HarvWSNet: A co-simulation framework for energy harvesting wireless sensor networks - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2013

HarvWSNet: A co-simulation framework for energy harvesting wireless sensor networks

Résumé

Recent advances in energy harvesting (EH) technologies now allow wireless sensor networks (WSNs) to extend their lifetime by scavenging the energy available in their environment. While simulation is the most widely used method to design and evaluate network protocols for WSNs, existing network simulators are not adapted to the simulation of EH-WSNs and most of them provide only a simple linear battery model. Therefore, there is a need for a framework suited to EH-WSN simulation and to lifetime prediction. We propose a co-simulation framework, HarvWSNet, based on WSNet and Matlab, that provides adequate tools for the simulation of the network protocols and the lifetime of EH-WSN. Indeed, the framework allows for the simulation of multi-node network scenarios while including a detailed description of each node's energy harvesting, management subsystem and its time-varying environmental parameters. A simulation case study based on a temperature monitoring application demonstrates HarvWSNet's ability to predict network lifetime while minimally penalizing simulation time.
Fichier principal
Vignette du fichier
HarvWSNet-_A_Co-Simulation_Framework_for_Energy_Harvesting_Wireless_Sensor_Networks_ICNC13.pdf (300.36 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-00931772 , version 1 (15-01-2014)

Identifiants

Citer

Amine Didioui, Carolynn Bernier, Dominique Morche, Olivier Sentieys. HarvWSNet: A co-simulation framework for energy harvesting wireless sensor networks. International Conference on Computing, Networking and Communications (ICNC), Jan 2013, San Diego, United States. pp.808-812, ⟨10.1109/ICCNC.2013.6504192⟩. ⟨hal-00931772⟩
446 Consultations
1533 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More