Study of 3D Wireless Sensor Network Based on Overlap Method

• Main Author: Wu Mingxin
• Format: Article
• Language: English
• Published: IFSA Publishing, S.L. 2013-11-01
• Series: Sensors & Transducers
• Subjects: Wireless sensor network; 3D; Algorithm; Nodes.
• Online Access: http://www.sensorsportal.com/HTML/DIGEST/november_2013/PDF_vol_159/P_RP_0026.pdf

Wireless sensor network as a new information acquisition technology has profound impact on people's work and life style, has the very high research value. Energy issues important factor restricting the development of the deep WSN is node, sensor nodes for processing data collected information and communication between nodes will speed up the energy consumption of nodes. Cover the deployment strategy is directly related to the optimal distribution of target area monitoring the degree of perception and limited resources of wireless sensor network, determines the service quality of the wireless sensor network to improve the. How to design an efficient coverage algorithm directly affects the coverage and network lifetime, because the actual environment of 3D wireless sensor network is more close to people, so the 3D WSN. Covering research has more realistic significance. At present, about the research of wireless sensor network many 3D covering literature, according to the general configuration of nodes is divided into deterministic coverage and random covering two aspects. This paper presents a wireless sensor network node for 3D scene coverage model and its deployment method, based on analyzing the common regular polyhedron models used in 3D space coverage, proposed a model based on covering the structure, on the basis of this theory to derive a quantitative relationship between coverage model and node sensing radius, more based on the quantitative relationship between the further calculation of network area remains fully covering the minimum number of nodes are required, the network regional 3D mesh finite mesh node coverage model in accordance with the deployment.