An intelligent dynamic replica selection model within grid systems

Abstract

Grid systems have emerged as a means of sharing computational resources and information. Providing services for accessing, sharing and modifying large databases is a crucial task for grid management systems. This paper proposes an artificial neural network (ANN) prediction mechanism that provides an enhancement to data replication solutions within grid systems. Current replication services often exhibit an increase in response time, reflecting the problems associated with the ever increasing size of databases. The proposed replica selection prediction model will locate files for incoming jobs using users' historical executions. Experimental results demonstrate the significant gains achieved by the proposed solution in terms of high accuracy and low overheads.