| In recent years,Wireless Sensor Networks(WSNs),as one of the key basic technologies of the Internet of Things,has been widely used in military intrusion monitoring,environmental monitoring,smart agriculture and other application fields with its advantages of low power consumption,low cost,distribution and self-organization,and provides services such as accurate data sensing,efficient transmission and processing for these application fields.In the above application scenarios,since sensor nodes are usually randomly deployed in a very harsh natural environment that is difficult for human beings to reach,it is very difficult to replace the battery of sensor nodes or make secondary energy supply.Once the node stops working due to energy exhaustion,and the obtained monitoring data is incomplete,it will lead to the network not working normally,orderly and efficiently.Therefore,how to prolong the network lifetime as much as possible under the condition of limited resources is an urgent problem for WSNs.Long-distance data receiving,forwarding and transmission are the main sources of network energy consumption,so many scholars put forward clustering routing protocol to effectively reduce network energy consumption and prolong network lifetime.In the clustering routing protocol,nodes are divided into multiple clusters,and then a suitable cluster head is selected in each cluster to collect,fuse and forward the sensing data of other nodes in the cluster,and the data in the cluster is transmitted to the base station for processing by multi-hop or single-hop among clusters.However,cluster heads usually consume energy earlier than other nodes because they undertake a lot of data forwarding and fusion tasks.In addition,unreasonable relay forwarding paths will lead to excessive load and unbalanced energy consumption of relay cluster heads,which will further accelerate the death of cluster heads.Therefore,how to optimally select the cluster head and its relay path is one of the key challenges to realize the high performance of cluster routing protocols.At present,clustering routing protocols usually adopt the LEACH-based probabilistic method of cluster head selection or the cluster head selection method based on swarm intelligence,etc.However,the rotation selection of cluster heads based on probability easily leads to a great difference in the number of cluster heads in each round.Besides,the cluster selection method based on swarm intelligence is usually more complex than the LEACH-based clustering routing protocol due to involving many parameters and how to cooperatively set the optimal values of various parameters is difficult.Aiming at minimizing network energy consumption and maximizing network lifetime,combining multi-threshold segmentation algorithm,swarm intelligence optimization algorithm and game theory,this paper proposes an energy-efficiency routing protocol based on multi-threshold segmentation(EERPMS)and a game theory and coverage optimization based multi-hop routing protocol(MRP-GTCO)for wireless sensor networks.The research contents in this paper are outlined as the following aspects:(1)Focusing on the optimal cluster formation problem of nodes,by constructing the relationship between multi-threshold image segmentation and node clustering,the node clustering problem is transformed into the optimal segmentation threshold solution problem.multi-threshold OTSU algorithm,node angle and number of nodes are used to form the objective function of the variance of node angle and number among clusters,and bat algorithm is used to find the optimal solution of the objective function to realize the optimal clustering among nodes,which effectively improves the uniformity of cluster head distribution and the load balance of cluster heads.(2)In view of the fact that the location and number of cluster heads in WSNs have great influence on data transmission efficiency and network lifetime.With the goal of minimizing network energy consumption,the relationship among regional size,cluster head location,cluster head number and network energy consumption is constructed,and the calculation theory of optimal cluster head number and location is put forward.Based on the above calculation theory of optimal cluster head number and location,a novel cluster head selection algorithm is proposed by combining the residual energy of nodes and the optimal location of cluster heads,which realizes the optimal election of cluster heads and effectively reduces the network energy consumption.(3)Based on the theory of non-cooperative game and covering optimization,considering the selfish problem of key nodes with high residual energy and large number of neighboring nodes,a node clustering game with selfish punishment mechanism is proposed,and the Nash equilibrium solution of the mixed strategy in this game is analyzed.In order to further improve the uniformity and rationality of cluster head distribution,the optimal cluster head coverage set is solved by combining the coverage optimization theory and particle swarm optimization algorithm,which effectively rationalizes the cluster head selection and reduces the cluster head energy consumption.(4)In order to reduce a large amount of energy consumption caused by long-distance data forwarding of cluster heads,the optimal multi-hop application theory between clusters is constructed for different network scenarios.On this basis,considering the position of relay cluster head,residual energy and load,an optimal relay selection algorithm is proposed to reduce the network energy consumption and prolong the network lifetime.Finally,EERPMS and MRP-GTCO protocols proposed in this paper are simulated on the MATLAB 2016 b simulation platform.By comparing the performance indexes such as cluster head distribution,cluster head energy consumption,network energy consumption and network lifetime,it is verified that the two protocols proposed in this paper can effectively reduce network energy consumption,improve network energy consumption balance and network working time. |
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