Research On Energy-saving Technology Of Zigbee Network Based On Data Compression And Cluster Routing

Wireless sensor network has the characteristics of low cost,high security and good realtime performance.It is widely used in the fields of public health,environmental monitoring,military and national defense,and has a good prospect for development.Wireless sensor nodes generally use battery power,once the node energy depletion,replacement and recovery is very troublesome.Therefore,it is necessary to study a kind of energy-saving wireless sensor network to improve the node energy utilization rate and prolong the network life time.Therefore,this thesis considers reducing the energy consumption of wireless sensor networks from two aspects:data compression and clustering routing.The main research contents are as follows:(1)Aiming at the problems of uneven distribution of cluster heads and unequal node energy consumption in traditional LEACH algorithm,a routing optimization algorithm based on improved genetic algorithm is proposed.In the clustering stage,the weight formula is introduced to make the nodes with sufficient energy near the base station more likely to be elected as cluster heads,avoiding the problem of too fast failure caused by the nodes with low energy being elected as cluster heads.In the data transmission stage,the fitness function is constructed based on the total distance from the initial cluster head node to the base station and the total average hops from common nodes in the region to the base station.After several searches,an optimal path from the initial cluster head node to the base station is found.Simulation results show that the proposed routing algorithm can reduce the path cost of node data transmission,balance node energy consumption,and extend the network life time.(2)Aiming at the problem of too fast energy consumption caused by a large amount of redundancy in the process of data packet forwarding between nodes,a data compression algorithm applied to wireless sensor networks is designed.The algorithm takes Haar wavelet algorithm as the carrier,and integrates Huffman coding on the basis of this algorithm.The purpose of improving the data compression ratio is to ensure the accuracy of data recovery.The specific approach is:firstly,the original data collected by the sensor node is curve fitted to convert the discrete signal into a continuous signal,and then the fitted signal is transformed by wavelet,and the corresponding wavelet coefficient is extracted according to the given threshold conditions for improved Huffman coding to reduce the data transmission volume.The features of the improved Huffman encoding are that the binary encoding of a certain number of bits is converted to the decimal encoding using the base conversion,and the storage space is further compressed by the secondary compression.The simulation results show that this algorithm can improve the compression ratio of wireless sensor networks significantly,and has certain accuracy in the reconstruction of original data.(3)Build a ZigBee system and apply the two energy-saving optimization algorithms mentioned above.The system uses TI’s CC2530 as the hardware platform and QT as the system software platform to realize data acquisition and transmission.Network test and data sending and receiving test show that the system has good stability and can work for a long time.The energy consumption test shows that the energy consumption of the whole network can be reduced and the life cycle of the network can be prolonged.