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SAOS 2013 : International Workshop on Self-optimisation in organic and autonomic computing systems | |||||||||||||
Link: http://www.informatik.uni-augsburg.de/lehrstuehle/oc/oc-ws-arcs13/ | |||||||||||||
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Call For Papers | |||||||||||||
The First International Workshop on "Self-optimisation in organic and autonomic computing systems" (SAOS 2013)
to be held at ARCS 2013 - Architecture of Computing Systems February 19th - 22nd 2013 Prague, Czech Republic http://www.informatik.uni-augsburg.de/de/lehrstuehle/oc/oc-ws-arcs13/ =============================================================================== *** Important dates *** ======================= Submission deadline: November 27th, 2012 [EXTENDED DEADLINE] Notification of acceptance: December 11th, 2012 *** Workshop theme *** ====================== Initiatives like Autonomic Computing (AC) and Organic Computing (OC) are based on the insight that we are increasingly surrounded by large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicating freely, and organising themselves in order to perform the required actions and services. The presence of networks of intelligent systems in our environment opens fascinating application areas but, at the same time, bears the problem of their controllability. Hence, different design concepts (like the MAPE cycle and the Observer/Controller framework) have been developed to allow for a self-organised control process at runtime that relieves the designer from specifying all possibly occurring situations and configurations within the design process. Instead, the system itself takes over responsibility to find proper reactions on perceived changes in the environmental conditions. As designers are not able to foresee all possibly occurring situations and circumstances the system will face during its operation time the self-organisation process of the system will focus on self-optimising the system’s behaviour. Such self-optimising behaviour can be achieved at various levels of the system’s design, ranging from basic control architectures over self-organised coordination or collaboration methods and domain-specific optimisation techniques to the application and customisation of machine learning algorithms. Furthermore, several related topics (e.g. trust and security in collaborative systems) provide necessary functionality to enable self-optimising behaviour in AC and OC systems. A special session will further address the question how methods, abstractions and ideas from the (statistical) physics perspective on complex adaptive systems – with examples coming from nature, society and technology – can be utilised in the design, modelling and analysis of organic and autonomic computing systems. Special emphasis will be laid on how the recently developed statistical mechanics of networks – encompassing complex and dynamic structures – can facilitate the design of robust and adaptive computing architectures that inherit some of the remarkable properties of natural systems. An important aim is to strengthen the ties between complementary research communities that otherwise rarely get in contact. * Part A: Architectural concepts for self-optimising behaviour * ================================================================ o Observer/Controller architectures o Autonomic concepts o Artificial Hormone Systems o Collaborative optimisation architectures * Part B: Algorithms and methods for self-optimisation * ======================================================== o Applications of machine learning techniques to real-world problems o Customisation of machine learning o Collaborative task-solving o Trust as performance-relevant technique in technical systems o Fitness landscape characterisation o Performance issues in online optimisation o Security issues in collaborative self-optimisation o Programming environments * Part C: Applications for self-optimisation * ============================================== o Applications with self-optimising system behaviour, i.e. from the following domains: o Robotics o Energy o Traffic o Smart homes o Communication o Sensor/Actuator networks * SPECIAL SESSION on “Complex Sciences in the Engineering of Computing Systems * ================================================================================ o Complex systems approaches in organic and autonomic computing systems o Self-organised formation and optimisation of communication networks o Applications of network science and graph theory in the assessment of resilience, robustness and trust in organic computing systems o Use of physics-inspired models and abstractions in systems engineering and analysis o Monte-Carlo methods for run-time adaptation and optimisation o Application of non-linear models for synchronisation and consensus phenomena o Probabilistic protocols for information diffusion and aggregation o Quantitative approaches to model and analyse emergent system properties o Modelling and analysis of dynamics on and of P2P, ad hoc and other communication networks *** Workshop details *** ========================= The Workshop will be held from February 19th to 22nd in conjunction with the 26th International Conference on Architecture of Computing Systems (ARCS 2013) in Prague, Czech Republic. The conference's web page is available at: http://arcs2013.fit.cvut.cz/ *** Submission Information *** ============================== Paper submission deadline: November 27th, 2012 Notification of acceptance: December 11th, 2012 Papers should not exceed 12 pages and be formatted according to Springer LNCS style. Formatting instructions are available at: http://www.springer.de/comp/lncs/authors.html Paper submission will be handled via the workshop's EasyChair installation: https://www.easychair.org/conferences/?conf=saos13 *** Workshop organisation *** ============================= Gregor Schiele, DERI Galway (IE) Ingo Scholtes, ETH Zürich (CH) Claudio Juan Tessone, ETH Zürich (CH) Sven Tomforde, Universität Augsburg (DE) Arno Wacker, Universität Kassel (DE) Program committee: ============================= Aimee Bailey, Global Environmental Institute Beijing (PRC) Jacob Beal, BBN Technologies / MIT CSAIL (US) Jean Botev, University of Luxembourg (LU) Uwe Brinkschulte, Johann Wolfgang Goethe-Universität Frankfurt am Main (DE) Sven Brueckner, Jacobs Technologies (US) Emre Cakar, Bosch GmbH Hildesheim (DE) Joydeep Chandra, Samsung Research (IN) Frank Dürr, Universität Stuttgart (DE) Markus Esch, Fraunhofer Research (DE) Niloy Ganguly, IIT Kharagpur (IN) Jörg Hähner, Universität Augsburg (DE) Martin Hoffmann, Volavis GmbH Leopoldshöhe (DE) Wolfgang Karl, Karlsruhe Institute of Technology (DE) Paul Kaufmann, University of Kassel (DE) Abdelmajid Khelil, TU Darmstadt (DE) Bernd Kleinjohann, C-Lab / Universität Paderborn (DE) Franziska Klügl, Örebro University (SE) Bivas Mitra, Université Catholique du Louvain (BE) Gero Mühl, Universität Rostock (DE) Christian Müller-Schloer, Leibniz Universität Hannover (DE) Michael Nolting, Volkswagen AG Wolfsburg (DE) Franz Rammig, Universität Paderborn (DE) Wolfgang Reif, Universität Augsburg (DE) Kay Römer, Universität zu Lübeck (DE) Hella Seebach, Universität Augsburg (DE) Bernhard Sick, Universität Kassel (DE) Jürgen Teich, Universität Erlangen-Nürnberg (DE) Matthias Tichy, Göteborgs Universitet (SE) Theo Ungerer, Universität Augsburg (DE) Torben Weis, Universität Duisburg-Essen (DE) Rolf P. Würtz, Ruhruniversität Bochum (DE) |
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