automated software engineering methods
•
Know-how
•
language engineering
•
source-to-model
•
model-to-source
•
source-to-source
•
mining repositories
•
continuous delivery
•
distributed components
•
Domains
•
embedded systems
•
administrative
•
fi nancial
•
games
•
Connected & collaborative
•
research & education
•
industry & government
Roadmap ICT
•
Roadmap ICT draft has a
fi rst class software theme
•
“
reliable & fl
exible software systems”
•
Needs your voiced support
•
Stake our claim that software is a leading factor
•
economically
•
socially
•
academically
Yearly
Inclusive
Excellent speakers
Topical posters
Discussion
Networking
Thursday
December 3rd
Amsterdam
SWAT - S
oftWare Analysis And Transformation
Big Software
a new start for long term collaboration
Andy Zaidman
Software Engineering
Andy Zaidman
Big Software Matchmaking Event
July 1, 2015
Software
Analytics
Software
Artifacts
People
Running
System
•
How to improve reliability, maintainability, …?
–
Should we do code reviewing, static analysis, …?
–
How should we test?
•
What should we do with our technical debt?
–
Do components with biggest business value change
more, show more bugs, …
TU Delft coordinating initiative
for research, education and
training in data science and
Domain-Specific Languages:
enabling software engineers
to systematically design & apply DSLs
Cloud Programming:
composing computations using
mathematically solid foundations
reactive extensions interactive extensions
Software for Data Science
Enabling programmability of
big data analytics
Problem: programming multi-core distributed cloud machines with Von Neumann programming languages Solution: programming languages that abstract from hardware, close to domain experts Problem: data engineers and
scientists not trained as software engineers
Derek Karssenberg
PCRaster Research Team – Derek Karssenberg
Faculty of Geosciences, Utrecht University
Geocomputation: simulation of land surface processes
Domains:
• Hydrology (e.g. river flows)
• Land use change (e.g. bioenergy expansion)
• Effects of environment on health (e.g. exposure to air pollution)
Objectives:
• Develop concepts and software frameworks
• Distribute software: PCRaster
Team:
• Software engineers (C++) and PhD students in geoinformatics
• Domain specialists (water management, health, human geography)
Models should be programmable by domain specialists
• Domain specialists (e.g. hydrologists) are the model builders
• Need for software providing the building blocks
Challenges: (1) modelling heterogeneous systems
Problem:
Lack of concepts and software frameworks integrating fields and
agents
Challenges: (2) scalability
• Big data (e.g. remote sensing) is input to models
• Requires concurrent execution of models (parallelization, CPU, I/O)
Problem:
Lack of software framework that allows models built on desktop
computers to be run on in a high-performance computing environment
(without modification)
Our solution
www.pcraster.eu
Model building framework with built-in support for:
•
Agents
and
fields
Looking for new project partners (companies, research inst.)
• Our team develops concepts and/or software framework
• Partner provides problem from a particular domain, e.g.
• Health & environment
(possibility to join Global Geo Health Data Centre in Utrecht)
• Water management
• Ecology
• Crop growth, bioenergy
• Sensor networks
• …
Contact:
Derek Karssenberg
[email protected]
http://www.pcraster.eu
www.pcraster.eu
Mark Roest
1-07-15
• Established in 1996
• Around 25 employees, with academic background in mathematics and IT
• About 2/3 with a PhD
• Located in Delft
•
1-07-15
VORtech – Services
Scientific software engineering
Developing scientific software
Accelerating and improving scientific software
Consultancy on scientific software and mathematics
Maintenance of scientific software
Specific expertise
•
High Performance Computing
31-01-12
Typical customer code (no relevant proprietary code):
50k to more than 1M lines of code
Fortran, C, C++, Pascal/Delphi
1Mb – 4Gb data files
Interest to learn about techniques for modernization, porting
Possible role as intermediary to customers with case studies
Mark Roest
[email protected]
06-4478 4413
Yanja Dajsuren
Centre for Mathematics and
Computer Science
Modernizing Big Legacy Software
Yanja Dajsuren, CWI
NWO Big Software Matchmaking Event
01-07-2015 Utrecht
Legacy software
•
Different modeling language
•
Different platform
•
More powerful hardware
Reo
Contact for comments and collaboration:
Tel:
+31(0)20 592 4007
Email:
[email protected]
Address:
Centrum Wiskunde&Informatica
Science Park 123
1098 XG Amsterdam
Patricia Lago
SIMPLE:
So*ware Innova1on in
coMPLex Eco-‐systems
Research partners
•
Patricia Lago (VU)
•
Paul Grefen & Maryam Razavian (TU/e)
•
Marcel Worring (UvA)
Industrial partners (in kind or poten1al)
•
Serge Hollander (OMALA)
•
Sander Klous (KPMG)
•
Maikel Bouricius (GreenIT Amsterdam)
•
?
The Context
9 IS SUE 2: 2015
MORE CONTROL
PLEASE…
CON N ECTED TRAVELERS : S ELF S ERVICE
IN THE ERA OF CONNECTED TRAVELERS, SELF-SERVICE AND MOBILITY ARE KEY UNDERPINNINGS IN THE EVOLVING RELATIONSHIP WITH PASSENGERS.
22 AIR TRANSPORT IT REVIEW 22 AIR TRANSPORT IT REVIEW 22 AIR TRANSPORT IT REVIEW
GATEWAY TO
THE INTERNET
OF THINGS
AS WE STEP TOWARDS THE INTERNET OF THINGS, BEACONS ARE PROVING TO BE A CRUCIAL PART OF THE MIX IN GETTING PROXIMITY AND CONTEXT INFORMATION TO MOBILE DEVICES.
AIR TRANSPORT IT REVIEW 22
CONNECTED TRAVEL: PROXIMITY
The Context
A Big-‐so*ware environment is [K. Dorst]:
–
Open
: degrees of visibility and transparency (data,
services)
–
Dynamic
: Con1nuous change (evolving requirements,
technologies, opportuni1es)
–
Complex
: Shared benefits and shared responsibili1es
–
Networked
: Mul1ple stakeholders
A field never explored before
The Problem
•
How to create so*ware that realizes sustainable
innova1on
in such a complex environment?
–
Miss opportuni1es (novel business, iden1fy shared
op1miza1ons, predict emerging markets)
–
On economic, social, environmental
sustainability
•
What is the data (so*ware proper1es, influencing
changes, contextual factors like usage) that should be
gathered to support sustainable
change
–
Miss opportuni1es (iden1fy changing requirements,
perform technological adapta1on)
–
On technical
sustainability
The SIMPLE Approach: ingredients
Visual Analy1cs
4 Reasoning & Decision Making
BASE-‐X: iden1fy innova1on opportuni1es
4 complex eco-‐systems
So*ware and Service Engineering
4 sustainability
Look for co-‐Funding for 2 PhD
candidates
Visual analy1cs 4 SIMPLE so*ware
So*ware
Engineering
4
Big-‐so*ware
environments
Design Decision
Making
4
Sustainable
innova1on
Alexandru Iosup
1
@AIosup
dr. ir. Alexandru Iosup
Parallel and Distributed Systems Group
Won IEEE Scale Challenge 2014!
Scalable + Available +
High Performance
Parallel and Distributed
2
The Parallel and Distributed Systems group
Fun, International, Visible Team
also, Award-Winning
Join us in 2015!
3
Scientific Challenges for a Golden Age in ICT
How to massivize ICT?
• Super-scalable, super-flexible, yet efficient ICT infrastructure
• Data-driven feedback loops for end-to-end automation of large-scale processes
• Understanding actual use of dynamic, compute- and data-intensive workloads
• DevOps for evolving, heterogeneous hardware and software
4
Big Software for clouds and big data
• Data-driven feedback loops for scalable, high-performance, efficient operation
• Meaningful operational logs, including performance and reliability data
• Open-source software stacks for cloud computing and big data processing,
including Hadoop / Spark, Giraph / other graph-processing systems
• Continuous (re-)deployment of systems of systems (deep stacks)
• Analysis and action based of heterogeneous datasets and user requirements
• Analysis of trust and privacy in distributed stacks
• Benchmarking clouds and big data
[email protected]
+31-15-2784433
@AIosup
http://pds.twi.tudelft.nl/~iosup/
https://www.linkedin.com/in/aiosup
PDS Group, Faculty EEMCS, TU Delft
Room HB07.050, Mekelweg 4, 2628CD Delft
6
Disclaimer: images used in this presentation
obtained via Google Images.
•
Images used in this lecture courtesy to many anonymous
contributors to Google Images, and to Google Image
Search.
Tommy van der Vorst
Research and strategic consultancy
Broadband/telecom ● human capital
●
GIS-data and -tools
Dashboards
‘Online reports’
Analysis modules
(Big) data sets
Dialogic Platform
Crawlers & scrapers
Surveys / webforms
Text mining
Customers &
stakeholders
Search
technology
Commercial data
sets & feeds
Partners
Researchers
Dialogic +
•
Researchers
who need a platform that provides user-
friendly, real-time and integrated data collection,
linkage, analysis and visualisation
•
Software suppliers
who can add smart algorithms to
the ‘treasure chest’, or see new applications of the
platform
And (obviously):
•
Customers
that have a monitoring-, evaluation- or
management question, that can be answered through
real-time analysis
Q & A
Tommy van der Vorst MSc
Researcher/consultant
dialogic.nl/vandervorst
nl.linkedin.com/in/tommyvdv
[email protected]
Aggregate Formatting Formulas lnteraction Metadata Recode Restructure Select Transform Values Variables http i 'api.dialogicinsight nlldata xml
Onderzoek en strategisch advies
Breedband/telecom ● onderwijs/arbeidsmarkt
●
GIS-data en -tools
Dashboards
‘Online rapport’
Analysemodules
(Big) datasets
Dialogic Platform
Crawlers & scrapers
Surveys / webforms
Tekstmining
Klanten /
stakeholders
Zoektechnologie
Commerciële
datasets/feeds
Partners
Onderzoekers
Dialogic +
•
Onderzoekers
die een platform nodig hebben waar
gebruiksvriendelijke en real-time dataverzameling,
koppeling, verwerking en visualisatie bij elkaar komen
•
Software suppliers
die slimme algoritmes kunnen
toevoegen aan de ‘schatkist’, of andere toepassingen
zien van het Platform
En uiteraard:
•
Opdrachtgevers
met een monitorings-, evaluatie- of
sturingsvraag hebben die te beantwoorden is met real-
time analyse
Paris Avgeriou
7/9/2015 | 1
Big Technical Debt
Managing Technical Debt with Big Data
Prof. dr.ir. Paris Avgeriou - [email protected]
Software Engineering and Architecture Group
http://www.cs.rug.nl/~paris/
The problem
7/9/2015 | 2
› Technical Debt: Quality Trade-offs
› Expedient now, expensive later!
•
50-75% on evolution
The solution
7/9/2015 | 3
› Platform for Managing Technical Debt
•
Source Code Analysis
•
Maching learning
› Outcome
•
Valuation of internal qualities
•
Accurate effort estimation
•
Actionable figures in dashboard
Joeri van Leeuwen
Van Leeuwen A Global Software Telescope for Radio Astronomy NWO Big Software
Joeri van Leeuwen
Van Leeuwen Searching for pulsars with LOFAR and fast transients with Apertif NAC Winter Meeting Jan 2015
•
Further intensification in software, HPC & storage ( Peta -> Exa )
•
One of the most demanding domains on IT
•
SW/HW require new solutions for scalability, awareness, performance/W, etc.
•
Algorithms
•
Development driven for parallelization / new classes of HPC platforms
•
Relevant for other big data domains: MRI, seismic imaging, remote sensing, &c.
•
For 1B Eur SKA telescope; need to deliver a next-gen processing platform
•
Builds on LOFAR/Westerbork + many opportunities for industry.
•
Working on PPS with several industrial relationships mainly in the software domain so
that they qualify for the procurement around 2017.
•
In the heart of the ICT Roadmap of Topsectoren,
extreme streaming data
•
Business value of PPS is the applicability of the approach to the broad area of big data,
streaming data, etc. – a very good candidate for further valorization
Van Leeuwen Searching for pulsars with LOFAR and fast transients with Apertif NAC Winter Meeting Jan 2015
Dr. Joeri van Leeuwen
Astronomer, Principal Investigator
[email protected]
Dr. Gert Kruithof
Head of R&D
[email protected]
Jeroen Keiren
Pitch Big Energy Data
Matchmaking event NWO 1 Juli 2015
Christoph Bockisch, Jeroen Keiren, Rody Kersten, Bernard van Gastel, Marko van Eekelen; Open Universiteit, The Netherlands/RU Nijmegen
The world-wide total energy consumption is steadily increasing, and energy is becoming a scarce resource. This also affects IT systems, to which a growing percentage of this energy drain is attributed. Furthermore, because hardware costs are decreasing, the operating costs of IT solutions are increasingly determined by energy costs. Reducing the energy consumption of IT systems can therefore offer both an immediate and long-term benefit to both the environment, through a lower consumption of scarce resources, and consumers, by lowering their energy bill.
In current practice effort is spent optimizing energy efficiency of hardware. However, the effects of software attract less attention. Still, software plays an important role in the energy consumption of software controlled systems.
Imagine I own an energy-efficient car. The actual energy consumption of the car depends on how heavy my right foot is, if I have a heavy foot, this results in a higher fuel consumption. Compare this to a software controlled system: the hardware (the car) can be energy efficient, but the actual consumption depends on the way it is used by the software (the right foot). Our key question is how to make this control software into a responsible driver.
We propose to investigate energy consumption of software controlled systems from different perspectives: (1) measure energy consumption of relevant devices at a high frequency generating a large amount of data; (2) use machine learning techniques to derive a model of the energy consumption of the hardware; and (3) use these energy models to determine and optimize the energy consumption caused by the software controlling these systems.
There are some existing approaches that consider the separate parts. The research challenge here is to provide an integrated, end-to-end approach and to validate the effectiveness of this process in practical case studies.
Currently, the software improvement group (SIG) has offered their support. IBM has shown an interest, and talks are currently ongoing. If you are interested in reducing energy consumption of software controlled systems, contact us!
Dr.ir. Jeroen J.A. Keiren
Pitch Big Energy Data
Matchmaking event NWO 1 Juli 2015
Christoph Bockisch, Jeroen Keiren, Rody Kersten, Bernard van Gastel, Marko van Eekelen; Open Universiteit, The Netherlands/RU Nijmegen
The world-wide total energy consumption is steadily increasing, and energy is becoming a scarce resource. This also affects IT systems, to which a growing percentage of this energy drain is attributed. Furthermore, because hardware costs are decreasing, the operating costs of IT solutions are increasingly determined by energy costs. Reducing the energy consumption of IT systems can therefore offer both an immediate and long-term benefit to both the environment, through a lower consumption of scarce resources, and consumers, by lowering their energy bill.
In current practice effort is spent optimizing energy efficiency of hardware. However, the effects of software attract less attention. Still, software plays an important role in the energy consumption of software controlled systems.
Imagine I own an energy-efficient car. The actual energy consumption of the car depends on how heavy my right foot is, if I have a heavy foot, this results in a higher fuel consumption. Compare this to a software controlled system: the hardware (the car) can be energy efficient, but the actual consumption depends on the way it is used by the software (the right foot). Our key question is how to make this control software into a responsible driver.
We propose to investigate energy consumption of software controlled systems from different perspectives: (1) measure energy consumption of relevant devices at a high frequency generating a large amount of data; (2) use machine learning techniques to derive a model of the energy consumption of the hardware; and (3) use these energy models to determine and optimize the energy consumption caused by the software controlling these systems.
There are some existing approaches that consider the separate parts. The research challenge here is to provide an integrated, end-to-end approach and to validate the effectiveness of this process in practical case studies.
Currently, the software improvement group (SIG) has offered their support. IBM has shown an interest, and talks are currently ongoing. If you are interested in reducing energy consumption of software controlled systems, contact us!
Dr.ir. Jeroen J.A. Keiren
Twitter: @jkeiren
Prof. dr. Marko van Eekelen