Abstract
Cloud Computing has seen massive growth over the past couple of decades, leading to exponential growth in energy consumption at data centres. Data centres consuming high amounts of energy leave a carbon footprint of the same scale, hence Cloud Service Providers (CSPs) have been looking for energy-efficient solutions to task scheduling in cloud to reduce the amount of carbon dioxide emission. Saving energy not only helps reduce the carbon footprint datacentres have on the environment, but also helps cover the costs of running multiple datacentres on the CSP’s end. In this paper, we propose an energy saving task scheduling heuristic for heterogeneous cloud systems which selects the optimal physical host containing virtual machines with the additional consideration of the utilization of any incoming task on that particular virtual machine. We compare the energy efficiency of our proposed heuristic with recent algorithms including ECTC, MaxUtil, Random, and FCFS on several benchmark and synthetic datasets to display its superiority in energy-efficient task scheduling in heterogeneous cloud environments. Our proposed heuristic, namely Energy Saving Power Spectrum-Aware Scheduling (ESPS) minimizes energy consumption in a heterogeneous cloud environment by about 38.65%, 33.59%, 53.02%, and 46.96% when compared to FCFS, MaxUtil, Random and ECTC respectively.
Highlights
Cloud computing enables consumers around the globe have access to remote, shared computing resources [1, 30]
Even in case of synthetic dataset, our proposed algorithm saves around 72.41%, 67.69%, 67.38% and 60.84% more energy when compared with ECTC, First Come First Serve (FCFS), MaxUtil and Random, respectively
We propose a new heuristic namely Energy Saving Power Spectrum-Aware Task Scheduling (ESPS) that keeps track of the least power difference in the operating power characteristics of different hosts in a cloud datacenter
Summary
Cloud computing enables consumers around the globe have access to remote, shared computing resources [1, 30]. The CSPs are able to meet the rising demand for these resources. Due to the increasing supply and demand of these resources, various power and energy related concerns are raised on behalf of the CSP. With the increase in energy consumption of the datacentres, another environmental concern is raised with the massive amount of CO2 emissions [38]. Even security of user data is a prime area of research in cloud computing [31]. The CSP desires that the energy consumed by the cloud resources during this workflow is minimized
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