Hierarchical Clustering Algorithm For Mobile Wireless Sensor Networks Based On Affinity Propagation And Fuzzy C-means

Mobile Wireless Sensor Networks(MWSNs)consist of many sensor nodes deployed in the monitoring area,it is a highly integrated technology that integrates multiple disciplines.As the foundation of the Internet of things,MWSNs has been widely used in many fields,such as military,communication,hospital and so on.Because of its bright prospect and high application value,it has become a hot topic for scholars.Because the energy of sensor nodes in the network is limited and hard to replace,it is an efficient method to study an efficient energy-saving algorithm to reduce the energy consumption and extend the lifetime of the network.In this thesis,the hierarchical clustering algorithm is presented based on affinity propagation(AP)clustering and fuzzy c-means clustering.In this thesis,an energy saving clustering algorithm is presented based on improved K-medoids and AP in MWSNs.Firstly,the AP algorithm is used to find the number and location of the initial cluster heads.After that,a new weight function is established by considering the communication distance,residual energy and moving speed of the nodes.Next,improved K-medoids method is used to find the optimized cluster heads and form the network topology based on the new weight function.Finally,the network enters the communication stage using greedy algorithm to transmit data.The simulation results display that the presented algorithm can reduce the energy consumption of the entire network and prolong the network lifetime.Compared with LEACH,LEACH-M and APSA,the network lifetime of the presented APEEA algorithm is extended by 719 rounds,684 rounds and 90 rounds,respectively.Meanwhile,the performance improvement of the energy consumption can achieve 16.553 J(66.2%),13.973 J(55.9%)and 3.544 J(14.2%),respectively.In this thesis,a centralized clustering algorithm TCMA is presented based on three-layer clustering structure in MWSNs.We analyzed the following three protocols,the distributed LEACH algorithm based on two-tiered clustering structure,the distributed TC-LEACH algorithm based on three-tiered clustering structure and the hybrid clustering algorithm HHCA based on three-tiered clustering structure.Combined with the fuzzy c-means algorithm,a centralized clustering algorithm TCMA based on three-layer clustering structure is proposed.In three-layer clustering structure,the first layer uses the APEEA algorithm to select the cluster head,and the second layer uses the fuzzy c-means clustering algorithm to select the grid head.For the mobility of nodes,in order to make the network communication stable,each grid head maintains a list of cluster heads associated with it,and each cluster head maintains a list of sensor nodes associated with it.Compared with TL-LEACH,HHCA and APEEA,the network lifetime of the presented TCMA algorithm is extended by 300rounds,180rounds and 90 rounds,respectively.Meanwhile,the performance improvement of the energy consumption can achieve 7.5J(30%),5.75J(23%)and 2.75J(11%),respectively.The simulation results display that the presented algorithm can reduce the energy consumption of the entire network and prolong the network lifetime.It can be found that the centralized hierarchical clustering is better than the hybrid hierarchical clustering in the mobile environment.