Intelligent Scheduling Optimization in Cloud Computing Massive Storage based on SALS Algorithm

Abstract

In recent years, cloud computing technology has been developed rapidly under the push of industry and academia, a large number of cloud computing system get applied, but the existing scheduling algorithm has not fully consider the users’ different demands for resources, can not well provided users resources to meet the requirements. In order to solve this problem, this paper proposed an improved algorithm based on SALS(self-adaptive load scheduling) algorithm, based on the cluster load monitoring, forecast the subsequent request arrival rate and size, select the appropriate scheduling algorithm for job scheduling, quickly adjust the corresponding parameter, assign the task to the right free resources to perform, so as to realize allocating appropriate resources for task under dynamic changing cloud resources environment, making the load balancing between each server in the cluster. The simulation test results show that whether for the computationally intensive task and data intensive tasks, the proposed SALS algorithm has better performance in terms of shorten the average response time compared with general SALS algorithm, and can transfer larger volume at the same time, thus save a lot of time for users.