This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/81111
Description
Title
Energy-Efficient Tracking in Sensor Networks
Author(s)
Fuemmeler, Jason Alan
Issue Date
2008
Doctoral Committee Chair(s)
Venugopal Veeravalli
Department of Study
Electrical and Computer Engineering
Discipline
Electrical and Computer Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
Abstract
We consider the problem of tracking one or more objects in an energy-efficient manner using a sensor network. The sensors in this network can enter an asleep mode where they conserve energy but are unable to help track the objects. We consider two assumptions for how the sleeping actions of the sensors are controlled. The first is to assume that sensors cannot be woken up externally but instead must set internal timers that determine when they will next come awake. The second is to assume that an arbitrary set of sensors can be woken up at each time step. Within each of these assumptions, the goal is to choose sleeping policies for the sensors that result in an optimal tradeoff between energy efficiency and tracking performance. We formulate this design problem using various assumptions for the number of objects, the object movement, the observations made by the sensors, and the measure of tracking performance. Even in the simplest cases we are unable to find optimal solutions to our design problems. However, we design suboptimal solutions and then characterize their performance. In many cases, we are able to demonstrate that our suboptimal policies are near optimal. In other cases, we demonstrate that our policies significantly outperform simple policies that do not make use of information about the object location. We also characterize the asymptotic performance of our suboptimal policies as the size of the network grows large.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.