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FleaNet : A Virtual Market Place on Vehicular Networks. Uichin Lee, Joon-Sang Park Eyal Amir, Mario Gerla Network Research Lab, Computer Science Dept., UCLA. Advent of VANETs. Emerging VANET applications Safety driving (e.g., TrafficView) Content distribution (e.g., CarTorrent/AdTorrent)

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fleanet a virtual market place on vehicular networks

FleaNet : A Virtual Market Place on Vehicular Networks

Uichin Lee, Joon-Sang Park Eyal Amir, Mario Gerla

Network Research Lab, Computer Science Dept., UCLA

advent of vanets
Advent of VANETs
  • Emerging VANET applications
    • Safety driving (e.g., TrafficView)
    • Content distribution (e.g., CarTorrent/AdTorrent)
    • Vehicular sensors (e.g., MobEyes)
  • What about commerce “on wheels”?
flea market on vanets
Flea Market on VANETs
  • Examples
    • A mobile user wants to sell “iPod Mini, 4G”
    • A road side store wants to advertise a special offer
  • How to form a “virtual” market place using wireless communications among mobile users as well as pedestrians (including roadside stores)?
  • FleaNet architecture
  • FleaNet protocol design
  • Feasibility analysis
  • Simulation
  • Conclusions
fleanet architecture system components
FleaNet Architecture-- System Components
  • Vehicle-to-vehicle communications
  • Vehicle-to-infrastructure (ad-station) communications

* Roadside stores (e.g., a gas station)

fleanet architecture query formats and management
FleaNet Architecture -- Query Formats and Management
  • Users express their interests using formatted queries
    • eBay-like category is provided
      • E.g., Consumer Electronics/Mp3 Player/Apple iPod
  • Query management
    • Query storage using a light weight DB (e.g., Berkeley DB)
    • Spatial/temporal queries
    • Process an incoming query to find matched queries (i.e., exact or approximate match)
      • E.g. Query(buy an iPod)  Query(sell an iPod)
fleanet protocol design
FleaNet Protocol Design
  • FleaNet building blocks
    • Query dissemination
    • Distributed query processing
    • Transaction notification
      • Seller and buyer are notified
      • This requires routing in the VANET
  • VANET challenges
    • Large scale, dense, and highly mobile
  • Goal: designing “efficient, scalable, and non-interfering protocols” for VANETs
query dissemination
Query Dissemination
  • Query dissemination exploiting vehicle mobility
  • Query “originator” periodically advertises its query to 1-hop neighbors
    • Vehicles “carry” received queries w/o further relaying

Yellow Car w/ Q1



Red Car w/ Q2



distributed query processing



Distributed Query Processing
  • Received query is processed to find a match of interests
    • Eg. Q1 – buy iPod / QM – sell iPod / Q2 – buy Car

(1) Find a matching query for Q2 No match found



Cyan car w/ QM

(2) Send a match notification msg to the originator of query QM



(1) Find a matching query for QM

 Found query Q1


Red car w/ Q2& carries Q1

transaction notification



Transaction Notification
  • After seeing a match, use Last Encounter Routing (LER) to notify seller/buyer
    • Forward a packet to the node with more “recent” encounter




Green car

Cyan car

Yellow car



Blue car





Originator of Q1

Red car


Current Time: T

Encounter timestamp

fleanet latency
FleaNet Latency
  • Restricted mobility patterns are harmful to opportunistic data dissemination
  • However, latency can be greatly improved by the popularity of queries
  • Popularity distribution of 16,862 posting (make+model) in the vehicle ad section of Craigslist (Mar. 2006)

Frequency (log)

Items (log)

fleanet scalability
FleaNet Scalability
  • Assume that only the query originator can “periodically” advertise a query to its neighbors
  • We are interested in link load
  • Load depends only on average number of neighbors and advertisement period (not on network size)
  • Example:
    • Parameter setting : R=250m, 1500B packet size, BW=11Mbps
    • N=1,000 nodes in 2,400m x 2,400m (i.e., 90 nodes within one’s communication range)
    • Advertisement period: 2 seconds
    • Worst case link utilization: < 4%
  • Ns-2 network simulator
  • 802.11b - 2Mbps, 250M radio range
  • Two-ray ground reflection model
  • “Track” mobility model
    • Vehicles move in the 2400mx2400m Westwood area in the vicinity of the UCLA campus
  • Metric
    • Average latency: time to find a matched query of interest

Westwood area, 2400mx2400m

simulation results
Simulation Results
  • Impact of density and speed
simulation results1
Simulation Results
  • Impact of query popularity
    • Popularity: the fraction of users with the same interest
    • For a single buyer, increase the number of sellers (e.g., N=200/0.1 = 20 sellers)
simulation results2

avg. stationary

avg. mobile

Simulation Results
  • Impact of ad-station location
    • Given N=100, fix each node in its initial location, and set it as a “stationary” ad-station (as a buyer)
    • measure the average latency to the remaining 99 mobile nodes (run 99 times, by taking turns as a seller: 1 buyer  1 seller)


Latency rank

  • Proposed a virtual market concept in VANETs:
    • A mix of mobile and stationary users carry out buy/sell transactions (or any other matching of common interests) using vehicular networks
  • Mobility-assisted query dissemination and resolution (scalable and non-interfering)
    • Node density/speed are closely related to the performance
    • Popularity of a query greatly improves the performance
    • Location of an ad-station is important to the performance
  • Future work
    • Query aggregation to improve the performance
      • Unpopular queries/queries from ad-stations
    • How to enforce cooperativeness of users?
    • Security: false query injection and spamming?