Data Collection Algorithm Based On Mobile Sink In Wireless Sensor Networks

Wireless sensor networks(WSNs)contain a large number of sensor nodes,which monitor the target area in real time and collect information.As a key technology in the field of data collection,it has now become the foundation of big data and artificial intelligence technology.In traditional WSNs,data forwarding between sensor nodes usually adopts multi hop mode.However,due to a large number of forwarding data from other nodes,nodes near Sink tend to die due to excessive energy consumption,resulting in network link interruption.In order to avoid this problem,researchers propose a method of mobile Sink to collect data.Mobile Sink moves according to a certain path in the monitoring area to collect the data of nodes in the network.The method of mobile Sink accessing each sensor node is not desirable.How to plan the path of mobile Sink in the sensing area,which makes the sensing data through less hops and gather to Sink nodes in limited delay,has become a challenge.The core problem of this dissertation is how to use mobile Sink to collect data in WSNs.In order to achieve the goal better,we need to save network energy,prolong network life cycle and reduce network delay.Therefore,according to the number of mobile Sink,this dissertation proposes the following two algorithms:data collection algorithm based on single mobile Sink and data collection algorithm based on multiple mobile Sink.The main work is as follows:1.A data collection algorithm based on single mobile sink is proposed.The algorithm is divided into two different stages:clustering and path planning:(1)in the clustering stage,the average residual energy of network nodes and the distribution density of neighbor nodes are considered;(2)in the path planning stage,for the selected n cluster head nodes,mobile sink will traverse the location of each cluster head according to the planned path to collect data.Mobile sink uses the improved minimum spanning tree prim algorithm for path planning,takes the Euclidean distance between cluster heads as weight,and finds the optimal path based on the minimum spanning tree formed by all cluster heads.Because there are multiple connection paths in some nodes of the minimum spanning tree,the idea of the improved algorithm in this chapter is:delete multiple branches of a node,and re connect all nodes,so that there is only one path in the whole region,and each cluster head node is only passed once,so as to get the shortest path of mobile sink and make the delay of network data collection the shortest.Experimental analysis and comparison with other algorithms show that the algorithm can effectively extend the network life cycle and reduce the delay of data collection2.A data collection algorithm based on multi mobile sink is proposed.Firstly,the whole network is divided into four regions,and the cluster heads are selected.The nearest cluster head to sink node is taken as the root node,and the minimum spanning tree among all cluster heads in the sub region is established.The root node collects the data of all cluster heads.At the same time,four mobile sink nodes and a primary sink are introduced into the network.The four mobile sinks collect data along the planned path at the same time.When the mobile sink moves to the root node,it decides whether to stay or not according to the need.When the sink node traverses the track,the data collection of the whole network is completed.At the end of each round,the mobile sink sends the collected data to the primary sink.After all four mobile sinks are sent,the next round of data collection is started at the same time.Finally,the experimental analysis of the algorithm and the comparison with other algorithms show that the four mobile sink algorithms can better solve the network delay problem and improve the efficiency of data collection on the basis of extending the network life cycle.Fig.ure[25]Table[1]Ref[57]...