Efficient data management in wireless sensor networks using peer-to-peer techniques [Elektronische Ressource] = Effizientes Datenmanagement in drahtlosen Sensornetzen durch Peer-to-Peer-Methoden / vorgelegt von Abdalkarim Awad

Abdalkarim Awad

Sujets

• Informatik

Informations

• Publié par: friedrich-alexander-universitat_erlangen-nurnberg
• Publié le: 01 janvier 2009
• Nombre de lectures: 9
• Langue: English
• Poids de l'ouvrage: 5 Mo

Extrait

AbdalkarimAwad
Efficient Data Management in Wireless Sensor
Networks using Peer-to-Peer Techniques
DissertationimFachInformatik
Lehrstuhl für Informatik 7
Rechnernetze und Kommunikationssysteme
University of Erlangen ∙ Dept. of Computer Science 7
Martensstr. 3 ∙ 91058 Erlangen ∙ Germany
www7.informatik.uni-erlangen.deEfficient Data Management in Wireless Sensor
Networks using Peer-to-Peer Techniques
—
Effizientes Datenmanagement in drahtlosen
Sensornetzen durch Peer-to-Peer Methoden
Der Technischen Fakultät der
Universität Erlangen-Nürnberg
zur Erlangung des Grades
DOKTOR-INGENIEUR
vorgelegt von
Abdalkarim Awad
Erlangen, den 6. Juli 2009Als Dissertation genehmigt von
der Technischen Fakultät der
Universität Erlangen-Nürnberg
Tag der Einreichung: 6. Juli 2009
Tag der Promotion: 30. November 2009
Dekan: Prof. Dr.-Ing. Reinhard German
Berichterstatter: PD Dr.-Ing. Falko Dressler
Prof. Dr.-Ing. Wolfgang Schröder-PreikschatI dedicate this work to my mother, to my wife
and
to my sons Isaac, Adam and EliasAcknowledgments
I’m indebted to many individuals who helped me during my doctoral studies. With-
out them, this dissertation would not have come into existence!
Firstly, I would like to express my appreciation to Prof. Reinhard German for giving
me the opportunity to pursue my post graduate studies in the Computer Networks and
Communication Systems group. I benefited tremendously from his wise counsel and
indispensable advice. Thanks for continuous encouragement, support, and insightful
comments. You have been a great supervisor.
Words cannot express my gratitude to Dr. Falko Dressler, the coordinator of our
research group, for his patience and guidance. He has been infinitely patient and
extremely supportive. I am blessed to have had him as my adviser. My first instinct
in writing this was to say that Falko has been so much more than just an advisor. On
second thought, an advisor is exactly what Falko has been -an incredible one- fulfilling
each of the many roles required of an advisor to perfection. Falko is an outstanding
teacher and a source of inspiration for me.
I am grateful to the other members of my thesis committee, especially to Prof.
Wolfgang Schröder-Preikschat for his effort and the time he invested in supporting my
research work.
I would also like to express my cordial thanks my fellow postgraduate students,
Christoph Sommer, Isabel Dietrich and Tobias Limmer. They provided me constant
encouragement and invaluable suggestions on my research, especially during the writing
phase of my PhD thesis. I would like also to thank Ulrich Klehmet and Armin Heindl.
Appreciation is also extended to all the staff members in the Computer Networks
and Communication Systems group, for their efforts in providing a friendly research
environment. Special grateful thanks go to the active secretaries of the department
Erika Hladky and Gerti Pastore for their willingness to help in any situation. Of course,
I cannot forget Chris Moog for her help in developing electronic boards.
Particular acknowledgment is due to DAAD (German Academic Exchange Service)
for the financial support during the study period in Germany.Abstract
The data-centric nature of Wireless Sensor Networks (WSNs) and the severe resource
constraints of the sensor nodes distinguish sensor data management from other commu-
nication networks. Both the client-server approach as well as the end-to-end communi-
cation principle that have been proposed in the for Mobile Ad Hoc Networks (MANETs)
do not suit the characteristics of WSNs. Efficient lookup and routing of sensor data are
of great significance for WSNs, especially as the size of these networks continues to
grow. On an abstract level, structured peer-to-peer protocols, which rely on Distributed
Hash Tables (DHTs) provide O(1) complexity for storing and retrieving data in the net-
work, seem overcome these restrictions. However, the fact that they rely on underlayer
routing techniques leads to inefficient resource usage in the context of sensor networks.
The combination of DHTs and underlayer routing led to the establishment of so called
virtual coordinate routing techniques. Most of these algorithms are quite complicated
and do not guarantee packet delivery on the shortest path. Additionally, only few of
them are implemented in real sensor nodes. In this dissertation, we present the Virtual
Cord Protocol (VCP), a virtual position based routing protocol that also provides means
for data management such as identifying, storing, and retrieving data items. The key
contributions of this protocol are independence of real location information by relying
on virtual relative positions of neighboring nodes, the simplicity of obtaining the virtual
positions, near optimal routing paths, and high scalability because only information
about direct neighbors is needed for routing. Furthermore, VCP provides a unique
position for each node and inherently prevents dead-ends. We extensively evaluated
VCP in a number of simulation experiments. The simulation results show that VCP
consistently provides high throughput and low overhead for a wide range of application
scenarios. We compared VCP with Dynamic MANET on Demand (DYMO), a typical
MANET protocol, and with Virtual Ring Routing (VRR), another virtual coordinate
viiviii Abstract
based approach. In static networks, both VCP and VRR clearly outperform DYMO. In
the case of frequent node failures, however, VCP benefits from its light-weight design.
Our protocol is more failure tolerant compared to VRR. We finally integrated data
replication techniques that support high success rates even in very unreliable sensor
networks. A prototype implementation on real sensor nodes outlines the feasibility of
our approach in a proof-of-concept study.