An Efficient Cloud Server Resource Scheduling using Ant Colony Optimization Algorithm

Cloud computing is a computational and storage infrastructure. A number of applications and growing technologies are getting resources from the cloud infrastructure. Resources in cloud computing are not statically distributed that are shared between all the applications therefore according to the demand of applications the cloud schedulers provides the resources to the jobs or processes. The schedulers are works to evaluate the available resources and manage the resource allocation to jobs for efficiently execution. But if the resource management is not performed in proper scenario then the job execution cost and process waiting time is increases in significant amount. In this context the proposed work is dedicated to find an efficient method for scheduling jobs according to the available resources. Therefore a hybrid technique that incorporates the properties of round robin technique and ACO (ant colony optimization) technique is developed. the proposed technique first categorize the entire work load in three main classes low, average, and high work load. Additionally then after the ACO optimization technique is employed for finding best match of resource sequence and jobs to maximize the job execution. The implementation of the proposed technique is performed using cloudSim simulator and their performance is computed in terms of waiting time, CPU utilization and execution time. The obtained performance of the proposed system shows efficient management of resources and low resource consumption.