Study of Different Replica Placement and Maintenance Strategies in Data Grid

Abstract

Data replication is an excellent technique to move and cache data close to users. By replication, data access performance can be improved dramatically. One of the challenges in data replication is to select the candidate sites where replicas should be placed. We use a multi-objective model to address the replica placement problem. The multi-objective model considers the objectives of p-median and p-center models simultaneously to select the candidate sites that will host replicas. The objective of the p-median model is to find the locations of p possible candidate replication sites by optimizing total (or average) response time; where the p-center model finds p candidate sites by optimizing maximum response time. A grid environment is highly dynamic so user requests and network latency vary constantly. Therefore, candidate sites currently holding replicas may not be the best sites to fetch replica on subsequent requests. We propose a dynamic replica maintenance algorithm that re-allocates to new candidate sites if a performance metric degrades significantly over last K time periods. Simulation results demonstrate that the dynamic maintenance algorithm with multi-objective static placement decision performs best in dynamic environments like data grids.