Reliability and efficiency analysis of distributed source coding in wireless sensor networks

  • Authors:
  • C. Fischione;S. Tennina;F. Santucci;F. Graziosi

  • Affiliations:
  • ACCESS Linnaeus Center, Electrical Engineering, Royal Institute of Technology, Stockholm, Sweden;University of L'Aquila, Poggio di Roio, Centre of Excellence DEWS and Department of Electrical and Information Engineering, Poggio di Roio, L’Aquila, Italy;University of L'Aquila, Poggio di Roio, Centre of Excellence DEWS and Department of Electrical and Information Engineering, Poggio di Roio, L’Aquila, Italy;University of L'Aquila, Poggio di Roio, Centre of Excellence DEWS and Department of Electrical and Information Engineering, Poggio di Roio, L’Aquila, Italy

  • Venue:
  • ICC'09 Proceedings of the 2009 IEEE international conference on Communications
  • Year:
  • 2009

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Abstract

We propose a comprehensive theoretical framework to evaluate reliability and energy consumption of distributed source coding (DSC) in wireless sensor networks (WSNs) applications. Energy efficiency and the amount of measurements that can be successfully decoded in tree-based WSNs employing DSC in the presence of different coding topologies and packet aggregation schemes (PA) are accurately characterized. The system model includes a realistic network architecture with multi-hop communication, automatic repeat request protocol (ARQ), packet losses due to channel impairments and collisions, and correlation properties of the sensed phenomena. Four DSC topologies and three alternatives of PA are considered. The analysis is carried out by evaluating the expressions of reliability of DSC in terms of probability of measurements that cannot be decoded (loss factor), and the efficiency in terms of average energy consumption of the network. Numerical results show that the best choice of DSC topology and packet aggregation depends highly on the network parameters and source characteristics. Therefore, the analysis developed in this paper can be used as an effective mean to optimize network operations.