Data gathering for network compressed coding enabled wireless sensor networks
Yunhe Li, Qinyu Zhang, Shaohua Wu, Bin Qian Cao · 2013
This paper presents an efficient data gathering framework of network coding (NC) coupled compressed sensing (CS) in wireless sensor networks (WSNs), called network compressed coding (NCC). We employ network coding to adapt to the dynamic nature of WSNs, such as moving obstacles and link failure. Measurements from sensor networks are often correlated because sensors nodes nearby observe the contiguous phenomenon, and the operation of the random linear network coding (RLNC) scheme is similar to that of the random projection in compressed sensing. Therefore, we introduce compressed sensing into the network coding (NC), to prevent all-or-nothing impact on NC. NCC simultaneously transmits and encodes specific packets of sensor measurements to form random projections for CS recovery. CS technology guarantees that the data gathered at all nodes are accurately recovered with a high probability from a small number of projections, which is less than the total number of source nodes in the network. Our simulation results show that, only less than half number of packets are required to reconstruct measurements with reasonable quality compared with the traditional network coding schemes. Also, NCC increases the data gathering efficiency by over 20% compared to the conventional NC scheme.