电子学报 ›› 2016, Vol. 44 ›› Issue (1): 123-129.DOI: 10.3969/j.issn.0372-2112.2016.01.018

• 学术论文 • 上一篇    下一篇

基于蚁群算法的面向服务软件的部署优化方法

李琳, 应时, 赵翀, 董波   

  1. 1. 武汉大学软件工程国家重点实验室, 湖北武汉 430072;
    2. 武汉大学计算机学院, 湖北武汉 430072
  • 收稿日期:2014-09-25 修回日期:2015-03-12 出版日期:2016-01-25 发布日期:2016-01-25
  • 通讯作者: 应时
  • 作者简介:李 琳 女,1988年出生于湖北随州,武汉大学博士生,主要研究方向为面向服务的软件开发、云计算、智能算法. E-mail:linl2012@whu.edu.cn.
  • 基金资助:

    国家自然科学基金(No.61373038,No.61070012);国家863高技术研究发展计划(No.2012AA011204-01)

Deployment Optimization of Service-Oriented Software Based on Ant Colony Algorithm

LI Lin, YING Shi, ZHAO Chong, DONG Bo   

  1. 1. State Key Lab of Software Engineering, Wuhan University, Wuhan, Hubei 430072, China;
    2. Computer School, Wuhan University, Wuhan, Hubei 430072, China
  • Received:2014-09-25 Revised:2015-03-12 Online:2016-01-25 Published:2016-01-25

摘要:

面向服务软件的部署优化问题是典型的NP难题.本文构建了基于性能改善的软件部署优化模型,设计了一种蚁群优化算法ACO-DO进行近似最优解的快速求解.该算法通过设计基于部署优化问题的启发式、改进部署方案的构建顺序、增加局部搜索过程实现蚁群算法求解效率的提升.通过不同规模的实例实验,验证了ACO-DO算法能够取得比现有的混合整数线性规划算法、蚁群算法和遗传算法更好的性能.

关键词: 面向服务的软件, 部署优化, 蚁群算法, 性能

Abstract:

The deployment optimization of service-oriented software is well known to be NP hard.In this paper, a software deployment optimization model is built for improving the performance of service-oriented software, and an Ant Colony Algorithm for Deployment Optimization (ACO-DO) is designed to solve it so that the near-optimal solutions can be obtained quickly.The algorithm improves ant colony algorithm by designing a heuristic based on the considered problem, optimizing the orders of constructing deployment solutions and adding a local search procedure.A series of instances with different sizes are tested and analyzed.The experimental results show that the designed ACO-DO algorithm performs better than the existing Mixed Integer Linear Programming, ant colony and genetic algorithms.

Key words: service-oriented software, deployment optimization, ant colony algorithm, performance

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