1. NAME: VINAY DWIVEDI Roll no.:
11EC65R12
VISUAL INFORMATION PROCESSING AND
EMBEDDED SYSTEMS
IIT KHARAGPUR

2. • Motivation
• Introduction
• Proposed Scenarios
• Data dissemination approaches and tradeoffs
• Challenges
• Conclusion
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3. Imagine traveling on a highway with traffic jam miles ahead…
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4. • Imagine driving to a new city and you want to find the best
parking lot
Millions wastage on gasoline
Hours of waiting time
• No real-time information provided
• e.g. current occupancy
Use a Parking Map!
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5. • Desirable system properties
• Data collection and distribution in a local environment
• Low information delivery latency
• Cheap deployment and communication
• Probable solutions
• Cellular ? Service fees
• Satellite ? High latency
• Vehicular Networks ?
• What is a vehicular network?
• Vehicles are equipped with sensing, computing and wireless devices
• Vehicles talk to road-side infrastructure (V2I) and other vehicles (V2V)
• Has all the desirable properties
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6. • Vehicular network is a subset of MANET (Mobile Ad-hoc
Network) where mobile nodes are wireless technology
equipped vehicles.
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7. Forward radar
Computing platform
Event data recorder (EDR)
Positioning system
Rear radar
Communication
facility
Display
(GPS)
Human-Machine Interface
A modern vehicle is a network of sensors/actuators on wheels !
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8. Content
Downloading
P2P
Advertising
Sensing the
environment
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9. • Involves peer-to-peer content distribution
• Files are shared using Bit-Torrent style.
• Hence the name CAR-Torrent is used.
• Parallel Downloading scheme is used.
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12. P2P location significant
advertising
 Access Points are not always available.
 Multihop downloading is having practical
limitations.
 Thus, Randomly selected “ad Segments” are used.
 The segments are epidemically disseminated.
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14. VAN can act as important sensor platform.
Vehicles can generate much larger volume of data
compared to traditional sensor system.
This scheme is called “Mob-Eyes”.
The data can be harvested for key problems of
forensic studies.
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16. Vehicular networks need to handle large
amounts of data (emergency messages,
videos etc)
How do we efficiently disseminate this
information?
• Characteristics
• High mobility
• Dynamic topology
• Receivers are a priori unknown
• Large scale
• High density
• Low penetration ratio
• Challenges
• Maintaining routing
tables is difficult
• Scalability
• Dealing with partitions
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17. • V2I / I2V dissemination
• Push based
• Pull based
• V2V dissemination
• Flooding
• Relaying
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18. • Infostation pushes out the data to everyone
• Applications: Traffic alerts, Weather alerts
• Why is this useful?
• Good for popular data
• No cross traffic  Low contention
• Drawback
• Everyone might not be interested in the same data
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19. • Request – Response model
• Applications: Email, Webpage requests
• Why is this useful?
• For unpopular / user-specific data
• Drawback
• Lots of cross traffic  Contention, Interference, Collisions
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20. • Basic Idea
• Broadcast generated and received data to neighbors
• Usually everyone participates in dissemination
• Advantages
• “Good” for delay sensitive applications
• Suitable for sparse networks
• Key Challenges
• How to avoid broadcast storm problem?
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21. • Basic Idea
• Instead of flooding the network, select a relay (next hop)
• Relay node forwards the data to next hop and so on
• Advantages
• Reduced contention  Scalable for dense networks
• Key Challenges
• How to select the relay neighbors?
• How to ensure reliability?
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22. • Not much literature on V2I / I2V communication
• How to deal with cross-traffic in the pull scheme
• Scheduling transmissions?
• How to combine push and pull ? What is hybrid ?
• Mobility traces for evaluation of dissemination
• Real traces are expensive to collect
• Not enough data points for simulation
• Need to extrapolate
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23. Vehicular network promises a huge advancement in
the field of mobile network.
For researchers it opens door of very nice domain.
As big organizations are funding these researches
progress will be pretty fast.
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24. References
[1] Mario Gerla , Leonard Kleinrock, Vehicular networks and the future of the
mobile internet, Elsevier, Computer Networks 55 (2011) 457–469.
[2] M. Motani, V. Srinivasan, P. Nuggehalli, PeopleNet: Engineering a
wireless virtual social network, in: ACM MobiCom’05, Cologne,
Germany, August–September 2005
[3] M. Conti, E. Gregori, G. Turi, A cross-layer optimization of gnutella for
mobile ad hoc networks, in: ACM MobiHoc, Urbana-Champaign, IL,
USA, 2005.
[4]A. Capone, M. Cesana, S. Napoli, A. Pollastro, MobiMESH: a complete
solution for wireless mesh networking, in: IEEE MASS’07, Pisa, Italy,
October 2007
[5]Pei-Chun Cheng, Jui-Ting Weng, Lung-Chih Tung, Kevin C. Lee, Mario
Gerla, Jerome Haerri, GeoDTN+Nav: a hybrid geographic and DTN
routing with navigation assistance in urban vehicular networks, in:
MobiQuitous/ISVCS 2008, Trinity College Dublin, Ireland, July 2008.
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