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ICSD: Integrated Cloud Services Dataset

机译:ICSD:集成云服务数据集

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摘要

The service composition problem in Cloud computing is formulated as a multiple criteria decision making problem. Due to the extensive search space, Cloud service composition is addressed as an NP-hard problem. Using a proper dataset is considered one of the main challenges to evaluate the efficiency of the developed service composition algorithms. According to the work in this paper, a new dataset has been introduced, called Integrated Cloud Services Dataset (ICSD). This dataset is constructed by amalgamating the Google cluster-usage traces, and a real QoS dataset. To evaluate the efficiency of the ICSD dataset, a proof of concept has been done by implementing and evaluating an existing Cloud service compositing approach; PSO algorithm with skyline operator using ICSD dataset. According to the implementation results, it is found that the ICSD dataset achieved a high degree of optimality with low time complexity, which significantly increases the ICSD dataset accuracy in Cloud services composition environment.
机译:云计算中的服务组成问题被制定为多标准决策问题。由于搜索空间广泛,云服务组成被称为NP难题。使用适当的数据集被认为是评估发发的服务组合算法效率的主要挑战之一。根据本文的工作,介绍了一个新的数据集,称为集成云服务数据集(ICSD)。通过合并Google Cluster-Usage Trave和Real QoS数据集来构造此数据集。为了评估ICSD数据集的效率,通过实施和评估现有的云服务合成方法来完成概念证明;使用ICSD DataSet与地平线运算符的PSO算法。根据实现结果,发现ICSD数据集具有低时间复杂度的高度最优,这显着提高了云服务组合环境中的ICSD数据集准确性。

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