This paper addresses the problem of engineering energy-efficient target detection applications using unattended Wireless Sensor Networks (WSNs) for long-lasting surveillance of areas of interest. As battery energy depletion is an issue in this context, an approach consists of switching on and off sensing and communication modules of wireless sensors according to duty cycles. Making these modules work in an intermittent fashion impacts (i) the latency of notification transmission (depending on the communication duty cycle) and (ii) the probability of missed target detection (depending on the number of deployed nodes and the sensing duty cycle). In order to optimize the system parameters according to performance objectives, we first derive an analytical engineering toolkit which evaluates the probability of missed detection (Pmd), the notification transmission latency (D), and the network lifetime (¿) under the assumption of random node deployment. Then, we show how this toolbox can be used to optimally configure system parameters under realistic performance constraints.
Engineering energy-efficient target detection applications in wireless sensor networks / P., Medagliani; J., Leguay; V., Gay; M., Lopez Ramos; Ferrari, Gianluigi. - (2010), pp. 31-39. (Intervento presentato al convegno 8th Ann. IEEE Int. Conf. on Pervasive Computing and Communications (PERCOM 2010) tenutosi a Mannheim, Germania nel Marzo-Aprile) [10.1109/PERCOM.2010.5466994].
Engineering energy-efficient target detection applications in wireless sensor networks
FERRARI, Gianluigi
2010-01-01
Abstract
This paper addresses the problem of engineering energy-efficient target detection applications using unattended Wireless Sensor Networks (WSNs) for long-lasting surveillance of areas of interest. As battery energy depletion is an issue in this context, an approach consists of switching on and off sensing and communication modules of wireless sensors according to duty cycles. Making these modules work in an intermittent fashion impacts (i) the latency of notification transmission (depending on the communication duty cycle) and (ii) the probability of missed target detection (depending on the number of deployed nodes and the sensing duty cycle). In order to optimize the system parameters according to performance objectives, we first derive an analytical engineering toolkit which evaluates the probability of missed detection (Pmd), the notification transmission latency (D), and the network lifetime (¿) under the assumption of random node deployment. Then, we show how this toolbox can be used to optimally configure system parameters under realistic performance constraints.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
