Research On Wireless Sensor Two-layer Network Limited Relay Node Placement Algorithm

The Internet of things is known as the third wave of the world information industry after the computer and Internet.As one of its core technologies,wireless sensor network(WSNs)has broad application prospects in many areas.In many application scenarios,WSNs is severely limited by energy and its own hardware and software resources,which has greatly slowed down the application scale of WSNs.Therefore,the energy consumption of wireless sensor networks has been the focus of research.In wireless sensor networks,by placing relay nodes(RNs)to reduce the energy consumption of sensor nodes and prolong the life cycle of network,it is a very effective method.This paper explores and studies the relay node placement scheme in wireless sensor networks.The following is the main research work of this article:Firstly,since RNs is placed in two-dimensional space,it does not fully reflect the effect of location factors on the placement of RNs.For this problem,this paper studies the situation of placing RNs in a three-dimensional space and the network structure is a double layer topology.A relay node placement algorithm based on mixed integer linear programming(MILP)is proposed.The algorithm first considers the physical model of the three dimensional space relay node.Then,the optimal placement of RNs is given based on the mixed integer linear programming,which makes the minimum transmission distance between each sensor node and the corresponding cluster head in the cluster.The scheme effectively reduces the node energy consumption and improves the packet delivery efficiency of the sensor network.Secondly,the limitation of the relay placement scheme based on MILP is analyzed.Because the NP difficult problem is a given position,the problem of determining the location of the relay is determined under certain conditions.Therefore,the problem of optimal placement of relay nodes in WSNs is a difficult problem of NP.In this paper,we use the optimized genetic algorithm(OGA)to solve the optimal placement of RNs in large-scale WSNs.The scheme first improves the evolutionary operators and convergence criteria in the genetic algorithm,and combines the simulated annealing algorithm(SA)to form an optimized genetic algorithm(OGA).Then,the optimized genetic algorithm is applied to the RNs placement of the large-scale WSNs.Simulation shows that this scheme improves the speed of solving the optimal solution and effectively prolongs the life cycle of the network.Finally,the RNs placement scheme proposed in the first two chapters is visualized.In view of the problem that the visual range of the traditional visualization system is too small and the AR markup is not applicable in some cases,a wireless sensor network visualization system based on relative position estimation technique is proposed.The system first calculates the coordinates of the sensor in the projection plane,then obtains the coordinates of the sensor on the display device through coordinate conversion,thus realizing the visualization of the RNs placement of WSNs,and the visual range is also improved.