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A Discrete Particle Swarm Optimization approach for Energy-efficient IoT services placement over Fog infrastructures

Abstract : The Internet of Things (IoT) encompasses both large-scale deployed physical infrastructures and software layers that enable intuitive and transparent creation of applications. This highly distributed, energy-greedy environment must ensure the quality of deployed services while taking into account the heterogeneity of capabilities and protocols as well as users and objects mobility. Deployment infrastructure has been redesigned to provide the necessary features, including paradigms such as software-defined networks and Fog computing. The purpose of this article is to study IoT services placement in a Fog architecture. We propose a model of the infrastructure and IoT applications as well as a placement strategy taking into account system's energy consumption and applications delay violations minimization with a Discrete Particles Swarm Optimization algorithm (DPSO). Simulations have been done with iFogSim simulator. Results have been compared with heuristics coming from the literature: Binary Partical Swarm optimization (BPSO), Dicothomous Module Mapping (DCT), CloudOnly, IoTFogOnly, IoTCloud (IC) and FogCloud (FC) placement approaches.
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Submitted on : Tuesday, June 30, 2020 - 11:37:09 AM
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Tanissia Djemai, Patricia Stolf, Thierry Monteil, Jean-Marc Pierson. A Discrete Particle Swarm Optimization approach for Energy-efficient IoT services placement over Fog infrastructures. 18th International Symposium On Parallel and Distributed Computing (ISPDC 2019), Jun 2019, Amsterdam, Netherlands. pp.32-40, ⟨10.1109/ISPDC.2019.00020⟩. ⟨hal-02884931⟩

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