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