结合语义与事务属性的QoS感知的服务优化选择

发布时间：2018-04-21 16:44

本文选题：语义链接匹配度 + 服务质量　；参考：《计算机应用》2016年08期

【摘要】：服务级别协议(SLA)等级感知的服务选择是NP难题。针对服务选择中维度与粒度方面的问题,提出结合语义与事务属性的服务质量(QoS)感知的服务优化选择模型。该模型从语义链接匹配度、QoS与事务三个维度对服务进行优化选择,并设计了支持多粒度的编码策略。针对服务选择中时间复杂度高的问题,提出了克隆选择与遗传算法相结合的混合优化算法。该算法首先采用动态适应度函数,逐代淘汰不满足约束的个体;其次给出了事务属性的优先级,并根据优先级设计了知识启发式的交叉与变异算子,以保证个体满足事务属性要求;最后在遗传算法中对优秀个体进行克隆选择,以增强对最优解的搜索能力。仿真实验中,该算法在服务选择的精确度和成功率方面均优于遗传算法;在时间花费上稍高于遗传算法但远低于穷举法。实验结果表明,所提算法能在较少时间花费的基础上保证服务选择的质量。
[Abstract]:Service level Agreement (SLA)-aware service selection is a NP problem. In order to solve the problem of dimension and granularity in service selection, a QoS aware service optimization model based on semantic and transaction attributes is proposed. The model optimizes service selection from three dimensions of semantic link matching, QoS and transaction, and designs a multi-granularity coding strategy. Aiming at the problem of high time complexity in service selection, a hybrid optimization algorithm combining clone selection and genetic algorithm is proposed. Firstly, the algorithm uses dynamic fitness function to eliminate individuals who do not meet the constraints generation by generation, and then gives the priority of transaction attributes, and designs the knowledge heuristic crossover and mutation operators according to the priority. In order to ensure that the individual meets the requirements of transaction attributes, and finally in the genetic algorithm to clone the selection of outstanding individuals to enhance the search ability of the optimal solution. In the simulation experiment, the algorithm is superior to the genetic algorithm in the accuracy and success rate of service selection, and the time cost is slightly higher than the genetic algorithm but far lower than the exhaustive method. Experimental results show that the proposed algorithm can guarantee the quality of service selection on the basis of less time.
【作者单位】：同济大学电子与信息工程学院;山东交通学院理学院;同济大学软件学院;
【基金】：国家自然科学基金资助项目(41405097) 山东交通学院科研基金资助项目(Z201342)~~
【分类号】：TP393.09

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