Call for Posters 7th International Workshop on Self-organizing Systems IWSOS 2013

IWSOS 2013
7th International Workshop on Self-organizing Systems 

http://ifisc.uib-csic.es/iwsos2013/ 

Palma de Mallorca, Spain
May 9-10, 2013

Technical co-sponsors: IFIP TC6 WG6.2, EC FP7 NoE EINS

Poster Abstract Submission Deadline: March 15, 2013

We are looking for submissions of research posters, from both academia and industry, describing research, exciting new research projects, and encouraging preliminary results on self-organizing systems.

** Poster Abstract Submission
The submission should be an extended abstract of two pages in two-column format. All submitted abstracts will undergo a peer review process. Accepted posters must be presented at the conference and will be published electronically in a book (ISBN-indexed) named "Emerging Ideas on Self-Organizing Systems".

Poster abstracts should use the following format: http://ifisc.uib-csic.es/iwsos2013/media/poster_latex_template.zip

Poster abstracts can be submitted via: https://www.edas.info/newPaper.php?c=13239&track=31695

** Important Dates
Submission deadline: March 31, 2013 extended!
Notification:        March 31, 2013
Camera-ready:        April 15, 2013

** Scope
The main themes of IWSOS 2013 are from the fields of techno-social systems and networks-of-networks with their unique and complex blend of cognitive, social, and technological aspects. We will analyse how these systems self-organize, acquire their structure, and evolve. Thus, we aim to advance our understanding of such key infrastructures in our societies and, more generally, of these sorts of self-organizational processes in nature. We are further interested in learning how to engineer such self-organizing networked systems to have desirable properties including dependability, predictability, and resilience in the face of the inevitable challenges that they face. Building on the success of its predecessors, this multi-disciplinary workshop aims at bringing together leading international researchers from complex systems, distributed systems, and communication networks to create a visionary forum for discussing the future of self-organization in networked systems. We invite the submission of manuscripts that present original research results on the themes of self-organization in techno-social systems and networks-of-networks.

** Key Topics
The workshop scope includes, but is not limited to, the following topical areas of self-organizing systems:
- Design and analysis of self-organizing and self-managing systems
- Inspiring models of self-organization in nature and society
- Structure, characteristics, and dynamics of self-organizing networks
- Self-organization in techno-social systems
- Self-organized social computation
- Self-organized communication systems
- Citizen Science
- Techniques and tools for modeling self-organizing systems
- Tools to quantify self-organization
- Control and control parameters of self-organizing systems
- Phase transitions in self-organizing systems
- Robustness and adaptation in self-organizing systems
- Self-organization in complex networks such as peer-to-peer, sensor,
  ad-hoc, vehicular, and social networks
- Self-organization in socio-economic systems
- User and operator-related aspects of man-made self-organizing systems
- Self-organizing multi-service networks and multi-network services
- Methods for configuration and management of large, complex networks
- Self-protection, self-configuration, diagnosis, and healing
- Self-organizing group and pattern formation
- Self-organizing mechanisms for task allocation, coordination and
  resource allocation
- Self-organizing information dissemination and content search
- Security and safety in self-organizing networked systems
- Risks and limits of self-organization
- The human in the loop of self-organizing networks
- Social, cognitive, and semantic aspects of self-organization
- Evolutionary principles of the (future, emerging) Internet
- Decentralized power management in the smart grid

Call for Papers 6th Complex Systems Modelling and Simulation Workshop (CoSMoS 2013)

Università degli Studi di Milano-Bicocca, Italy
1 day workshop held between 1 - 5 July 2013

http://www.cs.york.ac.uk/nature/cosmos/cosmos2013.html
cosmos2013-group@york.ac.uk

SPECIAL ISSUE OF NATURAL COMPUTING JOURNAL: we will be organising a special issue of the Natural Computing journal (http://www.springer.com/computer/theoretical+computer+science/journal/11047) based on the themes raised in the workshop. Suitable workshop submissions will be invited to submit to this special journal issue.

The 6th workshop on Complex Systems Modelling and Simulation (CoSMoS 2013) will take place as a 1-day satellite workshop of the Unconventional Computation and Natural Computation conference (http://ucnc2013.disco.unimib.it/) held between 1st and 5th July at the Università degli Studi di Milano-Bicocca, Italy. The CoSMoS workshops series provides a forum for research examining all aspects of the modelling and simulation of complex systems. This year, we will place a special focus on how complex systems simulations can be used to simulate unconventional and natural computation.

Constructing models and simulations of complex systems is a challenging and interdisciplinary task. Elements might include choice of modelling tools and techniques, simulation infrastructures, concurrency, the process of moving from models to simulations, arguing validity of simulations, and the identification of reusable engineering techniques such as patterns. The CoSMoS workshop series continues an initiative, based at the Universities of York and Kent, UK, to develop a framework and infrastructure for the construction of complex systems simulations.

Submitted papers will undergo a rigorous peer-review process and accepted papers will appear in the workshop proceedings published by Luniver Press. Proceedings of the previous CoSMoS workshop are available: http://www-users.cs.york.ac.uk/psa/cosmos2013/proceedings.html


AREAS OF INTEREST

We are seeking submissions that explore aspects of complex systems modelling and simulation, with a special focus on how complex systems simulations can be used to simulate unconventional and natural computation. Areas of interest include, but are not limited to:

* Complex systems simulation case-studies
* Modelling tools and techniques
* Simulation infrastructures
* Arguing validity of simulations
* Concurrency and distribution techniques
* Identification of reusable engineering techniques
* Working across scientific disciplines


SUBMISSIONS

We are accepting both full papers (to be presented orally) and abstracts (to be presented via a poster). Both full papers and abstracts will appear in the workshop proceedings.

For submission via abstract, please submit an abstract not longer than 2 pages of LNCS format that summarises the content of the poster you wish to present. Full papers can be of any length up to a maximum of 25 pages of LNCS format. If you wish to exceed the page limit, or have any other queries, then please email cosmos2013-group@york.ac.uk in advance of submission.

LNCS formatting details can be found here: http://www.springer.com/computer/lncs?SGWID=0-164-7-72376-0

Papers should be submitted via EasyChair here: https://www.easychair.org/conferences/?conf=cosmos2013


IMPORTANT DATES

* Paper Submission: 22 March 2013
* Notification of acceptance: 22 April 2013
* Camera ready copies: 6 May 2013
* CoSMoS Workshop: 1 day between 1 - 5 July 2013


WORKSHOP CHAIRS

* Paul Andrews, Department of Computer Science and York Centre for Complex Systems Analysis, University of York, UK
* Susan Stepney, Department of Computer Science and York Centre for Complex Systems Analysis, University of York, UK

You don’t cite me anymore - Scientific publications and the ravages of time

One of the most specific things about scientific literature is that scientific papers and books contain references to other papers. The number of citations has become an indicator for the impact of a result, the more other papers cite an article, the higher is its considered impact.

The number of citations a scientific paper gets is a result of interesting effects and interactions:

First, there is the Matthew effect, also known by the proverb "the rich get richer and the poor get poorer" can be observed, where a preferential attachment to larger nodes causing a power-law distribution of node degrees rather than a normal distribution which would be expected for any repeated random experiment with statistically independent trials. Due to this effect the average paper does not get the mean value of all citations, no, it gets close to zero. Most papers do not get more than 5 citations. But a few papers get cited a thousand times or even more often. Models assume that highly cited papers have a better chance of being cited in new papers can explain this behavior and predict a smooth power law distribution for paper citations.

However, to make the model accurate, there is another factor: time.

While the total number of citations for a given paper naturally can only increase over the years, the actual ability of papers to attract further citations dimishes over time - the paper "ages" (see Citation averages, 2000-2010). This applies even to classic papers, for example from Einstein or Hawking, which are no longer cited as they once were.

Matúš Medo and his colleagues from the University of Fribourg in Switzerland developed a model taking this aging factor into account. They found that a paper’s relevance decreases dramatically a few years after its publication.

Especially in our time of instant communication of results, it thus becomes very unlikely that a scientific paper gains in popularity after some time has passed. Sorry to crush your hopes, but if you have a meagerly cited paper now, it most likely won't become more popular in the future ;-)

 Links

1. Matthew Effect. Wikipedia
2. Matúš Medo, Giulio Cimini, and Stanislao Gualdi.Temporal Effects in the Growth of Networks. Phys. Rev. Lett. 107, 2011
3. W. Elmenreich. Why is it important to get cited?. Self-Organizing Networked Systems Blog. October 2012
4. Citation averages, 2000-2010, by fields and years. Times Higher Eduction 2011.

Five Misconceptions about Self-Organizing Systems

from W. Elmenreich, H. de Meer. Self-organizing networked systems for technical applications: A discussion on open issues:

 

Misconception #1: Self-organizing systems establish a class of systems

If a system is considered to be self-organizing or not depends mainly on the way how the system is observed, especially where the borderline between the observed system and its environment is drawn. C. Gershenson and F. Heylighen [1] propose the following perspective to overcome this problem: Instead of thinking of Self-Organizing Systems as an absolute class of systems, self-organization should be understood as a way of observing systems. Depending on the type of problem and the
desired solution, the way of observing a system as an Self-Organizing System can be beneficial or not.

 

Misconception #2: All Self-organizing systems are chaotic systems

There is a relation between chaos theory and self-organization in that a Self-Organizing System may show chaotic behavior, that is having critical turning points (also known as bifurcations) in the system behavior. However, a Self-Organizing System does not necessarily have to show such behavior. Instead, some Self-Organizing Systems also might approach their target state without a sensitive dependence on initial conditions.
Accordingly, a system with chaotic behavior may be built without employing the typical building blocks of Self-Organizing Systems such as distributed entities and local interactions.

 

Misconception #3: The emerging structure is a primary property of self-organizing systems

Self-Organizing Systems provide a powerful mechanism to create structure and patterns. This phenomenon can be observed in many physical and biological systems, such as the skin pigmentation of fish, the polygonal pattern of nest territories of fish such as Tilapia, or the cathedral-like buildings of termites.
However, the emerging pattern should not be seen as a primary property of an Self-Organizing System. There are Self-Organizing Systems, like homeostatic operational control in living beings, where such a structure is not present or is hidden from the observer. Thus, the emerging structure can be rather seen as a secondary property that indicate self-organization in many cases.

 

Misconception #4: Self-organizing systems are always based on evolutionary processes

Evolutionary processes, as best known from biological examples, are an iterative mechanism of change in the inherited traits of a population of organisms from one generation to the next. Evolutionary processes are driven by mutation, selection and recombination.
Many biological examples of self-organizing systems have emerged from an evolutionary process, which made the term self-organization connected to evolution. Thus, the connection of Self-Organizing Systems to evolutionary processes is not an obligatory one, since many non-biological examples of Self-Organizing Systems have developed without an evolutionary process, thus showing the possibility to design self-organizing without an evolutionary process.
However, an interesting research task for future technical systems arises in constructing Self-Organizing Systems, which implement an evolution of their local rules in order to adjust to new situations.

 

Misconception #5: Any self-organizing system will never need maintenance

Many Self-Organizing Systems show adaptive behavior, which means that they can operate well within a wide range of input parameters. However, that does not imply that a technical Self-Organizing System will have a low maintenance effort. Typically, a complex technical system that must operate over a considerable life time will require maintenance in order to provide its service during system lifetime.
It is an open question if maintenance of a technical system with self-organizing properties will be easier or more complicated to maintain than a traditionally designed technical application. On the one hand, properties like robustness might make it easier to replace parts of the system without disturbing the overall operation, on the other hand, diagnosis and maintenance of an Self-Organizing System might turn out to be more complex than in systems built following a more straightforward approach.

See also:

• [Self-Organizing Networked Systems Blogpost] So when do we call a system self-organizing?
• W. Elmenreich and H. de Meer. Self-organizing networked systems for technical applications: A discussion on open issues. In J.P.G. Sterbenz. K.A. Hummel, editor, Proceedings of the Third International Workshop on Self-Organizing Systems, pages 1–9. Springer Verlag, 2008.