Improving job scheduling performance with dynamic replication strategy in data grids

Authors:
Nguyen Dang Nhan;Soon Wook Hwang;Sang Boem Lim
Affiliations:
Korea Institute of Science and Technology Information, Daejeon, Republic of Korea;Korea Institute of Science and Technology Information, Daejeon, Republic of Korea;Konkuk University, Seoul, Republic of Korea
Venue:
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
Year:
2007

Citing 5
Cited 1

Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications

HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Simulation of Dynamic Data Replication Strategies in Data Grids

IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Evaluating Scheduling and Replica Optimisation Strategies in OptorSim

GRID '03 Proceedings of the 4th International Workshop on Grid Computing
The impact of data replication on job scheduling performance in the Data Grid

Future Generation Computer Systems
Integration of scheduling and replication in data grids

HiPC'04 Proceedings of the 11th international conference on High Performance Computing

A Decentralized Periodic Replication Strategy Based on Knapsack Problem

GRID '12 Proceedings of the 2012 ACM/IEEE 13th International Conference on Grid Computing

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Abstract

Dealing with a large amount of data in Data Grids makes the requirement for efficient data access more critical. In this paper, we proposed a new approach to replication problem by organizing the data into several data categories that it belongs to. This organizing will help improving placement strategy of data replication. We studied our approach in combination with scheduling issue and evaluating it through simulation. The result shows that our strategy has improved the scheduling performance by 30%.