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Study On Low Energy Dynamic Clustering Scheme Based On WSNs Data Aggregation

Posted on:2020-01-01Degree:MasterType:Thesis
Country:ChinaCandidate:W Q ZhangFull Text:PDF
GTID:2428330578954679Subject:Electronic and communication engineering
Abstract/Summary:PDF Full Text Request
Wireless Sensor Networks(WSNs)are mainly used to collaboratively sense and process information in the monitoring area.Sensor nodes have limited energy and are inconvenient to be replaced when the monitoring area is remote or dangerous.In addition,data collected by multiple sensor nodes in the same area may have more redundant information,which would not only affect communication overhead,but also consume a lot of energy.Therefore,it is of great application value to solve the problem of energy consumption in WSNs.Data aggregation technology removes redundant information in the network by means of feature extraction or data compression,reduces the amount of transmitting data and improves the efficiency of data collection.Data aggregation based on clustering structure can improve channel utilization and balance network energy consumption.In order to solve the problem of single factor in cluster head selection in existing clustering schemes,this thesis uses fuzzy logic to introduce a variety of factors affecting energy consumption to comprehensively select the cluster head,so as to prolong the lifetime of networks.The main contents of the thesis can be summarized as follows:(1)Firstly,the main ideas and characteristics of Low Energy Adaptive Clustering Hierarchy(LEACH)and the Distributed Energy-Efficient Clustering Algorithm(DEEC)are analyzed and compared.The effects of the initial energy,node size and sink position on the LEACH and DEEC are studied through experiments.(2)The LEACH clustering algorithm is improved,considering the residual energy of nodes,the relative distance between nodes and the base station,and the relative density of nodes,the fuzzy logic is used to select the best cluster head node adaptively,so as to prolong the lifetime of the network.The simulation results show that the LEACH clustering algorithm based on fuzzy logic can balance the energy consumption of the network more effectively than the traditional LEACH algorithm,and prolong the lifetime of the network effectively.(3)The fuzzy logic is introduced into the DEEC clustering algorithm of the heterogeneous network to improve the DEEC,and the adaptive dynamic cluster head selection is carried out considering the distribution density of the nodes and the relative distance from the node to the base station.The experiment analyzes the influence of different factors.The results show that the improved DEEC clustering algorithm can balance the energy consumption of the network and effectively prolong the survival time of the network,thus ensuring the accuracy of data aggregation and effectively improving network performance.In summary,the traditional LEACH algorithm and the DEEC algorithm of heterogeneous networks are improved in this thesis.Consider the energy of each node,the relative density of nodes and the relative distance between nodes and base stations,using fuzzy logic to select cluster heads adaptively.The experimental results show that the two improved schemes effectively balance the energy consumption of the network and prolong the survival time of the network effectively.
Keywords/Search Tags:Wireless sensor networks, Low energy, Adaptive dynamic clustering, Fuzzy logic
PDF Full Text Request
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