Download the full-sized PDF
Permanent link (DOI): https://doi.org/10.7939/R34D20
This file is in the following communities:
|Graduate Studies and Research, Faculty of|
This file is in the following collections:
|Theses and Dissertations|
Location-based routing and indoor location estimation in mobile ad hoc networks Open Access
- Other title
Routing, location-based routing, indoor localization, ad hoc and sensor networks
- Type of item
- Degree grantor
University of Alberta
- Author or creator
Haque, Israat Tanzeena
- Supervisor and department
- Examining committee member and department
Department of Computing Science
- Date accepted
- Graduation date
Doctor of Philosophy
- Degree level
In Mobile Ad Hoc NETworks (MANETs) autonomous nodes act both as traffic originators
and forwarders to form a multi-hop network.
Out-of-range nodes are reachable through a process called routing,
which is a challenging task due to the constraints of bandwidth and battery power.
Stateless location-based routing schemes have been proposed to avoid complex route
discovery and maintenance, whereby nodes make routing decisions based solely
on the knowledge of their location, the location of their neighbors, and the location of the destination.
Natural routing schemes based on these prerequisites suffer from problems like local maxima or loops.
We mitigate those problems by proposing randomized routing algorithms,
which outperform others in terms of the packet delivery ratio and throughput.
The prerequisite for location-based routing is knowing the location of a node.
Location information is more widely useful anyway for
location-aware applications like security, health care, robotics, navigation etc.
Locating a node indoors remains a challenging problem due to the unavailability of GPS signals under the roof.
For this goal we choose the RSS (Received Signal Strength)
as the relevant attribute of the signal due to its minimal requirements on the RF technology
of the requisite modules. Then profiling based localization is considered that does not
rely on any channel model (range-based) or the connectivity information (range-free),
but rather exploits the context of a node to infer that information into the estimation.
We propose a RSS profiling based indoor localization system, dubbed LEMON,
based on low-cost low-power wireless devices that offers better accuracy than other RSS-based schemes.
We then propose a simple RSS scaling trick to further improve the accuracy of LEMON.
Furthermore, we study the effect of the node orientation, the number and the arrangement
of the infrastructure nodes and the profiled samples, leading us to further
insights about what can be effective node placement and profiling.
We also consider alternate formulations of the localization problem,
as a Bayesian network model as well as formulated in a combinatorial fashion.
Then performance of different localization methods is compared and again LEMON ensures better accuracy.
An effective room localization algorithm is developed, and both single and multiple
channels are used to test its performance. Furthermore, a set of two-step localization
algorithms is designed to make the LEMON robust in the presence of noisy RSS and faulty device behavior.
- License granted by Israat Tanzeena Haque (firstname.lastname@example.org) on 2011-03-29T21:27:04Z (GMT): Permission is hereby granted to the University of
Alberta Libraries to reproduce single copies of
this thesis and to lend or sell such copies for
private, scholarly or scientific research purposes
only. Where the thesis is converted to, or
otherwise made available in digital form, the
University of Alberta will advise potential users
of the thesis of the above terms.
The author reserves all other publication and
other rights in association with the copyright in
the thesis, and except as herein provided, neither
the thesis nor any substantial portion thereof may
be printed or otherwise reproduced in any material
form whatsoever without the author's prior written
- Citation for previous publication
- Date Uploaded
- Date Modified
- Audit Status
- Audits have not yet been run on this file.
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 1245935
Last modified: 2015:10:12 12:04:31-06:00
Original checksum: 08e18c8fc12bcfc482c2b168b8b38398
Well formed: true
Status message: Improperly formed date offset=1230076
File title: reliable-peg.eps
File author: Israat Tanzeena Haque
Page count: 145