A cache-based approach toward improved scheduling in fog computing

Khan, O.A. and Malik, S.U.R. and Baig, F.M. and Islam, S.U. and Pervaiz, H. and Malik, H. and Ahmed, S.H. (2020) A cache-based approach toward improved scheduling in fog computing. Software: Practice and Experience. ISSN 0038-0644

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Abstract

Fog computing is a promising technique to reduce the latency and power consumption issues of the Internet of Things (IoT) ecosystem by enabling storage and computational resource close to the end-user devices with additional benefits such as improved execution time and processing. However, with an increase in IoT devices, the resource allocation and job scheduling became a complicated and cumbersome task due to limited and heterogeneous resources along with the locality restriction in such computing environment. Therefore, this paper proposes a cache-based approach for efficient resource allocation in fog computing environment, while maintaining the quality of service. The proposed algorithm is realized using iFogSim simulator and a comprehensive comparison is presented with the traditional First Come First Served and Shortest Job First policies. The performance evaluation revealed that with the proposed scheme the execution time, latency, processing delays and power consumption decreased by 38%, 11.1%, 6%, and 17.8%, respectively, as compared to those of the traditional schemes.

Item Type:
Journal Article
Journal or Publication Title:
Software: Practice and Experience
Additional Information:
This is the peer reviewed version of the following article: Khan, OA, Malik, SUR, Baig, FM, et al. A cache‐based approach toward improved scheduling in fog computing. Softw: Pract Exper. 2020; 1– 13. https://doi.org/10.1002/spe.2824 which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2824 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1712
Subjects:
ID Code:
143538
Deposited By:
Deposited On:
06 May 2020 14:45
Refereed?:
Yes
Published?:
Published
Last Modified:
06 Jul 2020 01:11