Ad hoc Network Evolution : From Battle Theaters to Vehicle Grids

CCW 2005

Huntington Beach, Oct 2005 Mario Gerla Computer Science Dept UCLA

Outline

• • • • • •

Battlefield vs Commerce: Opportunistic ad hoc networking Car to Car communications Car Torrent Ad Torrent Network games Cars as mobile sensor platforms

SATELLITE COMMS SURVEILLANCE MISSION AIR-TO-AIR MISSION Unmanned Control Platform COMM/TASKING COMM/TASKING

UAV-UAV NETWORK

STRIKE MISSION RESUPPLY MISSION SURVEILLANCE MISSION COMM/TASKING

UAV-UGV NETWORK

FRIENDLY GROUND CONTROL (MOBILE) Manned Control Platform

Algorithms and Protocols for a Network of Autonomous Agents

From battle theater to commerce

• • •

Most of the “funded” mobile ad hoc network research is aimed at:

– Military, large scale applications – Civilian applications (disaster recovery, homeland defense, planetary exploration, etc) – Large mobile sensor platform deployments

Is this technology ready for transfer to “commodity” ad hoc applications?

Where are the commercial applications?

Current ad hoc net designs

– Civilian emergency, tactical applications – Typically, large scale – Instant deployment – Infrastructure absent (so, must recreate it) – Very specialized mission/function (eg, UAV scouting behind enemy lines) – Critical : scalability, survivability, QoS, jam protection – Not critical : Cost, Standards, Privacy

Emerging, commercial ad hoc nets

– Commercial, “commodity” applications – Mostly, small scale – Cost is a major issue (eg, ad hoc vs 2.5 G) – Connection to Internet often available – Need not recreate “infrastructure”, rather “bypass it” whenever it is convenient – “Opportunistic” networking – Critical: • Standards are critical to cut costs and to assure interoperability • Privacy, security is critical

What is an opportunistic ad hoc net?

• • • •

wireless ad hoc extension of the wired/wireless infrastructure coexists with/bypasses the infrastructure generally low cost and small scale Examples

– Indoor W-LAN extended coverage – Group of friends networked with Bluetooth to share an expensive resource (eg, 3G connection) – Peer to peer networking in the urban vehicle grid

Opportunistic piggy rides in the urban mesh

Pedestrian transmits a large file in blocks to passing cars, busses The carriers deliver the blocks to the hot spot

Car to Car communications for Safe Driving

Vehicle type: Cadillac XLR Curb weight: 3,547 lbs Speed: 75 mph Acceleration:

+ 20m/sec^2

Coefficient of friction: .65

Driver Attention: Yes Etc.

Alert Status:

None

Vehicle type: Cadillac XLR Curb weight: 3,547 lbs Speed: 65 mph Acceleration:

- 5m/sec^2

Coefficient of friction: .65

Driver Attention: Yes Etc.

Alert Status:

None

Vehicle type: Cadillac XLR Curb weight: 3,547 lbs Speed: 75 mph Acceleration: Etc.

Alert Status:

Inattentive Driver on Right

Alert Status:

Slowing vehicle ahead

Alert Status:

Passing vehicle on left + 10m/sec^2

Coefficient of friction: .65

Driver Attention:

Yes

Alert Status:

Passing Vehicle on left

Vehicle type: Cadillac XLR Curb weight: 3,547 lbs Speed: 45 mph Acceleration:

- 20m/sec^2

Coefficient of friction: .65

Driver Attention:

No

Etc.

CarTorrent

: Opportunistic Ad Hoc networking to download large multimedia files

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

You are driving to Vegas You hear of this new show on the radio Video preview on the web (10MB)

Highway Infostation download

Internet file

Incentive for “ad hoc networking”

Problems: Stopping at gas station to 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

CarTorrent: Basic Idea

Internet Download a piece

Outside Range of Gateway Transferring Piece of File from Gateway

Internet

Co-operative Download

Vehicle-Vehicle Communication

Exchanging Pieces of File Later

Experimental Evaluation

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

Peer Selection Strategies

Possible selections: • 1)

Rarest First:

BitTorrent-like policy of searching for the rarest bitfield in your peerlist and downloading it • 2)

Closest Rarest

: download closest missing piece (break ties on rarity) • 3)

Rarer vs Closer:

weighs the rare pieces based on the distance to the closest peer who has that piece.

Impact of Selection Strategy

AdTorrent: Digital BillBoards for Vehicular Networks

V2V COM Workshop Mobiquitous 2005 Alok Nandan, Shirshanka Das Biao Zhou, Giovanni Pau, Mario Gerla

Digital Billboard

Safer :

Physical billboards can be distracting for drivers

Aesthetic :

The skyline is not marred by unsightly boards.

Efficient :

With the presence of a good application on the client (vehicle) side, users will see the Ad only if they actively search for it or are interested in it.

Localized :

The physical wireless medium automatically induces locality characteristics into the advertisements.

Digital Billboard

• • • •

Every Access Point (AP) disseminates Ads that are relevant to the proximity of the AP from simple text-based Ads to trailers of nearby movies, virtual tours of hotels etc business owners in the vicinity subscribe to this digital billboard service for a fee.

Need a location-aware distributed application to search, rank and deliver content to the end-user (the vehicle)

Hit Rate vs. Hop Count with LRU

Vehicular Sensor Network (VSN)

Uichin Lee, Eugenio Magistretti (UCLA)

•

Applications

– Monitoring road conditions for

Navigation Safety

or

Traffic control

– Imaging for

accident

or

crime site investigation

Infostation 1. Fixed Infrastructure 2. Processing and storage Car to Infostation 1. On-board “black box” 2. Processing and storage Car-Car multi-hop

VSN Scenario: storage and retrieval

• • Private Cars: – Continuously

collect

images on the street (store data locally) – Process the data and

detect

an event – –

Classify Post

the event as Meta-data (Type, Option, Location, Vehicle ID) it on distributed index Police retrieve data from distributed storage Meta-data : Img, -. (10,10), VID10 CRASH Meta-data : Img, Crash, (10,5), VID12

Distributed Index options

•

Info station based index

•

“Epidemic diffusion” index

–

Mobile nodes

periodically broadcast

meta-data

of events to their neighbors (via epidemic diffusion) – A

mobile agent

(the police) queries nodes and harvests events – Data may be dropped when temporally stale and geographically irrelevant

Epidemic: diffusion

VSN: Mobility-Assist Data Harvesting * Relay its Event to Neighbors * Listen and store other’s relayed events

VSN: Mobility-Assist Data Harvesting Data Rep Data Req 1. Agent (Police) harvests situation specific data from its neighbors 2. Nodes return the relevant data they have collected so far

VSN: Mobility-Assist Data Harvesting (cont)

• •

Assumption

– N disseminating nodes; each node

n i

advertises event

e i

• “k”-hop relaying (relay an event to “k”-hop neighbors) – v: average speed, R: communication range – ρ : network density of disseminating nodes – Discrete time analysis (time step

Δ t

)

Metrics

– Average event “percolation” delay – Average delay until all relevant data is harvested

Road Track Mobility Model

Event diffusion delay:Random Way Point

K=2,m=10 K=1,m=10 K=2,m=1 K=1,m=1

1. ‘k’-hop relaying 2. m event sources

Event diffusion delay: Route Tracks

1. ‘k’-hop relaying 2. m event sources

Vehicular Grid Research Opportunities

• • •

Lots of research done on “tactical” nets Hardly applicable to commercial ad hoc nets!

New research (beyond tactical) is critical for “opportunistic” deployment:

– – – – –

Security, privacy Incentive strategies Realistic mobility models Delay tolerant networking P2P protocols; proximity routing - epidemic dissemination

The End Thank You