A Novel Heterogeneous Wireless Sensor Node Deployment Algorithm with Parameter-Free Configuration

• Main Authors: Rungrote Kuawattanaphan, Paskorn Champrasert, Somrawee Aramkul
• Format: Journal
• Published: 2018
• Subjects: Computer Science; Engineering; Materials Science
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051635814&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/58481
• Institution: Chiang Mai University

OAPA The deployment of wireless sensor nodes affects the WSN performance such as the sensing coverage, the connectivity between sensor nodes, and the network lifetime. The deployment is much more complicated when sensor nodes are heterogeneous and there are some environmental obstacles in an area of interest. The deployment of heterogeneous sensor nodes in an area of interest with obstacles is a challenging problem and also proven to be an NP-Complete problem. This paper proposes and evaluates a wireless sensor node deployment algorithm, called DeVForce-AP. The proposed algorithm combines the benefits of the two well-known deployment algorithms, Delaunay triangulation method (D) and extended virtual force algorithm (eVForce), with the adaptive parameter tuning mechanism (AP). The DeVForce-AP attempts to improve the sensing coverage and network lifetime of the heterogeneous wireless sensor node. The practical deployment problems such as the environmental obstacles, the network connectivity, and the sensing coverage area have also been addressed. The DeVForce-AP consists of two steps. In the first step, the DeVForce-AP applies Delaunay triangulation method to find and eliminate the largest coverage hole in the area of interest. In the second step, the DeVForce-AP applies extended virtual force algorithm method to avoid the existence of environmental obstacles and maintain the network connectivity. Moreover, the proposed DeVForce-AP automatically adjusts its parameters to the environmental scenario. Thus, there is no need to configure parameters of the DeVForce-AP. The simulation results show that the proposed DeVForce-AP outperforms the random deployment, the traditional Delaunay triangulation deployment, and the traditional virtual force deployment methods.