Self-Healing Distributed Scheduling Platform

Abstract : Distributed systems require effective mechanisms to manage the reliable provisioning of computational resources from different and distributed providers. Moreover, the dynamic environment that affects the behaviour of such systems and the complexity of these dynamics demand autonomous capabilities to ensure the behaviour of distributed scheduling platforms and to achieve business and user objectives. In this paper we propose a self-adaptive distributed scheduling platform composed of multiple agents implemented as intelligent feedback control loops to support policy-based scheduling and expose self-healing capabilities. Our platform leverages distributed scheduling processes by (i) allowing each provider to maintain its own internal scheduling process, and (ii) implementing self-healing capabilities based on agent module recovery. Simulated tests are performed to determine the optimal number of agents to be used in the negotiation phase without affecting the scheduling cost function. Test results on a real-life platform are presented to evaluate recovery times and optimize platform parameters.
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Communication dans un congrès
Carlos Varela. 11th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid), May 2011, Newport Beach, CA, United States. IEEE, pp.225-234, 2011, 〈10.1109/CCGrid.2011.23〉
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Marc Frincu, Norha Villegas, Dana Petcu, Hausi Muller, Romain Rouvoy. Self-Healing Distributed Scheduling Platform. Carlos Varela. 11th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid), May 2011, Newport Beach, CA, United States. IEEE, pp.225-234, 2011, 〈10.1109/CCGrid.2011.23〉. 〈inria-00563670〉

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