分布式Web服务质量测量平台的设计与实现
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摘要
随着Web服务不断的推广,网络中出现大量功能相同或者相似的Web服务。由于用户地域和网络环境的不同,相同Web服务QoS相对于不同的用户可能会差异很大,因此在众多功能相同的Web服务中检索出满足用户需求的Web服务十分重要,需要一种针对用户的,能够快速、准确地推测多个功能相同服务的服务QoS的测量方法。本文提出一种分布式Web服务QoS测量平台,将整个网络映射成一个虚拟的三维坐标系统,通过对Web服务进行周期性的测量,统计分析测量数据,从而推测在用户端能够获取的Web服务QoS。
论文从研究现有的Web服务QoS预测方法入手,对比分析Web服务QoS预测的相关技术,提出了分布式Web服务质量测量平台,该平台能够准确的估测在用户端的Web服务QoS的方法。本文重点阐述分布式Web服务QoS测量平台的需求和关键技术、平台的设计与实现以及对测量平台的评估和准确性验证。Web服务在用户端能够获取的服务QoS主要由两个方面决定：1、Web服务所处的网络环境和服务端负载状况的不稳定性,Web服务的网络坐标会随之动态变化2、用户端的地理位置和网络环境的不同,Web服务在用户端呈现的服务QoS也会不尽相同,因此实现估测在用户端调用Web服务时能够的服务QoS属性值是比较难以解决的问题。
根据上面描述的问题,本论文通过对Web服务QoS预测研究的综述提出了Web服务QoS测量平台的需求,根据用户端端Web服务QoS的特点找出了Web服务QoS测量平台需要的关键技术,并确定了研究预测Web服务的QoS属性,包括响应时间和可靠性。本论文的主要研究内容包括Web服务的周期性测量；Web服务QoS测量节点、Web服务和用户的定位；用户端Web服务QoS的预测。最后对分布式Web服务QoS测量平台的总体架构进行设计和实现,并根据实际情况对平台进行了评估。
With the continued promotion of Web services, a large number of the same or similar Web services arise in network. As the difference of user's geographyand network environment, the same Web service QoS may be very different to different users, so it is very important to retrieve the right Web services that meet users'needs from the same functional Web services, and we need a measurement method that be able to quickly and accurately speculated the QoS of the multiple services with the same function. This paper presents a distributed Web service QoS measurement platform, the entire network is mapped into a virtual three-dimensional coordinate system, via periodic measurement of the Web services, statistical analysis of measurement data, which speculated that the client can obtain Web service QoS.
Papers starting from the study of existing Web services QoS prediction methods, comparative analysis of Web services QoS prediction technology, presents a distributed Web service quality measurement platform, the platform can accurately estimate the client Web service QoS. This article focuses on the needs and key technologies of the Distributed Web service QoS measurement platform, the design and realization of the platform, the assessment of the measurement platform and the accuracy of authentication. Web service QoS that can get from the client is determined mainly by two aspects:1, Web service which instability of the network environment and server load conditions, the Web services network coordinates will follow dynamic changes,2, the difference of the location and network environment of the users, so the estimation of the service QoS the can get from the client whenthe client calls the Web service is more difficult problem to solve.
According to the problems described above, the paperproposes the demand of the ditributed Web service QoS measurement platform by the overview of Web services QoS prediction, according to the user Web service QoS characteristics to identify the key technology of the Web service QoS measurement platform, and confirm the Web service QoS attributes of the pridiction, including response time and reliability. The main contents of this paper include periodic measurements; Web service QoS measurement node, Web services and user positioning; client Web service QoS prediction. Finally, the paper has the overall architecture of distributed Web service QoS measurement platform design and implementation of the platform, and assessment according to the actual situation.
论文从研究现有的Web服务QoS预测方法入手,对比分析Web服务QoS预测的相关技术,提出了分布式Web服务质量测量平台,该平台能够准确的估测在用户端的Web服务QoS的方法。本文重点阐述分布式Web服务QoS测量平台的需求和关键技术、平台的设计与实现以及对测量平台的评估和准确性验证。Web服务在用户端能够获取的服务QoS主要由两个方面决定：1、Web服务所处的网络环境和服务端负载状况的不稳定性,Web服务的网络坐标会随之动态变化2、用户端的地理位置和网络环境的不同,Web服务在用户端呈现的服务QoS也会不尽相同,因此实现估测在用户端调用Web服务时能够的服务QoS属性值是比较难以解决的问题。
根据上面描述的问题,本论文通过对Web服务QoS预测研究的综述提出了Web服务QoS测量平台的需求,根据用户端端Web服务QoS的特点找出了Web服务QoS测量平台需要的关键技术,并确定了研究预测Web服务的QoS属性,包括响应时间和可靠性。本论文的主要研究内容包括Web服务的周期性测量；Web服务QoS测量节点、Web服务和用户的定位；用户端Web服务QoS的预测。最后对分布式Web服务QoS测量平台的总体架构进行设计和实现,并根据实际情况对平台进行了评估。
With the continued promotion of Web services, a large number of the same or similar Web services arise in network. As the difference of user's geographyand network environment, the same Web service QoS may be very different to different users, so it is very important to retrieve the right Web services that meet users'needs from the same functional Web services, and we need a measurement method that be able to quickly and accurately speculated the QoS of the multiple services with the same function. This paper presents a distributed Web service QoS measurement platform, the entire network is mapped into a virtual three-dimensional coordinate system, via periodic measurement of the Web services, statistical analysis of measurement data, which speculated that the client can obtain Web service QoS.
Papers starting from the study of existing Web services QoS prediction methods, comparative analysis of Web services QoS prediction technology, presents a distributed Web service quality measurement platform, the platform can accurately estimate the client Web service QoS. This article focuses on the needs and key technologies of the Distributed Web service QoS measurement platform, the design and realization of the platform, the assessment of the measurement platform and the accuracy of authentication. Web service QoS that can get from the client is determined mainly by two aspects:1, Web service which instability of the network environment and server load conditions, the Web services network coordinates will follow dynamic changes,2, the difference of the location and network environment of the users, so the estimation of the service QoS the can get from the client whenthe client calls the Web service is more difficult problem to solve.
According to the problems described above, the paperproposes the demand of the ditributed Web service QoS measurement platform by the overview of Web services QoS prediction, according to the user Web service QoS characteristics to identify the key technology of the Web service QoS measurement platform, and confirm the Web service QoS attributes of the pridiction, including response time and reliability. The main contents of this paper include periodic measurements; Web service QoS measurement node, Web services and user positioning; client Web service QoS prediction. Finally, the paper has the overall architecture of distributed Web service QoS measurement platform design and implementation of the platform, and assessment according to the actual situation.
引文
[1]高云全.一种基于语义的Web服务动态组合及其实现计算机技术与发展.2009年6期：21-39.
[2]百度百科.http://baike.baidu.com/view/67105.htm.
[3]李静.对等网络环境下Web服务关键技术研究.山东师范大学,2010.
[4]陶燕燕.基于QoS的语义Web服务监控的研究.北京邮电大学,2009.
[5]刘鹏.’Web Services服务质量的研究.国防科学技术大学,2008.
[6]代艳红.基于QoS的服务发现改进模型.河北大学,2009.
[7]Xiaoyuan Su, Taghi M. Khoshgoftaar, A survey of collaborative filtering techniques, Advances in Artificial Intelligence archive,2009, pages 1-19.
[8]Chen Xi, Liu Xudong, Huang Zicheng, and so on. RegionKNN:a scalable hybrid collaborative filtering algorithm for personalized Web Service recommendation. In 2010 IEEE International Conference on Web Services,2010, pages 9-17.
[9]Ren Yingxin, Gu Qing, Qi Jingxian, Chen Daoxu. Reliability Prediction of Web Service Composition Based on DTMC.2009 Third IEEE International Conference on Secure Software Integration and Reliability,2009, pages 369-375.
[10]Changyou Xing, Ming Chen. Characteristics of Internet Latency and Their Impact on Distance Prediction Accuracy.2009 Seventh Annual Communications Networks and Services Research Conference,2009, pages 171-178.
[11]W3C.http://www. w3.org/TR/wsdl.
[12]IBM.http://www.ibm.com/developerworks/cn/webservices/ws-support-soa/index. html
[13]赵磊.http://elf8848.iteye.com/blog/1048707.
[14]Zhou Liang, Long Keping. The Accuracy Enhance of Technology Research of A Hierarchical IP Network Coordinate System. University of Electronic Science And Technology of China,2011, pages 23-28.
[15]wsywl.http://blog.csdn.net/wsywl/article/details/5727327
[16]PlanetLab.http://www.planet-lab.org/
[17]Liang Chen, Yipeng Feng, Jian Wu, Zibin Zheng. An Enhanced QoS Prediction Approach for Service Selection.2011 IEEE International Conference on Services Computing,2011, pages 727-728.
[18]Zibin Zheng, Michael R. Lyu. Collaborative Reliability Prediction of Service-Oriented Systems. The International Conference on Software Engineering (ICSE),2010, pages 35-45.
[19]Joseph Lee Rodgers; W. Alan Nicewander. Thirteen Ways to Look at the Correlation Coefficient. The American Statistician,1988.
[20]肖军等.基于SOA的Web服务质量评价模型的研究.中国管理信息化,2010年13期.
[21]黄晓涛.P2P流媒体内容分发服务质量保障的编码与传输技术研究.华中科技大学,2010.
[22]王家昱.基于SOA的媒体资源管理平台体系结构的研究与实现.北京邮电大学,2008.
[23]Baidu.http://baike.baidu.com/view/157153.htm
[24]李静.对等网络环境下Web服务关键技术研究.山东师范大学,2010.
[25]王创伟.基于QoS的Web服务发现技术的研究.现代计算机,2008年11期.
[26]张小刚.Web服务的QoS研究——SOAP报文传输性能研究.江南大学,2007.
[27]张晓慧.服务网络管理及QoS监控系统的设计与实现.天津大学,2009.
[28]黎玉琴.Web服务模型的QoS研究.西北师范大学,2009.
[29]刘永贤等.一种P2P网络中基于位置感知的节点选择策略.信息通信技术,2009年5期.
[30]刘永贤JP2P VoD系统目录服务器和分块请求调度机制的研究与实现.北京邮电大学,2010.
[31]Wsywl.http://blog.csdn.net/wsywl/article/details/5727327.
[32]贺培.Web服务QoS测量子系统的设计与实现.北京邮电大学,2011.
[2]百度百科.http://baike.baidu.com/view/67105.htm.
[3]李静.对等网络环境下Web服务关键技术研究.山东师范大学,2010.
[4]陶燕燕.基于QoS的语义Web服务监控的研究.北京邮电大学,2009.
[5]刘鹏.’Web Services服务质量的研究.国防科学技术大学,2008.
[6]代艳红.基于QoS的服务发现改进模型.河北大学,2009.
[7]Xiaoyuan Su, Taghi M. Khoshgoftaar, A survey of collaborative filtering techniques, Advances in Artificial Intelligence archive,2009, pages 1-19.
[8]Chen Xi, Liu Xudong, Huang Zicheng, and so on. RegionKNN:a scalable hybrid collaborative filtering algorithm for personalized Web Service recommendation. In 2010 IEEE International Conference on Web Services,2010, pages 9-17.
[9]Ren Yingxin, Gu Qing, Qi Jingxian, Chen Daoxu. Reliability Prediction of Web Service Composition Based on DTMC.2009 Third IEEE International Conference on Secure Software Integration and Reliability,2009, pages 369-375.
[10]Changyou Xing, Ming Chen. Characteristics of Internet Latency and Their Impact on Distance Prediction Accuracy.2009 Seventh Annual Communications Networks and Services Research Conference,2009, pages 171-178.
[11]W3C.http://www. w3.org/TR/wsdl.
[12]IBM.http://www.ibm.com/developerworks/cn/webservices/ws-support-soa/index. html
[13]赵磊.http://elf8848.iteye.com/blog/1048707.
[14]Zhou Liang, Long Keping. The Accuracy Enhance of Technology Research of A Hierarchical IP Network Coordinate System. University of Electronic Science And Technology of China,2011, pages 23-28.
[15]wsywl.http://blog.csdn.net/wsywl/article/details/5727327
[16]PlanetLab.http://www.planet-lab.org/
[17]Liang Chen, Yipeng Feng, Jian Wu, Zibin Zheng. An Enhanced QoS Prediction Approach for Service Selection.2011 IEEE International Conference on Services Computing,2011, pages 727-728.
[18]Zibin Zheng, Michael R. Lyu. Collaborative Reliability Prediction of Service-Oriented Systems. The International Conference on Software Engineering (ICSE),2010, pages 35-45.
[19]Joseph Lee Rodgers; W. Alan Nicewander. Thirteen Ways to Look at the Correlation Coefficient. The American Statistician,1988.
[20]肖军等.基于SOA的Web服务质量评价模型的研究.中国管理信息化,2010年13期.
[21]黄晓涛.P2P流媒体内容分发服务质量保障的编码与传输技术研究.华中科技大学,2010.
[22]王家昱.基于SOA的媒体资源管理平台体系结构的研究与实现.北京邮电大学,2008.
[23]Baidu.http://baike.baidu.com/view/157153.htm
[24]李静.对等网络环境下Web服务关键技术研究.山东师范大学,2010.
[25]王创伟.基于QoS的Web服务发现技术的研究.现代计算机,2008年11期.
[26]张小刚.Web服务的QoS研究——SOAP报文传输性能研究.江南大学,2007.
[27]张晓慧.服务网络管理及QoS监控系统的设计与实现.天津大学,2009.
[28]黎玉琴.Web服务模型的QoS研究.西北师范大学,2009.
[29]刘永贤等.一种P2P网络中基于位置感知的节点选择策略.信息通信技术,2009年5期.
[30]刘永贤JP2P VoD系统目录服务器和分块请求调度机制的研究与实现.北京邮电大学,2010.
[31]Wsywl.http://blog.csdn.net/wsywl/article/details/5727327.
[32]贺培.Web服务QoS测量子系统的设计与实现.北京邮电大学,2011.
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