Communication and Content sharing in the Urban Vehicle Grid Qualnet World Oct 27, 2006 Washington, D

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Communication and Content sharing in the Urban
Vehicle GridQualnet WorldOct 27,
2006Washington, DC

• Mario Gerla
• www.cs.ucla.edu/NRL

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Outline

• New vehicle roles in urban environments
• Opportunistic Ad Hoc Wireless Networks
• V2V applications
• Car Torrent
• MobEyes
• Network layer optimization
• Network Coding
• Conclusions

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New Roles for Vehicles on the road

• Vehicle as a producer of geo-referenced data
  about its environment
• Pavement condition
• Weather data
• Physiological condition of passengers, .
• Vehicle as Information Gateway
• Internet access, infotainment, P2P content
  sharing,
• Vehicle collaborates with other Vehicles and
  with Roadway
• Forward Collision Warning, Intersection Collision
  Warning.
• Ice on bridge,
• These roles demand efficient communications

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The urban wireless options

• Cellular telephony
• 2G (GSM, CDMA), 2.5G, 3G
• Wireless LAN (IEEE 802.11) access
• WiFI, Mesh Nets, WIMAX
• Ad hoc wireless nets (manly based on 802.11)
• Set up in an area with no infrastructure to
  respond to a specific, time limited need

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Wireless Infrastructure vs Ad Hoc
Infrastructure Network (WiFI or 3G)
Ad Hoc, Multihop wireless Network
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Ad Hoc Network Characteristics

• Instantly deployable, re-configurable (No fixed
  infrastructure)
• Created to satisfy a temporary need
• Portable (eg sensors), mobile (eg, cars)

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Traditional Ad Hoc Network Applications

• Military
• Automated battlefield
• Civilian
• Disaster Recovery (flood, fire, earthquakes etc)
• Law enforcement (crowd control)
• Homeland defense
• Search and rescue in remote areas
• Environment monitoring (sensors)
• Space/planet exploration

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New Trend Opportunistic ad hoc nets

• Driven by commercial application needs
• Indoor W-LAN extended coverage
• Group of friends sharing 3G via Bluetooth
• Peer 2 peer networking in the vehicle grid
• Access to Internet
• available, but it can be opportunistically
  replaced by the ad hoc network (if too costly
  or inadequate)

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Urban opportunistic ad hoc networking
From Wireless to Wired network Via Multihop
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Car to Car communications for Safe Driving
Vehicle type Cadillac XLRCurb weight 3,547
lbsSpeed 65 mphAcceleration -
5m/sec2Coefficient of friction .65Driver
Attention YesEtc.
Vehicle type Cadillac XLRCurb weight 3,547
lbsSpeed 75 mphAcceleration
20m/sec2Coefficient of friction .65Driver
Attention YesEtc.
Alert Status None
Alert Status None
Alert Status Inattentive Driver on Right
Alert Status Slowing vehicle ahead
Alert Status Passing vehicle on left
Vehicle type Cadillac XLRCurb weight 3,547
lbsSpeed 45 mphAcceleration -
20m/sec2Coefficient of friction .65Driver
Attention NoEtc.
Vehicle type Cadillac XLRCurb weight 3,547
lbsSpeed 75 mphAcceleration
10m/sec2Coefficient of friction .65Driver
Attention YesEtc.
Alert Status Passing Vehicle on left
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The Standard DSRC / IEEE 802.11p

• Car-Car communications at 5.9Ghz
• Derived from 802.11a
• three types of channels Vehicle-Vehicle service,
  a Vehicle-Gateway service and a control broadcast
  channel .
• Ad hoc mode and infrastructure mode
• 802.11p IEEE Task Group for Car-Car
  communications

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DSRC Channel Characteristics
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CarTorrent Opportunistic Ad Hoc networking to
download large multimedia files

• Alok Nandan, Shirshanka Das
• Giovanni Pau, Mario Gerla
• WONS 2005

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You are driving to VegasYou hear of this new
show on the radioVideo preview on the web
(10MB)

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One option Highway Infostation download
Internet
file
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Incentive for opportunistic ad hoc networking

• Problems
• Stopping at gas station for full download is a
  nuisance
• Downloading from GPRS/3G too slow
  and quite expensive
• Observation many other drivers are interested in
  download sharing (like in the Internet)
• Solution Co-operative P2P Downloading via
  Car-Torrent

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CarTorrent Basic Idea
Internet
Download a piece
Outside Range of Gateway
Transferring Piece of File from Gateway
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Co-operative Download Car Torrent
Internet
Vehicle-Vehicle Communication
Exchanging Pieces of File Later
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BitTorrent Internet P2P file downloading
Uploader/downloader
Uploader/downloader
Uploader/downloader
Tracker
Uploader/downloader
Uploader/downloader
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CarTorrent Gossip protocol
A Gossip message containing Torrent ID, Chunk
list and Timestamp is propagated by each peer
Problem how to select the peer for downloading
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Selection Strategy Critical
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CarTorrent with Network Coding

• Limitations of Car Torrent
• Piece selection critical
• Frequent failures due to loss, path breaks
• New Approach network coding
• Mix and encode the packet contents at
  intermediate nodes
• Random mixing (with arbitrary weights) will do
  the job!

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Random Linear Network Coding
e e1 e2 e3 e4 encoding vector tells how
packet was mixed (e.g. coded packet p ?eixi
where xi is original packet)
buffer
Receiver recovers original by matrix inversion
random mixing
Intermediate nodes
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CodeTorrent Basic Idea

• Single-hop pulling (instead of CarTorrent
  multihop)

Internet
Re-Encoding Random Linear Comb.of Encoded
Blocks in the Buffer
Outside Range of AP
Exchange Re-Encoded Blocks
Downloading Coded Blocks from AP
Meeting Other Vehicles with Coded Blocks
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Simulation Results

• Histogram of Number of completions per slot (Slot
  20sec)

200 nodes40 popularity
Time (seconds)
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Vehicular Sensor Network (VSN)IEEE Wiress
Communications 2006Uichin Lee, Eugenio
Magistretti (UCLA)
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Vehicular Sensor Applications

• Environment
• Traffic congestion monitoring
• Urban pollution monitoring
• Civic and Homeland security
• Forensic accident or crime site investigations
• Terrorist alerts

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Accident Scenario storage and retrieval

• Designated Cars
• Continuously collect images on the street (store
  data locally)
• Process the data and detect an event
• Classify event as Meta-data (Type, Option,
  Location, Time,Vehicle ID)
• Post it on distributed index
• Police retrieve data from designated cars

Meta-data Img, -. Time, (10,10), V10
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How to retrieve the data?

• Epidemic diffusion
• Mobile nodes periodically broadcast meta-data of
  events to their neighbors
• A mobile agent (the police) queries nodes and
  harvests events
• Data dropped when stale and/or geographically
  irrelevant

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Epidemic Diffusion - Idea Mobility-Assist
Meta-Data Diffusion
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Epidemic Diffusion - Idea Mobility-Assist
Meta-Data Diffusion
1) periodically Relay (Broadcast) its
Event to Neighbors 2) Listen and store
others relayed events into ones storage
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Epidemic Diffusion - Idea Mobility-Assist
Meta-Data Harvesting

• Agent (Police) harvestsMeta-Data from its
  neighbors
• Nodes return all the meta-datathey have
  collected so far

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VSN Mobility-Assist Meta-Data Harvesting (cont)

• Model Assumption
• N disseminating nodes each node ni advertises
  event ei
• k-hop relaying (relay an event to k-hop
  neighbors)
• v average speed, R communication range
• ? network density of disseminating nodes
• Discrete time analysis (time step ?t)
• Metrics
• Average event percolation delay
• Average delay until all relevant data is harvested

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Simulation Experiment

• Simulation Setup
• NS-2 simulator
• 802.11 11Mbps, 250m tx range
• Average speed 10 m/s
• Mobility Models
• Random waypoint (RWP)
• Real-track model (RT)
• Group mobility model
• merge and split at intersections
• Westwood map

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Meta-data harvesting delay with RWP

• Higher mobility decreases harvesting delay

Police
Private cars
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Harvesting Results with Real Track

• Restricted mobility results in larger delay

Police
Private cars
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U-Ve TUcla - Vehicular Testbed

• E. Giordano, A. Ghosh,
• G. Marfia, S. Ho, J.S. Park, PhD
• System Design Giovanni Pau, PhD
• Advisor Mario Gerla, PhD

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Project Goals

• Provide
• A platform to support car-to-car experiments in
  various traffic conditions and mobility patterns
• Remote access to U-VeT through web interface
• Extendible to 1000s of vehicles through WHYNET
  emulator
• potential integration in the GENI
  infrastructure
• Allow
• Collection of mobility traces and network
  statistics
• Experiments on a real vehicular network

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Big Picture

• We plan to install our node equipment in
• 50 Campus operated vehicles (including shuttles
  and facility management trucks).
• Exploit on a schedule and random campus fleet
  mobility patterns
• 50 Communing Vans
• Measure freeway motion patterns (only tracking
  equipment installed in this fleet).
• Hybrid cross campus connectivity using 10 WLAN
  Access Points .

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Related Car to Car Projects

• UMassDiesel (UMass)
• A Bus-based Disruption Tolerant Network (DTN)
• http//signl.cs.umass.edu/diesel
• VEDAS (UMBC)
• A Mobile and Distributed Data Stream Mining
  System for Real-Time Vehicle Monitoring and
  diagnostics
• http//www.cs.umbc.edu/hillol/vedas.html
• CarTel (MIT)
• Vehicular Sensor Network for traffic conditions
  and car performance
• http//cartel.csail.mit.edu
• RecognizingCars (UCSD)
• License Plate, Make, and Model Recognition
• Video based car surveillance
• http//vision.ucsd.edu/car_rec.html

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Conclusions

• Vehicular Communications offer opportunities
  beyond safe navigation
• Dynamic content sharing/delivery Car Torrent
• Pervasive, mobile sensing MobEyes
• Massive Network games
• Research Challenges
• New routing/transport models epidemic
  dissemination, P2P, Congestion Control, Network
  Coding
• Searching massive mobile storage
• Security, privacy, incentives

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Future Work

• Extending the P2P sharing concepts to pedestrians
  
• Health Networking
• Security, privacy in vehicular content sharing
• Network Coding
• Implement CodeCast congestion control and ETE
  recovery above UDP
• If loss used as feedback, key problem is
  discrimination between random error and
  congestion
• Network Coding solutions for intermittent
  connectivity
• Models that include mobility
• Vehicular tesbed experiments

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Publications

• Uichin Lee, Eugenio Magistretti, Biao Zhou, Mario
  Gerla, Paolo
• Bellavista, Antonio Corradi. MobEyes Smart Mobs
  for Urban
• Monitoring with a Vehicular Sensor Network. IEEE
• Wireless Communications, Sept 2006.
• J.-S. Park, D. Lun, Y. Yi, M. Gerla, M. Medard.
  CodeCast
• A Network Coding based Ad hoc Multicast Protocol.
  
• IEEE Wireless Communications, Oct 2006.
• J.-S. Park, D. Lun, M. Gerla, M. Medard.
  Performance
• Evaluation of Network Coding in multicast MANET.
• Proc. IEEE MILCOM 2006.
• U. Lee, J.-S. Park, J. Yeh, G. Pau, M. Gerla.
  CodeTorrent
• Content Distribution using Network Coding in
  VANET.
• Proc. of MobiShare, Los Angeles, Sept 2006.

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Support

• This work was supported by
• ARMY MURI Project DAWN (PI JJ Garcia)
  2005-2008 UCLA CoPI Rajive Bagrodia
• ARMY Grant under the IBM - TITAN Project (PI,
  Dinesh Verma, IBM) 2006-2011 UCLA CoPIs
  Deborah Estrin, Mani Srivastava
• NSF NeTS Grant - Emergency Ad Hoc Networking
  Using Programmable Radios and Intelligent Swarms
  2005-2009 PI Gerla, UCLA CoPIs - Soatto, Fitz,
  Pau

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The End

• Thank You