Routing, Localization And Positioning Protocols For Wireless Sensor And Actor Networks

299 Pages·2016·6.26 MB·English

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Electronic Theses and Dissertations, 2004-2019
2013
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Mustafa Akbas
University of Central Florida
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Routing, Localization and Positioning Protocols for
Wireless Sensor and Actor Networks
by
˙
Mustafa Ilhan Akba¸s
B.S. Electrical and Electronics Engineering, Middle East Technical University, 2003
M.S. Electrical and Electronics Engineering, Middle East Technical University, 2006
A dissertation submitted in partial fulfillment of the requirements
for the degree of Doctor of Philosophy
in the Department of Electrical Engineering and Computer Science
in the College of Engineering and Computer Science
at the University of Central Florida
Orlando, Florida
Fall Term
2013
Major Professor:
Damla Turgut
c 2013 by Mustafa I˙lhan Akba¸s
(cid:13)
ii
ABSTRACT
Wireless sensor and actor networks (WSANs) are distributed systems of sensor nodes and
actors that are interconnected over the wireless medium. Sensor nodes collect information
about the physical world and transmit the data to actors by using one-hop or multi-hop
communications. Actors collect information from the sensor nodes, process the information,
take decisions and react to the events.
This dissertation presents contributions to the methods of routing, localization and po-
sitioning in WSANs for practical applications. We first propose a routing protocol with
service differentiation for WSANs with stationary nodes. In this setting, we also adapt a
sports ranking algorithm to dynamically prioritize the events in the environment depending
on the collected data. We extend this routing protocol for an application, in which sensor
nodes float in a river to gather observations and actors are deployed at accessible points on
the coastline. We develop a method with locally acting adaptive overlay network formation
toorganizethenetworkwithactorareasandtocollectdatabyusinglocality-preservingcom-
munication. We also present a multi-hop localization approach for enriching the information
collected from the river with the estimated locations of mobile sensor nodes without using
positioning adapters. As an extension to this application, we model the movements of sen-
sor nodes by a subsurface meandering current mobility model with random surface motion.
Then we adapt the introduced routing and network organization methods to model a com-
plete primate monitoring system. A novel spatial cut-off preferential attachment model and
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center of mass concept are developed according to the characteristics of the primate groups.
We also present a role determination algorithm for primates, which uses the collection of
spatial-temporal relationships. We apply a similar approach to human social networks to
tackle the problem of automatic generation and organization of social networks by analyzing
and assessing interaction data. The introduced routing and localization protocols in this dis-
sertation are also extended with a novel three dimensional actor positioning strategy inspired
by the molecular geometry. Extensive simulations are conducted in OPNET simulation tool
for the performance evaluation of the proposed protocols.
iv
ACKNOWLEDGMENTS
I would like to thank OPNET Technologies Inc. for supporting my research by providing
OPNET Modeler software under OPNET University Program.
I would like to thank my advisor, Dr. Damla Turgut who provided me the vision to pro-
ceed and gave me the freedom to explore through every step of my Ph.D study. I appreciate
Dr. Michael Georgiopoulos, Dr. Mostafa A. Bassiouni, Dr. Ladislau B¨olo¨ni and Dr. Yue
Zhao for serving as members of my dissertation committee. Their suggestions and advices
have helped me immensely to improve my research. I would like to thank Dr. Matthias R.
Brust for creating time to meet me face-to-face or online whenever I needed.
My sincere thanks go to my mentor at my first job, Semih Gu¨l, and my M.S. advisor Dr.
Cu¨neyt Bazlama¸cı, both of whom encouraged me to pursue a Ph.D. I owe an appreciation
to my friends Onur Gu¨lc¸at, Serta¸c Cinel, Do˘ga Somer and Dr. Do˘ga Gu¨rsoy, who have been
the sources of laughter and support for over twenty years and never let me feel alone.
I thank my fellow labmates, Drs. Swastik Brahma, Yi Luo, Wenjing Wang and Gu¨rkan
Solmaz for their assistance and support over the years. I was lucky to meet Dr. Zubair
Ahmad as my first labmate. I have had his support both in research and in daily life
¨
throughoutmyPh.D.IwouldliketothankDr. Tongu¸cOztek, FıratS¸eker, AtillaCing¨ozand
Dr. Mustafa Gu¨l for helping me in any sorts of issues ranging from my scientific questions to
fixing my car. Special thanks to my long lost sister Melike Minareci, positive energy booster
Henriette Schoen and the best cook in Orlando, Dr. Maria Bull.
v
I am forever grateful to my parents, Songu¨l and Hilmi Akba¸s, who always provide unflag-
ging support. It wouldn’t be even possible to start and continue this work without feeling
their endless love. My older brother, Dr. Sami Og˘uzhan Akba¸s, has been an inspiring ex-
ample in my life; I thank him, my sister-in-law Selvet Duygu and my nephew, Batuhan. I
˙
also want to thank my family-in-law Isfendiyar, Arzu and Esin S¨oyler for their support and
the joy they brought into my life.
I feel fortunate to have the chance for opening a new chapter of my life in Orlando.
I not only worked with great people, but also met my wonderful wife, Aslı S¨oyler Akba¸s.
Her encouragement, patience, love and ingenious ideas have been my invaluable resources to
finish this work. I can only “promise her anything” to express my gratitude.
Finally, this dissertation is dedicated to my grandmother, Hatice Akba¸s, whom I lost
during the time of my Ph.D study.
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TABLE OF CONTENTS
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxiii
CHAPTER 1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Wireless sensor and actor networks . . . . . . . . . . . . . . . . . . . . . . . 2
1.2 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4 Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
CHAPTER 2 RELATED WORK . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1 Network organization and routing . . . . . . . . . . . . . . . . . . . . . . . 12
2.2 Localization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.3 Animal monitoring with WSANs . . . . . . . . . . . . . . . . . . . . . . . . 21
2.4 Node positioning in aerial networks . . . . . . . . . . . . . . . . . . . . . . . 25
CHAPTER 3 LIGTHWEIGHT ROUTING WITH DYNAMIC INTERESTS . . . . 30
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3.1 Network organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.1.1 Actor areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.1.2 Communication backbone . . . . . . . . . . . . . . . . . . . . . . . . 33
3.2 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.2.1 Interest subscription . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.2.2 Ranking interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.2.3 Data transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.3 Simulation study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.3.1 Simulation environment . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.3.2 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
CHAPTER 4 SELF ORGANIZED ROUTING . . . . . . . . . . . . . . . . . . . . . 64
4.1 System model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.1.1 Sensor nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.1.2 Actors and the sink . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
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4.2 Self-organized and fair routing protocol . . . . . . . . . . . . . . . . . . . . 69
4.2.1 Network organization . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.2.2 Data transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.2.3 Illustration of SOFROP . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.3 Simulation study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.3.1 Simulation environment and metrics . . . . . . . . . . . . . . . . . . 86
4.3.2 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
CHAPTER 5 MULTI HOP LOCALIZATION . . . . . . . . . . . . . . . . . . . . . 96
5.1 Network organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.1.1 Network layout . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.1.2 Weight assignment for nodes . . . . . . . . . . . . . . . . . . . . . . 100
5.1.3 Adapting k . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
5.1.4 Mobility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
5.2 Localization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
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