Research On The Optimal Localization Algorithms Of Nodes Of WSNs In Three-dimensional Space

Wireless sensor network (WSN) as a hot research field that is emerging, frontier and multidisciplinary has already had and will continue to have a profound impact on human life. Compared to the common communication network, WSN is widely used in the areas of military, environment, health, family and industry and so on. Among the supporting technologies in WSNs, the nodes localization is of great importance and, needs particular studies.This thesis mainly discusses the optimal localization of nodes in WSNs based on the distance-measurement technique in three-dimensional space. The nodes localization is an optimization problem in essence, therefore, intelligent optimization strategies such as simulated-annealing algorithm and genetic algorithm are naturally introduced to achieve more accurate information of the nodes distribution. In order to confirm the effectiveness of these intelligent localization algorithms that are simulated annealing localization (SA-L) and genetic algorithm localization (GA-L), the maximum likelihood algorithm (ML) is chosen as a contrast in the numerical simulation.Choosing the positioning accuracy and computing time as evaluation standards of excellent algorithms, three algorithms are compared under the circumstances of different distance-measurement errors, different beacon nodes density, and different nodes amount. It shows that the positioning accuracy of SA-L and GA-L algorithms is higher than that of ML algorithm for all given distance-measurement errors. The larger the distance-measure error is, the more remarkable will the advantage of the intelligent algorithms have. It also suggests that under different beacon nodes density, both SA-L and GA-L algorithms can provide higher positioning accuracy than ML algorithm. And what is more, the effect of the beacon nodes density to the positioning accuracy for SA-L and GA-L algorithms is non-significant. Therefore, the two algorithms make it possible to gain higher positioning accuracy with lower cost by distributing only a few beacon nodes in WSNs. Superior adaptability is shared by all the algorithms. The GA-L algorithm gets the highest positioning accuracy but takes the longest time to compute, while the SA-L algorithm not only achieves good positioning accuracy, but also spends less computing time.In conclusion, the application of SA-L and GA-L algorithms about nodes localization of WSNs in three-dimensional space can effectively reduce positioning error and get higher positioning accuracy and better positioning performances. The GA-L algorithm has the highest positioning accuracy, however, when considering the positioning accuracy and the computing time of the algorithm at the same time, the SA-L algorithm is more suitable.