Node self-positioning is one of the supporting technologies for wireless sensor network applications. In this paper, a clustering localizationalgorithm is proposed for large-scale high-density wireless sensor network...
详细信息
Node self-positioning is one of the supporting technologies for wireless sensor network applications. In this paper, a clustering localizationalgorithm is proposed for large-scale high-density wireless sensor networks. Firstly, the potential of the node is defined as the basis for the election of the cluster head. The distance between the nodes in the network is calculated indirectly by the relationship between the received signal strength and the communication radius. The topology information in each cluster is saved by the cluster head, and the linear programming method is used in the cluster head to implement the cluster internal relative positioning. Then, from the sink node, the inter-cluster location fusion is gradually implemented, and finally the absolute positioning of the whole network is realized. Compared with the centralized convex programming algorithm, the proposed algorithm has low computational complexity, small traffic, high positioning accuracy, and does not need to know the signal attenuation factor in the environment in advance, and there is anti-noise ability.
Node self-localization is one of the important research topics in WSN. APIT is a major range-free localizationalgorithm. Compared with other range-free algorithms, APIT can achieve more high precision position estima...
详细信息
ISBN:
(纸本)9781424421138
Node self-localization is one of the important research topics in WSN. APIT is a major range-free localizationalgorithm. Compared with other range-free algorithms, APIT can achieve more high precision position estimation with small communication cost However, APIT requires high anchor node density. Besides, in the process of APIT test, it is easy to increase InToOut error and OutToIn error. In allusion to these flaws, based on APIT, this paper expands the definition of neighbor node and import neighbor legality inspection and proposes an improved APIT node self-localization algorithm in WSN. Simulation results show that the improvements to A-PIT test can reduce the IntoOut error and OutToIn error effectively, and improve the precision of position estimation.
Node self-localization is one of the important research topics in WSN. APIT is a major range-free localizationalgorithm. Compared with other range-free algorithms, APIT can achieve more high precision position estima...
详细信息
Node self-localization is one of the important research topics in WSN. APIT is a major range-free localizationalgorithm. Compared with other range-free algorithms, APIT can achieve more high precision position estimation with small communication cost. However, APIT requires high anchor node density. Besides, in the process of APIT test, it is easy to increase InToOut error and OutToIn error. In allusion to these flaws, based on APIT, this paper expands the definition of neighbor node and import neighbor legality inspection and proposes an improved APIT node self-localization algorithm in WSN. Simulation results show that the improvements to APIT test can reduce the IntoOut error and OutToIn error effectively, and improve the precision of position estimation.
One Center-Three Benchmark (OCTB) is different from other localizationalgorithms. There is a high-power center node in the WSN, which can cover with the whole networks. In addition, there are three anchor nodes act a...
详细信息
ISBN:
(纸本)9781424412198
One Center-Three Benchmark (OCTB) is different from other localizationalgorithms. There is a high-power center node in the WSN, which can cover with the whole networks. In addition, there are three anchor nodes act as benchmarks. All free nodes may compute the distance to the center node according to the RSSI of the center node. At the same time, they compute the distance to their neighbors. The information of distance and neighbors is transmitted to the Base-station, where the coordinate position of all free nodes will be figured out. The algorithm improves the precision of free nodes' position and reduces demanding of nodes distributing density (connectivity) greatly, but also, saves traffic and power. The cost of hardware is hardly increased.
暂无评论