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

TL;DR

This paper presents an improved self-stabilizing service discovery framework for large-scale P2P systems, introducing the COPIF scheme to enhance the existing DLPT approach with proven correctness and efficient experimental validation.

Contribution

The paper introduces the self-stabilizing COPIF scheme, enhancing the DLPT-based service discovery framework with a new algorithm and correctness proof for dynamic P2P environments.

Findings

Significant efficiency improvements demonstrated in experiments

Successful proof of correctness for the COPIF algorithm

Enhanced stability and scalability in P2P service discovery

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.