《计算机应用研究》|Application Research of Computers

一种基于杂草优化的全局Web服务选择算法

Global Web service selection algorithm based on weed optimization

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作者 马良荔,苏凯,肖斌,苏晓光
机构 海军工程大学 a.计算机工程系;b.装备经济管理系,武汉 430033
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文章编号 1001-3695(2017)08-2412-05
DOI 10.3969/j.issn.1001-3695.2017.08.040
摘要 随着网络中的Web服务数量的暴增,基于QoS的服务选择成为保证组合服务质量和可靠性的关键环节。针对当前服务选择算法全局优化能力弱的问题,将服务选择建模为带约束的非线性最优化问题,并提出一种基于杂草优化的服务选择算法。首先随机产生一组服务选择可行解并将其编码为杂草个体,进而根据个体的QoS效用值确定个体的繁殖数,最后以高斯分布方式指导种群的扩散完成对解空间的快速搜索。理论分析与实验结果表明,该算法有效性和鲁棒性强,可获得相较于已有文献更优的全局解。
关键词 Web服务;服务选择;服务质量;杂草优化
基金项目 国家自然科学基金资助项目(51509252)
总装预研基金资助项目
军工程大学科研发展基金资助项目
本文URL http://www.arocmag.com/article/01-2017-08-040.html
英文标题 Global Web service selection algorithm based on weed optimization
作者英文名 Ma Liangli, Su Kai, Xiao Bin, Su Xiaoguang
机构英文名 a.Dept.ofComputerEngineering,b.Dept.ofEquipmentEconomics&Management,NavalUniversityofEngineering,Wuhan430033,China
英文摘要 With the increasing number of Web services on network, QoS based service selection becomes a key factor to ensure the quality and reliability of service-oriented system. Existing service selection algorithm fail to achieve global results. To attack this problem, this paper modeled the service selection problem as a constrained non-linear optimization problem. Then it proposd a weed optimization based service selection algorithm. Firstly, it randomly generated and coded a group of feasible solutions to weed individual. Then, it calculated the reproduction numbers of weed individuals based on their QoS utility value. Finally, the weed population would spread in manner of Gaussian distribution to search the solution space. The theoretical analysis and experimental results demonstrate the efficiency and robustness of the proposed algorithm. This approach can achieve better global results than existing state-of-the-art approaches.
英文关键词 Web service; service selection; quality of service(QoS); weed optimization
参考文献 查看稿件参考文献
  [1] Saleem M S, Ding Chen, Liu Xumin, et al. Personalized decision-strategy based Web service selection using a learning-to-rank algorithm[J] . IEEE Trans on Services Computing, 2015, 8(5):727-739.
[2] 胡建强, 李涓子, 廖桂平. 一种基于多维服务质量的局部最优服务选择模型[J] . 计算机学报, 2010, 33(3):526-534.
[3] Hwang S, Hsu C, Lee C. Service selection for Web services with probabilistic QoS[J] . IEEE Trans on Services Computing, 2015, 8(3):467-480.
[4] Weng Jianshu, Miao Chunyan, GOH A. An entropy-based approach to protecting rating systems from unfair testimonies[J] . IEICE Trans on Information and Systems, 2006, 89(9):2502-2511.
[5] Liu Siyuan, Zhang Jie, Miao Chunyan, et al. iCLUB:an integrated clustering-based approach to improve the robustness of reputation systems[C] //Proc of the 10th International Conference on Autonomous Agents and Multiagent Systems. 2011:1151-1152.
[6] Ardagna D, Pernici B. Adaptive service composition in flexible processes[J] . IEEE Trans on Software Engineering, 2007, 33(6):369-384.
[7] 张成文, 苏森, 陈俊亮. 基于遗传算法的QoS感知的Web服务选择[J] . 计算机学报, 2006, 29(7):1029-1037.
[8] 刘书雷, 刘云翔, 张帆, 等. 一种服务聚合中QoS全局最优服务动态选择算法[J] . 软件学报, 2007, 18(3):651-655.
[9] 张氢, 陈丹丹, 秦仙蓉, 等. 杂草算法收敛性分析及其在工程中的应用[J] . 同济大学学报:自然科学版, 2011, 38(11):1689-1693.
[10] Mehrabian A R, Lucas C. A novel numerical opimization algorithm inspired from weed colonization[J] . Ecological Informatics, 2006, 1(4):355-366.
[11] Karimkashi S, Kishk A A. Invasive weed optimization and its features in electromagnetics[J] . IEEE Trans on Antennas and Propagation, 2010, 58(4):1269-1278.
[12] Zeng Liangzhao, Benatallah B, Dumas M, et al. Quality driven Web services composition[C] //Proc of the 12th International Conference on World Wide Web. 2003:411-421.
[13] Al-Masri E, Mahmoud Q H. Discovering the best Web service[C] //Proc of the 16th International Conferenceon World Wide Web. 2007:1257-1258.
[14] Al-Masri E, Mahmoud Q H. QoS-based discovery and ranking of Web services[C] //Proc ofthe 16th IEEEInternational Conference on Computer Communications and Networks. 2007:529-534.
[15] Su K, Ma L, Guo X, et al. An efficient parameter adaptive genetic algorithm for service selection with end-to-end QoS constraints[J] . Journal of Computational Information Systems, 2014, 10(2):581-588.
收稿日期 2016/5/22
修回日期 2016/7/5
页码 2412-2416
中图分类号 TP311
文献标志码 A