Abstract
At present, range-free localization algorithm is the mainstream of node localization method, which has made tremendous achievements. However, there are few algorithms that can be used in concave regions, and the existing algorithms have defects such as hop distance error, excessive time complexity and so on. To solve these problems, this paper proposes a two-stage PSO (Particle Swarm Optimization) algorithm for wireless sensor nodes localization in “concave regions”. In the first stage, it proposes a method of distance measuring based on similar path search and intersection ratio, and completes the initial localization of unknown nodes based on maximum likelihood estimation. In the second stage, the improved PSO algorithm is used to optimize the initial localization results in the previous stage. The experimental result shows that the localization error of this algorithm is always within 10% and the execution time is maintained at about 20 s when the communication radius and beacon node ratio is changing. Therefore, the algorithm can obtain high localization accuracy in wireless sensor network with “concave regions”, requiring low computing power for nodes, and energy consumption. Given this, it can greatly extend the service life of sensor nodes.
Highlights
In Formula (35), T represents the times of experiments, (x, y) is the actual coordinate of node u, the estimated coordinate is, communication radius is R, the total amount of sensor nodes is NAmount, the amount of beacon nodes is BAmount
A concave boundary was randomly generated within the square communication region which with the area of 40,000 square meters, so that the communication region became a concave region, 100 nodes were randomly deployed in the communication area to simulate various sensor networks by changing communication radius and proportion of beacon nodes in the WSN
For the problem of the nodes localization algorithm in the concave area, this paper studied the deficiencies of various concave area localization algorithms based on beacon node selection, communication area division, shortest distance correction, etc
Summary
The WSN (Wireless Sensor Network) is a distributed sensor network, and its tip is a sensor node that can perceive physical, chemical, behavioral, and biological information in the external environment. The nodes in WSN communicate through wireless, so the deployment of the network is simple, the setting is flexible, and it can be connected to the Internet through wireless [1]. When the sensor node in WSN is working, it sends the physical, chemical, behavioral, and biological information collected from the environment to the gathering node, the gathering node transmits it to the internet or terminal computer. In actual application, it is useful only when the information collected by sensor nodes is combined with the coordinates
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
