基于凸函数证据理论的关联感知云服务信任模型
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摘要
针对大规模分布式云计算系统中的服务可信度辨别问题,提出一种基于凸函数证据理论的关联感知云服务信任模型。对云计算系统中云服务提供商、服务和用户之间的信任关系进行形式化描述,充分挖掘了同一服务商中的不同云服务之间的关联性,利用凸函数证据理论对有序命题的处理能力,构建了云计算系统中的可信服务推荐方法,根据用户需求为其提供合理可靠的云服务。与经典证据理论方法的对比结果表明,基于凸函数证据理论的关联感知云服务信任模型在保证有效性和健壮性的同时,充分利用了云计算系统中云服务之间的关联信息,能够根据用户的请求提供合理的云服务。
Aiming at distinguishing service credibility in the large-scale distributed cloud computing system,we propose a relevance-aware cloud service trust model based on convex evidence theory.The model formally describes the trust relationship among service providers,services and users in the cloud computing system.Then,the correlation between different services from the same service provider is revealed.Furthermore,the model uses the convex evidence theory to deal with ordered propositions and finally builds a credible service recommendation method for the cloud computing system,which can provide reasonable and reliable cloud services for users according to user needs.Through the comparison with the classical evidence theory,the experimental results demonstrate the validity and robustness of the relevance-aware cloud service trust model based on convex evidence theory while can make full use of correlation information among cloud services in the cloud computing system and provide reasonable cloud services according to user requests.
Aiming at distinguishing service credibility in the large-scale distributed cloud computing system,we propose a relevance-aware cloud service trust model based on convex evidence theory.The model formally describes the trust relationship among service providers,services and users in the cloud computing system.Then,the correlation between different services from the same service provider is revealed.Furthermore,the model uses the convex evidence theory to deal with ordered propositions and finally builds a credible service recommendation method for the cloud computing system,which can provide reasonable and reliable cloud services for users according to user needs.Through the comparison with the classical evidence theory,the experimental results demonstrate the validity and robustness of the relevance-aware cloud service trust model based on convex evidence theory while can make full use of correlation information among cloud services in the cloud computing system and provide reasonable cloud services according to user requests.
引文
[1]Ping Yu,Xiang Yang,Zhang Bo,et al.Implementation of parallel PageRank algorithm based on MapReduce[J].Computer Engineering,2014,40(2):31-34.(in Chinese)
[2]Xie Zhi-ming,Wang Peng.Parallel matrix Apriori algorithm based on MapReduce architecture[J].Application Research of Computers,2017,34(2):401-404.(in Chinese)
[3]Liu Gui-xia,Li Guang-li,Li Han.Algorithms for detecting gene-gene interactions based on cloud platform[J].Journal of Jilin University(Science Edition),2014,52(3):546-550.(in Chinese)
[4]Yong W,Zhe Z,Fang W.A parallel algorithm of association rules based on cloud computing[C]∥Proc of International ICST Conference on Communications&Networking in China,2014:415-419.
[5]Liu Peng.Cloud computing[M].3rd edition.Beijing:Publishing House of Electronics Industry,2015.(in Chinese)
[6]Mell P,Grance T.A NIST definition of cloud computing[J].Communications of the ACM,2015,53(6):1-7.
[7]Ding Yan,Wang Huai-min,Shi Pei-chang,et al.Trusted cloud service[J].Journal of Computer Science,2015,38(1):133-149.(in Chinese)
[8]Li Jia-fei,Zhou Bin,Liu Da-you,et al.Massive information fusion algorithm and its application in status evaluation[J].Journal of Software,2014,25(9):2026-2036.(in Chinese)
[9]Ding Hai-yang,Li Xi-guang,Gong Chang-qing.Trust evaluation model in cloud computing[J].Computer Engineering and Design,2016,37(8):2007-2010.(in Chinese)
[10]Shu Jian,Liang Chang-yong.Dynamic trust model based on DS evidence theory under cloud computing environment[J].Computer Science,2016,43(8):105-109.(in Chinese)
[11]Fang En-guang,Wu Qing.Evidence theory based cloud computing trust model research[J].Computer Applications and Software,2012,29(4):68-70.(in Chinese)
[1]平宇,向阳,张波,等.基于MapReduce的并行PageRank算法实现[J].计算机工程,2014,40(2):31-34.
[2]谢志明,王鹏.基于MapReduce架构的并行矩阵Apriori算法[J].计算机应用研究,2017,34(2):401-404.
[3]刘桂霞,李广力,李涵.云平台下基因-基因相互作用识别算法[J].吉林大学学报(理学版),2014,52(3):546-550.
[5]刘鹏.云计算[M].第3版.北京:电子工业出版社,2015.
[7]丁滟,王怀民,史佩昌,等.可信云服务[J].计算机学报,2015,38(1):133-149.
[8]李嘉菲,周斌,刘大有,等.海量信息融合方法及其在状态评价中的应用[J].软件学报,2014,25(9):2026-2036.
[9]丁海洋,李席广,拱长青.云计算环境下的信任评估模型[J].计算机工程与设计,2016,37(8):2007-2010.
[10]束柬,梁昌勇.基于DS理论的多源证据融合云安全信任模型[J].计算机科学,2016,43(8):105-109.
[11]方恩光,吴卿.基于证据理论的云计算信任模型研究[J].计算机应用与软件,2012,29(4):68-70.
[2]Xie Zhi-ming,Wang Peng.Parallel matrix Apriori algorithm based on MapReduce architecture[J].Application Research of Computers,2017,34(2):401-404.(in Chinese)
[3]Liu Gui-xia,Li Guang-li,Li Han.Algorithms for detecting gene-gene interactions based on cloud platform[J].Journal of Jilin University(Science Edition),2014,52(3):546-550.(in Chinese)
[4]Yong W,Zhe Z,Fang W.A parallel algorithm of association rules based on cloud computing[C]∥Proc of International ICST Conference on Communications&Networking in China,2014:415-419.
[5]Liu Peng.Cloud computing[M].3rd edition.Beijing:Publishing House of Electronics Industry,2015.(in Chinese)
[6]Mell P,Grance T.A NIST definition of cloud computing[J].Communications of the ACM,2015,53(6):1-7.
[7]Ding Yan,Wang Huai-min,Shi Pei-chang,et al.Trusted cloud service[J].Journal of Computer Science,2015,38(1):133-149.(in Chinese)
[8]Li Jia-fei,Zhou Bin,Liu Da-you,et al.Massive information fusion algorithm and its application in status evaluation[J].Journal of Software,2014,25(9):2026-2036.(in Chinese)
[9]Ding Hai-yang,Li Xi-guang,Gong Chang-qing.Trust evaluation model in cloud computing[J].Computer Engineering and Design,2016,37(8):2007-2010.(in Chinese)
[10]Shu Jian,Liang Chang-yong.Dynamic trust model based on DS evidence theory under cloud computing environment[J].Computer Science,2016,43(8):105-109.(in Chinese)
[11]Fang En-guang,Wu Qing.Evidence theory based cloud computing trust model research[J].Computer Applications and Software,2012,29(4):68-70.(in Chinese)
[1]平宇,向阳,张波,等.基于MapReduce的并行PageRank算法实现[J].计算机工程,2014,40(2):31-34.
[2]谢志明,王鹏.基于MapReduce架构的并行矩阵Apriori算法[J].计算机应用研究,2017,34(2):401-404.
[3]刘桂霞,李广力,李涵.云平台下基因-基因相互作用识别算法[J].吉林大学学报(理学版),2014,52(3):546-550.
[5]刘鹏.云计算[M].第3版.北京:电子工业出版社,2015.
[7]丁滟,王怀民,史佩昌,等.可信云服务[J].计算机学报,2015,38(1):133-149.
[8]李嘉菲,周斌,刘大有,等.海量信息融合方法及其在状态评价中的应用[J].软件学报,2014,25(9):2026-2036.
[9]丁海洋,李席广,拱长青.云计算环境下的信任评估模型[J].计算机工程与设计,2016,37(8):2007-2010.
[10]束柬,梁昌勇.基于DS理论的多源证据融合云安全信任模型[J].计算机科学,2016,43(8):105-109.
[11]方恩光,吴卿.基于证据理论的云计算信任模型研究[J].计算机应用与软件,2012,29(4):68-70.