The University of Southampton
University of Southampton Institutional Repository

Using an energy aware adaptive scheduling algorithm to increase sensor network lifetime

Using an energy aware adaptive scheduling algorithm to increase sensor network lifetime
Using an energy aware adaptive scheduling algorithm to increase sensor network lifetime
Sensor network research is an area which has experienced rapid growth in the last decade. One area in which it is proving particularly popular is that of environmental monitoring. Areas which have benefited from environmental monitoring include; volcanoes, crops, wildlife and, the test bed used for this thesis: glaciers. One of the main challenges faced by these networks is that of power management. This becomes even more important when energy harvesting techniques are used, as the availability of energy cannot be reliably predicted.

In order to address this issue, an algorithm has been developed which allows a sensor node to adapt its schedule based on the available energy. This is achieved by using the average battery voltage to approximate energy reserves, then scaling the scheduled sensing tasks accordingly. This algorithm has been designed to work with differential GPS sensors which require multiple nodes to record in synchronisation. This means that a co-ordination system has been implemented to allow synchronisation between multiple
systems with no direct communication methods.

This thesis makes three main contributions to sensor network research: the development of a flexible platform for gateway nodes, the development and analysis of an energy aware adaptive scheduling algorithm, and algorithms for the use of alternate communication links to provide resilience in communications. Each of these contributions has been tested in Iceland as part of a real deployment to asses how they actually perform. During this deployment it has been possible to gather more data about the Skalafellsjokull glacier than has previously been achievable.
University of Southampton
Basford, Philip James
efd8fbec-4a5f-4914-bf29-885b7f4677a7
Basford, Philip James
efd8fbec-4a5f-4914-bf29-885b7f4677a7
Martinez, Kirk
5f711898-20fc-410e-a007-837d8c57cb18

Basford, Philip James (2015) Using an energy aware adaptive scheduling algorithm to increase sensor network lifetime. University of Southampton, Physical Sciences and Engineering, Doctoral Thesis, 186pp.

Record type: Thesis (Doctoral)

Abstract

Sensor network research is an area which has experienced rapid growth in the last decade. One area in which it is proving particularly popular is that of environmental monitoring. Areas which have benefited from environmental monitoring include; volcanoes, crops, wildlife and, the test bed used for this thesis: glaciers. One of the main challenges faced by these networks is that of power management. This becomes even more important when energy harvesting techniques are used, as the availability of energy cannot be reliably predicted.

In order to address this issue, an algorithm has been developed which allows a sensor node to adapt its schedule based on the available energy. This is achieved by using the average battery voltage to approximate energy reserves, then scaling the scheduled sensing tasks accordingly. This algorithm has been designed to work with differential GPS sensors which require multiple nodes to record in synchronisation. This means that a co-ordination system has been implemented to allow synchronisation between multiple
systems with no direct communication methods.

This thesis makes three main contributions to sensor network research: the development of a flexible platform for gateway nodes, the development and analysis of an energy aware adaptive scheduling algorithm, and algorithms for the use of alternate communication links to provide resilience in communications. Each of these contributions has been tested in Iceland as part of a real deployment to asses how they actually perform. During this deployment it has been possible to gather more data about the Skalafellsjokull glacier than has previously been achievable.

PDF __soton.ac.uk_ude_personalfiles_users_jo1d13_mydesktop_Basford.pdf - Version of Record
Available under License University of Southampton Thesis Licence.
Download (19MB)

More information

Published date: February 2015
Organisations: University of Southampton, Web & Internet Science

Identifiers

Local EPrints ID: 375503
URI: https://eprints.soton.ac.uk/id/eprint/375503
PURE UUID: 559732d5-80af-486a-90a9-d884f4438138
ORCID for Philip James Basford: ORCID iD orcid.org/0000-0001-6058-8270
ORCID for Kirk Martinez: ORCID iD orcid.org/0000-0003-3859-5700

Catalogue record

Date deposited: 22 Apr 2015 10:43
Last modified: 06 Jun 2018 13:01

Export record

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.

×