Title: Path self-deployment algorithm of three-dimensional space in directional sensor networks

Authors: Li Tan; Chaoyu Yang; Minghua Yang; Xiaojiang Tang

Addresses: School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 10048, China ' School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 10048, China ' School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 10048, China ' School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 10048, China

Abstract: In contrast to the two-dimensional directional sensor networks, the three-dimensional directional sensor networks increase complexity and diversity. External environment and sensor limitations impact the target monitoring and coverage. Adjustment strategies provide better auxiliary guide in the process of self-deployment, while strengthening the monitoring area coverage rate and monitoring capability of sensor nodes. We propose a path self-deployment algorithm three-dimension path self-deployment algorithm (TPSA) based on above issues. The concept of virtual force extends from two-dimensional to three-dimensional, including target path control. The node gets locational information about monitoring target and target path in the initialisation, calculates the virtual force of them, finally obtains the next movement location and direction. We analyse the process of self-deployment of both static and polymorphic nodes. The simulation results verify that the proposed algorithm enables better node control in the deployment process and improves the efficiency of the sensor node deployment.

Keywords: directional sensor networks; path self-deployment; three-dimensional deployment; virtual force.

DOI: 10.1504/IJHPCN.2019.102125

International Journal of High Performance Computing and Networking, 2019 Vol.14 No.3, pp.257 - 264

Received: 06 Jun 2017
Accepted: 01 Nov 2017

Published online: 03 Sep 2019 *

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