English

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

Distributed, Parallel, and Cluster Computing 2012-07-06 v1

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.

Keywords

Cite

@article{arxiv.1207.1337,
  title  = {Optimization in a Self-Stabilizing Service Discovery Framework for Large Scale Systems},
  author = {Eddy Caron and Florent Chuffart and Anissa Lamani and Franck Petit},
  journal= {arXiv preprint arXiv:1207.1337},
  year   = {2012}
}

Comments

(2012)

R2 v1 2026-06-21T21:31:13.403Z