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Call for Participation
Seventh IEEE International Conference on Self-Adaptive and Self-Organizing Systems
(SASO 2013)
Philadelphia (PA), USA; 9-13 September 2013 --- https://www.cs.drexel.edu/saso2013/
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---------- NEWS ------------------------------------------------------------------------------------------
- Registration for SASO 2013 is now open (https://www.cs.drexel.edu/saso2013/registration.html )
- special rate for SASO participants accommodation is active until August 8
(https://www.cs.drexel.edu/saso2013/accommodations.html)
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Aims and Scope
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The aim of the Self-Adaptive and Self-Organizing systems conference series (SASO) is to provide a forum for the foundations of a principled approach to engineering systems, networks and services based on self-adaptation and self-organization. The complexity of current and emerging networks, software and services, especially in dealing with dynamics in the environment and problem domain, has led the software engineering, distributed systems and management communities to look for inspiration in diverse fields (e.g., complex systems, control theory, artificial intelligence, sociology, and biology) to find new ways of designing and managing such computing systems. In this endeavour, self-organization and self-adaptation have emerged as two promising interrelated approaches.
Many significant research problems exist related to self-adaptive or self-organizing systems. A challenge in self-adaptation is often to identify how to change specific behavior to achieve the desired improvement. Another major challenge is to predict and control the global system behavior resulting from self-organization. Yet more challenges arise from the confluence of self-adaptation with self-organization. For instance, how do self-* mechanisms that work well independently operate in combination? How are meso-level structures formed which leverage micro-level behavior to achieve desirable macro-level outcomes, and avoid undesirable ones?
The seventh edition of the SASO conference embraces the inter-disciplinarity and the scientific, empirical and application dimensions of self-* systems; it thus aims to attract participants with different backgrounds, to foster cross-pollination between research fields, and to expose and discuss innovative theories, frameworks, methodologies, tools, and applications.
SASO welcomes novel results on both self-adaptive and self-organizing systems research. It seeks to emphasize the interconnection of basic research between and within fields, and the increasing protrusion of self-* systems into the human sphere, evaluating their impact on society, environmental sustainability, commerce, living/working spaces and critical infrastructure. Therefore contributions are welcomed that: apply self-* principles to solve real-world problems; unpick the entanglement of self-* systems and human users in socio-technical systems; present advances in self-* mechanisms or analyses with potentially broad application; investigate the combination and interconnection of self-* mechanisms; and/or identify and evaluate new self-* principles or mechanisms from the study of natural or engineered systems.
Contributions must present novel theoretical or experimental results, or practical approaches and experiences in building or deploying real-world systems, applications, tools, frameworks, etc. Contributions contrasting different approaches for engineering a given family of systems, or demonstrating the applicability of a certain approach for different systems, are equally encouraged. Where relevant and appropriate, accepted papers will also be encouraged to submit accompanying papers for the Demo or Poster Sessions.
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Topics of Interest
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The topics of interest to SASO include, but are not limited to:
- Self-* systems theory: theoretical frameworks and models; biologically- and socially-inspired paradigms; inter-operation of self-* mechanisms;
- Self-* systems engineering: hardware, software and middleware development frameworks and methods, platforms and toolkits; self-* materials;
- Self-* system properties: robustness, resilience and stability; emergence; computational awareness and self-awareness; reflection;
- Self-* cyber-physical and socio-technical systems: human factors and visualization; self-* social computers; crowdsourcing and collective awareness;
- Applications and experiences of self-* systems: cyber security, transportation, computational sustainability, big data and creative commons, power systems.
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Tutorials
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- T1: Formal Models of Social Processes: The Pursuit of Computational Justice in Self-Organising Multi-Agent Systems
- T2: From Self-Organizing Mechnanisms to Design Patterns to Engineering Self-Organizing Applications
- T3: Adaptivity via Situation Awareness and Self-Modeling
- T4: Complex Structures and Collective Dynamics in Networked Systems: Foundations for Self-Adaptation and Self-Organization
See https://www.cs.drexel.edu/saso2013/tutorials.php for more information.
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Workshops
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- WS1: Adaptive Host and Network Security (AHAN 2013)
- WS2: Second International Workshop on Socially Adaptive and Socio-Aware Information and Communication Systems (SocioAware 2013)
- WS3: 4th edition of the Workshop and Symposium on Trustworthy Self-Organising and Autonomous Systems (TSOAS 2013)
- WS4: 3rd AWARE workshop on Challenges for Achieving Self-Awareness in Autonomic Systems (AWARE 2013)
- WS5: Computationally Adapted {laws | policies | norms} for Self-Organising Systems (CA*OS 2013)
See https://www.cs.drexel.edu/saso2013/workshops.php for more information.
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Invited speeches
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** No equations, no variables: a computer-assisted approach to modeling complex systems **
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By Yannis Kevrekidis (Princeton University)
In current modeling practice for complex systems, including agent-based and network-based simulations, the best available descriptions of a system often come at a fine level (atomistic, stochastic, individual-based) while the questions asked and the tasks required by the modeler (parametric analysis, optimization, control) are at a much coarser, averaged, macroscopic level. Traditional modeling approaches start by deriving macroscopic evolution equations from the microscopic models. I will review a mathematically inspired, systems-based computational enabling technology that allows the modeler to perform macroscopic tasks acting on the microscopic models directly in an input-output mode. This "equation-free" approach circumvents the step of obtaining accurate macroscopic descriptions. I will discuss applications of this approach and its linking with recent developments in data mining algorithms, exploring large complex data sets to find good "reduction coordinates".
Yannis Kevrekidis studied Chemical Engineering at the National Technical University in Athens. He then followed the steps of many alumni of that department to the University of Minnesota, where he studied under Rutherford Aris and Lanny Schmidt (also Dick McGehee and Don Aronson in Mathematics) on computational studies of dynamical systems, which still remains the main theme of his research. He was a Director's Fellow at Los Alamos in 1985-86. He has been at Princeton since 1986, where he teaches Chemical Engineering and also Applied and Computational Mathematics. His research interests are centered around the dynamics of physical and chemical processes, types of instabilities, pattern formation, and their computational study. In more recent years he has developed an interest in multiscale computations. He has been a Packard Fellow, a Guggenheim Fellow and the Ulam Scholar at LANL. He holds the Colburn and Wilhelm Awards of the AIChE, and a Humboldt Prize. Last year he was the
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utzwiller Fellow at the Max Planck Institute for the Physics of Complex Systems in Dresden.
** Architectured Self-Organized Systems: Toward the Best of Both Worlds by "Morphogenetic Engineering" **
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By Rene Doursat (Complex Systems Institute, Paris CNRS & Ecole Polytechnique)
Engineering is torn between an attitude of strong design and dreams of autonomous devices. It wants full mastery of its artifacts, but also wishes these artifacts were much more adaptive or "intelligent". Meanwhile, the escalation in system size and complexity has rendered the tradition of rigid top-down planning and implementation in every detail unsustainable. In this context, natural complex systems, large sets of elements interacting locally and behaving collectively, can constitute a powerful source of inspiration and help create a new generation of artificial systems with the desired "self-x" properties absent from classical engineering. Historically, along these lines, the observation of neurons and genes has given rise to machine learning and evolutionary algorithms. Yet, these domains have also shifted their focus toward classical optimization and search problems, away from emergent computation.
In this talk, I want to show other avenues of bio-inspired design stressing the importance and benefits of a genuine self-organization in architectured systems-as exemplified by the growth of multicellular organisms or the nests of social insects. I will present a new field of research, "morphogenetic engineering" (ME; http://doursat.free.fr/morpheng.html ), which explores the artificial design of complex morphologies that can reproducibly arise without central or external control. Potential applications range from swarm robotics to distributed software, techno-social networks and synthetic biology. What they have in common is a myriad of hardware/software/bioware agents that can be programmed to dynamically build structures on the sole basis of peer-to-peer communication. Four main groups of ME methodologies will be reviewed: constructing, coalescing, developing and generating. Then, I will describe
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wo of my studies: the evolutionary development of animated organisms in a 3D virtual world ( http://doursat.free.fr/mapdevo.html ) and the self-assembly of abstract graph topologies ( http://doursat.free.fr/nets.html ). In all cases, the challenge is not to build a system directly but to find and/or evolve the proper rules that its components should follow to build it for you.
Rene Doursat is a Research Scientist and former Director of the Complex Systems Institute, Paris, under the French research council CNRS. He also co-founded the European Complex Systems Master's at Ecole Polytechnique, Paris, where he is an Adjunct Lecturer. Previously, he was a Visiting Assistant Professor in computer science at the University of Nevada, Reno, after an engineering period in the San Francisco Bay Area's software industry. An alumnus of Ecole Normale Superieure, Paris, he completed his PhD in 1991 and a postdoc in computational neuroscience at the Ruhr-Universitat Bochum, Germany. The main theme of Rene Doursat's research is bio-inspired models and simulations of "morphogenetic engineering" systems (book with Springer-Verlag), i.e. how complex architectures (e.g. software, robotic, network, neural) can self-organize from a swarm of heterogeneous agents via dynamical, developmental, and evolutionary processes. He was the General Chair of ECAL 2011, the European
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onference on Artificial Life, and organized or created a dozen other conferences and workshops. He wrote over 100 publications, among which 40 full papers and chapters, and 10 edited books, proceedings and journal issues. In 2013, he moved to Washington DC, and received formal affiliations with Drexel University and George Mason University. He also holds a teaching appointment at the School of Engineering of The Catholic University of America in DC.
** Meeting the Challenge of Large-Scale Socio-Technical Systems Development in the Age of Complexity **
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By Jeffrey Wilcox (Vice President, Engineering Corporate Engineering and Technology Lockheed Martin Corporation)
Organizations like Lockheed Martin have evolved over the past half-century to solve highly-complex problems for a highly-complex set of stakeholders. During this time, the systems engineering discipline has been at the core of how our industry approached and met these challenges. It has served us well for decades. In recent years, however, the increasing complexity of these challenges has stressed our ability to sense and adapt to a terrain that is rapidly changing in multiple dimensions.
This talk will explore those changes, identify where traditional approaches are being stressed, and provide suggestions for how the research community can advance and support the creation of effective complex systems and enterprises.
Jeffrey J. Wilcox is the Vice President for Engineering at the Lockheed Martin Corporation. In this capacity, he is responsible for leading the development and execution of engineering strategy for the Lockheed Martin Engineering Enterprise and its 60,000 engineers, scientists, and technologists. Previously, Mr. Wilcox was the Vice President for Systems and Software Engineering at Lockheed Martin. In that role, he was responsible for directing the development and implementation of enterprise-wide systems and software engineering processes, tools, technology, and training with special emphasis on complex, software-intensive systems development. Prior to joining Lockheed Martin,
Mr. Wilcox served in a variety of increasingly responsible positions at the Science Applications International Corporation (SAIC), including Senior Vice President, where he led business planning and analysis for the Technology and Advanced Systems business unit.
Mr. Wilcox graduated from Drexel University with a master's degree in Electrical Engineering and Case Western Reserve University with a degree in Biomedical Engineering. Mr. Wilcox holds an honorary doctorate of Engineering from Stevens Institute of Technology. Mr. Wilcox is an American Institute of Aeronautics and Astronautics (AIAA) Associate Fellow and a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
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Accommodations
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A block of rooms has been reserved for SASO 2013 participants and accompanying guests at a special rate at the Sheraton Hotel near Drexel University. The block reservation will be held until August 8, 2013, so please make reservations before then.
Contact the hotel directly at +1-888-627-7071 and mention "SAS0 2013" to get the reserved rooms and special rates. Or you may reserve rooms online at https://www.starwoodmeeting.com/Book/IEEESASO
Other Philadelphia hotels may be found at http://www.visitphilly.com/hotels
Note that Drexel University is in the University City District, which is near Center City.
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Program
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Information about the program is available at https://www.cs.drexel.edu/saso2013/program.php
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Program Chairs
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Tom Holvoet
KU Leuven, Belgium
Jeremy Pitt
Imperial College London, England
Ichiro Satoh
National Institute of Informatics, Tokyo, Japan