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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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https://hal.inria.fr/hal-00714775
Contributor : Anissa Lamani <>
Submitted on : Thursday, July 5, 2012 - 3:14:27 PM
Last modification on : Tuesday, April 27, 2021 - 3:37:48 PM
Long-term archiving on: : Thursday, December 15, 2016 - 8:55:24 PM

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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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