Next Article in Journal / Special Issue
Modelling and Simulation of a Cloud Platform for Sharing Distributed Digital Fabrication Resources
Previous Article in Journal
Distributed Management Systems for Infocommunication Networks: A Model Based on TM Forum Frameworx
Previous Article in Special Issue
Autonomous Wireless Sensor Networks in an IPM Spatial Decision Support System
Open AccessFeature PaperArticle

An Efficient Energy-Aware Tasks Scheduling with Deadline-Constrained in Cloud Computing

LAVETE laboratory, Mathematics and Computer Science Department, Science and Technical Faculty Hassan 1 University, Settat 26000, Morocco
Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
Author to whom correspondence should be addressed.
This paper is an extended version of the conference paper: BEN ALLA, H.; BEN ALLA, S.; TOUHAFI, A.; EZZATI, A.: Deadline and Energy Aware Task Scheduling in Cloud Computing. Presented at the 4th International Conference on Cloud Computing Technologies and Applications (CloudTech 2018), Brussels, Belgium, 26–28 November 2018.
Computers 2019, 8(2), 46;
Received: 26 March 2019 / Revised: 12 May 2019 / Accepted: 3 June 2019 / Published: 10 June 2019
Nowadays, Cloud Computing (CC) has emerged as a new paradigm for hosting and delivering services over the Internet. However, the wider deployment of Cloud and the rapid increase in the capacity, as well as the size of data centers, induces a tremendous rise in electricity consumption, escalating data center ownership costs and increasing carbon footprints. This expanding scale of data centers has made energy consumption an imperative issue. Besides, users’ requirements regarding execution time, deadline, QoS have become more sophisticated and demanding. These requirements often conflict with the objectives of cloud providers, especially in a high-stress environment in which the tasks have very critical deadlines. To address these issues, this paper proposes an efficient Energy-Aware Tasks Scheduling with Deadline-constrained in Cloud Computing (EATSD). The main goal of the proposed solution is to reduce the energy consumption of the cloud resources, consider different users’ priorities and optimize the makespan under the deadlines constraints. Further, the proposed algorithm has been simulated using the CloudSim simulator. The experimental results validate that the proposed approach can effectively achieve good performance by minimizing the makespan, reducing energy consumption and improving resource utilization while meeting deadline constraints. View Full-Text
Keywords: Cloud Computing; priority; energy consumption; deadline; task scheduling; dynamic queues Cloud Computing; priority; energy consumption; deadline; task scheduling; dynamic queues
Show Figures

Figure 1

MDPI and ACS Style

BEN ALLA, S.; BEN ALLA, H.; TOUHAFI, A.; EZZATI, A. An Efficient Energy-Aware Tasks Scheduling with Deadline-Constrained in Cloud Computing. Computers 2019, 8, 46.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop