Distortion Analysis for Real-Time Reconstruction of Correlated Data Field in Heterogeneous Sensor Networks

This paper deals with the analysis of distortion introduced in the real time reconstruction of a spatio-temporally correlated field by a sink node. The field is measured by a randomly deployed network of heterogeneous sensors and the data is sent to the sink node. For the sake of analysis, we assume that the network consists of multiple clusters consisting of two types of nodes: cluster head and cluster member nodes. Given the initial energy capacities for both types of nodes, we determine the number of nodes needed for each type such that balanced energy consumption is achieved. Given the number of nodes of each type available in the network, we set up a mathematical model and analyze the average distortion in the reconstructed field. We study the relationship of this distortion with varying number of nodes, and determine the minimum number of nodes of each type needed to realize the reconstruction within a given distortion constraint. The work presented in this paper can be extended to consider different clustering methods, intra-cluster transmission schemes, and signal models.

[1]  Kin K. Leung,et al.  A dynamic clustering and energy efficient routing technique for sensor networks , 2007, IEEE Transactions on Wireless Communications.

[2]  Deborah Estrin,et al.  Coping with irregular spatio-temporal sampling in sensor networks , 2004, CCRV.

[3]  Catherine Rosenberg,et al.  A minimum cost heterogeneous sensor network with a lifetime constraint , 2005, IEEE Transactions on Mobile Computing.

[4]  Catherine Rosenberg,et al.  Design guidelines for wireless sensor networks: communication, clustering and aggregation , 2004, Ad Hoc Networks.

[5]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[6]  Martin Vetterli,et al.  On the optimal density for real-time data gathering of spatio-temporal processes in sensor networks , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[7]  Xiaobo Zhang,et al.  Distortion Analysis for Real-Time Data Gathering of Spatially-Temporally Correlated Fields in Sensor Networks , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[8]  I.F. Akyildiz,et al.  Spatial correlation-based collaborative medium access control in wireless sensor networks , 2006, IEEE/ACM Transactions on Networking.

[9]  S. Foss,et al.  On a Voronoi aggregative process related to a bivariate Poisson process , 1996, Advances in Applied Probability.

[10]  S. Fossy,et al.  On a Voronoi Aggregative Process Related to a Bivariate Poisson Process , 1996 .