NUTS scheduling approach for cloud data centers to optimize energy consumption

Abstract

The cloud data center is accommodated with many servers for cloud-based services which cause more consumption of energy and menace cost factors in computing tasks. Many existing scheduling techniques hinge on allocating task where scheduling algorithm is not based on assigning tasks through urgent and non-urgent task scheduling using dynamic voltage frequency scaling (DVFS) controller. In demand to reduce energy consumption and to maintain the quality of services, this paper proposes non-urgent and urgent task scheduling (NUTS) algorithm using DVFS, to restraint and scheduling of task in the more efficient way for minimizing the power consumption of the IT equipment. To increase the energy efficiency, we proposed scheduling queue and non-completed task queue for scheduling urgent, non-urgent and non-completed tasks to ally utilization of resources efficiently and to decrease the consumption of energy in the data center. In this paper, we compared proposed algorithm with two existing standard scheduling algorithms. The experimental results boast that NUTS algorithm performs better than the existing algorithms and can centrist energy efficiency in cloud data center.