计算机工程与应用2013，Vol.49Issue(5)：103-107,219,6.DOI:10.3778/j.issn.1002-8331.1108-0378
基于云计算的ACO-K中心点资源优化算法
ACO-K medoids resource optimization algorithm based on cloud computing
摘要
Abstract
Cloud computing has received increasingly attention from network computing model research, which can realize several kinds of resource sharing and dynamic resource allocation. However, how to effectively route storage resource in cloud, reduce dynamic load and take into account global load balancing are important problems to be solved. ACO is a bionics optimization algorithm with advantages of strong robustness, intelligent search, global optimization, easy to combine with other algorithms, K-medoids is an improved algorithm of k-means, of strong robustness and less susceptible to the impact of extreme data. Combined with priorities of these two algorithms, this paper proposes a kind of ACO-K-medoids resource allocation and optimization algorithm based on cloud computing. The algorithm can get the optimal computing resources and improve efficiency of cloud computing. Simulation experiments in the end of paper verify the efficiency of this algorithm.关键词
云计算/资源分配/K中心点算法/蚁群算法(ACO)/动态负荷Key words
cloud computing/resource allocation/K-medoids algorithm/ant colony algorithm/dynamic load分类
信息技术与安全科学引用本文复制引用
孟颖,罗可,刘建华,姚丽娟..基于云计算的ACO-K中心点资源优化算法[J].计算机工程与应用,2013,49(5):103-107,219,6.基金项目
国家自然科学基金(No.11171095,No.10871031) （No.11171095,No.10871031）
湖南省自然科学衡阳联合基金(No.10JJ8008) （No.10JJ8008）
湖南省科技计划项目(No.2011FJ3051) （No.2011FJ3051）
湖南省教育厅重点项目(No.10A015). （No.10A015）
