Machine learning based delay tolerant protocols for underwater acoustic wireless sensor networks

116 Pages·2017·1.04 MB·English

Machine Learning Based Delay Tolerant
Protocols for Underwater Acoustic
Wireless Sensor Networks
Lin Zou
School of Electrical, Electronic and Computer Engineering
The University of Western Australia
This thesis is presented for the degree of
Doctor of Philosophy
September 2014

Declaration
This is to certify that:
• the thesis contains no material that has been accepted for the
award of any other degree or diploma in any university or other
tertiary institution and, to the best of my knowledge and belief,
contains no material previously published written by another
person, except where due reference has been made in the text,
• the thesis comprises only my original work towards the PhD,
• due acknowledgement has been made in the text to all other
material used,
• thethesisislessthan100,000wordsinlength, exclusiveoftables,
maps, bibliographies and appendices,
• I give consent to this copy of the thesis, when deposited in the
University Library, being available for loan, photocopying and
dissemination through the library digital thesis collection.
Lin Zou, September 2014
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Acknowledgements
First and foremost, I would like to sincerely express my gratitude to
my supervisors, Dr. David (Defeng) Huang and Dr. Roberto Togneri,
for their support during the course of my studies. Without their
enthusiasm, dedication, and confidence in me, this work would have
been impossible. For the past few years, they has put great effort into
helping me find direction and have assisted me in conducting this
research. I have often benefited from their knowledge and experience
in both my research and life. Thanks Dr. Huang and Dr. Togneri for
offering me such a rewarding experience during the course of my PhD
studies.
Also, many thanks to my colleagues in the research group SPWCL at
theUniversityofWesternAustraliafortheirinsightfuldiscussionsand
social activities. I would especially like to express my appreciation to
Prof. Angela (Yingjun) Zhang and her group members at the Chinese
University of Hong Kong (CUHK). It was a great pleasure to have an
opportunity to work with them at CUHK as a visiting scholar. Their
insights, discussions and generous help have led me to my fruitful
research. I would also like to thank my parents and my husband for
their understanding, support and most of all, their love over the past
years.
Finally, I also gratefully acknowledge my host institution, the School
of Electrical, Electronic and Computer Engineering at the University
of Western Australia, and the Endeavor Scholarship Office for their
financial and administrative support during my term.
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Publications
BOOK CHAPTER
• L. Jin, D. Huang, Y.J. Zhang and L. Zou, “Cognitive acous-
tics: a way to extend the lifetime of underwater acoustic sensor
networks,” in Cognitive Communications: Distributed Artificial
Intelligence (DAI), Regulatory Policy & Economics. John Wiley
& Sons, 2012.
CONFERENCE
• L. Zou, D. Huang, R. Togneri, “A Neural-Q-Learning Based Ap-
proach for Delay Tolerant Underwater Acoustic Wireless Sensor
Networks”, Proceedings of CCSCI2014, January 2014, Toronto,
Canada, accepted October 2013.
• L. Zou, D. Huang, R. Togneri, “A Q-Learning Based Approach
for Delay Tolerant Underwater Acoustic Wireless Sensor Net-
works”, Proceedings of APWCS2013, August 2013, Seoul, Ko-
rea, accepted June 2013.
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I would like to dedicate this thesis to my loving parents ...
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