Multiple mobile beacon set moving path planning method based on network density clustering of wireless sensor network

Abstract

The invention relates to a multiple mobile beacon set moving 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 three mobile beacon nodes. 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 mobile beacons is planned; the local path of the mobile beacons is planned; the mobile beacons move 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, 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 packet, 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, and in particular relates to a mobile path planning method for multiple mobile beacon groups in a wireless sensor network 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 suppo...

AI Technical Summary

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 problems of collinear beacon positions, long beacon moving paths and network positioning time.

[0011] (2) Most of the path planning methods assume that the network is evenly deployed. When the network is not evenly deployed, if the mobile beacon traverses the entire network according to the static mobile beacon path planning method, it will not only cause the beacon moving path and network positioning time to be too long. long, and greatly reduces the utilization of beacons

[0012] (3) Most path planning methods only use a single mobile beacon, which saves network costs but increases the positioning time of the entire network, which is limited in practical applications

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