Ad hoc Network Evolution : From Battle Theaters to Vehicle

Grids

CCW 2005Huntington Beach, Oct 2005

Mario GerlaComputer 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

SURVEILLANCE MISSION

SURVEILLANCE MISSION

AIR-TO-AIR MISSION

STRIKE MISSION

FRIENDLY GROUND CONTROL

(MOBILE)

RESUPPLY MISSION

SATELLITE COMMS

Unmanned Control Platform

COMM/TASKING

COMM/TASKING

MannedControl Platform

COMM/TASKING

UAV-UAV NETWORK

Algorithms and Protocols for a Network of Autonomous Agents

UAV-UGV NETWORK

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 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

CarTorrent : Opportunistic Ad Hoc networking to download

large multimedia files

Alok Nandan, Shirshanka DasGiovanni Pau, Mario Gerla

WONS 2005

You are driving to VegasYou 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

Download a piece

Internet

Transferring Piece of File from Gateway

Outside Range of Gateway

Co-operative Download

Vehicle-Vehicle Communication

Internet

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 WorkshopMobiquitous 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)

Infostation

Car-Car multi-hop

1. Fixed Infrastructure2. Processing and storage

1. On-board “black box” 2. Processing and storage

Car to Infostation

• Applications– Monitoring road conditions for Navigation Safety or Traffic

control– Imaging for accident or crime site investigation

VSN Scenario: storage and retrieval

• Private Cars: – 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)– Post it on distributed index

• Police retrieve data from distributed storage

CRASHMeta-data : Img, -.

(10,10), VID10

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 Req

1. Agent (Police) harvests situation specific data from its neighbors

2. Nodes return the relevant datathey have collected so far

Data Rep

VSN: Mobility-Assist Data Harvesting (cont)

• 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– ρ : network density of disseminating nodes– Discrete time analysis (time step Δt)

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

Road Track Mobility Model

Event diffusion delay:Random Way Point

1. ‘k’-hop relaying2. m event sources

Fraction of Infected

Nodes K=1,m=1

K=1,m=10

K=2,m=10

K=2,m=1

Event diffusion delay: Route Tracks

1. ‘k’-hop relaying2. m event sources

Fraction of Infected

Nodes

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