A Novel Strategy for Performance and Analysis of Web Service Business Activity using Particle Swarm Optimization Technique

Abstract: Data mining is an interdisciplinary subfield of computer science. The web services business activity developed by the OASIS (Organization for the Advancement of Structured Information Standards) groups. The framework developed had an initiator, a coordinator, and more than one participant. But with increased number of participants and unlimited number of clients and servers the problem of fault recognition became critical. The problem of faulty nodes at either client or server node was detected by lightweight Byzantine Fault Tolerant (BFT) system. The BFT is used for the selection of the appropriate server and client nodes using a Travelling salesman problem. The problem of both client and server node selection was further improved by the use of a heuristic technique known as Particle Swarm Optimization which helps in finding the global best and local best server and client nodes. PSO gives a better and faster method of fault tolerance and enhances the performances than BFT.

Keywords: Data mining, Byzantine Fault Tolerant system, Particle Swarm Optimization and Organization for the Advancement of Structured Information Standards