利用前景理论的不确定QoS感知Web服务选择
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摘要
在QoS不确定条件下,为使Web服务选择结果满足用户QoS属性需求和选择服务时的风险态度,该文提出了一种基于前景理论的不确定QoS感知Web服务选择方法.首先,选取用户QoS需求作为参照点,比较用户需求与Web服务QoS属性关系得出相较于用户需求的收益和损失,并构建风险收益矩阵和风险损失矩阵;然后利用经验分布函数对Web服务QoS属性的不确定性进行描述;最后考虑用户的风险态度,根据得出的风险矩阵和QoS属性的分布概率,分别使用前景理论中的价值函数和概率权重函数计算得出候选服务的综合前景值并进行排序选择.选择结果满足用户需求和风险态度,从而使得选择结果能最大程度上满足用户期望.通过实验验证该服务选择方法的合理性和有效性.
Under the condition of uncertain QoS,in order to make the results of Web service selection satisfy the user's QoS attribute requirement and the risk attitude of selecting service,this paper proposes an uncertain QoS aware Web service selection method based on the prospect theory. First,the requirement of user is selected as the reference point for QoS attribute requirements,and the risky gain matrix and risky loss matrix are constructed by calculating the gasses and losses for the QoS attribute values relative to the reference points. Then,the empirical distribution function is used to describe the uncertainty of Web service QoS attribute. Finally,considering the user's risk attitude,according to the risky matrix and the distribution probability of QoS attribute,the comprehensive prospect values of the candidate services are calculated by using the value function and the probability weight function in the prospect theory,and these values are selected and sorted. The selection results satisfy users' needs and risk attitudes,so that the selection results can satisfy users' expectations to the greatest extent. The rationality and effectiveness of the service selection method are verified by experiments.
Under the condition of uncertain QoS,in order to make the results of Web service selection satisfy the user's QoS attribute requirement and the risk attitude of selecting service,this paper proposes an uncertain QoS aware Web service selection method based on the prospect theory. First,the requirement of user is selected as the reference point for QoS attribute requirements,and the risky gain matrix and risky loss matrix are constructed by calculating the gasses and losses for the QoS attribute values relative to the reference points. Then,the empirical distribution function is used to describe the uncertainty of Web service QoS attribute. Finally,considering the user's risk attitude,according to the risky matrix and the distribution probability of QoS attribute,the comprehensive prospect values of the candidate services are calculated by using the value function and the probability weight function in the prospect theory,and these values are selected and sorted. The selection results satisfy users' needs and risk attitudes,so that the selection results can satisfy users' expectations to the greatest extent. The rationality and effectiveness of the service selection method are verified by experiments.
引文
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[24] Sheng Q Z,Benatallah B,Dumas M,et al. SELF-SERV:a platform for rapid composition of Web services in a peer-to-peer environment[C]. Proceedings of the 28th VLDB Conference,Hong Kong,China,2002:1051-1054.
[25] Zhou Yan-ju,Ying Ren-ren,Chen Xiao-hong,et al. The ordering model of tw o product new sboy based on prospect theory[J]. Journal of M anagement Sciences in China,2013,16(11):17-29.
[3]付晓东,岳昆,邹平,等.随机服务质量感知的Web服务信誉度量模型[J].计算机集成制造系统,2011,17(8):1844-1850.
[6]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.
[11]李玲,刘敏,成国庆.一种基于FAHP的多维QoS局部最优服务选择模型[J].计算机学报,2015,38(10):1997-2010.
[12]彭桃,刘建勋,唐明董,等.考虑不确定QoS值的Web服务选择方法[J].小型微型计算机系统,2015,36(11):2467-2472.
[13]张龙昌.均衡收益和风险的Web服务Skyline查询[J].北京邮电大学学报,2017,40(1):124-129.
[16]康国胜,刘建勋,唐明董,等. QoS全局最优动态Web服务选择算法[J].小型微型计算机系统,2013,34(1):73-76.
[17]李睿.前景理论研究综述[J].社会科学论坛,2014,(2):214-222.
[25]周艳菊,应仁仁,陈晓红,等.基于前景理论的两产品报童的订货模型[J].管理科学学报,2013,16(11):17-29.
[2] Rosario S,Benveniste A,Haar S,et al. Probabilistic QoS and soft contracts for transaction-based Web services orchestrations[J].IEEE Transactions on Services Computing,2009,1(4):187-200.
[3] Fu Xiao-dong,Yue Kun,Zou Ping,et al. Stochastic QoS-aware reputation measurement model of Web services[J]. Computer Integrated M anufacturing Systems,2011,17(8):1844-1850.
[4] Kahneman D,Tversky A,Prospect Theory. An analysis of decision making under risk[J]. Econometrica,1979,47(2):263-291.
[5] Tversky A,Kahneman D. Advances in prospect theory:cumulative representation of uncertainty[J]. Journal of Risk&Uncertainty,1992,5(4):297-323.
[6] Hu Jian-qiang,Li Juan-zi,Liao Gui-ping. A multi-QoS based local optimal model of service selection[J]. Chinese Journal of Computers,2010,33(3):526-534.
[7] Gao Yan,Na Jun,Zhang Bin,et al. An environment adaptation approach for composite services based on local Pareto optimal servies set[C]. Proceedings of the International Conference on Electronic Information and Electrical Engineering. Changsha,China,2012:888-892.
[8] Parejo J A,Segura S,Fernandez P,et al. QoS-aware web services composition using GRASP w ith path relinking[J]. Expert Systems w ith Applications,2014,41(9):4211-4223.
[9] Iordache R,Moldoveanu F. A genetic algorithm for automated service binding[J]. Procedia Engineering,2014,69(1):1162-1171.
[10] Alrifai M,Skoutas D,Risse T. Selecting skyline services for QoSbased w eb service composition[C]. International Conference on World Wide Web,ACM,2010:11-20.
[11] Li Ling,Liu Min,Cheng Guo-qing. A local optimal model of service selection of muti-QoS based on FAHP[J]. Chinese Journal of Computers,2015,38(10):1997-2010.
[12] Peng Tao,Liu Jian-xun,Tang Ming-dong,et al. Web service selection w ith uncertain QoS[J]. Journal of Chinese Computer Systems,2015,36(11):2467-2472.
[13] Zhang Long-chang. Web services skyline query balancing the benefits and risks[J]. Journal of Beijing University of Posts and Telecommunications,2017,40(1):124-129.
[14] Zheng Z,Lyu M R. An adaptive QoS-aware fault tolerance strategy for w eb services[J]. Empirical Softw are Engineering,2010,15(4):323-345.
[15] Zheng Zi-bin,Michael R. Optimal fault tolerance strategy selection for Web services[J]. International Journal of Web Services Research,2010,7(4):21-40.
[16] Kang Guo-sheng,Liu Jian-xun,Tang Ming-dong,et al. Dynamic Web services selection algorithm w ith globally optimal QoS[J].Journal of Chinese Computer Systems,2013,34(1):73-76.
[17] Li Rui. A review of prospect theory research[J]. Tribune of Social Sciences,2014,(2):214-222.
[18] Zheng Z,Zhang Y,Lyu M. Distuributed QoS evaluation for realw orld Web services[C]. Proceeding of the 8th IEEE International Conference on Web Services,Washington DC,IEEE Computer Society,2010:83-90.
[19] Markowitz H. Porfolio selection[J]. Theory&Practice of Investment M anagement Asset Allocation Valuation Portfolio Construction&Strategies Second Edition,1952,7(1):77-91.
[20] Yoon K P,Hwang C L. Multiple attribute decision making:an introduction[J]. European Journal of Operational Research,1995,4(4):287-288.
[21] Zi J,Zheng T. Strategic decisions for groping ball based on the criteria of expected monetary value and expected value of perfect information[J]. Chinese Journal of Engineering M athematics,2002,46(46):21-44.
[22] Hsin-Ting Su,Yeou-Koung Tung. Minimax expected opportunity loss:a new criterion for risk-based decision making[J]. Engineering Economist,2012,57(4):247-273.
[23] Liang Z,Guo J. Optimal proportional reinsurance under two criteria:maximizing the expected utility and minimizing the value at risk[J]. Anziam Journal,2010,51(4):449-463.
[24] Sheng Q Z,Benatallah B,Dumas M,et al. SELF-SERV:a platform for rapid composition of Web services in a peer-to-peer environment[C]. Proceedings of the 28th VLDB Conference,Hong Kong,China,2002:1051-1054.
[25] Zhou Yan-ju,Ying Ren-ren,Chen Xiao-hong,et al. The ordering model of tw o product new sboy based on prospect theory[J]. Journal of M anagement Sciences in China,2013,16(11):17-29.
[3]付晓东,岳昆,邹平,等.随机服务质量感知的Web服务信誉度量模型[J].计算机集成制造系统,2011,17(8):1844-1850.
[6]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.
[11]李玲,刘敏,成国庆.一种基于FAHP的多维QoS局部最优服务选择模型[J].计算机学报,2015,38(10):1997-2010.
[12]彭桃,刘建勋,唐明董,等.考虑不确定QoS值的Web服务选择方法[J].小型微型计算机系统,2015,36(11):2467-2472.
[13]张龙昌.均衡收益和风险的Web服务Skyline查询[J].北京邮电大学学报,2017,40(1):124-129.
[16]康国胜,刘建勋,唐明董,等. QoS全局最优动态Web服务选择算法[J].小型微型计算机系统,2013,34(1):73-76.
[17]李睿.前景理论研究综述[J].社会科学论坛,2014,(2):214-222.
[25]周艳菊,应仁仁,陈晓红,等.基于前景理论的两产品报童的订货模型[J].管理科学学报,2013,16(11):17-29.