An Efficient Energy-Aware Tasks Scheduling with Deadline-Constrained in Cloud Computing †
1
LAVETE laboratory, Mathematics and Computer Science Department, Science and Technical Faculty Hassan 1 University, Settat 26000, Morocco
2
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; https://doi.org/10.3390/computers8020046
Received: 26 March 2019
/
Revised: 12 May 2019
/
Accepted: 3 June 2019
/
Published: 10 June 2019
(This article belongs to the Special Issue Advances and Innovations in Cloud Computing Technologies and Applications (CloudTech 2018))
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
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
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. https://doi.org/10.3390/computers8020046
AMA 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(2):46. https://doi.org/10.3390/computers8020046
Chicago/Turabian StyleBEN ALLA, Said, Hicham BEN ALLA, Abdellah TOUHAFI, and Abdellah EZZATI. 2019. "An Efficient Energy-Aware Tasks Scheduling with Deadline-Constrained in Cloud Computing" Computers 8, no. 2: 46. https://doi.org/10.3390/computers8020046
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
