计算机科学与应用  >> Vol. 4 No. 3 (March 2014)

Web服务组合QoS最优化问题研究
Research on the Qos Optimization of Web Service Composition Process

DOI: 10.12677/CSA.2014.43010, PDF, HTML, 下载: 2,433  浏览: 8,887  科研立项经费支持

作者: 李香善, 苏子义:东北师范大学计算机科学与信息技术学院,长春

关键词: QoSWeb服务组合算法布谷鸟算法Qos; Web Service Composition Algorithm; Cs Algorithm

摘要: 随着云计算的蓬勃发展,Web服务的研究和应用也迎来了新的挑战。传统的服务组合一般只考虑到服务的功能性需求,对服务的非功能性需求和总体服务质量(QoS)考虑较少。本文首先对近年来基于QoS的服务组合问题进行了归纳总结,目前大多数研究都是基于粒子群算法、模拟退火算法,skyline方法等。本文做出新的尝试,提出将布谷鸟算法应用于服务组合问题,通过使用从QWS数据集中挑选出的相似服务构建服务集进行实验,与传统的应用粒子群算法的服务组合方法进行对比,对提出的方法的可行性进行了验证。
Abstract: With the fast development of the cloud computing, the research on the Web Service has faced more challenges. Generally, traditional Web Service composition algorithms only take the consid- eration of the functional requirements, but care little about the non-functional requirements. This paper summarizes the research about the Web Services composition, most of which are based on the PSO algorithm, simulated annealing algorithm, skyline algorithm, etc. In this paper, we at- tempt to apply CS algorithm to the Web Service composition problem. Through experimenting on the services sets which are built by choosing similar services in the QWS dataset, comparing with the traditional method which uses PSO algorithm on the Web Service composition problem, the feasibility of the proposed method is verified.

文章引用: 李香善, 苏子义. Web服务组合QoS最优化问题研究[J]. 计算机科学与应用, 2014, 4(3): 50-58. http://dx.doi.org/10.12677/CSA.2014.43010

参考文献

[1] Tao, Q., Chang, H.-Y., Gu, C.-Q. and Yi, Y. (2012) A Novel Prediction Approach for Trustworthy QoS of Web Ser-vices. Expert Systems with Applications, 39, 3676-3681.
[2] 欧伟杰, 曾承, 曾青, 彭智勇, 王珍珍, 刘波, 马景燕 (2013) QoS感知的高效抽象服务选择. 小型微型计算机系统, 1, 1-8.
[3] 苏森, 李飞, 杨放春 (2008) 分布式环境中服务组合的迭代选择算法. 中国科学(E辑: 信息科学), 10, 1717-1732.
[4] 冯建周, 孔令富 (2013) 基于QoS的Web服务组合中多路径全局优化方法的研究. 小型微型计算机系统, 7, 1493-1497.
[5] 王尚广, 孙其博, 杨放春 (2011) 基于全局QoS约束分解的Web服务动态选择. 软件学报, 7, 1426-1439.
[6] Mardukhi, F., Ne-matBakhsh, N., Zamanifar, K. and Barati, A. (2013) QoS decomposition for service composition using genetic algorithm. Applied Soft Computing, 13, 3409-3421.
[7] 陈锦鹏, 万里 (2013) 基于离散粒子群算法全局QoS最优的Web服务选择. 网络安全技术与应用, 1, 50-53.
[8] 梅俊, 程耕国, 鲍考明 (2012) 基于QoS的动态Web组合服务选择方法. 工业控制计算机, 12, 70-72.
[9] 康国胜, 刘建勋, 唐明董, 徐宇 (2013) QoS全局最优动态Web服务选择算法. 小型微型计算机系统, 1, 73-76.
[10] 李金忠, 夏洁武, 刘昌鑫, 曾劲涛, 李满华 (2013) 一种新的QoS全局最优Web服务选择算法. 微电子学与计算机, 3, 97-101.
[11] Liu, M., Wang, M.R., Shen, W.M., Luo, N. and Yan, J.W. (2012) A quality of service (QoS)-aware execution plan selection approach for a service composition process. Future Generation Computer Systems, 28, 1080-1089.
[12] 夏亚梅, 程渤, 陈俊亮, 孟祥武, 刘栋 (2012) 基于改进蚁群算法的服务组合优化. 计算机学报, 2, 270-281.
[13] Yang, X.S. and Deb, S. (2009) Cuckoo search via Levy flights. Proceedings of World Congress on Nature & Biologically Inspired Computing, Coimbatore, 9-11 December 2009, 210-214.
[14] Zeng, L.Z., Benatallah, B., Dumas, M., et al. (2003) Quality driven Web Service composition. Proceedings of the International World Wide Web Conference, Budapest, 20-24 May 2003, 411-421.
[15] Alrifai, M. and Risse, T. (2009) Combining global optimization with local selection for efficient QoS aware service composition. ACM, New York, 881-890.
[16] Dong, Y.Y., Ni, H., Deng, H.J., et al. (2011) Service selection strategy offering global optimal quality of service. Journal of Chinese Computer System, 32, 455-459.