Dynamic Service Selection Based on Adaptive Global QoS Constraints Decomposition

Dynamic Service Selection Based on Adaptive Global QoS Constraints Decomposition
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基于自适应全局QoS约束分解的动态服务选择

DOI:
10.3390/sym11030403
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发表时间:
2019-03
期刊:
影响因子:
2.7
通讯作者:
Zhai Huawei
Zhai Huawei
中科院分区:
综合性期刊4区
文献类型:
--
作者:
Yuan Yuan;Zhang Weishi;Zhang Xiuguo;Zhai Huawei

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随着越来越多的Web服务具有相同或相似的功能,但不同的服务质量(QoS),QoS感知的服务组合的挑战是有效地选择合适的组件服务,以实现最大的效用,并满足全球QoS约束,以较低的时间成本。本文提出了一种基于自适应全局QoS约束分解的动态服务选择方法。采用模糊逻辑技术和文化遗传算法,自适应地将全局QoS约束分解为近似最优的局部约束。根据近似最优的局部约束条件,为每个服务类在运行时间内有效地选择最优服务。实验结果表明,该方法不仅获得了近似最优解,而且显著减少了计算时间,具有良好的适应性和可扩展性。
As there are more and more available Web services with the same or similar functionalities but different Quality of Service (QoS), the challenge of QoS-aware service composition is to efficiently select appropriate component services to achieve maximum utility and meet the global QoS constraints with low time cost. In this paper, we propose a dynamic service selection approach based on adaptive global QoS constraints decomposition. Fuzzy logic technology and Cultural Genetic Algorithm are used to adaptively decompose global QoS constraints into near-optimal local constraints. According to the near-optimal local constraints, the optimal service is selected for each service class during the running time efficiently. Experimental results show that the proposed approach not only achieves the near-optimal solution, but also significantly reduces the computation time, and has good adaptability and scalability.
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