An Information-Theoretic Approach for Energy-Efficient Collaborative Tracking in Wireless Sensor Networks

In this paper, the problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. Aiming at an efficient resource solution, the research adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimize the energy consumption of the tracking task using the energy model by Wang, 2001. We layout a cluster-based architecture to address the limitations in computational, battery power and communications of the sensor devices. We consider the computation of the posterior Cramer-Rao bound (PCRB) in the tracking based on received signal strength measurements. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented particle filter, both in the centralized and in the distributed manner. Their performance are compared with the theoretical lower bound PCRB. To save energy, a node selection procedure based on greedy algorithms is proposed. The node selection problem is formulated as a cross-layer optimization problem and it is solved using greedy algorithms.

ARIENZO Loredana; 

2010-07-06

HINDAWI PUBLISHING CORPORATION

JRC57412

1687-1499,   

http://downloads.hindawi.com/journals/wcn/2010/641632.pdf,    https://publications.jrc.ec.europa.eu/repository/handle/JRC57412,   

10.1155/2010/641632,