Research Of Energy Management Of Energy-Harvesting Wireless Sensor Networks

Wireless sensor networks (WSN) is often applied in the desert, the forest, the bridge and architecture environments to finish the monitoring tasks. It is hard to recharge or replace batteries for the nodes under these environments, while energy is an important factor to restrict the performance of wireless sensor networks, if we can take full advantage of the natural energy under these environment, the lifetime of nodes and networks will be greatly prolonged. With the development of natural energy harvesting technology, there have been designs of solar energy used for charging nodes. But considering the randomness and instability of ambient energy, it is necessary to find an adaptive strategy for the nodes to operate properly. Meanwhile, in order to reduce the network energy consumption and balance the network load, it is also important to study on the routing protocol of energy harvesting wireless sensor networks (EH-WSN).For the characteristics of ambient energy harvesting, energy prediction algorithm has always been of significant concern for ambient powered nodes. This dissertation studied on an energy prediction algorithm based on historical data weighting and proposed a Prediction based Energy-Harvesting clustering routing algorithm PEHC. In cluster head selection stage, it predict the coming ambient energy first, nodes with higher prediction value and more residual energy are more likely to act as cluster heads. Other nodes join the cluster according to the communication cost. The MATLAB simulation results show that PEHC can improve network energy balance which preforms better than existing algorithms.In order to further verify the performance of the algorithm above, solar energy harvesting sensor network is designed under the background of the health monitoring program research for the building structure of IOT. The node hardware support low power mode?solar energy harvesting and power management. For the embedded software, Configurable sampling mechanism is applied to improve the efficiency of collection and the optimization design of duty cycle based on the predicted results has improved the utilization efficiency of solar energy. These works provide a practical idea for the design of EH-WSN.