A Replica Selection Strategy On Ant-algorithm in Data-intensive Applications

Jinxian Lin, Ling Yang, Yuying Zheng

Abstract


In data-intensive applications, multiple copies of the same data were created to improve reliability and reduce the bandwidth consumption. Replica selection is the crucial factor in accessing data quickly and effectively. It affects task scheduling, thereby affecting the efficiency and service quality of the application. Within this paper, a modified replica selection strategy based on ant-algorithm in data-intensive grid is proposed. The strategy is implemented and compared with other file replica selection algorithms on simulator OptorSim. The experiments results show that the strategy discussed in this thesis has certain advantages in balancing the load of sites and reducing the mean job time.

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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