An Evolutionary-Based Algorithm for Smart-Living Applications Placement in Fog Networks

Moallemi, Raheleh and Bozorgchenani, Arash and Tarchi, Daniele (2020) An Evolutionary-Based Algorithm for Smart-Living Applications Placement in Fog Networks. In: 2019 IEEE Globecom Workshops (GC Wkshps). IEEE Publishing. ISBN 9781728109619

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Abstract

Fog computing is an emerging model, complementing the cloud computing platform, introduced to support the Internet of Things (IoT) processing requests at the edge of the network. Smart-living IoT scenarios require the execution of multiple processing tasks at the edge of the network and leveraging on the Fog Computing approach results to be a worthwhile solution. Genetic Algorithms (GA) are a heuristic search and optimization class of techniques inspired by natural evolution. We propose two GA-based approaches for optimizing the processing task placement in a fog computing edge infrastructure aiming to support the Smart-living IoT nodes requests. The numerical results obtained in Matlab show that both GA-based approaches allow to maximize the covered areas while minimizing the resource wastage through the minimization of the overlapping areas

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Contribution in Book/Report/Proceedings
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©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:
150141
Deposited By:
Deposited On:
10 Feb 2021 14:00
Refereed?:
Yes
Published?:
Published
Last Modified:
25 Oct 2021 00:41