动态QoS数据驱动的可靠Web服务选择

张龙昌; 杨艳红

doi:10.11999/JEIT150831

动态QoS数据驱动的可靠Web服务选择

doi: 10.11999/JEIT150831

张龙昌¹,
杨艳红²

1.
(渤海大学信息科学与技术学院锦州 121013) ②(渤海大学图书馆锦州 121013)

基金项目:

国家自然科学基金(41371425)，教育部人文社会科学研究青年基金(15YJC870028)，辽宁省自然科学基金(2015020009)，辽宁省教育厅科学技术研究(L2014451)，辽宁省社会科学规划基金(L15BTQ002)

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出版历程
- 收稿日期: 2015-07-09
- 修回日期: 2016-01-11
- 刊出日期: 2016-06-19

Dynamic QoS Data-driven Reliable Web Service Selection

ZHANG Longchang¹,
YANG Yanhong²

1.
(College of Information Science and Technology, Bohai University, Jinzhou 121013, China)
2.
(Library, Bohai University, Jinzhou 121013, China)

Funds:

The National Natural Science Foundation of China (41371425), Humanity and Social Science Youth Foundation of Ministry of Education of China (15YJC870028), Natural Science Foundation of Liaoning Province (2015020009), General Project of Science and Technology Research of Education Department of Liaoning Province of China (L2014451), Social Science Planning Fund of Liaoning Province of China (L15BTQ002)

摘要

摘要: 基于服务质量(QoS)的Web服务最优选择是一个热点问题。高度动态的QoS数据导致QoS模型的不确定性，对可靠的Web服务选择构成巨大的挑战，该文提出动态QoS数据驱动的可靠Web服务选择(DQoS_RSS)。首先利用均值标准差刻画QoS数据的效益和风险，提高QoS描述的准确度；接着建立不确定服务Skyline集，缩小搜索空间，提高选择效率；借鉴优劣解距离法(TOPSIS)，设计2种Web服务选择算法，获得体现用户需求的最优服务。另外，介绍2种QoS模型转换器，以及能够适应QoS动态变化的QoS模型自适应调整机制。最后，实验分析验证了该方法的优越性和高效性。
- Web服务 /
- 服务选择 /
- QoS数据 /
- Skyline /
- 均值标准差
Abstract: The optimal Web service selection based on QoS is still a hot issue. Highly dynamic QoS data leading to uncertainty QoS model is a huge challenge for reliable Web service selection. This paper presents Dynamic QoS Data-driven Reliable Web Service Selection (DQoS_RSS). First, DQoS_RSS uses mean and standard deviation to portray the benefit and risk of QoS and to improve the accuracy of QoS description. Then, the uncertain service Skyline set is built to reduce the search scope, to improve the efficiency of Web service selection. Drown on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) theory, 2 kinds of service selection algorithm are designed to obtain the optimal Web service reflecting users QoS needs. In addition, 2 kinds of QoS model converter are introduced to convert QoS data to QoS model; and the QoS model adaptive adjustment mechanism is introduced too, which can adapt to the dynamic changes of QoS. Finally, some experiments demonstrate the superiority and efficiency of the presented approach.
- Web service /
- Service selection /
- QoS data /
- Skyline /
- Mean and standard deviat

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