Energy-efficient distributed data storage for wireless sensor networks based on compressed sensing and network coding

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Journal Article
IEEE Transactions on Wireless Communications, 2013, 12 (10), pp. 5087 - 5099
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Recently, distributed data storage (DDS) for Wireless Sensor Networks (WSNs) has attracted great attention, especially in catastrophic scenarios. Since power consumption is one of the most critical factors that affect the lifetime of WSNs, the energy efficiency of DDS in WSNs is investigated in this paper. Based on Compressed Sensing (CS) and network coding theories, we propose a Compressed Network Coding based Distributed data Storage (CNCDS) scheme by exploiting the correlation of sensor readings. The CNCDS scheme achieves high energy efficiency by reducing the total number of transmissions N ttot and receptions N rtot during the data dissemination process. Theoretical analysis proves that the CNCDS scheme guarantees good CS recovery performance. In order to theoretically verify the efficiency of the CNCDS scheme, the expressions for N ttot and N rtot are derived based on random geometric graphs (RGG) theory. Furthermore, based on the derived expressions, an adaptive CNCDS scheme is proposed to further reduce N ttot and N rtot . Simulation results validate that, compared with the conventional ICStorage scheme, the proposed CNCDS scheme reduces N ttot , N rtot , and the CS recovery mean squared error (MSE) by up to 55%, 74%, and 76% respectively. In addition, compared with the CNCDS scheme, the adaptive CNCDS scheme further reduces N ttot and N rtot by up to 63% and 32% respectively. © 2002-2012 IEEE.
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