Application of Discrete Particle Swarm Optimaization for Service Selection in Grid

Hongxia Xia, Jun Zhang, Xianming Zhao, Huazhu Song
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Abstract

Service selection plays a very important role in the grid middleware. Firstly, a service redundancy strategy is adapted and the corresponding target equation is designed for improving the QoS of the whole workflows in the grid. Secondly, considering of determining a optimal service schema virtually belongs to a combinatorial optimization problem, a resolving algorithm based on discrete particle swarm optimization to find a global optimum is proposed, and its encoding methods are given, In which, the suitable parameters in the algorithm are decided through the adjustment experiments. Finally, the results of some experiments show that the algorithm is feasible, and compared with some other algorithms, such as local optimization, greedy algorithm etc, the algorithm in the paper is more effective.
离散粒子群算法在电网服务选择中的应用
服务选择在网格中间件中起着非常重要的作用。首先,采用服务冗余策略,设计相应的目标方程,提高网格中整个工作流的QoS;其次,考虑到最优服务模式的确定实质上属于组合优化问题,提出了一种基于离散粒子群算法的全局最优求解算法,给出了其编码方法,并通过调整实验确定了算法中合适的参数。最后,通过实验验证了该算法的可行性,并与局部优化、贪心算法等算法进行了比较,证明了本文算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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