Energy-Aware Cloud Task Scheduling algorithm in heterogeneous multi-cloud environment

Article type: Research Article

Authors: Pradhan, Roshni^* | Satapathy, Suresh Chandra

Affiliations: KIIT Deemed to be University, Bhubaneswar, India

Correspondence: [*] Corresponding author: Roshni Pradhan, KIIT Deemed to be University, Bhubaneswar, India. Tel.: +91 9439659354; E-mail: [email protected].

Abstract: Cloud computing is growing massively in the world of information technology. As a result of which the number of servers and virtual machines is increasing day by day. It leads to huge energy consumption and carbon emission. In this regard, task scheduling has drawn the attention of cloud service providers to reduce energy consumption and increase cloud utilization. This is a crucial issue in a heterogeneous cloud environment. In this paper, energy consumption issues of cloud datacenters are addressed and an Energy-Aware Cloud Task Scheduling (EACTS) algorithm is proposed. It is taking the concept from traditional min-min, max-min, and sufferage heuristics and merge with the energy model. These heuristics are implemented on the heterogeneous cloud environment. EACTS energy model focuses on the estimation of energy consumption in cloud datacenters. The proposed algorithms estimated the makespan, cloud utilization, and energy consumption for a benchmark dataset. The experimental results obtained from EACTS algorithm provides a valid arbitration between energy efficiency and makespan. It has shown the comparison between above mentioned algorithms for various scheduling parameters.

Keywords: Cloud computing, virtual machines, energy consumption, cloud utilization, datacenter, task scheduling, makespan

DOI: 10.3233/IDT-210048

Journal: Intelligent Decision Technologies, vol. 16, no. 2, pp. 279-284, 2022