The University of Southampton
University of Southampton Institutional Repository

Optimising the barrier coverage of a wireless sensor network with hub-and-spoke topology using mathematical and simulation models

Optimising the barrier coverage of a wireless sensor network with hub-and-spoke topology using mathematical and simulation models
Optimising the barrier coverage of a wireless sensor network with hub-and-spoke topology using mathematical and simulation models
Deploying wireless sensor networks (WSNs) to form a barrier that provides surveillance against illegal intruders (or targets) is a fundamental sensor-allocation problem. In this paper, we consider a WSN barrier coverage problem with hub-and-spoke topology in which communication hubs form central hubs that are connected to sensors via spokes. We develop and compare three models. The first two are mathematical models: an Integer Non-Linear Program (INLP) and an Integer Linear Program (ILP). The third is an Optimisation-via-Simulation (OvS) model, which comprises agent-based simulation and heuristics. We consider the following factors in the models: multiple sensor and target types, probabilistic detection function, sensor reliability, communication range, communication interference, network topology and budget constraints. The experiment shows that the INLP solutions are close to ILP global optimum solutions. The ILP model is only practical for a small problem, while the INLP and OvS models can cope with bigger ones. OvS can handle more realistic assumptions more easily, such as intelligent targets that can move freely across the barrier, and the movement speed depends on the path taken. To solve this using ILP, we need to reformulate the ILP model but it is very challenging. Hence, our contributions are twofold: (1) our models are more elaborate than other models in the literature and (2) this is the first work that demonstrates how OvS is used to solve a barrier coverage problem and demonstrates its benefit of handling more realistic assumptions.
0305-0548
36-48
Karatas, Mumtaz
93a4833f-3dd8-4539-acac-807f065d1a50
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Karatas, Mumtaz
93a4833f-3dd8-4539-acac-807f065d1a50
Onggo, Bhakti Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80

Karatas, Mumtaz and Onggo, Bhakti Stephan (2019) Optimising the barrier coverage of a wireless sensor network with hub-and-spoke topology using mathematical and simulation models. Computers & Operations Research, 106, 36-48. (doi:10.1016/j.cor.2019.02.007).

Record type: Article

Abstract

Deploying wireless sensor networks (WSNs) to form a barrier that provides surveillance against illegal intruders (or targets) is a fundamental sensor-allocation problem. In this paper, we consider a WSN barrier coverage problem with hub-and-spoke topology in which communication hubs form central hubs that are connected to sensors via spokes. We develop and compare three models. The first two are mathematical models: an Integer Non-Linear Program (INLP) and an Integer Linear Program (ILP). The third is an Optimisation-via-Simulation (OvS) model, which comprises agent-based simulation and heuristics. We consider the following factors in the models: multiple sensor and target types, probabilistic detection function, sensor reliability, communication range, communication interference, network topology and budget constraints. The experiment shows that the INLP solutions are close to ILP global optimum solutions. The ILP model is only practical for a small problem, while the INLP and OvS models can cope with bigger ones. OvS can handle more realistic assumptions more easily, such as intelligent targets that can move freely across the barrier, and the movement speed depends on the path taken. To solve this using ILP, we need to reformulate the ILP model but it is very challenging. Hence, our contributions are twofold: (1) our models are more elaborate than other models in the literature and (2) this is the first work that demonstrates how OvS is used to solve a barrier coverage problem and demonstrates its benefit of handling more realistic assumptions.

Text
COR_article_accepted_version - Accepted Manuscript
Restricted to Repository staff only until 15 September 2020.
Request a copy

More information

Accepted/In Press date: 14 February 2019
e-pub ahead of print date: 15 February 2019
Published date: 1 June 2019

Identifiers

Local EPrints ID: 428376
URI: https://eprints.soton.ac.uk/id/eprint/428376
ISSN: 0305-0548
PURE UUID: 947f22d2-b64a-4d9f-a5c3-7a7bd46885b4
ORCID for Bhakti Stephan Onggo: ORCID iD orcid.org/0000-0001-5899-304X

Catalogue record

Date deposited: 22 Feb 2019 17:30
Last modified: 20 Jul 2019 00:21

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×