Enhanced Dynamic Load Balancing Mechanism in Cloud Environment with Modified Grey Wolf Optimization Algorithm

Cloud is very effective technology, which works over the Internet provides services such as servers, storage, networking, workstations, virtual environment etc. This technology supports the distributed environment with different servers to complete the tasks. On demand of these services, the way to balance the heavy load and allow scheduling the task plays vital role. To attain enormous performance in virtual environment, many algorithms to handle those are already developed. We can implement virtualization on operating systems to balance the work load and attain better overall performance. Based on the availability of resources, we can avail more than one container to fasten the execution completion. Incoming tasks should be schedule to all available servers in equal manner based on resource availability is called load balancing. Among multiple containers, the incoming requests are assigned to available one is called task scheduling. In this paper, Improved Grey Wolf Optimization (GWO) is implemented for load balancing and SJF is implemented for task scheduling, through which we can obtain maximum throughput with minimal makespan.