云计算中一种改进的猴群算法在资源分配中研究

Research of an Improved Monkey Algorithm of Cloud Computing in Resource Allocation

摘要:

针对云计算中的任务完成时间和费用如何进行更好的分配问题,文章将猴群算法引入到云计算资源分配中,针对猴群算法自身存在收敛速度快,易陷入局部最优的情况；在猴群算法的初始化中引入混沌算法来优化位置,对算法中的爬过程采用定位步长和对望过程的视野距离引入参数进行改进；改进后的算法在性能和收敛速度有了明显了改进,通过CloudSim仿真平台表明文章算法与其他智能算法相比在资源分配时间,能量消耗以及资源节点吞吐量,传输率方面方面具有一定的改进,提高了云计算资源分配效率。

Abstract:

Aiming at how to better allocate costs and time to complete a task in cloud computing, in this paper, monkey algorithm is introduced into the resource allocation of cloud computing. Aiming at that the monkey algorithm is easy to fall into local optimum with fast convergence speed, chaos algorithm is introduced in the initialization of monkey algorithm to optimize the location. During the climbing process of the algorithm, parameters are introduced into the positioning step and vision distance of the watching process to make the improvement. The improved algorithm has been improved significantly in performance and convergence speed, and the CloudSim simulation platform shows that compared with other intelligent algorithms, the algorithm in this paper has been improved to a certain extent in resource allocation including time, energy consumption as well as resource node throughput and transmission rate, thus it improves the efficiency of cloud computing’s resource allocation.