A Framework for User Priority Guidance Based Scheduling for Load Balancing in Cloud Computing

Cloud computing has emerged as a new model of computing based on Internet. A cloud with large shared pool of resources provides computing resources on demand in pay as you go. wo important aspects must be considered: i) from the user perspective latency must be decreased and tasks to be completed as expected, ii) from the service provider perspective, effective utilization of computing resources is vital. Many existing solutions that focus on optimized scheduling for improving load balancing do not consider user priority guidance. When user-guided priority is considered, the scheduling follows well informed approach and it can lead to more efficient load balancing. Therefore it is important to have scheduling algorithms that are guided by user priority for better optimization of load balancing. In this paper we propose an algorithm known as User Priority based Scheduling for Load Balancing (UPS-LB) which divides user tasks into elastic and inelastic groups and schedule them for enhanced load balancing. In fact, the algorithm makes rescheduling decisions for heavy loaded resources to improve efficiency of load balancing in cloud computing. We built a prototype application to demonstrate proof of the concept. Our empirical study revealed that the proposed UPS-LB algorithm has comparable performance improvement over its predecessors such as Min-Min, LBIMM and PALBIMM.