Research of improved shuffled frog leaping algorithm in cloud computing resources

Abstract

Resource scheduling under the condition of cloud computing has always been the focus of current research. This paper analyzes the current situation of cloud computing and introduces shuffled frog leaping algorithm in resource allocation. Aiming at that shuffled frog algorithm is easy to fall into local optimum with fast convergence speed, artificial vector machine is introduced into the subgroups of shuffled frog leaping algorithm, then, self-adaptive crossover probability is introduced into the algorithm’s interior searching. The improved shuffled frog leaping algorithm effectively avoids the algorithm from falling into local optimum and meanwhile shortens the time of global searching and optimum. Classic function proves the performance of algorithm in this paper is improved greatly, and CloudSim platform demonstrates that algorithm in this paper can improve the system’s efficiency into processing tasks and make resource allocation in cloud computing reasonable and effective.