| Wireless Sensor Network(WSN) are currently used to monitor a wide range of military,environmental,civil,and health-care applications.Finding the location of the sensor where the event occurred is an intrinsic and integral part of any WSN application and represents a major challenge because without finding the position of the sensor that is reporting the sensed data,the latter will not be useful.This requires the positioning mechanism and algorithm and obtain the location of the nodes in wireless sensor network.In order to overcome the low accuracy and high energy consumption of localization algorithm based on distance in Wireless Sensor Network as the main target, a Particle Swarm Optimization Localization Algorithm based on Neighboring Degree (PNDLA) was proposed. A built-in routing algorithm which alleviates the sensors from the overhead incurred in establishing routes to the base station can also be tailored to route the node ID and distance information in the form of packets to the base station. Base station used MDS-MAP algorithm to calculate node coordinates.Defined a target function and if node coordinates didn’t meet the constraint violation, upgraded node with modified particle swarm optimization algorithm.The main content of this paper is as follows:First of all, the concept, main characteristics of wireless sensor network and the structure of the system were described.The necessity of node localization and important significance were introduced. Some classical localization algorithm in detail the principle, classification methods, steps and performance were elaborated.Secondly, range-free localization algorithm was influenced by computational complexity, high energy consumption and low accuracy of positioning.According to the characteristics of neighborhood distribution model, a range-free localization algorithm based on adjacent degree is put forward.The algorithm selected the best beacon nodes to participate in orientation and calculated the distance based on the distribution of nodes.Then error correction of beacon node is done. The distance information was transmitted to the base station.Therefore; base stations use the MDS-MAP algorithm to determine the coordinates of the node.Again, in this paper, the traditional particle swarm optimization (PSO) algorithm was modified.It is used to optimize the node positioning error.Moreover introducing the filter parameters, part of particle which deviated from the optimal solution will be released after iteration. Preserved to the particle path optimization.This methods not only sped up the convergence rate, but also improved the positioning accuracy.Finally, simulations were conducted on NS-2 platform.Change the parameters which the algorithm was involved, observe and analysis the result of the experiment.The performance of the proposed approach was evaluated and compared to other peer algorithms.Draw the conclusion:Results show that significant enhancement is obtained with the proposed algorithm in terms of node distance estimation error and position error. |
