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Topics. Seminar WS 12/13 Organic Computing. Self-organizing swarm robots Proactive thermal management in multi-core systems Self-optimizing (distributed) resource allocation Self healing reconfigurable hardware systems. Supervisor: Thomas Ebi Chair for Embedded Systems (CES).

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  1. Topics Seminar WS 12/13Organic Computing • Self-organizing swarm robots • Proactive thermal management in multi-core systems • Self-optimizing (distributed) resource allocation • Self healing reconfigurable hardware systems • Supervisor: Thomas Ebi Chair for Embedded Systems (CES)

  2. What is Organic Computing? Merriam Webster Dictionary on „organic“: • of, relating to, or derived from living organisms • having the characteristics of an organism : developing in the manner of a living plant or animal • forming an integral element of a whole • having systematic coordination of parts Learning from nature The whole is more than the sum of its parts

  3. What is Organic Computing? • Self-X Properties (“Autonomic Computing” IBM) • Self-Organization • Self-Configuration • Self-Optimization • Self-Healing • Self-Protection

  4. Swarm Intelligence • Collective behavior in decentralized, self-organized systems • Particle Swarm Optimization • Ant Colony Algorithm [ M Dorigo (Hrsg). Ant colony optimization and swarm intelligence. 5th International Workshop, ANTS (2006) ] [ RC Eberhart, Y Shi. Particle Swarm Optimization: Developments, Applications and Resources. CEC (2001). ] [ V Maniezzo, A Carbonaro. Ant Colony Optimization: an Overview. Essays and Surveys in Metaheuristics (2001). ] [ P Svenson et al. Swarm Intelligence for logistics: Background. Technical report (2004).]

  5. Multi-Agent Systems • Autonomous acting entities (agents) working together to reach a given goal [ M Wiering et al. Learning in Multi-Agent Sytems. (2000). ] [ L Panait, S Luke. Cooperative Multi-Agent Learning: The State of the Art. (2005). ] [ M Wooldridge. An Introductionto Multiagent Systems. John WileyandSons Ltd (2002). ] [ MS Greenberg et al. Mobile Agentsand Security. (1998) . ]

  6. Evolutionary Algorithms • Four major paradigms • Genetic Algorithms • Genetic Programming • Evolutionary Programming • Evolutionary Strategies [ Darrell Whitley. An Overview of Evolutionary Algorithms: Practical Issues and Common Pitfalls. (2001). ] [ PJ Fleming, RC Purshouse. Evolutionary algorithms in control systems engineering: a survey. Control Engineering Practice 10:1223–1241 (2002). ]

  7. Paper and Presentation • Paper • LaTeX and Word Templates • 10-12 pages • In German or English • Correct scientific writing (structure, references, …) • typos, duplicate words, … are avoidable • Presentation • 25 minutes • Projector is available  PowerPoint, OpenOffice, PDF

  8. Paper: Basic Structure • Abstract • Introduction • Related Work • Main part • One or more approaches • Results/Comparison • Conclusion • Bibliography

  9. Literature Research • Reading paper references • Search engines, e.g. Google, Yahoo, and so on • Wikipedia • Not to be referenced in the paper • Paper search engine http://scholar.google.com • University library • Journal papers via “Elektronische Zeitschiftenbibliothek” • Portals • ACM • IEEE Xplore • DBLP

  10. Dates and Deadlines • Feb. 10 End of lectures • Feb., Week 1 Presentation I • Jan., Week 4 Slides have to be finished • Jan., Week 3 Preliminary final version of slides • Jan., Week 2 Paper has to finished • Dec., Week 2 Preliminary final version of paper • Nov., Week 4 First version of paper • Nov., Week 2 Structure of paper • Nov., Week 1 First ideas, read papers

  11. Topics • Self-organizing swarm robots • Algorithms/methods used for organizing swarms and their benefit over static approaches • E.g.: “Evolving self-organizing behaviors for a swarm-bot • Proactive thermal management in multi-core systems • Methods used for predicting future temperatures based on past observations and comparison to reactive approaches • E.g.: “Proactive thermal management in MPSoCs” • Self-optimizing (distributed) resource allocation • Agent based resource allocation [for example in clouds or many-core chips (focus on one)] and benefits [for instance due to scalability] • E.g.: “DistRM” (many-core), “agent-based resource allocation for grid computing” • Self healing reconfigurable hardware systems • Adaptive fault tolerance using reconfigurable logic • E.g.: “eDNA”, “Fine-grained self-healing hardware for large-scale autonomic systems”

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