Synchronization-based data gathering scheme using chaotic pulse-coupled neural networks in wireless sensor networks

Wireless sensor networks (WSNs) have attracted significant interests of many researchers because they have great potential as a means of obtaining information of various environments remotely. WSNs have their wide range of applications, such as natural environmental monitoring in forest regions and environmental control in office buildings. In WSNs, hundreds or thousands of micro-sensor nodes with such resource limitation as battery capacity, memory, CPU, and communication capacity are deployed without control in a region and used to monitor and gather sensor information of environments. Therefore, scalable and efficient network control and/or data gathering scheme for saving energy consumption of each sensor node is needed to prolong WSN lifetime. In this paper, assuming that sensor nodes synchronize to intermittently communicate with each other only when they are active for realizing the long-term employment of WSNs, we propose a new synchronization scheme for gathering sensor information using chaotic pulse-coupled neural networks (CPCNN). We evaluate the proposed scheme using computer simulation and discuss its development potential. In simulation experiment, the proposed scheme is compared with previous synchronization scheme based on a pulse-coupled oscillator model to verify its effectiveness.