基于蚁群的云计算资源调度研究

针对云计算环境中资源调度的问题,提出了一种基于改进蚁群的云计算资源调度算法。在算法中添加了查找表,存储其他蚂蚁推荐的节点。当任务分类比较明确的时候,查找表的优点更加地突出。在信息素的计算中加入了成功率因子,成功率越高的节点被选中的概率就越大。本文使用Cloud Sim对算法进行了仿真,仿真结果表明提出的算法缩短了搜寻资源节点的时间,从而使任务可以更快地获得资源并执行,保证了任务能够按时完成。

Resource Scheduling Research on Cloud Computing Based on Ant Colony

Aiming at the problem of resource scheduling in cloud computing environment, a resource scheduling strategy based on an improved ant colony algorithm is proposed. The look-up tables that are used to store the nodes recommended by other ants are added in this algorithm. Especially when the task classification is relatively clear, the advantage of the look-up tables is more prominent. The factor of success rate is added in the calculation of pheromone, and the higher the success rate, the greater the probability for the node to be chosen will be. A series of simulations for the algorithm are performed by using the CloudSim. The simulation results show that the proposed algorithm can reduce the time for searching the nodes, and makes the tasks obtain resource faster and to be completed on time.