Title: Maximisation of the number of β-view covered targets in visual sensor networks

Authors: Ling Guo; Deying Li; Yongcai Wang; Zhao Zhang; Guangmo Tong; Weili Wu; Dingzhu Du

Addresses: School of Information Science and Technology, Northwest University, Xi'an, 710127, China ' School of Information, Renmin University of China, Beijing, 100872, China ' School of Information, Renmin University of China, Beijing, 100872, China ' College of Mathematics Physics and Information Engineering, Zhejiang Normal University, Zhejiang, 321004, China ' Department of Computer Science, University of Texas at Dallas, TX, 75080, USA ' Department of Computer Science, University of Texas at Dallas, TX, 75080, USA ' Department of Computer Science, University of Texas at Dallas, TX, 75080, USA

Abstract: In some applications using visual sensor networks (VSNs), the facing directions of targets are bounded. Therefore existing full-view coverage (all the facing directions of a target constitutes a disk) is not necessary. We propose a novel model called β-view coverage model through which only necessary facing directions of a target are effectively viewed. This model uses much fewer cameras than those used by full-view coverage model. Based on β-view coverage model, a new problem called β-view covered target maximisation (BVCTM) problem is proposed to maximise the number of β-view covered targets given some fixed and freely rotatable camera sensors. We prove its NP-hardness and transform it into an Integer Linear Programming problem equivalently. Besides, a (1 - e^-1)-factor approximate algorithm and a camera-utility based greedy algorithm are given for this problem. Finally, we conduct many experiments and investigate the influence of many parameters on these two algorithms.

Keywords: VSNs; visual sensor networks; target coverage; β view coverage.

DOI: 10.1504/IJSNET.2019.098557

International Journal of Sensor Networks, 2019 Vol.29 No.4, pp.226 - 241

Received: 17 Apr 2018
Accepted: 18 Sep 2018
Published online: 27 Mar 2019 *

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