Multi-layered Model for Performance Evaluation of oneM2M-based IoT Solution - Réseaux, Informatique, Systèmes de Confiance
Communication Dans Un Congrès Année : 2024

Multi-layered Model for Performance Evaluation of oneM2M-based IoT Solution

Résumé

In this paper we evaluate the impact of standards in terms of performance and their applicability in the field of IoT system design and deployment. We focus on the global IoT oneM2M standard. Our objective is to evaluate a oneM2M-based IoT solution regarding different relevant Key Performance Indicators. We propose a multi layered-model of an IoT standardized solution, able to tackle applicative, infrastructure and deployment aspects. Based on this model, we are able to globally evaluate and analyze, through simulation, the adequacy of a deployment with respect to the initial applicative constraints and the chosen oneM2M standard implementation. In our case, the constraints are mix-critical coming from the e-Health remote monitoring of patient by their physician but also the management of the patient in case of vital emergency situation. By tuning the system configuration and parameters of the proposed applicative scenario, we evaluate, by simulation, the KPIs of a oneM2M-based IoT solution by exploiting (1) the different features of the standard, (2) the capabilities of the underlying infrastructure, and (3) the performance of the oneM2M stacks used in the solution. The simulation and performance evaluation are based on two tools developed by the authors. One is a specific profiler for oneM2M open-source stack, whereas the simulation and performance evaluation is build on top of the OMNeT++ discrete event simulator.
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Dates et versions

hal-04749511 , version 1 (27-11-2024)

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  • HAL Id : hal-04749511 , version 1

Citer

Samir Medjiah, Thierry Monteil, Marie-Agnès Peraldi-Frati, Luigi Liquori. Multi-layered Model for Performance Evaluation of oneM2M-based IoT Solution. IFIP-IoT Conference 2024 - 7th IFIP WG 5.5 International Cross-Domain Conference on Internet of Things, Université Côte d'Azur; IFIP, Nov 2024, Nice, France. ⟨hal-04749511⟩
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