Load Balancing with Optimal Cost Scheduling Algorithm

Abstract

In a cloud computing environment a proper load balancing technique is required to execute a process and manage the resource. In a distributed environment it is difficult to achieve this, as different resources have different configuration and capacity. Generally, load balancers generate the mapping of tasks to resources, based on some particular objectives. Load balancers employ a function that takes into account the necessary objectives to optimize a specific outcome. The commonly used load balancing objectives in a cloud computing environment are related to the tasks completion time and resource utilization. They use a specific approach for mapping the tasks to suitable cloud resources in order to satisfy user requirements. However, the majority of these strategies are static in nature. They produce a good schedule given the current state of cloud resources and do not take into account changes in resource availability. On the other hand, dynamic scheduled load balancer considers the current state of the system. It is adaptive in nature and able to generate efficient schedules. This improves the overall performance of the system. In this paper we have proposed a new technique to achieve load balancing called Load Balancing with Optimal Cost Scheduling Algorithm. The user selects a list of services available from the service pack. The scheduler processes these tasks to the virtual machine (VM) based on the configuration and computing power of the VM. This task is achieved with minimum execution cost which is a profit for the service provider and minimum execution time which is an advantage for both service provider and the user.