Self-characteristics based Energy-Efficient Resource Scheduling for Cloud

Abstract

Energy optimization in cloud computing is more attractive and much consideration in resource management, where, energy consumption is also one of the important metrics that should be included to resource management technique apart from performance and utilization of resource metric. The majority of existing methodologies for scheduling of resources are focusing on cost and execution time. In fact, the resource failures also distract the execution of cloud resource provisioning, which results in more operative cost and time. In this paper, the self-optimized energy efficient resource management strategy has been consider, which gives the optimal solution to maximize the resource utilization and identify the faulty resources to avoid misleading of scheduling. This strategy, allocate the resources to the workloads submitted by the cloud user by the fulfillment of the QoS with less SLA violation rate and maximizes the resource utilization at low cost. The novelty of this paper is to applied Antlion Optimization algorithm to find the optimal resource. The experimental results are evidence of utmost performance of proposed work.