Abstract
Organic Computing systems are increasingly open for subsystems (or agents) to join and leave. Thereby, we can observe classes of similarly behaving agents, including those that try to exploit or even damage the system. In this paper, we describe a novel concept to cluster agent groups at runtime and to estimate their contribution to the system. The goal is to distinguish between good, suspicious and malicious agent groups to allow for counter measures. We demonstrate the potential benefit of our approach within simulations of a Desktop Grid Computing system that resembles typical Organic Computing characteristics such as self-organisation, adaptive behaviour of heterogeneous agents, and openness.
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This research is funded by the research unit “OC-Trust” (FOR 1085) of the German Research Foundation (DFG).
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Kantert, J., Scharrer, R., Tomforde, S., Edenhofer, S., Müller-Schloer, C. (2016). Runtime Clustering of Similarly Behaving Agents in Open Organic Computing Systems. In: Hannig, F., Cardoso, J.M.P., Pionteck, T., Fey, D., Schröder-Preikschat, W., Teich, J. (eds) Architecture of Computing Systems – ARCS 2016. ARCS 2016. Lecture Notes in Computer Science(), vol 9637. Springer, Cham. https://doi.org/10.1007/978-3-319-30695-7_24
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DOI: https://doi.org/10.1007/978-3-319-30695-7_24
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