[ecoop-info] CFP: 1st International Workshop on Models at run.time for Self-aware Computing Systems

[Sebastian Götz]

Call for Papers
                  1st International Workshop on Models at run.time
                         for Self-aware Computing Systems
                         In conjunction with ICAC  2016
                       Würzburg, Germany, July 18th, 2016
                     http://st.inf.tu-dresden.de/MRT16-ICAC/

                                 Important Dates

               Submissions of abstracts: March     16th, 2016
               Submissions of papers:    March     23rd, 2016
               Notification:             April     17th, 2016
               Camera Ready:             May        6th, 2016
               Workshop date:            July      18th, 2016


Introduction

In order to most effectively use models at runtime, self-aware computing 
systems
need increasingly powerful ways of observing their operational 
environment  and
their own performance and behavior and  then  building  and refining  
their own
models accordingly.  An inherent principle of  self-aware computing  
systems is
having diverse  feedback  loops, which  build  a causal connection  
between the
computing  system  and  a  reflective layer. The computing system is 
continously
observed  and,   based  on  this, the system is  able to update and 
modify  its
models to reason about its goals, context, operational environment  and 
its own
resources, decisions and actions.

To  effectively   and   efficiently  realize these  feedback loops,  
models and
especially  modifiable   and   updatable   models at runtime   are 
essential.  The
models at run. time  paradigm  proposes  to  use runtime models as 
abstractions of
the computing system for the purpose   of  more efficient reasoning  
upon  both
its runtime  observations  and   learned   knowledge.   Hence, 
models at runtime is
especially looking for  more  innovative   approaches  to the causal 
connection
between the system and the runtime model, with particular focus on a 
transaction
concept for this causal connection for such issues as  timing, roll-back 
ability
and data-consistency.

Goal

The goal of this workshop is  to  provide  a  bridging  podium for  
researchers
working in  the area of self-awareness, self-modelling, autonomous  and 
organic
computing,  as well as self-adaptive and self-organizing  systems with  
a focus
on runtime  representations  that can be used by the system to reason 
about its
goals, context, operational environment and  its  own  resources, 
decisions and
actions.

Topics of interest

We are particularly interested in work  covering  the  following 
non-exhaustive
list of topics:
- languagues and formalisms for runtime representations
- approaches realizing the causal connection between  the computing  
system  and
   its reflective layer
- applications and case studies involving runtime representations
- a general discourse on
   - the need for and characteristics of runtime representations
   - the properties of causal connections (e.g., temporal properties, 
uncertainty,
     etc.)
- interdisciplinary approaches to models at run.time, as  for example  the  
mutual
   influence (or coercion) of socio-technical systems
- How runtime models can address basic principles of areas such as game 
theory.
- Distributed models at run.time, i.e., having multiple, interacting 
systems, each
   having its own runtime model and in general, issues of  models at  
runtime in
   large scale systems
- Incomplete, partial models
- Impacts of uncertainty
- Approaches to real-time model-building, refinement
- Relevant theory on transactions
- Relevant lessons learned from bio-inspired, socially-inspired, 
unconventional
   systems
- Modular  models at run.time,  i.e.,  approaches  to  improve  the 
modularity  of
   models at run.time systems for better reuse
- Co-evolving   models at run.time,  i.e.,  systematic  approaches to  
synchronize
   multiple, interacting models at run.time systems
- For those papers focusing on executable models at runtime,  we 
encourage  the
   investigation of how  the feedback  from  the  systems  are 
reflected  in the
   executable  models  (so  that  they   have  causal (bi-)connections  
with the
   systems)

The workshop participants will be selected based on their experience  
and  ideas
related to this maturing field. You are  invited  to  apply  for 
attendance  by
sending:
- a full paper (8 pages) on original research, lessons learned from 
realizing
an approach or experiences on transferring a research prototype into 
practice,
- a position paper (6 pages) covering a well-argued vision or position,

All papers must conform to the double-column  IEEE  formatting 
guidelines.   At
least three PC members  will  review  each  submission.   The authors  
will  be
notified about acceptance before the  ICAC  2016  early registration  
deadline.


Organizers
- Sebastian Götz (main contact), TU Dresden, Germany
- Kirstie Bellman, Topcy House Consulting, US
- Nelly Bencomo, Aston University, UK
- Gordon Blair, Lancaster University, UK

Program Committee

- Franck Chauvel, SINTEF, Norway
- Hui Song, SINTEF, Norway
- Mahdi Derakhshanmanesh, University of Koblenz-Landau, Germany
- Antonio Filieri, Imperial College, UK
- Ta’id Holmes, Deutsche Telekom AG, Germany
- Jean-Marc Jézéquel, Triskell Team,IRISA, France
- Chris Landauer, The Aerospace Corporation, USA
- Holger Giese, Universität Potsdam, Germany
- Matthias Tichy, Uni. Ulm, Germany
- Thomas Vogel, Universität Potsdam, Germany
- Kurt Geihs, Uni. Kassel, Germany
- Lars Grunske, HU Berlin, Germany
- Yves La Traon, Uni. Luxembourg, Luxembourg
- Lionel Seinturier, Uni. Lille, France

Further Information
Web site: http://st.inf.tu-dresden.de/MRT16-ICAC/
Contact:  Sebastian Götz (sebastian.goetz at acm.org)

-- 
Dr.-Ing. Sebastian Götz
Researcher

Technische Universität Dresden
Fakultät für Informatik
Institut für Software- und Multimediatechnik
Lehrstuhl für Softwaretechnologie
www: http://www.st.inf.tu-dresden.de/
Mail: sebastian.goetz at acm.org
Kontakt: INF 2082
Tel.: +49 351 463 38346

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