为了提高Web服务选择效率,首先提出了一种树形结构组合服务服务质量计算模型,采用二叉树表示组合服务中的任务(抽象服务)及依赖关系,自底向上逐层汇聚服务质量属性,通过树形结构避免了大量的重复计算,减少了组合服务服务质量的计算时间.然后提出了一种基于量子遗传算法的服务选择方法,采用二维多量子比特编码染色体,并附加标志位表示多路径信息,用量子旋转门实现个体的进化.对比实验结果表明,相对于传统遗传算法,基于量子遗传算法的服务选择方法能在更短的时间内得到更好的解.
To improve the efficiency of web services selection, a computational model for computing the QoS attributes of composite services is first presented, which utilizes a binary tree to express the dependency relationship of tasks in composite services, and aggregates the QoS attributes of different nodes in a bottom-up fashion. As a result, the QoS computing time is reduced by avoiding unnecessary repetitive computation. Then a web services selection approach based on the QGA (Quantum Genetic Algorithm) is proposed. Two dimensional multi-qubits (quantum bits) are employed to code chromosomes with attached identifier marking multi-paths. The quantum rotation gate is introduced to accelerate individual evolution. Experimental results show that, compared with the TGA (Traditional Genetic Algorithm), the QGA can give a better solution in a shorter time.