Regulative Growth Codes: Enhancing Data Persistence in Sparse Sensor Networks

Growth Codes (GC) enhances the data persistence in dense sensor networks. However, GC exchanges data with neighbors in a completely random way, which may lead to uneven sensor data distribution in sparse sensor network. This significantly reduces the efficiency of GC data acquisition and fault-tolerance in sparse sensor network with less connectivity. In this paper, we propose Regulative Growth Codes (RGC) which use a random sequencing policy in data exchange operation instead of the completely random policy used in GC, and introduce the self-detection mechanism to reduce the redundant exchange. Simulation results show that the performance of RGC is better than GC in sparse sensor networks.