A Dynamic Replica Placement Strategy in Grid Environment
Grid computing emerges in part from the need to integrate a collection of distributed computing resources to offer performance unattainable by any single machine. Grid technology facilitates data sharing across many organizations in different geographical locations. Data replication is an excellent technique to move and cache data close to users. Replication reduces access latency and bandwidth consumption. It also facilitates load balancing and improves reliability by creating multiple data copies. One of the challenges in data replication is to select the candidate sites where replicas should be placed, which is known as the allocation problem. One performance metric to determine the best place to host replicas is select for optimum average (or aggregated ) response time. We use the p-median model for the replica placement problem. The p-median model has been exploited in urban planning to find locations where new facilities should be built. In our problem, the p-median model finds the locations of p candidate sites to place a replica that optimize the aggregated response time. A Grid environment is highly dynamic so user requests and network latency vary constantly. Therefore, the 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 sties if a performance metric degrades significantly over last K time periods. Simulation results demonstrate that the dynamic maintenance algorithm with static placement decisions performs best in dynamic environments like Data Grids.