Research On Localization Algorithm In Wireless Sensor Networks Based On Multidimensional Scaling

As an emerging technology,wireless sensor networks are applied to various fields of society.Real-time acquisition of monitoring information and the demand for the geographic location of nodes support the rapid development of wireless sensor networks.In order to pursue the real-time and accuracy of node coordinate positions,various node positioning algorithms have been proposed.Multidimensional scaling positioning algorithm(MDS-MAP)is widely favored as a positioning algorithm with a wide range of applications and low cost.However,the positioning accuracy of MDS-MAP in the actual environment where the nodes are unevenly distributed and the network topology is irregular cannot meet the demand,and the algorithm performance is seriously degraded.Therefore,it is extremely important to propose an MDS positioning algorithm that has strong adaptability to the uneven distribution of nodes and irregular network topology.To this end,the work of this thesis mainly shows as follows:(1)Based on the theory,research on the theoretical knowledge of wireless sensor networks and node positioning technology;Supported by examples,introduced the practical application of MDS technology in positioning algorithms;Analyze the limitations and improvement directions of MDS-MAP based on numerous dissertations.(2)In order to solve the problem of uneven distribution of nodes in the Multidimensional Scaling positioning algorithm and large positioning errors in an environment with irregular network topology,Improved fast clustering-based multidimensional scaling(IFC-MDS)is proposed.In the stage of distance matrix construction,the algorithm uses the idea of combining Euclidean distance and heuristic algorithm to determine the distance between multi-hop nodes,and uses the density of nodes as a weighting factor to weight the distance.It effectively avoids the distance error caused by the shortest path algorithm,and improves the accuracy of the distance measurement value of multi-hop nodes.Simulation comparison experiments show that the algorithm effectively improves the positioning accuracy.(3)In order to further optimize the algorithm to improve the positioning accuracy,while improving the positioning progress while avoiding the algorithm from falling into convergence as soon as possible,an improved IFC-MDS algorithm(PSOCO-MDS)is proposed.In order to optimize the coordinate transformation parameters,the algorithm adds the particle swarm optimization algorithm(PSOCO)with crossover operation in the coordinate transformation stage of IFC-MDS.Simulation comparison experiments show that the positioning accuracy of the optimized PSOCO-MDS algorithm is better than that of IFC-MDS.