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A fuzzy logic-based method for solving the scheduling problem in the cloud environments using a non-dominated sorted algorithm

机译:一种基于模糊逻辑的方法,用于使用非主治排序算法解决云环境中的调度问题

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摘要

Cloud computing as a new model of delivering IT services on the Internet has attained highattention recently. In this new paradigm, efficient service management causes the high qualityof provided services. Scheduling as one of the most important duties of service managementis a key problem in cloud computing that affects the total system performance. In most cases,the meta-heuristic methods are used for optimizing the scheduling issues instead of traditionalmethods. One of the influential evolutionary algorithms for optimizing the complicated problemsis a non-dominated sorting particle swarm optimization (NSPSO) technique. In this paper, wepropose a meta-heuristic technique using the NSPSO model for decreasing total cost andconsumed total time. Furthermore, fuzzy set theory is applied to select the best solution.Simulation results have indicated that the efficiency of NSPSO is improved. In the many types ofexperiment, the proposed NSPSO algorithm was appropriate to keep a good spread of solutionsand good converge. In addition, the diversity preserving mechanism applied in NSPSO hasimprovement against the other two investigated algorithms.
机译:云计算作为在互联网上提供IT服务的新模型已经达到高关注最近。在这种新的范例中,高效的服务管理导致高质量提供的服务。整体调度服务管理的最重要的职责之一是云计算中的关键问题,影响总系统性能。在大多数情况下,元启发式方法用于优化调度问题而不是传统方法。用于优化复杂问题的有影响力的进化算法之一是一种非支配排序粒子群优化(NSPSO)技术。在本文中,我们使用NSPSO模型提出了一个元启发式技术,以降低总成本和消耗总时间。此外,应用模糊集理论选择最佳解决方案。仿真结果表明,NSPSO的效率得到改善。在许多类型中实验,所提出的NSPSO算法适合保持良好的解决方案传播良好的融合。此外,在NSPSO中应用的多样性保存机制改善其他两个调查算法。

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