DOI: 10.3724/SP.J.1087.2013.03591

Journal of Computer Applications (计算机应用) 2013/33:12 PP.3591-3595

Iteration MapReduce framework for evolution algorithm

Modular programming of MapReduce greatly simplifies the implementation difficulty of distributed programming; however, its application scope is limited. In view of that MapReduce cannot be used to solve iteration algorithm, a new iteration MapReduce framework was proposed for evolutionary algorithm based on the study of MapReduce framework. The basic structure of the MapReduce was introduced, and the defects in implementing iteration algorithm were pointed out. The realization requirements and implementation of the proposed MapReduce framework were introduced, and the feasibility of abnormal mechanism was proposed and verified. At last, the new MapReduce framework was verified on Hadoop. The experimental results show that the parallel genetic algorithm based on the iteration MapReduce framework has higher speedup than that of MapReduce framework.

Key words:cloud computing,MapReduce,evolutionary algorithm,iteration,Hadoop

ReleaseDate:2014-07-21 16:58:58