Decentralized detection in IEEE 802.15.4 wireless sensor networks

Authors:
Marco Martalò;Chiara Buratti;Gianluigi Ferrari;Roberto Verdone
Affiliations:
Wireless Ad hoc and Sensor Networks Laboratory, Department of Information Engineering, University of Parma, Parma, Italy;Wireless Communication Laboratory, Department of Electronics, Computer Sciences, and Systems, University of Bologna, Bologna, Italy;Wireless Ad hoc and Sensor Networks Laboratory, Department of Information Engineering, University of Parma, Parma, Italy;Wireless Communication Laboratory, Department of Electronics, Computer Sciences, and Systems, University of Bologna, Bologna, Italy
Venue:
EURASIP Journal on Wireless Communications and Networking - Special issue on signal processing-assisted protocols and algorithms for cooperating objects and wireless sensor networks
Year:
2010

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Abstract

We present a mathematical model to study decentralized detection in clustered wireless sensor networks (WSNs). Sensors and fusion centers (FCs) are distributed with the aim of detecting an event of interest. Sensors are organized in clusters, with FCs acting as cluster heads, and are supposed to observe the same common binary phenomenon. A query-based application is accounted for; FCs periodically send queries and wait for replies coming from sensors. After reception of data, FCs perform data fusion with a majority-like fusion rule and send their decisions to an access point (AP), where a final data fusion is carried out and an estimate of the phenomenon is obtained. We assume that sensors are IEEE 802.15.4-compliant devices and use the medium access control (MAC) protocol defined by the standard, based on carrier-sense multiple access with collision avoidance. Decentralized detection and MAC issues are jointly investigated through analytical modelling. The proposed framework allows the derivation of the probability of decision error at the AP, when accounting for packets' losses due to possible collisions. Our results show that MAC losses strongly affect system performance. The impact of different clustering configurations and of noisy communications is also investigated.