vehicular grid communications: the role of the internet infrastructure wicon 2006 boston, august 3,...
TRANSCRIPT
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Vehicular Grid Communications: the role of the Internet
Infrastructure
Wicon 2006Boston, August 3, 2006
Presented by Mario GerlaUCLA CSD [email protected]
www.cs.ucla.edu/NRL
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Outline
Emerging urban vehicle applications Routing in a highly mobile urban
environment A case for geo-routing Geo Location Service
Extending Geo routing to the infrastructure
To use or not to use the infrastructure? load balance
Conclusions
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Urban Vehicle Grid Applications
– Safe navigation– Content distribution (video, ads)– Vehicle as mobile sensor platform
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Safe DrivingVehicle type: Cadillac XLRCurb weight: 3,547 lbsSpeed: 65 mphAcceleration: - 5m/sec^2Coefficient of friction: .65Driver Attention: YesEtc.
Vehicle type: Cadillac XLRCurb weight: 3,547 lbsSpeed: 45 mphAcceleration: - 20m/sec^2Coefficient of friction: .65Driver Attention: NoEtc.
Vehicle type: Cadillac XLRCurb weight: 3,547 lbsSpeed: 75 mphAcceleration: + 20m/sec^2Coefficient of friction: .65Driver Attention: YesEtc.
Vehicle type: Cadillac XLRCurb weight: 3,547 lbsSpeed: 75 mphAcceleration: + 10m/sec^2Coefficient of friction: .65Driver Attention: YesEtc.
Alert Status: None
Alert Status: Passing Vehicle on left
Alert Status: Inattentive Driver on Right
Alert Status: None
Alert Status: Slowing vehicle aheadAlert Status: Passing vehicle on left
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Co-operative Download: Car Torrent
Vehicle-Vehicle Communication
Internet
Exchanging Pieces of File Later
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Digital Billboard: Ad Torrent
• Every Access Point (AP) disseminates Ads that are relevant to the proximity of the AP
• Passing cars pick up the Ads• What is an Ad?
– simple text message– trailer of nearby movies, – virtual tour of hotels etc
• Business owners in the vicinity subscribe to this digital billboard service for a fee.
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Vehicular Sensor Network (VSN) (UCLA)
Infostation
Car-Car multi-hop
1. Fixed Infrastructure2. Processing and storage
1. On-board “black box” 2. Processing and storage
Car to Infostation
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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 tracking
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Accident Scenario: storage and retrieval• Designated Cars:
– Continuously collect images - cars, license plates etc (store data locally)
– Process the data and detect an event– Classify the event as Meta-data (Type, Option, Location, Vehicle
ID)– Post it on “distributed index” (P2P network)
• Police search the index and retrieve data from “witness” cars
Crash!Meta-data : Img, -. (10,10), V10
Meta-data : Img, Crash, (10,5), V12
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How to set up the index and 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 {event + witness ID}
• Data dropped when stale and/or geographically irrelevant
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Epidemic Diffusion + Harvesting
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Epidemic Diffusion + Harvesting
1) “periodically” Relay (Broadcast) its Event to Neighbors 2) Listen and store other’s relayed events into one’s storage
Keep “relaying” its meta-data to neighbors
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Epidemic Diffusion + Harvesting
Meta-Data Req
1. Agent (Police) harvestsMeta-Data from its neighbors
2. Nodes return all the meta-datathey have collected so far
Meta-Data Rep
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Routing in the Vehicle Grid
• Mostly “proximity routing”; some long range routing also present
• Proactive routing (eg OLSR)– Does not scale to hundreds of 1,000’s
• On Demand routing (eg AODV)– AODV type flood search too costly
• Enter geo-routing– Most scalable (no state needed in routers)– GPS available; local coordinates used in blind
areas (tunnels, parking lots, urban canyons)– Geo Location Service: distributed implementation
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GLS (Geo Location Service)
• Equivalent to DNS to find geo addresses• Maps vehicle ID (driver, VIN, license plate,
etc) to the (more or less) current location• A minimum of location history helps (say,
location at T-1min and T- 2min)• Distributed implementation • For resilience, dual implementation:
– In the urban Internet infrastructure– In the wireless Vehicle Grid (to survive
Infrastructure collapse)
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Infrastructure based GLS: Overlay Location Service (OLS)
Vehicular ID hashed into overlay proxies (like Chord P2P overlay)
Mapping: Vehicular ID <=> location
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Georouting through the infrastructure
• IPv6 addressing (xy coordinates in header extension)
• How to make the system resilient to failures/attacks? – If access points fail, use GLS implemented in grid
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Grid vs Infrastructure routing
• The trade offs: grid short paths vs fast wires• Baseline: Shortest path routing
– Short connections should go grid– Packets to remote destinations on infrastructure
• Next step: Access Points and Overlay assist in the decision– Propagation of congestion info from Overlay to
wireless using 3 hop beaconing (say) every second
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Simulation Experiments Wired link
Car
AP
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Traffic pattern
• Car to access point:– APT fraction of traffic ( APT = 50%, 75%, 90%)
• Car to Car:– 1- APT Traffic fraction
• Source/destination pair distance– Say, 40% of pairs < 300 m away– 30% < 1km– 30% < 10 km
• Total # of sessions: • 200 UDP sessions with variable offered rate
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Four routing strategies
• Set #1: all C2C connections are grid routed
• Set #2: all C2C connections are routed to the nearest AP’s
• Set #3 - shortest geo-distance routing
• Set #4 - same as #3, but now use also the load info advertised by AP’s
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(APT = 25%, Total 200 CBR pairs)
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1 2 3 4 5 6 7 8
Traffic Load (Pkt/Second)
Deliv
ery R
atio
Set 1 Set 2
Set 3 Set 4
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(APT = 25%, Total 200 CBR pairs)
0
1
2
3
4
5
6
7
1 2 3 4 5 6 7 8
Traffic Load (Pkt/Second)
Avg. D
ata Pa
cket D
elay (s
)
Set 1 Set 2
Set 3 Set 4
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0
0,10,2
0,3
0,40,5
0,6
0,7
0,80,9
1
2 3 4 5 6 7 8 9 10 11 12 13 14
Path Length
% T
raffic
Load
Ad Hoc Load
Infrastructure Load
Wireless grid vs infrastructure load split as a function of path length
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Summary• Transparent Geo routing across Infrastructure• Grid Efficient Grid/Infrastructure load balancing
– Simulation (Qualnet)– Analytic, multicommodity flow optimization
• Seamless switch from “Infrastructure assist” to “grid only” mode in case of disaster/attack
• The “role” of the Internet – Geo Location Service Support– Load balance– V-Grid Congestion control
• Future work: Authentication; security; DoS protection