基于文化社会认知算法的云服务优化组合研究

计算机科学 ›› 2013, Vol. 40 ›› Issue (5): 103-106.

基于文化社会认知算法的云服务优化组合研究

刘志中,王志坚,薛霄,鲁保云

河南理工大学计算机科学与技术学院焦作454000;河海大学计算机与信息工程学院南京210098;河南理工大学计算机科学与技术学院焦作454000;河南理工大学计算机科学与技术学院焦作454000

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金面上基金项目(61175066),国家自然科学基金青年基金项目(60905041,61202136),中国博士后科学基金(20110490396),河南省高校科技创新人才资助

Research on Cloud Service Composition Based on Culture Social Cognitive Optimization Algorithm

LIU Zhi-zhong,WANG Zhi-jian,XUE Xiao and LU Bao-yun

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： QoS感知的云服务优化组合是云计算领域亟需解决的问题。针对该问题,首先对社会认知算法进行了改进,然后将改进的社会认知算法纳入文化算法的框架之内,构造了新颖的文化社会认知算法,并采用该算法解决QoS感知的云服务优化组合问题。实验结果表明,文化社会认知算法在求解云服务优化组合问题时具有较强的搜索能力和较快的收敛速度；同时,该算法具有很强的推广性,可以用来求解其他类似的组合优化问题。

关键词: 云服务,云服务组合,服务质量,文化算法,社会认知算法

Abstract: QoS-aware cloud service composition is an challenge problem in the field of cloud computing．To solve this problem,this paper first improved the social cognitive optimization,and then put the improved SCO algorithm into the framework of Culture Algorithm,constructed a novel algorithm--culture social cognitive optimization(C-SCO),finally,used C-SCO to solve the QoS-aware cloud service composition problem．Experiment results show that C-SCO has stronger searching ability and faster convergence speed when solving cloud service composition problem．At the same time,C-SCO can also be used to solve other combination optimal problem.

Key words: Cloud computing,Cloud service composition,Quality of service,Social cognitive optimization,Culture algorithm

刘志中,王志坚,薛霄,鲁保云. 基于文化社会认知算法的云服务优化组合研究[J]. 计算机科学, 2013, 40(5): 103-106. https://doi.org/

LIU Zhi-zhong,WANG Zhi-jian,XUE Xiao and LU Bao-yun. Research on Cloud Service Composition Based on Culture Social Cognitive Optimization Algorithm[J]. Computer Science, 2013, 40(5): 103-106. https://doi.org/

参考文献

[1] Leavitt N．Is Cloud Computing Really Ready for Prime Time?[J]．IEEE Computer Society Press,2009,42(1):15-20
[2] 周红伟,李琦.基于云计算的空间信息服务系统研究[J].计算机应用研究,2011,8(7):2586-2588
[3] Vaquero L,Rodero-Marino L,Caceres J,et al．A break in theclouds :towards a cloud definition[J]．SIGCOMM Computer Communication Review,2009,39(1):50-55
[4] 孙香花．云计算研究现状与发展趋势[J]．计算机测量与控制,2011,19(5):998-1001
[5] 李乔,郑啸.云计算研究现状综述[J].计算机科学,2011,8(4):32-37
[6] 孙坦,黄国彬.基于云服务的图书馆建设与服务策略[J].图书馆建设,2009,9:1-6
[7] Ferrer A J,Hernandez F,Tordsson J,et al．OPTIMIS:Aholistic appraoch to cloud service provisioning[J]．Future Generation Computer Systems,2012,28:66-77
[8] Gutierrez-Garcia J O,Sim K-M．Self-Organiziing Agents for Ser-vice Composition in Cloud Computiiong[C]∥The Procee-dings of the International Conference on Cloud Computing Technology and Sciences．2010:59-66
[9] Canfora G,Penta D,Esposito M,et al．A lightweight approach for QoS-aware service composition[C]∥Proc．2^nd International Conference on Service oriented Computing(ICSOC,04)．NewYork,USA,2004:36-47
[10] Zeng L,Benatallah B,Ngu A H H,et al．QoS-Aware Middleware for Web Services Composition[J]．IEEE Transactions on Software Engineering,2004,30(5):311-327
[11] 刘书雷,刘云翔,张帆．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,2007,8(3):646-656
[12] Fang Qi-qing,Peng Xiao-ming,Liu Qing-hua,et al．A GlobalQoS Optimizing Web Services Selection Algorithm based on MOACO for Dynamic Web Service Composition[J]．International Forum on Information Technology and Application,2009,1:37-42
[13] 孙学胜,曹玖新,刘波,等．基于多目标粒子群优化的服务选择算法[J]．东南大学学报:自然科学版,2009,9(4):684-689
[14] Xie X F,Zhang W J．Solving engineerin g design problems by social cognitive optimization[C]∥Proceedings of the Genetic and Evolutionary Computat ion Conference．2004:26
[15] Xie X F,Zhang W J,Yang Z L．Social cognitive optimization for nonlinear programming problems[C]∥Proceedings of the International Conference on Machine Learning and Cybernetics．Beijing,China,2002:779-783
[16] Reynolds R G．An introduction to cultural algorithms[C]∥Proceedings of the Third Annual Conference on Evolutionary Programming.1994:131-139
[17] Wang Xiao-ying,Xue Yuan-yuan,Fan Li-hua,et al． Research on Adaptive QoS-Aware Resource Reservation Management in Cloud Service Environments[C]∥The Proceedings of the International Conference on Services Computing Conference(APSCC)．IEEE Asia-Pacific,2011:147-152
[18] Wang Zhi-jian,Liu Zhi-zhong,Zhou Xiao-feng,et al．An ap-proach for composite web service selection based on DGQoS[J]．The International Journal of Advanced Manufacturing Techno-logy,2011,56:1-13
[19] 陈彦萍,张建科,孙家泽,等．一种基于混合智能优化的服务选择模型[J].计算机学报,2010,33(11):2116-2125
[20] Dillenbourg P．Collaborative Learning:Cognitive and Computational Approaches．Advances in Learning and Instruction Series[M]．New York,NY:Elsevier Science,Inc,1999
[21] Peng B．Knowledge and population swarms in cultural algo-rithms for dynamic environments [D]．USA Wayne State University,2005
[22] 张佩云．基于语义的Web服务组合研究[D]．南京:南京理工大学,2008

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