This document summarizes a dissertation defense on multi-hop ad hoc networking and applications like MANET and VANET. The dissertation studied challenges in general multi-hop networks, proposed a new vehicular network architecture using mobility prediction, and conducted experiments comparing real networks to simulations. It explored routing protocols, cross-layer interactions, and applications like streaming video over multi-hop wireless networks. Future work is outlined on system design, algorithm analysis, and wireless resource scheduling for vehicular networks.

1. A Comprehensive Study on
Multi-hop Ad hoc Networking and Applications:
MANET and VANET
Joarder Mohammad Mustafa Kamal
M.Res. Dissertation Defence
Staffordshire University
September 16, 2010

2. Introduction
• Multi-hopping with relay nodes • Decentralised coordination
• Network resource sharing • Infrastructure less
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3. Research Challenges
• General-purpose multi-hop ad hoc network
• Scalability and Interoperability
• Mobility and Internet – Applications and Scenarios
• Transport layer protocols – TCP/UDP enhancements
• Wireless PHY and MAC enhancements
• Suitable routing protocols
• Cross-layer protocol interactions
• Power and bandwidth consumption
Realism of reality
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4. Aim and Objectives
• Aim
• Real-life implementation and experimentations of Multi-hop
Ad hoc Network and its variations
• Develop a new ITS/WAVE network architecture based on
mobility prediction utilising the vehicular ad hoc networking
• Objectives
• Real-life Experimentations Vs. Simulation – Real MANET
• Propose guidelines for realistic simulation and analysis
• Explore and in-detail analysis of VANET/ITS/WAVE architecture
and realistic simulations – mobility models, routing, etc.
• Integration of VANET/WAVE and Mobility Data Mining – case
studies, simulations, mathematical analysis
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5. Multi-hop Ad hoc Networks
B
• Mobile Ad hoc Network
169.254.216.93
A D (MANET) – truly dynamic
169.254.172.66 C 169.254.93.156
169.254.74.133
OBU
OBU
• Vehicular Ad hoc OBU
Network (VANET) –
OBU
fixed/semi-fixed OBU OBU
patterns OBU
OBU
OBU (On-board Unit), RSU (Road-side Unit)
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6. Real Experiment Vs. Simulation: Topology
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7. Real Experiment Vs. Simulation: Cases
Case Scenario Source  Network Protocol Used Experiment/
Destination Experiment Simulation Simulation Time
in sec.
Case-1 Scenario-1 A-D ICMP CBR over UDP 300
Case-2 Scenario-2 A-D ICMP CBR over UDP 120
Case-3 Scenario-3 A-D ICMP CBR over UDP 120
Case-4 Scenario-4 A-D ICMP CBR over UDP 120
Case-5 Scenario-1 A-B, C, D HTTP over TCP FTP over TCP 180
Case-6 Scenario-1 A-D HTTP over TCP FTP over TCP 300
• Open field experiment using Olsrd in IEEE 802.11g network
• Simulation – ns-2/UM-OLSR
• 100 ICMP/CBR packets of 1500 bytes size, bidirectional
• Performance metrics – throughput, PDR, E2E delay, etc.
• Shadowing propagation with path-loss; β=2.3 and σdB=6.0 dB
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8. Case-1: String Topology with Static Nodes
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9. Case-2: String Topology with Roaming Node
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10. Case-3: String Topology with End Node Swap
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11. Case-4: Hybrid Topology
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12. Case-5: String Topology with No Restriction
• Streaming Video
from A to B, C, D
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13. Case-6: String Topology with Restriction
• Streaming Video
from A to D
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14. VANET Simulation – Non-rush Scenarios
• Street Map of Washington, DC, USA (TIGER/Line 2006)
• VanetMobiSim/ns-2, urban scenario, 20/210 vehicles, TCP/UDP
• IEEE 802.11a Vs. 802.11p with AODV/DSR; then AODV Vs. OLSR
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15. IEEE 802.11a Vs. 802.11p with AODV, DSR
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• 20 vehicles in a non-rush scenarios 15

16. AODV Vs. OLSR in IEEE 802.11p draft
• 5 different traffic
patterns are used
• Non-rush hour scenario
with 210 vehicles
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17. WAVE/ITS Simulation with NCTUns-6.0
• UK M42 Motorway J4, Active Traffic Management (ATM)
• No. of Vehicles: 1/2/4
• Agent Controlled 802.11p cars
• Ricean fading (β=2.8 and σdB=6.0dB)
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18. ITS Scenarios in IEEE 1609/WAVE
• Data Rate: 3Mbps
• Simulation: 115, 60 sec
• 1500 bytes UDP data
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19. Mobility Prediction-based ITS Network
Vehicular Information
Management (VIM) Systems
Mobility Data Mining
Vehicle’s
Current Mobility Mobile Internet
Information Office/Home
Networks
On-demand service After Market Solutions
from roadside service Providers
providers Predictive Mobility
OBU Information Safe Distance Notification
Adaptive Cruise Control
RSU
Onboard Navigation
RSU
Network Packet
OBU
Routing and
Forwarding Decision
Blind Spot Notifications
Lane Departure Warning
Cooperative Forward Collision Warning Speed Limit Warning RSU – Roadside Unit
Pedestrian Crossing Notification OBU – Onboard Unit
Emergency Road Work Warning

20. POGR – Specialise Case Scenarios
Scenario-1 Scenario-2
Greedy Packet Forwarding
based on predictive mobility
information
Opportunistic
DTN is an
Routing is required
emerging
while OBUs are out
technology for
of the direct
future
communication
ubiquitous
range of any RSU
mobile
and need V2V
computing and
communication
communication
Scenario-3
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21. POGR: ns-2 Model for Specific Case Analysis
Centralised VIM and Prediction-based Opportunistic Greedy Routing
W(0) (POGR)
DM Engine
- Mobility Data Mining
- Mobility Prediction
RSU Gateway - Mobility Pattern Analysis
W(1)
POGR Case Analysis
• Greedy Forwarding
RSU(1) RSU(2)
• Opportunistic Routing
• Delay Tolerant Networking (DTN)
Car-C
Car-B
Car-D
Car-A

22. POGR Scenarios: AODV Vs. OLSR
ns-2 Simulation Model
• IEEE 802.11p MAC and PHY
• 5.8GHz Band with 20MHz channel
• 3Mbps data rate
• Mobile IP enabled OBU
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23. POGR – Mathematical Modelling
Time Space
NIP
ϬTi Time, t1 Time, t2 Time, t1 Time, t2
Time, t1
S I D
δt
I D
ϕ(distTSI, distGSI)δt
distTSI
• The value of time required to receive a data packet from node S to D through intermediate
node I for ith time over a time period [t1, t2] can be written as,
• ϕ(X, Y)δt is the cumulative change function of variable X and Y over a time of δt
• For nth time the above equation can be written as below,
• Number of time intervals required to know the predictive trajectory may be calculated as
• GLU is the frequency in time required for the on-board positioning system to update location
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24. Conclusion
• Summary of Contributions:
• Multi-hop ad hoc networking – real-life experimentations
provide appropriate guidelines and lessons learned to design
realistic simulation models
• VANET/WAVE – Mobility Data Mining Net. Architecture –
provide a new approach in ITS utilising prediction on vehicular
mobility - POGR routing algorithm
• Applications – Streaming audio/video over multi-hop wireless
mesh network (wireless video surveillance system), Internet
resource sharing and intelligent on-board navigation and
communication medium for vehicles
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25. Future Works
System design and basic building block for software architecture Roadside Units
Correctness and complexity analysis of POGR algorithm (RSU)
On-board Unit Router V2V and I2V
(OBU) Planner High Rate
Cooperative Communication
Location and Information
V2V
Mobility Exchange
Medium Rate
Information Multi-hop Communication
Wireless Vehicular Ad hoc I2V
On-board Communication Networking Low Rate
Sensors Interface Communication
Vehicle
Control
Mechanics Wireless channel
On-board Visualisation allocation and
for Information, application request
Warnings and scheduling based on
Notifications timing priority

26. Selective Reference
• Marco Conti, JC, Andrea Passarella (ed.) 2007, Multi-hop Ad Hoc Networks from
Theory to Reality, Nova Science Publishers, Inc., New York.
• C. Siva Ram Murthy, BSM 2004, Ad Hoc Wireless Networks Architectures and
Protocols, Prentice Hall.
• Hannes Hartenstein, KPL (ed.) 2010, VANET Vehicular Applicaitons and Inter-
Networking Technologies, John Wiley and Sons, Ltd, Publication.
• Stephan Olariu, MCW (ed.) 2009, Vehicular Networks From Theory to Practice, CRC
Press.
• Mobility, Data Mining and Privacy - Geographic Knowledge Discovery 2008,
Springer.
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27. Research Team
Joarder Dr. Mohammad Dr. Alison L Prof. Hongnian Yu,
Mohammad Shahidul Hasan, Carrington, Third Supervisor
Mustafa Kamal, First Supervisor Second Supervisor
Research Student
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28. Thank You
Questions?
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