Dynamic self-adaptive replica location method in data grids

Within data grid environments, data replication is a general mechanism to improve performance and availability for distributed applications. However, it is a challenging problem to find the physical locations of multiple replicas of desired data efficiently in large-scale wide area data grid systems. In this paper, we proposed a new dynamic self-adaptive distributed replica location method - DSRL to solve the problem. In DSRL, each data element has a home node, which maintains the indices of the location information replicas. Home nodes are used to support locating multiple replicas of the same data element efficiently. Meanwhile, DSRL employs local location nodes which maintain the local replica information of data elements to support local query for local replicas. A dynamic mapping technique that can adapt to the joining or departing of home nodes is utilized to spread global replica location information evenly on location nodes. The correctness and properties of DSRL are presented and proved. Analysis and experiments show that DSRL can achieve low latency, good scalability, reliability, adaptability and ease of implementation.