Distributed multitarget probabilistic coverage control algorithm for wireless sensor networks
type: Item
instance of: scholarly article
title: Distributed multitarget probabilistic coverage control algorithm for wireless sensor networks
zbMATH Open document ID: 1407.93377
DOI: 10.1155/2014/421753
author: Ying Tian
author: Yang Ou
author: Hamid Reza Karimi
author: Yan Tao Liu
author: Jian-qun Han
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: This paper is concerned with the problem of multitarget coverage based on probabilistic detection model. Coverage configuration is an effective method to alleviate the energy-limitation problem of sensors. Firstly, considering the attenuation of node's sensing ability, the target probabilistic coverage problem is defined and formalized, which is based on Neyman-Peason probabilistic detection model. Secondly, in order to turn off redundant sensors, a simplified judging rule is derived, which makes the probabilistic coverage judgment execute on each node locally. Thirdly, a distributed node schedule scheme is proposed for implementing the distributed algorithm. Simulation results show that this algorithm is robust to the change of network size, and when compared with the physical coverage algorithm, it can effectively minimize the number of active sensors, which guarantees all the targets \(\gamma\)-covered.
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 93C55
Mathematics Subject Classification ID: 68M10
zbMATH DE Number: 7016407
Wikidata QID: Q59067025
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/421753
OpenAlex ID: W2030783887
cites work: Data-driven monitoring for stochastic systems and its application on batch process
description: scientific article; zbMATH DE number 7016407