基于时间序列的感知QoS的云服务组合

摘要/Abstract

摘要：

研究基于时间序列的感知QoS的云服务组合，将服务的QoS偏好随时间不断变化的过程纳入云服务组合的研究范围，将云服务组合建模成时间序列的相似度对比问题。分别用欧几里得距离和扩展Frobenius范数距离度量二维时间序列的相似度，继而用基于主成分分析的扩展Frobenius范数距离和欧几里得距离、BruteForce等方法度量多维时间序列的相似度，通过实验对比验证扩展Frobenius范数距离度量相似度在时间和准确性上的优越性。关

关键词: 时间序列, QoS, 云服务组合, 相似度对比

Abstract:

In this paper, we study QoS-aware cloud service composition based on time series, taking the sustaining change process of service QoS preference into research scope of cloud service composition,and transform the composition of cloud services into similarity comparison problems between time series.Euclidean distance and the extend Frobenius norm distance are used to measure similarity between two-dimensional time series respectively. In the next,the extend Frobenius norm distance or Euclidean distance based on principal component analysis and BruteForce method are adopted to measure the similarity between multidimensional time series. Experiments show that the extend Frobenius norm distance has better performance on similarity measurement in time and accuracy.

Key words: time series;QoS;cloud service composition;similarity comparison

肖文娟，段玉聪. 基于时间序列的感知QoS的云服务组合[J]. J4, 2014, 36(11): 2061-2066.

XIAO Wenjuan，DUAN Yucong. QoS-aware cloud service composition based on time series [J]. J4, 2014, 36(11): 2061-2066.

参考文献［20］

［1］	Strunk A. QoSaware service composition:A survey［C］∥Proc of the 2010 8th IEEE European Conference on Web Services(ECOWS’10), 2010:6774.
［2］	Canfora G, Di Penta M, Esposito R, et al. An approach for QoSaware service composition based on genetic algorithms［C］∥ Proc of the 2005 ACM Conference on Genetic and Evolutionary Computation（GECCO’05）, 2005:10691075.
［3］	Gao C,Cai M,Chen H.QoSaware service composition based
	Table 1Comparison of similarity on twodimensional time series表1二维时间序列相似度对比结果请求服
	务类型欧几里得距离度量扩展Frobenius范数距离度量0.1/0.90.3/0.70.5/0.50.7/0.30.9/0.103/321.9369848756152/2.243246744710582/2.486891282933622/2.7305358211566610/2.8078311807299210/2.6459195097181818/355.7040052212098/1.936386894784848/2.197064950831648/2.457743006878448/2.718421062925248/2.97909911897203213/860.13099396108317/4.7004738533263112/4.6540973064072412/4.2750662632489312/3.8960352200906113/3.35726820393366318/282.02558391860821/1.9363433565637519/2.0756242016234119/2.173954282169219/2.272284362714999/2.37061444326079423/257.91726147795423/1.8172807204055123/2.2323270375084823/2.6473733546114525/2.8860910143735225/3.09579328146301 on treecoded genetic algorithm ［C］∥Proc of the 31st IEEE Annual International Computer Software and Applications Conference（COMPSAC）,2007:361367.
［4］	Ma Y,Zhang C.Quick convergence of genetic algorithm for QoSdriven web service selection ［J］. Computer Networks, 2008,52 (5):10931104.
［5］	Tang M,Ai L.A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition［C］∥ Proc of IEEE Congress on Evolutionary Computation, 2010:18.
［6］	Ai L, Tang M, Fidge C. Partitioning composite web services for decentralized execution using a genetic algorithm ［J］. Future Generation Computer Systems, 2011, 27 (2):157172.
［7］	Wu Q, Zhu Q, Li P. A caching mechanism for QoSaware service composition ［J］. Journal of Web Engineering ,2012,11 (2):119130.
［8］	Chen Liang,Sun Min.Web services composition method based on immune genetic algorithm［J］. Computer Engineering, 2010, 36(10):226230.(in Chinese)
［9］	Zheng X,Luo J,Song A.Ant colony system based algorithm for QoSaware web service selection［C］∥ Proc of the 4th International Conference on Grid Service Engineering and Management( GSEM), 2007:3950.
［10］	Dhore S R, Kharat M. QoS based web services composition using ant colony optimization:Mobile agent approach ［J］. International Journal of Advanced Research in Computer and Communication Engineering, 2012, 1(7):519527.
［11］	Zhou Xianzhong,Wu Kui,Xiao Yihong.Automatic web service composition based on any colony algorithm［C］∥Proc of Decision Evaluation and Science, 2009:228236.(in Chinese)
［12］	Shen Jiquan, Zheng Xuefeng, Tu Xuyan. An approach to service composition based on ant colony algorithm［J］.Journal of Wuhan University of Technology (Transportation Science & Engineering), 2009, 33(6):11791182.(in Chinese)
［13］	Yin Rongwang,Mao Zhijian.A QoSguaranteed web service composition［J］. Computer Knowledge and Technology (Network Communication and Security), 2007(11):12761278.(in Chinese)
［14］	Liu Qing, Zhang Shilong, Yang Rui, et al. Web service composition with QoS bound based on simulated annealing algorithm［J］. Journal of Southeast University(English Edition),2008,24(3):308311.
［15］	Li Zhen. Research on hybrid QoSaware semantic web service composition decision making algorithm ［D］. Beijing:Beijing University of Posts and Telecommunications, 2008.(in Chinese)
［16］	Liu Zhizhong, Lei Guanjun, Xue Xiao, et al. Research on QoSaware cloud service optimal composition ［J］. Application Research of Computers, 2012, 29(10):39193921.(in Chinese)
［17］	Xu Meng, Cui Lizhen, Li Qingzhong. An extend graphplanning based on topK service composition method［J］. Acta Electronica Sinica, 2012, 40(7):14041409.(in Chinese)
［18］	Zhen Ye,Bouguettaya A,Zhou Xiaofang.QoSaware cloud service composition based on economic models［C］∥Proc of the 10th International Conference on ServiceOriented Computing (ICSOC),2012:111126.
［19］	Zhen Ye,Bouguettaya A,Zhou Xiaofang.QoSaware cloud service composition using time series［C］∥Proc of the 11th International Conference on ServiceOriented Computing (ICSOC), 2013:922.
［20］	Guo Xiaofang, Li Feng. Analysis on similarity of multivariate time series based on Eros ［J］. Computer Engineering and Applications, 2012, 48(23):111114.(in Chinese)
	附中文参考文献：
［8］	陈亮,孙敏.基于免疫遗传算法的Web 服务组合方法［J］.计算机工程,2010,36(10):226230.
［11］	周献中,吴奎,萧毅鸿.基于蚁群算法的Web服务自动组合［C］∥决策科学与评价,2009:228236.
［12］	沈记全,郑雪峰,涂序彦.一种基于蚁群算法的服务组合方法［J］.武汉理工大学学报(交通科学与工程版),2009,33(6):11791182.
［13］	殷荣网,冒志建.一种有QoS保障的服务组合方法［J］.电脑知识与技术(网络通讯与安全),2007(11):12761278.
［15］	李祯.混合QoS模型感知的语义Web服务组合决策算法研究［D］.北京：北京邮电大学,2008.
［16］	刘志中,雷冠军,薛霄,等.QoS感知的云服务优化组合研究［J］.计算机应用研究,2012, 29(10):39193921.
［17］	徐猛,崔立真,李庆忠.基于扩展图规划的topK服务组合方法研究［J］.电子学报,2012,40(7):14041409.
［20］	郭小芳,李锋.基于Eros的多元时间序列相似度分析［J］.计算机工程与应用,2012,48（23）:111114.

[1]	刘南艳, 魏鸿飞, 马圣祥. 融合局部动态特征的面部表情识别[J]. 计算机工程与科学, 2023, 45(05): 849-858.
[2]	苟平章, 马琳, 郭保永, 原晨. 基于软件定义网络的多约束QoS双路径路由优化方法[J]. 计算机工程与科学, 2023, 45(01): 46-56.
[3]	王堃, 郑晨, 张立中, 陈志刚. 一种基于SARIMA-LSTM模型的电网主机负载预测方法[J]. 计算机工程与科学, 2022, 44(11): 2064-2070.
[4]	赵春兰, 李屹, 何婷, 武刚, 王兵. 基于动态隶属度的模糊时间序列模型的水质预测研究[J]. 计算机工程与科学, 2022, 44(08): 1488-1496.
[5]	赵林锁, 陈泽, 丁琳琳, 宋宝燕. 基于RELM的时间序列数据加权集成分类方法[J]. 计算机工程与科学, 2022, 44(03): 545-553.
[6]	颜廷龙, 李瑛, 王凤芹. 基于MRF模型的飞机飞行动作识别划分算法[J]. 计算机工程与科学, 2022, 44(01): 159-164.
[7]	于琼, 田宪. 基于组合模型的非线性时间序列预测算法[J]. 计算机工程与科学, 2021, 43(10): 1817-1825.
[8]	罗磊, 陈照云, 王俪璇. 用户QoS感知的GPU集群深度学习任务动态调度[J]. 计算机工程与科学, 2021, 43(08): 1331-1340.
[9]	郭全盛, 李栋, 张蕾, 魏楚元. 基于时间点过程的时间序列预测模型[J]. 计算机工程与科学, 2021, 43(07): 1299-1307.
[10]	殷炜宏, 王若愚, 段倩倩, 李国强. 基于时态边缘算子的时间序列自主分段表示法[J]. 计算机工程与科学, 2021, 43(06): 1104-1111.
[11]	罗莉, 周宏伟, 周理, 潘国腾, 周海亮, 刘彬. 一种多核处理器直连接口QoS的设计与验证[J]. 计算机工程与科学, 2021, 43(04): 620-627.
[12]	童钊, 叶锋, 刘碧篮, 邓小妹, 梅晶, 刘宏. 移动边缘计算中多约束下的任务卸载和资源分配算法[J]. 计算机工程与科学, 2020, 42(10高性能专刊): 1869-1879.
[13]	王腾1，焦学伟2，高阳2. 一种基于Attention-GRU和iForest的周期性时间序列异常检测算法[J]. 计算机工程与科学, 2019, 41(12): 2217-2222.
[14]	孙霞，吴楠楠，张蕾，陈静，冯筠. 基于深度学习的MOOCs辍学率预测方法[J]. 计算机工程与科学, 2019, 41(05): 893-899.
[15]	董哲1,唐湘滟1,程杰仁1,2,张晨1,林福生1. 基于HMM时间序列预测和混沌模型的DDoS攻击检测方法[J]. 计算机工程与科学, 2018, 40(12): 2164-2172.