One of the major sources of energy waste in wireless sensor networks (WSNs) is idle listening, that is, the cost of actively listening for potential packets. This article focuses on reducing idle-listening time via a dynamic duty-cycling technique which aims at optimizing the sleep interval between consecutive wake-ups. We considered a receiver-initiated MAC method for WSNs in which the sender waits for a beacon signal from the receiver before starting to transmit. Since each sender receives beacon signals from several nodes, the data are routed on multiple paths in a data collection network. In this context, we propose an optimization framework for minimizing the energy waste of the most power-hungry node of the network. To this aim, we first derive an analytic model that predicts nodes’ energy consumption. Then, we use the model to derive a distributed optimization technique. Simulation results via NS-2 simulator are included to illustrate the accuracy of the model, and numerical results assess the validity of the proposed scheme.

Abrardo, A., Balucanti, L., Mecocci, A. (2013). A game theory distributed approach for energy optimization in WSNs. ACM TRANSACTIONS ON SENSOR NETWORKS, 9(4) [10.1145/2489253.2489261].

A game theory distributed approach for energy optimization in WSNs

ABRARDO, ANDREA;BALUCANTI, LAPO;MECOCCI, ALESSANDRO
2013-01-01

Abstract

One of the major sources of energy waste in wireless sensor networks (WSNs) is idle listening, that is, the cost of actively listening for potential packets. This article focuses on reducing idle-listening time via a dynamic duty-cycling technique which aims at optimizing the sleep interval between consecutive wake-ups. We considered a receiver-initiated MAC method for WSNs in which the sender waits for a beacon signal from the receiver before starting to transmit. Since each sender receives beacon signals from several nodes, the data are routed on multiple paths in a data collection network. In this context, we propose an optimization framework for minimizing the energy waste of the most power-hungry node of the network. To this aim, we first derive an analytic model that predicts nodes’ energy consumption. Then, we use the model to derive a distributed optimization technique. Simulation results via NS-2 simulator are included to illustrate the accuracy of the model, and numerical results assess the validity of the proposed scheme.
2013
Abrardo, A., Balucanti, L., Mecocci, A. (2013). A game theory distributed approach for energy optimization in WSNs. ACM TRANSACTIONS ON SENSOR NETWORKS, 9(4) [10.1145/2489253.2489261].
File in questo prodotto:
File Dimensione Formato  
paper 1.pdf

non disponibili

Tipologia: Post-print
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 473.02 kB
Formato Adobe PDF
473.02 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/44996
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo