东北大学学报:自然科学版 ›› 2015, Vol. 36 ›› Issue (1): 1-5.DOI: 10.12068/j.issn.1005-3026.2015.01.001

• 信息与控制 •    下一篇

一种求解有状态服务选取问题的遗传算法

赵秀涛, 张斌, 孙若男, 葛亮   

  1. (东北大学 信息科学与工程学院, 辽宁 沈阳110819)
  • 收稿日期:2013-11-24 修回日期:2013-11-24 出版日期:2015-01-15 发布日期:2014-11-07
  • 通讯作者: 赵秀涛
  • 作者简介:赵秀涛(1985-),男,山东临沂人,东北大学博士研究生; 张斌(1964-),男,辽宁沈阳人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(61100090); 中央高校基本科研业务费专项资金资助项目(N110204006,N120804001,N110604002,N120604003).

A Genetic Algorithm for Stateful Service Selection

ZHAO Xiu-tao, ZHANG Bin, SUN Ruo-nan, GE Liang   

  1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
  • Received:2013-11-24 Revised:2013-11-24 Online:2015-01-15 Published:2014-11-07
  • Contact: ZHANG Bin
  • About author:-
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摘要: 基于QoS的Web服务选取问题,通常认为应用工作流中的任务是相互独立的,而在很多实际应用中,工作流的某些任务之间往往需要共享状态信息,由此增加了任务绑定约束,使得求解复杂度提高,影响了选取效率.针对现有方法的不足,提出了一种面向有状态服务选取的遗传算法,其中重新定义了交叉操作和变异操作,使得所有个体均满足任务状态关联绑定约束,同时在个体评价策略中引入罚函数,并进行个体相似性判断以防止过早收敛.实验表明,提出的算法在有状态服务选取问题中,可求得质量良好的解,且收敛速度快,选取效率亦优于现有算法.

关键词: 服务选取, 服务质量, 有状态服务, 状态关联绑定约束, 遗传算法

Abstract: Tasks in the workflow of an application are generally considered to be independent of each other in current web service selection based on QoS. In practice, however, state information is often shared among some tasks in the workflow, which adds binding constraints between tasks and web services, resulting in higher time complexity and lower selection efficiency. Aiming at drawbacks of the existing methods, a genetic algorithm for stateful service selection was proposed. In the proposed algorithm, genetic operations including crossover and mutation were redefined in order to make all individuals meet state-correlate binding constraints among tasks. In addition, to prevent premature convergence, penalty function was introduced into individual evaluation strategy; moreover, similarity judgment between individuals was also included in the algorithm.The experiments results showed that with regards to stateful service selection, good solution and fast convergence rate can be obtained using the proposed algorithm; furthermore, the proposed algorithm is more efficient than the existing algorithms.

Key words: service selection, QoS(quality of service), stateful service, state-correlate binding constraints, genetic algorithm

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