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首页> 外文会议>IEEE International Conference on computer supported cooperative work in design >Comparative Analysis of Evolutionary Algorithms Based on Swarm Intelligence for QoS Optimization of Cloud Services
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Comparative Analysis of Evolutionary Algorithms Based on Swarm Intelligence for QoS Optimization of Cloud Services

机译：基于群智能的云服务QoS优化进化算法比较分析

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摘要

As the technology of cloud computing becomes mature, the service idea of IT resources has been promoted rapidly. The various available cloud services have different quality of service (QoS). Different users have different QoS requirements for services. Finding the best QoS strategy which a user is satisfied with is a multi-criteria NP-hard problem. The completed theory and applied research have proved that the swarm intelligence method can effectively solve most multiobjective optimization problems. Therefore, a Pareto optimal solution for QoS strategy can be found by an evolutionary algorithm based on swarm intelligence. However, so far, only few solutions based on these approaches have been proposed and there exists no comparative study published to date. This motivated us to perform an analysis of state of the art evolutionary algorithm based on swarm intelligence. By a large number of contrast experiments under different circumstances, three QoS evolutionary algorithms based on swarm intelligence are analyzed and compared.
机译：随着云计算技术的成熟，IT资源的服务理念得到了快速推广。各种可用的云服务具有不同的服务质量（QoS）。不同的用户对服务有不同的QoS要求。寻找用户满意的最佳QoS策略是一个多准则NP难题。完整的理论和应用研究证明，群体智能方法可以有效地解决大多数多目标优化问题。因此，可以通过基于群体智能的进化算法找到QoS策略的Pareto最优解。但是，到目前为止，仅提出了几种基于这些方法的解决方案，并且迄今为止还没有发表比较研究。这促使我们对基于群体智能的最新进化算法进行分析。通过在不同情况下的大量对比实验，分析和比较了三种基于群体智能的QoS进化算法。

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