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Fuzzy Control Based Resource Scheduling in IoT Edge Computing

Samah Alhazmi, Kailash Kumar*, Soha Alhelaly
College of Computing and Informatics, Saudi Electronic University, Riyadh, Kingdom of Saudi Arabia
* Corresponding Author: Kailash Kumar. Email:

Computers, Materials & Continua 2022, 71(3), 4855-4870. https://doi.org/10.32604/cmc.2022.024012

Received 30 September 2021; Accepted 12 November 2021; Issue published 14 January 2022

Abstract

Edge Computing is a new technology in Internet of Things (IoT) paradigm that allows sensitive data to be sent to disperse devices quickly and without delay. Edge is identical to Fog, except its positioning in the end devices is much nearer to end-users, making it process and respond to clients in less time. Further, it aids sensor networks, real-time streaming apps, and the IoT, all of which require high-speed and dependable internet access. For such an IoT system, Resource Scheduling Process (RSP) seems to be one of the most important tasks. This paper presents a RSP for Edge Computing (EC). The resource characteristics are first standardized and normalized. Next, for task scheduling, a Fuzzy Control based Edge Resource Scheduling (FCERS) is suggested. The results demonstrate that this technique enhances resource scheduling efficiency in EC and Quality of Service (QoS). The experimental study revealed that the suggested FCERS method in this work converges quicker than the other methods. Our method reduces the total computing cost, execution time, and energy consumption on average compared to the baseline. The ES allocates higher processing resources to each user in case of limited availability of MDs; this results in improved task execution time and a reduced total task computation cost. Additionally, the proposed FCERS m 1m may more efficiently fetch user requests to suitable resource categories, increasing user requirements.

Keywords

IoT; edge computing; resource scheduling; task scheduling; fuzzy control

Cite This Article

S. Alhazmi, K. Kumar and S. Alhelaly, "Fuzzy control based resource scheduling in iot edge computing," Computers, Materials & Continua, vol. 71, no.3, pp. 4855–4870, 2022.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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