Energy-Aware Topology Control Strategy for Human-Centric Wireless Sensor Networks

Authors
Meseguer, Roc; Molina, Carlos; Ochoa, Sergio F.; Santos, Rodrigo Martin
Publication Year
2014
Language
English
Format
article
Status
Published version
Description
The adoption of mobile and ubiquitous solutions that involve participatory or opportunistic sensing increases every day. This situation has highlighted the relevance of optimizing the energy consumption of these solutions, because their operation depends on the devices’ battery lifetimes. This article presents a study that intends to understand how the prediction of topology control messages in human-centric wireless sensor networks can be used to help reduce the energy consumption of the participating devices. In order to do that, five research questions have been defined and a study based on simulations was conducted to answer these questions. The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes. These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior. Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.
Fil: Meseguer, Roc . Universidad Politecnica de Catalunya; España
Fil: Molina, Carlos. Universitat Rovira I Virgili; España
Fil: Ochoa, Sergio F.. Universidad de Chile; Chile
Fil: Santos, Rodrigo Martin. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras. Laboratorio de Sistemas Digitales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto de Investigación en Ingeniería Eléctrica; Argentina
Subject
Human-Centric Wireless Sensor Network
Energy Consumption
Topology Control Messages
Message Prediction
Participatory Sensing
Opportunistic Sensing
Ciencias de la Información y Bioinformática
Ciencias de la Computación e Información
CIENCIAS NATURALES Y EXACTAS
Access level
Open access
License
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repository
CONICET Digital (CONICET)
Institution
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identifier
oai:ri.conicet.gov.ar:11336/11754