A VOP-based Value Analysis and Optimization Method for Service Selection and Composition

2014 International Conference on Service Sciences Pub Date : 2014-05-22 DOI:10.1109/ICSS.2014.36

Chao Ma, Xiaofei Xu, Zhongjie Wang

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Abstract

Service selection and composition are important issues to realize IT-enabled service systems. Service stakeholders obtain different service values in the solutions of service selection and composition with the same function but different QoS. The service value achieved from service systems is a critical factor to evaluate and to select the suitable services for the solution of service selection and composition. A value analysis and optimization method for service selection and composition based on value-oriented priority (VOP) is presented in this paper. Firstly, the quantitative analysis method of VOP-based service elements is presented, which includes value contribution analysis, sensitivity analysis and trade-off point analysis. Then the value optimization model for minimal cost is given for solving the problems between expected service values and the constraints of service systems. In order to solve this service value optimization problem, a VOP-based artificial bee colony (VOPABC) algorithm is proposed. Finally, the validity of VOPABC algorithm is proved through simulation experiments.

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基于vop的服务选择与组合价值分析与优化方法

服务选择和组合是实现支持it的服务系统的重要问题。在功能相同但QoS不同的服务选择和组合方案中，服务涉众获得的服务值不同。服务系统获得的服务价值是服务选择与组合解决方案中评价和选择合适服务的关键因素。提出了一种基于价值导向优先级(VOP)的服务选择与组合的价值分析与优化方法。首先，提出了基于vop的服务要素的定量分析方法，包括价值贡献分析、敏感性分析和权衡点分析。然后，针对服务系统的约束条件与服务期望值之间的问题，建立了最小成本的价值优化模型。为了解决这一服务价值优化问题，提出了一种基于vopp的人工蜂群(VOPABC)算法。最后，通过仿真实验验证了VOPABC算法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2014 International Conference on Service Sciences

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