V2V applications:End to end or broadcast-based?

Panel

VANET 2007, Sept 10, 2007

Mario Gerla

Computer Science Dept, UCLA

www.cs.ucla.edu

End to end vs broadcast based

• VANET E2E networking (without infrastructure) extremely challenging:– An urban VANET may have over 100,000 nodes– Nodes move in unpredictable ways– End to end routing is HARD

• AODV and OLSR do not scale• Geo-routing can get trapped in “dead ends”• Geo Location Service not very scalable

– TCP over several hops “in motion” is a nightmare!– Intermittent connectivity in most cases

• So, end to end applications (a la mesh network) hard to deploy

• However….

Where are the E2E applications?

• Very few urban scenarios/applicatios require “true” E2E networking:

– Emergency, disaster recovery (eg, earthquake, hostile attack)

– Urban warfare

• Generally, these are situations where the Infrastructure has failed

PowerBlackout

STOP

PowerBlackout

STOP

Broadcast based applications

• The most popular VANET applications are “broadcast” based– Safe navigation - neighborhood broadcast– Content sharing - P2P proximity routing– Distributed urban sensing - Epidemic dissemination

Car to Car broadcast for Safe Driving

Vehicle 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

Co-operative Download: Car Torrent

Vehicle-Vehicle Communication

Internet

Exchanging Pieces of File en route

Accident Scenario: storage and retrieval

• Designated Cars (eg, busses, taxicabs, UPS, police agents, etc): – Continuously collect images on the street (store data locally)– Process the data and detect an event– Classify the event as Meta-data (Type, Option, Location, Vehicle ID)– Epidemically disseminate -> distributed index

• Police retrieve data from designated cars

Meta-data : Img, -. (10,10), V10

CRASH

- Sensing - P rocessing

Crash Summary Reporting

Summary Harvesting

Epidemic Diffusion - Idea: Mobility-Assist Meta-Data Diffusion

Epidemic Diffusion - Idea: Mobility-Assist Meta-Data Diffusion

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

Epidemic Diffusion - Idea: Mobility-Assist Meta-Data 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

The Future

• Future VANET applications will be broadcast, proximity routing based

• However, proximity and broadcast only removes the E2E complexity

• Enormous challenges still ahead:• Navigation safety

– “liability” stigma– strict delay constraints

• Location aware content, Infotainment– Driver distraction -> more accidents?– Virus scare

• Urban Sensing– Business model not clear (who makes money?)– Privacy issues

Thank You