Fuzzy Logic Based QoS Optimization Mechanism for Service Composition
Fuzzy Logic Based QoS Optimization Mechanism for Service Composition
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DOI：
10.1109/sose.2013.28
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发表时间：
2013-03
期刊：
影响因子：
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通讯作者：
Silvana de Gyvés Avila;K. Djemame
中科院分区：
文献类型：
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作者：
Silvana de Gyvés Avila;K. Djemame
对服务质量的日益重视和高度变化的环境使得组合服务的管理成为一项既耗时又复杂的任务。自适应方法旨在通过调整组合服务以适应环境条件、保持功能和质量级别以及减少人为干预来缓解管理问题。提出了一种基于模糊逻辑实现自寻优的自适应方法。该优化模型通过分析组合服务执行过程中不同阶段收集的历史和真实服务质量数据进行服务选择。模糊推理系统的使用使得能够评估测量的Qos值，有助于决定是否需要适配以及如何执行服务选择。实验结果表明，用例场景的全局服务质量有了显著提高，响应时间减少了20.5%，成本减少了33.4%，能耗减少了31.2%。
Increase emphasis on Quality of Service and highly changing environments make management of composite services a time consuming and complicated task. Adaptation approaches aim to mitigate the management problem by adjusting composite services to the environment conditions, maintaining functional and quality levels, and reducing human intervention. This paper presents an adaptation approach that implements self-optimization based on fuzzy logic. The proposed optimization model performs service selection based on the analysis of historical and real QoS data, gathered at different stages during the execution of composite services. The use of fuzzy inference systems enables the evaluation of the measured QoS values, helps deciding whether adaptation is needed or not, and how to perform service selection. Experimental results show significant improvements in the global QoS of the use case scenario, providing reductions up to 20.5% in response time, 33.4% in cost and 31.2% in energy consumption.