Cloud Computing Resource Scheduling Based On Ant Colony Optimization

Cloud computing architecture can provide users with rich resources such as computing, storage, network, but also can provide users with a dynamic data services and computing platform. Virtual resource allocation scheme is the key to successful cloud computing architectures,and a good resource allocation scheme for the good role in the cloud platform has important significance.Ant colony algorithm is a traditional algorithm about the distribution of resource scheduling in the cloud environment.It has the characteristics of heterogeneity,distributed, and the initial condition being not high, is very suitable in cloud computing environment resource adjustment. At the same time, the algorithm also exist the insufficient of resource node load imbalance and low resource utilization. To make up for the shortage of the traditional ant colony algorithm, this paper presents a pretreatment mechanism of degradation factor, and improve the ant colony algorithm,and carry out the simulation experiment based on the results of the study. Experimental results show that the reasonable choice of the premise of degradation factor, resource scheduling strategy based on optimization of ant colony algorithm has better load balance and a better resource utilization, and the optimized ant colony algorithm short the average time of task execution, and has stronger global searching ability.When pretreating the degradation factor, the key is to determine degradation factor value range. This paper adopts a dynamic and eclectic method, mainly based on the following two points to consider:(1) in the cloud computing environment, a new node often will be joins to the cloud environment, at the same time the node will be forced to exit the cloud environment, and this dynamic is one of the resource adjustment characteristics;(2)degradation factor selection must be moderate, So-called dynamic, is according to the adjustment of the difference environment dynamically choose value of degradation factor limits; So-called compromise, the middle value 0.5 is the first step is to determine, and then around the first input larger value, and then input the value of the smaller cycles in turn through this method can obtain the boundaries of degradation factor.Simulation experiment of this paper is divided into two steps: one is to choose the degradation factor; Second is the simulation of the optimized ant colony algorithm andthe standard ant colony algorithm. Then analyze the the results of optimized ant colony algorithm and the standard ant colony algorithm.