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    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Systems and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Systems and Software, 154, 2019 DOI: 10.1016/j.jss.2019.04.058

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    Embargo ends: 24/04/20

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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ROUTER: Fog Enabled Cloud based Intelligent Resource Management Approach for Smart Home IoT Devices

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>1/08/2019
<mark>Journal</mark>Journal of Systems and Software
Volume154
Number of pages14
Pages (from-to)125-138
Publication statusPublished
Early online date24/04/19
Original languageEnglish

Abstract

There is a growing requirement for Internet of Things (IoT) infrastructure to ensure low response time to provision latency-sensitive real-time applications such as health monitoring, disaster management, and smart homes. Fog computing offers a means to provide such requirements, via a virtualized intermediate layer to provide data, computation, storage, and networking services between Cloud datacenters and end users. A key element within such Fog computing environments is resource management. While there are existing resource manager in Fog computing, they only focus on a subset of parameters important to Fog resource management encompassing system response time, network bandwidth, energy consumption and latency. To date no existing Fog resource manager considers these parameters simultaneously for decision making, which in the context of smart homes will become increasingly key. In this paper, we propose a novel resource management technique (ROUTER) for fog-enabled Cloud computing environments, which leverages Particle Swarm Optimization to optimize simultaneously. The approach is validated within an IoT-based smart home automation scenario, and evaluated within iFogSim toolkit driven by empirical models within a small-scale smart home experiment. Results demonstrate our approach results a reduction of 12% network bandwidth, 10% response time, 14% latency and 12.35% in energy consumption.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Journal of Systems and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Systems and Software, 154, 2019 DOI: 10.1016/j.jss.2019.04.058