Research On Node Design And Scheduling Algorithm For Solar Energy Harvesting WMSNs

Nowadays,wireless multimedia sensor networks has been invested logistics engineering,environmental monitoring,intelligient city,modern agriculture and other application fields heavily.Due to the ability to perceive rich multimedia information,the energy consumption problem is more serious.However,the energy supply based on limited battery power hinders its flexible design and long-term deployment.Environmental energy harvesting technology enables WMSNs node to extract energy from the environment,which provides an effective technical means for extending the lifetime of network.This thesis designs a low-power WMSNs node with energy replenishment based on the Raspberry Pi development board and solar energy collection technology.The main modules consisted of solar harvesting module,processor module,image sensor module,wireless communication module,the solar battery charging module,UPS HAT charging regulator module and secure digital memory card storage module.The appropriate software was developed according to the different modules,including the program design of wireless communication network environment,image sensor module software and node transmission implemention based on real time transport protocol.The test results show that the WMSNs nodes have lower energy consumption,it can collect and store environmental energy as well as drive the operation of nodes,which can be widely used in environmental monitoring and other fields.Based on this node design program,this thesis proposes a new WMSNs node scheduling algorithm.Setting three types of priorities for all nodes in the network,and adjust nodes based on the role of nodes in the network clustering structure,the remaining energy of the nodes,the replenishment energy of the solar energy,the working interval of nodes and the working state of the previous stage of nodes.By reducing the network performance of some lower priority nodes,which reduce the amount of data transmission of networks,balancing network energy consumption and maintaining the energy state of the network,which in turn provides long-term stable network operation and avoids node failure.Theoretical analysis and simulation results show that this algorithm can improve network performance effectively.