The University of Southampton
University of Southampton Institutional Repository

Validating an integer non-linear program optimization model of a wireless sensor network using agent-based simulation

Validating an integer non-linear program optimization model of a wireless sensor network using agent-based simulation
Validating an integer non-linear program optimization model of a wireless sensor network using agent-based simulation
Deploying wireless sensor networks (WSN) along a barrier line to provide surveillance against illegal intruders is a fundamental sensor-allocation problem. To maximize the detection probability of intruders with a limited number of sensors, we propose an integer non-linear program optimization model which considers multiple types of sensors and targets, probabilistic detection functions and sensor-reliability issues. An agent-based simulation (ABS) model is used to validate the analytic results and evaluate the performance of the WSN under more realistic conditions, such as intruders moving along random paths. Our experiment shows that the results from the optimization model are consistent with the results from the ABS model. This increases our confidence in the ABS model and allows us to conduct a further experiment using moving intruders, which is more realistic, but it is challenging to find an analytic solution. This experiment shows the complementary benefits of using optimization and ABS models.
1340-1351
Institute of Electrical and Electronics Engineers Inc.
Karatas, Mumtaz
93a4833f-3dd8-4539-acac-807f065d1a50
Onggo, Bhakti Satyabuhdi Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Karatas, Mumtaz
93a4833f-3dd8-4539-acac-807f065d1a50
Onggo, Bhakti Satyabuhdi Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80

Karatas, Mumtaz and Onggo, Bhakti Satyabuhdi Stephan (2016) Validating an integer non-linear program optimization model of a wireless sensor network using agent-based simulation. In 2016 Winter Simulation Conference (WSC). Institute of Electrical and Electronics Engineers Inc. pp. 1340-1351 . (doi:10.1109/WSC.2016.7822188).

Record type: Conference or Workshop Item (Paper)

Abstract

Deploying wireless sensor networks (WSN) along a barrier line to provide surveillance against illegal intruders is a fundamental sensor-allocation problem. To maximize the detection probability of intruders with a limited number of sensors, we propose an integer non-linear program optimization model which considers multiple types of sensors and targets, probabilistic detection functions and sensor-reliability issues. An agent-based simulation (ABS) model is used to validate the analytic results and evaluate the performance of the WSN under more realistic conditions, such as intruders moving along random paths. Our experiment shows that the results from the optimization model are consistent with the results from the ABS model. This increases our confidence in the ABS model and allows us to conduct a further experiment using moving intruders, which is more realistic, but it is challenging to find an analytic solution. This experiment shows the complementary benefits of using optimization and ABS models.

Full text not available from this repository.

More information

Published date: 11 December 2016

Identifiers

Local EPrints ID: 425181
URI: https://eprints.soton.ac.uk/id/eprint/425181
PURE UUID: 6d84770b-fbd1-41fb-96c9-75026eb439c5
ORCID for Bhakti Satyabuhdi Stephan Onggo: ORCID iD orcid.org/0000-0001-5899-304X

Catalogue record

Date deposited: 11 Oct 2018 16:30
Last modified: 10 Dec 2019 01:22

Export record

Altmetrics

Contributors

Author: Mumtaz Karatas

University divisions

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.

×