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Dynamically Controlling Offloading Thresholds in Fog Systems

School of Computer Science and Informatics, Cardiff University, Cardiff CF24 3AA, UK
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Academic Editors: Marco Picone and Taehong Kim
Sensors 2021, 21(7), 2512; https://doi.org/10.3390/s21072512
Received: 11 February 2021 / Revised: 25 March 2021 / Accepted: 31 March 2021 / Published: 3 April 2021
(This article belongs to the Special Issue Edge/Fog Computing Technologies for IoT Infrastructure)
Fog computing is a potential solution to overcome the shortcomings of cloud-based processing of IoT tasks. These drawbacks can include high latency, location awareness, and security—attributed to the distance between IoT devices and cloud-hosted servers. Although fog computing has evolved as a solution to address these challenges, it is known for having limited resources that need to be effectively utilized, or its advantages could be lost. Computational offloading and resource management are critical to be able to benefit from fog computing systems. We introduce a dynamic, online, offloading scheme that involves the execution of delay-sensitive tasks. This paper proposes an architecture of a fog node able to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to minimize overall delay, maximize throughput, and minimize energy consumption at the fog layer. Compared to other benchmarks, our approach could reduce latency by up to 95%, improve throughput by 71%, and reduce energy consumption by up to 67% in fog nodes. View Full-Text
Keywords: fog computing; computational offloading; dynamic offloading threshold; resource management; minimizing delay; minimizing energy consumption; maximizing throughputs fog computing; computational offloading; dynamic offloading threshold; resource management; minimizing delay; minimizing energy consumption; maximizing throughputs
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MDPI and ACS Style

Alenizi, F.; Rana, O. Dynamically Controlling Offloading Thresholds in Fog Systems. Sensors 2021, 21, 2512. https://doi.org/10.3390/s21072512

AMA Style

Alenizi F, Rana O. Dynamically Controlling Offloading Thresholds in Fog Systems. Sensors. 2021; 21(7):2512. https://doi.org/10.3390/s21072512

Chicago/Turabian Style

Alenizi, Faten; Rana, Omer. 2021. "Dynamically Controlling Offloading Thresholds in Fog Systems" Sensors 21, no. 7: 2512. https://doi.org/10.3390/s21072512

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