Optimization in a Self-Stabilizing Service Discovery Framework for Large Scale Systems - Archive ouverte HAL
Rapport (Rapport De Recherche) Année : 2012

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

Résumé

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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Dates et versions

hal-00714775 , version 1 (05-07-2012)

Identifiants

Citer

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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