Presentation of Multi Level Data Replication Distributed Decision Making Strategy for High Priority Tasks in Real Time Data Grids

Naghmeh Esmaily, M. Jafari, Mehran Mohsen Zadeh
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Abstract

Real time data grids are some type of data grids in which the jobs should be done within a definite time period. If this period takes a longer time, the programs will not possibly be executed within the specified time period. Data replication issue is brought up as a procedure for prompt access to data and execution of programs within the specified deadline in the grids. In data replication, the parameters under assessment for replication, selection of the file to be replicated, number of replications and the location of new copies are important challenges that should be addressed. In this paper, dynamic replication algorithm of a new data called Distributed Date Replication (DDR) is introduced that improves the mentioned challenges and meets real time data by distributed decision for replication in three levels. Simulation results showed that the average time for executing the jobs and server traffic in DDR algorithm decreased as compared to other algorithms and less jobs failed.
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实时数据网格中高优先级任务的多级数据复制分布式决策策略
实时数据网格是某些类型的数据网格,其中的作业应在确定的时间段内完成。如果设置的时间过长,则程序可能无法在指定的时间内执行。数据复制问题是作为在网格中指定的截止日期内快速访问数据和执行程序的过程提出的。在数据复制中,评估复制的参数、选择要复制的文件、复制的数量和新副本的位置是应该解决的重要挑战。本文提出了一种新的数据动态复制算法——分布式数据复制(DDR),该算法通过三层复制的分布式决策来解决上述问题,满足实时数据的需求。仿真结果表明,与其他算法相比,DDR算法中作业的平均执行时间和服务器流量都有所减少,作业失败的情况也有所减少。
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