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Optimization of makespan and resource utilization in the fog computing environment through task scheduling algorithm

R. Vijayalakshmi

Government Arts and Science College, Sivakasi, Virudhunagar, Tamil Nadu, India

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V. Vasudevan

Alasalingam University, Krishnankoil, Virudhunagar, Tamil Nadu, India

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Seifedine Kadry

http://orcid.org/0000-0002-1939-4842

Department of Mathematics and Computer Science, Faculty of Sciecne, Beirut Arab University, Lebanon

E-mail Address: s.kadry@bau.edu.lb

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, and

R. Lakshmana Kumar

Department of Computer Applications, Hindusthan College of Engineering and Technology, Coimbatore, Tamil Nadu, India

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https://doi.org/10.1142/S021969131941025XCited by:13 (Source: Crossref)

This article is part of the issue:

Special Issue: Machine Learning Algorithms for Signal Processing
Editors: G. Manogaran, N. Chilamkurti and C.-H. Hsu

Abstract

The Fog computing is rising as a dominant and modern computing model to deliver Internet of Things (IoT) computations, which is an addition to the cloud computing standard to get it probable to perform the IoT requests in the network of edge. In those above independent and dispersed environment, resource allocation is vital. Therefore, scheduling will be a test to enhance potency and allot resources properly to the tasks. This paper offers a distinct task scheduling algorithm in the fog computing environment that tries to depreciate the makespan and maximize resource utilization. This algorithm catalogues the task based on the mean Suffrage value. The suggested algorithm gives much resource utilization and diminishes makespan. Our offered algorithm is compared with different alive scheduling for performance investigation, and test results confirm that our algorithm has a more significant resource utilization rate and low makespan than other familiar algorithms.

Keywords:

AMSC: 68U01, 68M20

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