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

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.

Key words: cloud computing, resource allocation, K-medoids algorithm, ant colony algorithm, dynamic load