Wireless sensor networks (WSNs) are becoming more and more a pervasive tool to monitor a wide range of physical phenomena. The opportunities arising from the many potential applications raise a series of technical challenges coupled with implementation constraints, such as energy supply, latency and vulnerability. The need for an efficient design of a WSN requires a strict interplay between the sensing and communication phases. In this article, we provide an overview of various distributed detection and estimation algorithms, incorporating the constraints imposed by the communication channel and the application requirements. We consider both cases where sensing is distributed, but the decision is centralized, and the case where the decision itself is totally decentralized. Specific attention is devoted to achieve globally optimal results through the interaction of nearby nodes only. We show how the topology of the network plays a significant role in the performance of the distributed algorithms, in terms of energy expenditure and latency. Then, we show how to optimize the network topology in order to minimize energy consumption or to match the graph describing the statistical dependencies among the variables observed by the nodes.

Distributed detection and estimation in wireless sensor networks

Barbarossa S.;Sardellitti S.;Di Lorenzo P.
2014

Abstract

Wireless sensor networks (WSNs) are becoming more and more a pervasive tool to monitor a wide range of physical phenomena. The opportunities arising from the many potential applications raise a series of technical challenges coupled with implementation constraints, such as energy supply, latency and vulnerability. The need for an efficient design of a WSN requires a strict interplay between the sensing and communication phases. In this article, we provide an overview of various distributed detection and estimation algorithms, incorporating the constraints imposed by the communication channel and the application requirements. We consider both cases where sensing is distributed, but the decision is centralized, and the case where the decision itself is totally decentralized. Specific attention is devoted to achieve globally optimal results through the interaction of nearby nodes only. We show how the topology of the network plays a significant role in the performance of the distributed algorithms, in terms of energy expenditure and latency. Then, we show how to optimize the network topology in order to minimize energy consumption or to match the graph describing the statistical dependencies among the variables observed by the nodes.
978-0-12-396500-4
File allegati a questo prodotto
File Dimensione Formato  
Barbarossa_Distributed-detection_2014.pdf

solo gestori archivio

Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 2.36 MB
Formato Adobe PDF
2.36 MB 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: http://hdl.handle.net/11573/1119359
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact