Optimization in a Self-Stabilizing Service Discovery Framework for Large Scale Systems

Abstract : Ability to find and get services is a key requirement in the development of large-scale distributed sys- tems. We consider dynamic and unstable environments, namely Peer-to-Peer (P2P) systems. In previous work, we designed a service discovery solution called Distributed Lexicographic Placement Table (DLPT), based on a hierar- chical overlay structure. A self-stabilizing version was given using the Propagation of Information with Feedback (PIF) paradigm. In this paper, we introduce the self-stabilizing COPIF (for Collaborative PIF) scheme. An algo- rithm is provided with its correctness proof. We use this approach to improve a distributed P2P framework designed for the services discovery. Significantly efficient experimental results are presented.
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Rapport
[Research Report] 2012
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Soumis le : jeudi 5 juillet 2012 - 15:14:27
Dernière modification le : vendredi 20 avril 2018 - 15:44:24
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  • HAL Id : hal-00714775, version 1
  • ARXIV : 1207.1337

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Eddy Caron, Florent Chuffart, Anissa Lamani, Franck Petit. Optimization in a Self-Stabilizing Service Discovery Framework for Large Scale Systems. [Research Report] 2012. 〈hal-00714775〉

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