Mario Gerla Computer Science Dept UCLA

1. HOMELAND SECURITY IN THE STREETS- THE VEHICLE GRIDHomeland Defense WorkshopSorrento, Italy, Oct 18-21 Mario Gerla Computer Science Dept UCLA

2. Outline • Urban Homeland Defense • Cable TV installations vs mobile sensor platforms • “Ad Hoc” Wireless Networks • Conventional vs Opportunistic • Vehicle Communications Standards • V2V applications • Car Torrent • MobEyes • Autonomous evacuation • Beyond vehicles • Health networks against bio attacks • Under water networks against harbor attacks

3. Urban Homeland Security - CCTV • In urban areas, the first line of defense has traditionally been fixed video cameras • Chicago, the leader in the US: • 2,000 remote-control cameras and motion-sensing software are planned to spot crimes or terrorist acts • 1,000 already installed at O'Hare International Airport • A few links below: • 1. http://www.usatoday.com/news/nation/2004-09-09-chicago-surveillance_x.htm • 2. http://www.securityinfowatch.com/online/The-Latest/Chicago-to-Increase-Presence-of-Surveillance-Cameras-on-Streets/9578SIW306 • 3. http://blog.publiceye.silkblogs.com/City-of-Chicago.1771.category

4. Emerging City Wide Surveillance Systems With 4 millions CCTV cameras around the country, Britain is to become the first country in the world where the movements of all vehicles on the roads are recorded. Jennifer Carlile, MSNBC CHICAGO — A surveillance system that uses 2,000 remote-control cameras and motion-sensing software to spot crimes or terrorist acts as they happen is being planned for the city. Debbie Howlett, USA TODAY

5. Urban Defense - Britain • More than 4 million CCTV cameras operating around the country: • Britain has more video surveillance than anywhere else in the world. • 96 cameras at Heathrow airport, 1,800 in train stations, • 6,000 on the London Underground, • 260 around parliament, • 230 used for license plate recognition in the city center, and the dozens surveying West End streets. • In London it's said that the average resident is viewed by 300 cameras a day. • References http://www.msnbc.msn.com/id/5942513 http://news.independent.co.uk/uk/transport/

6. Urban surveillance by CCTV • CCTV surveillance has benefits: • Data collected in a data base via the very high speed urban wired infrastucture • High resolution video is good for criminal recognition • However: • Cameras cannot be installed at all locations • Cameras can be taken out by terrorists • The central data collection facility can be sabotaged • Enter mobile video collection/storage platforms: • Vehicles • People • Robots • Mobile “eyes” are an excellent complement to CCTV • In this talk we will focus on VEHICLES

7. Mobile Surveillance - Challenges • New challenges: • wireless communications medium • wireless data protocols/architectures • distributed storage strategy • search of the distributed, mobile data base • Let us begin with the wireless medium challenge

8. The urban wireless “waves” • Wave #1: cellular telephony (1980) • Still, biggest profit maker • Wave #2 : wireless Internet access (1995) • Wireless LANs, WiFI, Mesh Nets, WIMAX • Most Internet access on Campuses is wireless • Urban Mesh Nets are rapidly proliferating in the US; Europe and Asia to follow soon • Cellular providers (2.5 G and 3G) are trying to keep up • Wave #3: ad hoc wireless nets (now) • Set up in an area with no infrastructure; to respond to a specific, time limited need

9. The 3rd wave: Infrastructure vs Ad Hoc Infrastructure Network (WiFI or 3G) Ad Hoc, Multihop wireless Network

10. Ad Hoc Network Characteristics • Instantly deployable, re-configurable (No fixed infrastructure) • Created to satisfy a “temporary” need • Portable (eg sensors), mobile (eg, cars) • Multi-hopping ( to save power, overcome obstacles, etc.)

11. Typical Ad Hoc Network Applications Military • Automated battlefield Civilian • Disaster Recovery (flood, fire, earthquakes etc) • Law enforcement (crowd control) • Homeland defense • Search and rescue in remote areas • Environment monitoring (sensors) • Space/planet exploration

12. 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 Typical Ad Hoc Network

13. Traditional ad hoc net architectures • Tactical battlefield: • no infrastructure • Civilian emergency: • infrastructure, if present, was destroyed • Instant deployment • Specialized missions (eg, UAV scouting) • Critical: scalability, survivability, QoS, jam protection • Non critical: Cost, Standards, Privacy • These architectures are not suitable for “every day” urban communications • Enter: “Opportunistic” Ad Hoc Networks

14. New Trend: “Opportunistic” ad hoc nets • Great for commercial applications • Indoor W-LAN extended coverage • Group of friends sharing 3G via Bluetooth • Peer 2 peer networking in the vehicle grid • Cost is a major issue • Access to Internet: • available, but; • “bypass it” with “ad hoc” if too costly or inadequate • Critical: Standards -> cost reduction and interoperability • Critical: Privacy, security

15. 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

16. Urban car to car communications:the vehicle grid

17. New Vehicle Roles on the road • Vehicle as a producer of geo-referenced data about its environment • Pavement condition • Probe data for traffic management • Weather data • Physiological condition of passengers, ….

18. Vehicle Roles (cont) • Vehicle & Vehicle, Vehicle & Roadway as collaborators • Cooperative Active Safety • Forward Collision Warning, Blind Spot Warning, Intersection Collision Warning……. • In-Vehicle Advisories • “Ice on bridge”, “Congestion ahead”,…. • Vehicle as Information Gateway (Telematics) • Internet access, infotainment, dynamic route guidance, …… • These roles demand efficient communications

19. Transit Vehicle Car to Car/Curb communications Transit Signal Priority up to 1000 ft Transit Vehicle Stop Traffic Signal Grass Divider Collision Avoidance E-Transaction: gas, movie, …. Gas Pumps IDB Data Transfer * Graphic created from Broady Cash (ARINC) Not to Scale

20. Convergence to a Standard:Government, Industry, Academia • ACM created Vehicular Ad-hoc Networks Workshop - VANET • IEEE created V2VCOM • Federal Communications Commission created DSRC • The record in this proceeding overwhelmingly supports the allocation of spectrum for DSRC based ITS applications to increase traveler safety, reduce fuel consumption and pollution, and continue to advance the nations economy. • FCC Report and Order, October 22, 1999, FCC 99-305 • Amendment with licensing rules in December 2003 • DSRC Standards • ASTM E17.51, IEEE 802.11p • http://grouper.ieee.org/groups/scc32/dsrc/ • Automotive companies created Vehicle Safety Communications Consortium (VSCC) • Final Report Submitted January 2005 • USDOT/CAMP have created Cooperative Intersection Collision Avoidance (CICAS) Consortium • http://www.its.dot.gov/cicas/cicas_workshop.htm

21. USDOT Vehicle Infrastructure Integration Initiative • http://www.itsa.org/vii.html • The VII Initiative is a cooperative effort between Federal and state departments of transportation (DOTs) and vehicle manufacturers to evaluate the technical, economic, and social/political feasibility of deploying a communications system to be used primarily for improving the safety and efficiency of the nation's road transportation system.

22. The Standard: DSRC / IEEE 802.11p • Car-Car communications at 5.9Ghz • Derived from 802.11a • three types of channels: Vehicle-Vehicle service, a Vehicle-Gateway service and a control broadcast channel . • Ad hoc mode; and infrastructure mode • 802.11p: IEEE Task Group for Car-Car communications

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

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

25. One option: Highway Infostation download Internet file

26. Incentive for opportunistic “ad hoc networking” Problems: Stopping at gas station for full 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

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

28. Co-operative Download: Car Torrent Internet Vehicle-Vehicle Communication Exchanging Pieces of File Later

29. BitTorrent: Internet P2P file downloading Uploader/downloader Uploader/downloader Uploader/downloader Tracker Uploader/downloader Uploader/downloader

30. 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

31. Selection Strategy Critical

32. CarTorrent with Network Coding • Limitations of Car Torrent • Piece selection critical • Frequent failures due to loss, path breaks • New Approach –network coding • “Mix and encode” the packet contents at intermediate nodes • Random mixing (with arbitrary weights) will do the job!

33. Network Coding e = [e1e2e3 e4] encoding vector tells how packet was mixed (e.g. coded packet p = ∑eixiwhere xiis original packet) buffer Receiver recovers original by matrix inversion random mixing Intermediate nodes

34. Single-hop pulling (instead of CarTorrent multihop) Buffer Buffer Buffer B1 *a1 B2 *a2 *a3 File: k blocks B3 + “coded” block *ak Bk Random Linear Combination CodeTorrent: Basic Idea Internet Re-Encoding: Random Linear Comb.of Encoded Blocks in the Buffer Outside Range of AP Exchange Re-Encoded Blocks Downloading Coded Blocks from AP Meeting Other Vehicles with Coded Blocks

35. Simulation Results • Avg. number of completion distribution 200 nodes40% popularity Time (seconds)

36. Simulation Results • Impact of mobility • Speed helps disseminate from AP’s and C2C • Speed hurts multihop routing (CarT) • Car density+multihop promotes congestion (CarT) Avg. Download Time (s) 40% popularity

37. Vehicular Sensor Network (VSN)IEEE Wiress Communications 2006Uichin Lee, Eugenio Magistretti (UCLA)

38. Vehicular Sensor Applications • Environment • Traffic congestion monitoring • Urban pollution monitoring • Civic and Homeland security • Forensic accident or crime site investigations • Terrorist alerts

39. In Car System CCTV Mobile Unit Infrastructure-Based Centralized Approach- UK ANPR System Vehicle passes ANPR Camera ANPR s/w checks database Decision taken to stop vehicle Source: Automatic Number Plate Recognition (ANPR) - Driving Down Crime - Denying Criminals the Use of the Road

40. Accident Scenario: storage and retrieval • Designated Cars: • Continuously collect images on the street (store data locally) • Process the data and detectan event • Classify the event asMeta-data (Type, Option, Location, Vehicle ID) • Post it on distributed index • Police retrieve data from designated cars Meta-data : Img, -. (10,10), V10

41. How to retrieve the data? • “Epidemic diffusion” : • Mobile nodes periodically broadcast meta-data of events to their neighbors • A mobileagent(the police) queries nodes and harvests events • Data dropped when stale and/or geographically irrelevant

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

43. Keep “relaying” its meta-data to neighbors 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

44. Meta-Data Rep Meta-Data Req Epidemic Diffusion- Idea: Mobility-Assist Meta-Data Harvesting • Agent (Police) harvestsMeta-Data from its neighbors • Nodes return all the meta-datathey have collected so far

45. Simulation Experiment • Simulation Setup • NS-2 simulator • 802.11: 11Mbps, 250m tx range • Average speed: 10 m/s • Mobility Models • Random waypoint (RWP) • Real-track model (RT) : • Group mobility model • merge and split at intersections • Westwood map

46. Higher mobility decreases harvesting delay Number of Harvested Summaries Time (seconds) Meta-data harvesting delay with RWP V=25m/s V=5m/s

47. Number of Harvested Summaries Time (seconds) Harvesting Results with “Real Track” • Restricted mobility results in larger delay V=25m/s V=5m/s

48. Protecting vehicles against road perils

49. Evacuation from a Tunnel after a Fire: Emergency Video Streaming • Multimedia type message propagation helps road safety • Precise situation awareness via video • Drivers can make better informed decisions Real-time Video Streaming Fire inside the Tunnel Source: http://www.landroverclub.net/Club/HTML/MontBlanc.htm

50. Emergency Video Streaming • Problems • Potential volume of multimedia traffic • Unreliable wireless channel • Multimedia data delivery service that is reliable and efficient and real time • Our Approach: Random network coding