Abstract—For the energy-constraint of nodes in wireless sensor networks, a sparse random projection algorithm based on minimum energy consumption tree (SRP-MET) is proposed in this paper. Compressive Sensing is applied to data compression. And it minimizes the number of source node by means of sparse random projection. The relay nodes is chosen on the principle of minimum energy consumption, and the spanning tree routing is created based on the idea of centralized greedy increasing tree to match the projection matrix. Simulation results show that, on the condition of reliable communication links, the proposed algorithm not reconstruct the original data accurately, but also effectively reduce the energy consumption and prolong the network lifetime by balance the network load.

Index Terms—Wireless sensor network, compressive sensing, sparse random projection

Cite: Chong Wang, Xia Zhang, and Ou Li, "Sparse Random Projection Algorithm Based on Minimum Energy Tree in Wireless Sensor Network," Journal of Communications, vol. 10, no. 9, pp. 740-746, 2015. Doi: 10.12720/jcm.10.9.740-746