Research Of Node Localization Algorithm Based On Classification Of Unknown Node In WSN

With the development of technology, wireless sensor networks which are integrated with wireless communication technology and embedded technology and sensor technology begin to be widely used. Localization technology of nodes is playing an increasingly important role as one of the most important technologies in wireless sensor networks. Many traditional localization algorithms study the localization of the unknown nodes in an ideal environment. However, because of the random distribution of wireless sensor nodes, sensor nodes are prone to be uneven distribution which has a great affect on localization accuracy. Improving localization accuracy under uneven distribution of sensor nodes is an important research direction in wireless sensor networks, In this paper, classification of unknown node is studied to take different localization information.Classification of unknown nodes is classifying the unknown nodes according to different available localization information, when wireless sensor networks have network cavity, this paper classifies unknown nodes into unknown nodes with sufficient localization information and unknown nodes around the cavity and unknown nodes in the wireless sensor network with sparse anchor nodes and normal unknown nodes. Completing localization of unknown nodes with different localization information based on the characteristics of different unknown node. The simulation results validate its effectiveness.In order to improve the adaptability of the algorithm, this paper combines mobile anchor nodes and boundary anchor nodes and local anchor nodes. Network cavity makes some unknown nodes lose the ability of getting enough localization information. To solve this problem, this paper proposes a filling method with mobile anchor nodes. Getting network cavity information with search algorithm of network cavity and supplying localization information according to filling model with mobile anchor nodes. The algorithm finds out boundary anchor nodes and the local anchor nodes with position information and hops of anchor nodes, and gives two kinds of anchor nodes different weights for different situations. To reduce the influence of network cavity to localization of unknown nodes, combining boundary anchor nodes and local anchor nodes. The simulation results testify that the use of three kinds of anchor nodes improves the localization performance of algorithm.