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

LI Lin; YING Shi; ZHAO Chong; DONG Bo

doi:10.3969/j.issn.0372-2112.2016.01.018

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

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- Deployment Optimization of Service-Oriented Software Based on Ant Colony Algorithm
- Acta Electronica Sinica Vol. 44, Issue 1, Pages: 123-129(2016)
- 作者机构：
  
  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
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2016.01.018
  CLC： TP311
- Published Online：25 January 2016，
  
  Published：2016
- 稿件说明：
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LI Lin, YING Shi, ZHAO Chong, et al. Deployment Optimization of Service-Oriented Software Based on Ant Colony Algorithm[J]. Acta Electronica Sinica, 2016, 44(1): 123-129.
DOI：

LI Lin, YING Shi, ZHAO Chong, et al. Deployment Optimization of Service-Oriented Software Based on Ant Colony Algorithm[J]. Acta Electronica Sinica, 2016, 44(1): 123-129. DOI： 10.3969/j.issn.0372-2112.2016.01.018.

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.

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.

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