EPTS: Energy-saving pre-emptive task scheduling for homogeneous cloud systems

Abstract

The importance of cloud computing grows staggeringly by the day as newer technology is introduced resulting in greater connectivity across systems worldwide inculcating higher demand for resources supplied by cloud providers. Every datacentre responsible for providing these resources consumes a hefty amount of power and cloud service providers have to bear the monetary costs that come with it. Recent studies show that energy consumption of resources at utilizations over 70% grows non-linearly and hence it is best to avoid resources reaching high levels of utilization. In this paper, we introduce EPTS (Energy-saving Pre-emptive Task Scheduling) that utilizes the 0-70% interval of utilization of resources and evenly distributes the energy consumption of tasks by pre-empting tasks consuming high amounts of power by less power-demanding tasks. These pre-empted tasks are rescheduled into the virtual machines where they may result in lower utilization rates, hence increasing energy conservation. We compare EPTS with MaxUtil and FCFS (First Come First Serve) via thorough experimentation on different synthetic datasets and show that EPTS outperforms MaxUtil and FCFS by approximately 50% in terms of energy consumption.