基于全局QoS分解的多约束服务选取方法

Multi-constraint Service Selection Based on Decomposition of Global QoS

随着云计算环境下Web服务数量的快速增长,用户对动态的服务组合提出了新的要求,即在较短的时间内获取满足多约束条件下的高质量组合服务。针对上述要求,提出了基于全局QoS(QualityofService)分解的多约束服务选取方法,使用文化遗传算法对全局QoS约束进行最优分解,同时结合候选服务之间的功能性约束对服务进行过滤,从而缩小候选服务空间。设计自适应替换策略用来动态调整QoS约束边界,从而确保能够通过局部最优获得高质量的组合服务。仿真实验证明该方法能够用较短时间获取接近全局最优的组合服务,满足服务选取的动态性和实时性。

With the rapid growth of Web services in cloud computing environment, users make new demands on dynamic service composition, that quickly selects composite service which can meet multi-constraints. According to the demand, a multi-constraint service selection method based on decomposition of global QoS was proposed. A new cultural genetic algorithm was designed to decompose the global QoS constraints, and services were filtered by combining with the functional constraints between candidate services. An adaptive replacement strategy was used to dynamically adjust QoS constraint boundaries, so as to ensure the most appropriate composite service obtained by local selection. Experimental results show that the method can obtain nearly optimal composite service with a low time cost, which meets the dynamical and real-time features of service selection.