3rd International Workshop on „Self-optimisation in Autonomic and Organic Computing Systems" (SAOS15)
Tuesday, 24th March, 2015
- 09:00 Welcome
- 09:10 Keynote: Sanaz Mostaghim (University of Magdeburg)):
"Swarm Intelligence: Basic Principles of Self-Oranization in Technical Systems"
- 10:00 Jan Kantert (Leibniz Universität Hannover):
"Measuring Self-Organisation in Distributed Systems by External Observation"
- 11:00 - 11:30 Matthias Sommer (University of Augsburg):
"A Systematic Study on Forecasting of Traffic Flows with Artificial Neural Networks"
- 11:30 - 12:00 Alexander Schiendorfer (University of Augsburg):
"Active Learning for Abstract Models of Collectives"
- 12:00 - 12:30 Stefan Rudolph (University of Augsburg):
"An Online Influence Detection Algorithm for Organic Computing Systems“
- 13:30 Georg von Zengen (Technical University of Braunschweig): “Adaptive Channel Selection for Interference Reduction in Wireless Sensor Networks”
- 14:00 Nizar Msadek (University of Augsburg):
"A Mechanism for Minimising Trust Conflicts in Organic Computing Systems"
- 14:30 Adnan Al-Anbuky (Auckland Technical University):
"Public Space Ambient Intelligence: Benefits, Approaches and Challenges"
- 15:30 Jörg Hähner (University of Augsburg):
"Runtime Self-Integration as Key Challenge for Mastering Interwoven Systems"
- 16:00 Discussion: “Current Trends and Challenges for Organic Computing"
- 16:30 Closing Remarks
Call for Paper
Initiatives such as 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 challenges caused by so-called Interwoven Systems (IwS). That is, invite contributions discussing concepts to achieve controllability and manageability of connected or coupled systems that were initially not meant to interact with each other. A key contribution towards a better control of IwS is a qualified support of self-integration in IwS elements. In order to make this challenge more accessible, effort can be subdivided into six distinct areas: Due to changes in the overall IwS, e.g., new elements, the overall system architecture (element structure, communication structure, algorithms, parameters, etc.) cannot be predetermined at design-time. Basis for a resulting self-integration process is, first, the ability of elements for online dependency detection and modelling and, second the ability for online goal adaptation. Then, techniques for a continuous re-design for self-integration, i.e., an adaptation of various aspects of an IwS system architecture can be established. These self-integration processes must be complemented by techniques for a long-term self-improvement, i.e., self-inspection and long-term self-adaptation. As IwS are open, vulnerable systems, we need techniques to model and consider trust, reputation, and security mechanisms. Methods for a theoretical analysis of self-integration processes at different levels will be crucial for a better understanding of IwS at design-time and to provide necessary information about the IwS at runtime.
Part A: Architectural concepts for self-optimising behaviour
- Observer/Controller architectures
- Autonomic concepts
- Artificial Hormone Systems
- Collaborative optimisation architectures
Part B: Algorithms and methods for self-optimisation
- Applications of machine learning techniques to real-world problems
- Customisation of machine learning
- Fitness landscape characterisation
- Performance issues in online optimisation
- Programming environments
- Online and Runtime Optimisation techniques
Part C: Applications for self-optimisation
Applications with self-optimising system behaviour, i.e. from the following domains:
- Smart homes
- Sensor/Actuator networks
Part D: Interwoven Systems & Self-Integration
- Online dependency detection and modelling
- Online goal adaptation
- Continuous re-design for self-integration
- Long-term self-improvement and self-inspection
- Trust, reputation, and security mechanisms
- Theoretical analysis of self-integration processes
- The Workshop is held in conjunction with the 28th International Conference on Architecture of Computing Systems (ARCS 2015)
- Held from March 24th to 27th, 2015
- In Porto, Portugal
- Workshop will take place either March 24, 2015 or March 25, 2015
- ARCS 2015 homepage: ARCS2015
Schedule and submission
- Jörg Hähner, Universität Augsburg (DE)
- Gregor Schiele, DERI Galway (IE)
- Ingo Scholtes, ETH Zürich (CH)
- Sven Tomforde, Universität Augsburg (DE)
- Arno Wacker, Universität Kassel (DE)
- Jacob Beal, BBN Technologies, USA
- Kirstie Bellman, The Aerospace Company
- Jean Botev, Universität Luxembourg, Luxembourg
- Uwe Brinkschulte, Universität Frankfurt, Germany
- Frank Dürr, Universität Stuttgart, Germany
- Jörg Hähner, Universität Augsburg, Germany
- Paul Kaufmann, Universität Paderborn Germany
- Abdelmajid Khelil, Huawei Technologies GmbH, Germany
- Chris Landauer, The Aerospace Company
- Erik Maehle, Universität Lübeck, Germany
- Bivas Mitra, Indian Institute of Technology Kharagpur, India
- Gero Mühl, Universität Rostock, Germany
- Christian Müller-Schloer, Leibniz Universität Hannover, Germany
- Wolfgang Reif, Universität Augsburg, Germany
- Christian Renner, Universität Lübeck, Germany
- Gregor Schiele, DERI Galway (IE)
- Ingo Scholtes, ETH Zürich (CH)
- Hella Seebach, Universität Augsburg, Germany
- Bernhard Sick, Universität Kassel, Germany
- Jürgen Teich, Universität Nürnberg-Erlangen, Germany
- Matthias Tichy, Chalmers Technical University and University of Gothenburg, Sweden
- Sven Tomforde, Universität Augsburg, Germany
- Theo Ungerer, Universität Augsburg, Germany
- Arno Wacker, Universität Kassel, Germany
- Torben Weis, Universität Duisburg-Essen, Germany
- Stefan Wildermann, Universität Nürnberg-Erlangen, Germany
- Rolf Würtz, Ruhr-Universität Bochum, Germany