An Efficient Honey Bee Approach for Load Adjusting in Cloud Environment

Abstract

Cloud computing is an Internet-based approach that delivers on-demand processing resources and information to the users in a shared mode. At the serving end, there is a prerequisite of proper scheduling and load adjusting to deal with the enormous measure of data. Our algorithm aims to distribute the equal load on each server in the cloud network and additionally enhances the asset usage. With the proposed approach, the honey bee inspired load adjusting (HBI-LA) method has been used for balancing the load of the virtual machine and schedule the task with respect of their priorities. Because of over-burdening of the task on a machine, there may be a chance of CPU crash. To overcome this problem, aging is applied to gradually enhance the priority of those jobs having longer waiting time as compared to the predefined time. At last, we compared our proposed work with the existing HBB-LB in terms of CPU time, execution time and waiting time. The examination of these three parameters demonstrates that the proposed algorithm requires less CPU time, less execution time and less waiting time than existing algorithm, hence it shows better performance and less energy consumption than the existing one.