Research On WSN Node Positioning Based On Swarm Intelligence Algorithm In Three-dimensional Spac

Localization technology is one of the important supporting technologies for 3D Wireless Sensor Networks(WSN),because the accuracy of node location determines the performance of WSN.The existing 3D localization algorithms have low localization accuracy.In order to improve the accuracy of node localization,the 3D homogeneous WSN localization algorithm and 3D heterogeneous WSN localization algorithm are proposed in this paper based on the population intelligence optimization algorithm,respectively.The main work is as follows.(1)Comparing the localization performance of 9 swarm intelligence optimization algorithms in 3D WSN,the Water Flow Optimizer(WFO)with better overall localization performance was selected for calculating the coordinates of the nodes.And a multi-strategy improved water flow optimizer(IWFO)is proposed to address the lack of performance of WFO.Firstly,the Halton sequence is introduced to initialize the initial population of WFO to be evenly distributed in the search space to improve the population diversity.Secondly,the nonlinear laminar flow operator and turbulent flow operator are introduced to better balance the exploration and exploitation capability of the algorithm.The position update strategy of the laminar flow phase of the algorithm is also improved to enhance the global search capability of the algorithm.Finally,the Cauchy mutation perturbation strategy is introduced to perturb the solution of the algorithm to enhance the ability of the algorithm to jump out of the local optimum.The simulation experiments of IWFO with the nine remaining algorithms on benchmark test functions show that IWFO has better optimization performance.IWFO and five algorithms are applied to the 3D WSN localization algorithm separately,and the experimental results show that IWFO achieves the smallest localization error,which proves that IWFO is more suitable for application in 3D WSN localization.(2)Aiming at the problem of large 3D DV-Hop localization error,a 3D WSN localization algorithm based on multi-communication radius improvement is proposed.Firstly,the distance estimation phase of the 3D DV-Hop is improved.The single communication radius broadcast information of anchor nodes is improved to multi-communication radius broadcast information.The number of multi-communication radius is set using the ratio of anchor nodes and the average number of nodes within the communication range of a single node to reasonably subdivide the neighbor relationship between nodes,which effectively reduces the estimation error of distance.The hop count threshold is set to control the energy overhead from multi-communication radius broadcasting.Secondly,the four non-coplanar anchor nodes closest to the unknown nodes are selected to participate in localization.The IWFO algorithm is used to calculate the coordinates of the unknown nodes in the search space to further reduce the localization error.The experimental results show that compared with several other algorithms,the proposed 3D WSN localization algorithm based on improved multi-communication radius has higher localization accuracy.(3)Aiming at the problem that the existing localization algorithms have large localization errors in 3D Heterogeneous Wireless Sensor Networks(HWSN),a 3D HWSN localization algorithm based on improved max-similarity path is proposed.Firstly,the maximum similar path method is improved to address the problem of large error in the distance estimation stage.The average of the jump distances of the anchor nodes at both ends of the maximum similar path is used to calculate the jump distances of different parts from the original path.The cosine theorem is introduced to correct the fold distance to a straight line distance to improve the accuracy of distance estimation.Secondly,the potential region of unknown nodes is narrowed down using neighboring anchor nodes.Then the coordinates of the unknown nodes are quickly searched with IWFO,which improves the localization accuracy and localization speed.The experimental results show that the proposed localization algorithm has higher localization accuracy and localization speed compared with several other localization algorithms.