WebNeg: A Genetic Algorithm Based Approach for Service Negotiation

Khayyam Hashmi, Amal Alhosban, Zaki Malik, B. Medjahed
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引用次数: 13

Abstract

Automated negotiation among Web services not only provides an effective way for the services to bargain for their optimal customizations, but also allows the discovery of overlooked potential solutions. A number of negotiation supporting techniques have been used to find solutions that are acceptable to all parties in the negotiation. However, employing these solutions for automated negotiations among Web services has its own challenges. In this paper, we present the design of a Negotiation Web service that would be used by both the consumers and providers of Web services for conducting negotiations. This negotiation service uses a genetic algorithm(GA) based approach for finding acceptable solutions in multi-party and multi-objective negotiations. In addition to the traditional genetic operators of crossover and mutation, the search is enhanced using anew operator called the Norm. Norm operator represents the cumulative knowledge of all the parties involved in the negotiation process. GA performance with the new Norm operator is compared to the traditional GA, hill-climber and random search techniques. Experimental results indicate the practicality of our approach in facilitating the negotiations involved in a Web service composition process. Specifically, the proposed GA with Norm operator performs better than other approaches.
基于遗传算法的服务协商方法
Web服务之间的自动协商不仅为服务提供了一种有效的方式来协商它们的最佳定制,而且还允许发现被忽视的潜在解决方案。一些谈判支持技巧被用来寻找谈判各方都能接受的解决办法。然而,将这些解决方案用于Web服务之间的自动协商有其自身的挑战。在本文中,我们提出了协商Web服务的设计,Web服务的消费者和提供者都可以使用它来进行协商。此协商服务使用基于遗传算法(GA)的方法在多方和多目标协商中寻找可接受的解决方案。除了传统的交叉和突变的遗传算子,搜索增强了新的算子称为规范。规范算子代表谈判过程中各方知识的累积。将新范数算子与传统遗传算法、爬坡算法和随机搜索算法的性能进行了比较。实验结果表明,我们的方法在促进Web服务组合过程中涉及的协商方面具有实用性。具体而言,采用Norm算子的遗传算法的性能优于其他方法。
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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