Research On Low Power Technology Of Wireless Sensor Networks For Urban Perception

The problem of "urban disease" is the consequence of the accelerated pace of urban development.Their specific performance is population expansion,resource shortages,security risks,environmental pollution,traffic congestion,etc.The emergence of smart city provides a feasible solution to the problem of urban disease,which brings creative changes to the basic necessities of life.Urban perception network provides a series of real-time monitoring data of urban infrastructure for the construction of smart city.To promote the construction of smart city has become the main trend of development at home and abroad of the city.Wireless sensor network(WSN),applied to the urban perceived network,with various sensors,data centric,service for the purpose,can realize the intelligent monitoring and management of city infrastructure.This paper builds a perceived network framework.Combined the common problem in WSN: low power consumption,this paper proposes a study of network energy consumption from two aspects: single-node hardware design and relay node deployment in the network layer,the main contents of this paper are as follows:(1)Puts forward a hardware design of sensor nodes for the general perceived network of city.According to the characteristics of urban perceived network,sensor node hardware requirements and architecture is analyzed.With low power consumption as the main design goals,determine the models of the main controlling chip,RF chip and other chips of the sensor nodes,in the meantime,analyze and design their peripheral circuit.Finally realize the hardware design of sensor nodes.(2)Poses an improved differential evolution algorithm,which is based on the lack of the standard differential evolution algorithm that is easy to fall into local optimum and premature convergence.According to the characteristics of the algorithm,two improved methods are presented.One is adaptive parameter control;the other is multi-differential strategy selection.On the basis of these ideas,the improvement principle is expounded,and five different test functions are selected.The method is verified by MATLAB simulation program.The results show that the algorithm can converge quickly and not easily fall into the local optimal solution,and to some extent,the emergence of precocious phenomena is avoided.(3)Proposes a network model for urban perception,which can control the energy consumption of the whole network by introducing relay nodes.In this paper,the Dijkstra algorithm is used to find the optimal routing path of energy,and the improved differential evolution algorithm is used to minimize the average energy consumption of the network,so as to obtain the relay node deployment information.Through the simulation results,the effectiveness of the improved differential evolution algorithm and the effect of energy consumption optimization are analyzed.(4)Tests surveillance system of termites around urban buildings.Combined with the actual project,the sensor node performance and power consumption are tested.And get the node hardware low power level.Finally,the relay node is deployed based on the result of the optimization algorithm,which effectively reduces the overall energy consumption of the network.