Research of localization algorithm based on weighted Voronoi diagrams for wireless sensor network

Abstract

Wireless sensor network (WSN) is formed by a large number of cheap sensors, which are communicated by an ad hoc wireless network to collect information of sensed objects of a certain area. The acquired information is useful only when the locations of sensors and objects are known. Therefore, localization is one of the most important technologies of WSN. In this paper, weighted Voronoi diagram-based localization scheme (W-VBLS) is proposed to extend Voronoi diagram-based localization scheme (VBLS). In this scheme, firstly, a node estimates the distances according to the strength of its received signal strength indicator (RSSI) from neighbor beacons and divides three beacons into groups, whose distances are similar. Secondly, by a triangle, formed by the node and two beacons of a group, a weighted bisector can be calculated out. Thirdly, an estimated position of the node with the biggest RSSI value as weight can be calculated out by three bisectors of the same group. Finally, the position of the node is calculated out by the weighted average of all estimated positions. The simulation shows that compared with centroid and VBLS, W-VBLS has higher positioning accuracy and lower computation complexity.

A node localization algorithm based on Voronoi diagram and support vector machine for wireless sensor networks

“…To locate in a more fine-grained environment, this article uses the combination of Voronoi diagram and SVM to locate, which can further improve the positioning accuracy under the condition of relatively low energy consumption and complexity. Finally, compared with the localization algorithm proposed by Zixiao et al 32 and Cai et al, 33 the performance of the proposed VD-SVM algorithm is more excellent.…”

“…To verify the location method proposed in this article, we compare the performance with the two location algorithms in Zixiao et al 32 and Cai et al 33 In the performance verification, MATLAB 2015b is used for experimental simulation and the network size is set to 150 m 3 150 m 3 150 m. This section mainly carries on the performance verification analysis from three aspects, namely, the communication radius, the number of anchor nodes, and the total number of nodes. To ensure the accuracy of the experimental results, 100 groups of experiments were carried out to calculate the average value of the experimental results.…”

“…To ensure the accuracy of the experimental results, 100 groups of experiments were carried out to calculate the average value of the experimental results. In experimental verification, the proposed positioning algorithm is compared with two positioning algorithms ORSS-VBLS 32 and W-VBLS 33 to verify the performance of the proposed algorithm.…”

Range-free 3D node localization in anisotropic wireless sensor networks

“…Further, proposed RFHPSO and RFBBO methods are compared with range-based methods proposed in [9]. 16 M a n u s c r i p t Figure 16: RFHPSO-based distance between actual nodes and estimated nodes M a n u s c r i p t Figure 17: RFBBO-based distance between actual nodes and estimated nodes Range-free localization algorithms are cost effective but less accurate, a range-free localization algorithm needs to be develop in such a manner that it does not require costly RSS based techniques but can determine the node locations with high accuracy. A combination of range-based and range-free localization algorithms can be an effective solution for localization problems.…”

“…In [16], range-free weighted Voronoi diagram-based localization scheme (W-VBLS) is proposed to extend Voronoi diagram-based localization scheme (VBLS). In this scheme, RSSI technique is used to estimate distance from three similar distance neighbor.…”