Cloud Server Optimization with Load Balancing and Green Computing Techniques Using Dynamic Compare and Balance Algorithm

Abstract

Cloud computing is a business oriented concept to provide online IT resources and IT services on demand using pay per use model where main goal of cloud service provider is to use cloud computing resources efficiently and gain profits marginally. One of the challenging areas in cloud computing is frequent optimization of cloud server. It mainly concerns with the load balancing of cloud data centers to improve efficiency of the host machine and minimize number of active host machine to support green computing concept. To balance the load of entire data center, we need to transfer the virtual machines of the overloaded host to the light weighted host using migration techniques. In this paper, we introduce a threshold based Dynamic compare and balance algorithm (DCABA) for cloud server optimization. Unlike the traditional server optimization strategies which consider only load balancing and scheduling of resources based on the usage of CPU, RAM and BW in physical servers, DCABA also minimizes the number of host machines to be powered on, for reducing the cost of cloud services. Our approach can serve the purpose of service cost reduction in cloud industry with effective utilization of available resources.