Research based on Effective Resource Allocation of Improved SFLA in Cloud Computing

It is the focus of current cloud research as how to reasonably use resources in cloud computing. In this paper, shuffled frog leaping algorithm is introduced into the cloud computing resource allocation, and aiming at its slow speed in getting solution and being easy to fall into local optimum, improvement is made. First, reverse learning algorithm is used to initialize the algorithm; then, cross factor is introduced into the local research; finally, evolutionary strategy is adopted in selecting the optimal solution combining the global search and local search to improve the performance of improved algorithm. It has be proven through the Cloudsim platform that algorithm in this paper effectively solves the problem of resource allocation and improves the efficiency of resource allocation.