[1]杨丽琴,康国胜.基于梯度的改进动态Web服务选择算法[J].计算机技术与发展,2019,29(05):32-37.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 007]
 YANG Li-qin,KANG Guo-sheng.An Improved Dynamic Web Services Selection Algorithm Based on Gradient[J].,2019,29(05):32-37.[doi:10. 3969 / j. issn. 1673-629X. 2019. 05. 007]
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基于梯度的改进动态Web服务选择算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年05期
页码:
32-37
栏目:
智能、算法、系统工程
出版日期:
2019-05-10

文章信息/Info

Title:
An Improved Dynamic Web Services Selection Algorithm Based on Gradient
文章编号:
1673-629X(2019)05-0032-06
作者:
杨丽琴12康国胜2
1. 上海中医药大学 计算机综合教研室,上海 201203;2. 复旦大学 计算机科学技术学院,上海 201203
Author(s):
YANG Li-qin12KANG Guo-sheng2
1. Computer Teaching and Research Office,Shanghai University of Traditional Chinese Medicine, Shanghai 201203,China;2. School of Computer Science,Fudan University,Shanghai 201203,China
关键词:
服务组合服务选择QoS全局优化梯度粒子群算法
Keywords:
service compositionservice selectionQoS global optimizationgradientPSO
分类号:
TP311
DOI:
10. 3969 / j. issn. 1673-629X. 2019. 05. 007
摘要:
随着 Web2. 0 的迅速发展,互联网上发布的 Web 服务越来越多,不同服务供应商提供的服务通过整合以提供功能更强大的组合服务。 每个服务节点上功能相似的 Web 服务的 QoS(quality of service)不同,因此,QoS 全局最优动态 Web 服务选择成为了服务组合中的一大挑战。 在传统的粒子群优化算法的基础上引入梯度的思想,文中设计了一种用于解决动态 Web 服务选择问题的改进算法 gPSO-GODSS。 将问题抽象为带 QoS 约束的多目标组合优化问题,并进一步将其向单目标转化。 利用梯度的方法改进粒子群算法的更新速度,从而改进算法的收敛速度,最终产生一组满足约束条件的优化服务组合流程集。 理论分析和实验结果证明了该算法的可行性和有效性,且 gPSO-GODSS 算法收敛的执行效率和收敛速度均优于已有的 PSO-GODSS 算法。
Abstract:
As the rapid development of Web2. 0,there are more and more Web services on the Internet. Web services from different service providers can be integrated to form a composited service. As the Web services on each node with similar functions have different QoS (quality of service), dynamic Web service selection with global QoS optimization becomes a critical issue in Web service composition. In order to solve the problem,based on the basic particle swarm optimization ( PSO) and the thought of gradient,we propose a gPSO-GODSS (global optimal of dynamic Web services selection based on PSO with gradient). We abstract the original Web service selection problem into a multi - objective services composition optimization with global QoS constraints, which is further transformed into a single-object. The gradient method is used to improve the update speed of basic PSO,thus improving the convergence speed of the PSO-GODSS algorithm. Then,the improved PSO is exploited to produce a set of optimal services composition process with QoS constraints. Theoretical analysis and experimental results indicate the feasibility and efficiency of this algorithm,and the execution efficiency and convergence rate of gPSO-GODSS algorithm are both better than the existing PSO-GODSS algorithm.

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更新日期/Last Update: 2019-05-10