The AppLeS parameter sweep template: user-level middleware for the grid
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Simulation of Dynamic Grid Replication Strategies in OptorSim
GRID '02 Proceedings of the Third International Workshop on Grid Computing
Identifying Dynamic Replication Strategies for a High-Performance Data Grid
GRID '01 Proceedings of the Second International Workshop on Grid Computing
The Globus Project: A Status Report
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
A Unified Resource Scheduling Framework for Heterogeneous Computing Environments
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Integration of scheduling and replication in data grids
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
Scalable and distributed mechanisms for integrated scheduling and replication in data grids
ICDCN'08 Proceedings of the 9th international conference on Distributed computing and networking
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Data grids seek to harness geographically distributed resources for large-scale data-intensive problems. Such problems involve loosely coupled jobs and large data sets mostly distributed geographically. Data grids have found applications in scientific research, in the field of high-energy Physics, Life Sciences etc. The issues that need to be considered in the data grid research area include: resource management including computation management and data management. Computation management include scheduling of jobs, scalability, response time involved in such scheduling, while data management include data replication in selected sited, data movement when required. Therefore, scheduling and replication assumes great importance in a data grid environment. In this paper, we have developed several scheduling strategies based on a developed replication strategy. The scheduling strategies are called Matching based Scheduling (MJS), Cost base Scheduling (CJS) and Latency based Scheduling (LJS). Among these, LJS and CJS perform similarly and MJS performs worse than both of them.