Research On Energy Consumption Optimization Of WSN Based On Hierarchical Clustering

With the development of technologies and concepts such as Internet +,smart home,Io T and industry 4.0,wireless sensor network as their core component has rapidly developed.During the deployment of wireless sensor network,the data dimension used in the traditional hierarchical division is relatively simple,which can lead to the imbalance of energy consumption among clusters.The data aggregation after network partition is relatively inefficient.In view of these constraints,this dissertation takes hierarchical clustering method as the general argument,discusses the application of bottom-up clustering method in network stratification and its effect on energy balance.Then based on CHAMELEON clustering,a multi-level data aggregate system is established.Through the work in these two aspects,a new strategy for energy consumption research of wireless sensor networks is proposed.First,this dissertation demonstrates the effect of double cluster head non-uniform clustering algorithm based on BIRCH improvement on network energy balance.The original BIRCH clustering algorithm was adapted to fit the characteristics of wireless sensor networks,and a new dimension is added to traditional hierarchical cluster network routing.At the same time,the non-uniform clustering is objectify through the new dimension to balance uneven energy consumption caused by uniform clustering.Secondly,the multi-dimensional double-head clustering strategy is introduced to optimize the selection mechanism of the existing algorithms from 3d to 4d,and the corresponding selection strategy is adopted according to the different working characteristics of the these nodes.Through these schemes,the network equilibrium is improved.Secondly,this dissertation discusses the data aggregation based on CHAMELEON clustering.This scheme bring data characteristics into consideration.In this way,the redundant information is compressed during the aggregation,so that the efficiency can be improved,and the availability of data can be guaranteed through the region fusion strategy.In addition,in the transmission phase,use the split path transmission to improve efficiency of data transmission.The scheme this dissertation proposed can improve the life cycle of the network.Finally,through the experimental simulation and result analysis,this dissertation verifies the equilibrium of network energy consumption from three aspects: network survival node,network residual energy,and energy consumption variation of different node types in the network.The experiment shows that the performance of the proposed algorithm is better than that of the comparison algorithms.At the same time,the validity of the multi-level data fusion architecture is proved by the comparison of data compression rate.In terms of data transmission efficiency and data delivery rate comparison,the proposed scheme is also over-perform the comparison algorithms.