Mario Gerla Computer Science Dept UCLA

1. Ad hoc Network Evolution : From Battle Theaters to Vehicle Grids CCW 2005Huntington Beach, Oct 2005 Mario Gerla Computer Science Dept UCLA

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

3. SURVEILLANCE MISSION AIR-TO-AIR MISSION STRIKE MISSION RESUPPLY MISSION FRIENDLY GROUND CONTROL (MOBILE) SATELLITE COMMS SURVEILLANCE MISSION UAV-UAV NETWORK COMM/TASKING COMM/TASKING Unmanned UAV-UGV NETWORK Control Platform COMM/TASKING Manned Control Platform Algorithms and Protocols for a Network of Autonomous Agents

4. 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?

5. 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

6. 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

7. 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

8. 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

9. 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: 75 mphAcceleration: + 20m/sec^2Coefficient of friction: .65Driver Attention: YesEtc. Alert Status: None Alert Status: None Alert Status: Inattentive Driver on Right Alert Status: Slowing vehicle ahead Alert Status: Passing vehicle on left 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: + 10m/sec^2Coefficient of friction: .65Driver Attention: YesEtc. Alert Status: Passing Vehicle on left

10. CarTorrent : Opportunistic Ad Hoc networking to download large multimedia files Alok Nandan, Shirshanka Das Giovanni Pau, Mario Gerla WONS 2005

11. You are driving to VegasYou hear of this new show on the radioVideo preview on the web (10MB)

12. Highway Infostation download Internet file

13. 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

14. CarTorrent: Basic Idea Internet Download a piece Outside Range of Gateway Transferring Piece of File from Gateway

15. Co-operative Download Internet Vehicle-Vehicle Communication Exchanging Pieces of File Later

16. Experimental Evaluation

17. 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

18. 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.

19. Impact of Selection Strategy

20. AdTorrent: Digital BillBoards for Vehicular Networks V2V COM Workshop Mobiquitous 2005 Alok Nandan, Shirshanka Das Biao Zhou, Giovanni Pau, Mario Gerla

21. 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.

22. 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)

23. Hit Rate vs. Hop Count with LRU

24. Applications Monitoring road conditions for Navigation Safety or Traffic control Imaging for accident or crime site investigation Vehicular Sensor Network (VSN)Uichin Lee, Eugenio Magistretti (UCLA) 1. Fixed Infrastructure 2. Processing and storage Infostation Car to Infostation 1. On-board “black box” 2. Processing and storage Car-Car multi-hop

25. 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 Meta-data : Img, Crash, (10,5), VID12 Meta-data : Img, -. (10,10), VID10 CRASH

26. 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 mobileagent(the police) queries nodes and harvests events • Data may be dropped when temporally stale and geographically irrelevant

27. Epidemic: diffusion

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

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

30. 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

31. Road Track Mobility Model

32. Event diffusion delay:Random Way Point K=2,m=10 Fraction of Infected Nodes K=1,m=10 K=2,m=1 K=1,m=1 1. ‘k’-hop relaying2. m event sources

33. Event diffusion delay: Route Tracks Fraction of Infected Nodes 1. ‘k’-hop relaying2. m event sources

34. 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

35. The End Thank You