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Dynamically controlling offloading thresholds in fog systems

Alenizi, Faten and Rana, Omer 2021. Dynamically controlling offloading thresholds in fog systems. Sensors 21 (7) , 2512. 10.3390/s21072512

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Abstract

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

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Additional Information: This is an open access article distributed under the Creative Commons Attribution License
Publisher: MDPI
ISSN: 1424-8220
Date of First Compliant Deposit: 12 April 2021
Date of Acceptance: 31 March 2021
Last Modified: 12 Apr 2021 10:30
URI: http://orca.cf.ac.uk/id/eprint/140423

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