Mobile beacon path planning method based on network density clustering of wireless sensor network

A wireless sensor and mobile beacon technology, applied in wireless communication, network topology, electrical components, etc., can solve the problems of collinear beacon position, lower beacon utilization, long beacon moving path and network positioning time, etc., to achieve Improve positioning rate and positioning accuracy, improve beacon utilization, and reduce costs

Active Publication Date: 2014-11-05
HOHAI UNIV CHANGZHOU
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Problems solved by technology

Among the three methods, Scan has the shortest movement path, and the mobile beacon moves along the y-axis direction, but its linear movement path will cause unknown nodes to receive several collinear mobile beacon beacon signals, especially when the beacon communication The radius is too small, causing many unknown nodes to fail to locate
[0010] (1) Most of the existing research mainly stays in the path planning of static mobile beacons. This path planning method has the

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  • Mobile beacon path planning method based on network density clustering of wireless sensor network
  • Mobile beacon path planning method based on network density clustering of wireless sensor network
  • Mobile beacon path planning method based on network density clustering of wireless sensor network

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[0106] n=2, that is, when the number of hops in the cluster is 2, the network clustering result is as follows image 3 shown. After determining the location of the cluster head, the mobile beacon performs global path planning to determine the sequence of traversing the cluster heads, and traverses a in a clockwise direction when traversing each cluster 1 = 0.27R and a 2 =0.54R of the regular hexagon, that is, the side length of the regular hexagon increases by 0.27R. Among the six vertices of the regular hexagon, choose the direction of the vertex closest to the center of the next regular hexagon as the exit, and move to the next cluster head. This step continues until the mobile beacon has traversed all the cluster heads, as in Figure 4 shown.

[0107] The unknown node continuously monitors and receives beacon information, and uses the received signal strength indicator (RSSI) to measure the distance between mobile beacons, namely where P R (d) represents the received ...

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Abstract

The invention relates to a mobile beacon path planning method based on network density clustering of a wireless sensor network. The network comprises a plurality of static unknown nodes which are not evenly deployed and one mobile beacon node. The method includes the steps that network clustering is performed based on an DBCSAN; the positions of cluster heads are estimated; the overall path of a mobile beacon is planned; the local path of the mobile beacon is planned; the mobile beacon moves along the planned path at a constant speed v, a beacon data packet is broadcast every other time interval with the current position as a circle center and R as a communication radius when each cluster is traversed, and each beacon data packet comprises the position of the mobile beacon at the moment and the beacon; the unknown nodes are used for continuously monitoring and receiving the beacon data packets, and the positions of the unknown nodes are calculated through a three-side measurement method; positioned nodes are upgraded into static beacons to assist in positioning the remaining unknown nodes. The method is high in positioning accuracy and beacon utilization rate, the beacon moving path is short, and communication expenditure is small.

Description

technical field [0001] The invention belongs to the field of wireless sensor networks, in particular to a wireless sensor network mobile beacon path planning method based on network density clustering. Background technique [0002] In recent years, with the development of wireless communication and digital electronic technology, Wireless Sensor Networks (WSNs) have been favored by government departments, industry, academia and scientific research all over the world due to their highly interdisciplinary nature and broad application prospects. The research on it has become one of the most challenging topics in the current IT field, and its application scenarios include environmental monitoring, biomedicine, industrial automation control, smart home and many other fields. Location information is of vital significance to the application of WSNs. Effective and reliable positioning technology and its optimization method are the key supporting technologies that must be overcome for...

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Application Information

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IPC IPC(8): H04W40/02H04W84/18
Inventor 张晨语韩光洁朱川江旭江金芳王峰鲍娜
Owner HOHAI UNIV CHANGZHOU
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