计算机应用与软件2017，Vol.34Issue(3)：13-20,26,9.DOI:10.3969/j.issn.1000-386x.2017.03.003
改进蚁群算法及其在云服务组合优化中的应用研究
IMPROVED ANT COLONY ALGORITHM AND ITS APPLICATION IN CLOUD SERVICE COMPOSITION OPTIMIZATION
李东星 1陈喆 1钱双洋 1焦扬1
作者信息
- 1. 解放军信息工程大学 河南 郑州 450004
- 折叠
摘要
Abstract
Aiming at the dynamic, instability, multiple QoS attribute restrictions and other issues in service composition process, we propose an optimized and service combination fitted dynamic aggregation pheromone updating ant colony algorithm (WJ-I-ACO) , including improved local optimization algorithm based on clustering analysis and improved global optimization algorithm based on dynamic differential.The effectiveness and feasibility of the algorithm are verified through MATLAB simulations.Based on this, we analyze the optimization strategy of cloud service composition and give the path optimization method for service composition.关键词
蚁群算法/云服务/优化/WJ-I-ACOKey words
Ant colony algorithm/Cloud service/Optimization/WJ-I-ACO分类
信息技术与安全科学引用本文复制引用
李东星,陈喆,钱双洋,焦扬..改进蚁群算法及其在云服务组合优化中的应用研究[J].计算机应用与软件,2017,34(3):13-20,26,9.
