Ad hoc Network Evolution : From Battle Theaters to Vehicle Grids CCW 2005 Huntington Beach, Oct 2005

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Ad hoc Network Evolution From Battle Theaters
to Vehicle Grids CCW 2005Huntington Beach,
Oct 2005

• Mario Gerla
• Computer Science Dept
• UCLA

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Outline

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

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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
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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?

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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

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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

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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

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Why opportunistic ad hoc networking?

• All Internet access will soon be wireless
• Most Internet terminals will be mobile with
  multiple radio interfaces (WiFi, Bluetooth, 3G
  etc)
• Yet, single hop access from terminal may not be
  feasible, or may not be efficient!
• Obstacles distance
• Cost
• Inefficient use of resources
• Proximity networking application
• etc
• Enter Opportunistic multi-hop networking

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Urban opportunistic ad hoc networking
From Wireless to Wired network Via Multihop
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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
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Car to Car communications for Safe Driving
Vehicle type Cadillac XLRCurb weight 3,547
lbsSpeed 65 mphAcceleration -
5m/sec2Coefficient of friction .65Driver
Attention YesEtc.
Vehicle type Cadillac XLRCurb weight 3,547
lbsSpeed 75 mphAcceleration
20m/sec2Coefficient 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/sec2Coefficient of friction .65Driver
Attention NoEtc.
Vehicle type Cadillac XLRCurb weight 3,547
lbsSpeed 75 mphAcceleration
10m/sec2Coefficient of friction .65Driver
Attention YesEtc.
Alert Status Passing Vehicle on left
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DSRC/IEEE 802.11p Enabler of Novel Applications

• 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 that intends to
  standardize DSRC for Car-Car communications
• DSRC Dedicated Short Range Communications

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DSRC Channel Characteristics
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Hot Spot
Hot Spot
Vehicular Grid as Opportunistic Ad Hoc Net
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Hot Spot
Hot Spot
Vehicular Grid as Emergency Net
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Vehicular Grid as Emergency Net
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CarTorrent Opportunistic Ad Hoc networking to
download large multimedia files

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

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

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Highway Infostation download
Internet
file
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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

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CarTorrent Basic Idea
Internet
Download a piece
Outside Range of Gateway
Transferring Piece of File from Gateway
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Co-operative Download
Internet
Vehicle-Vehicle Communication
Exchanging Pieces of File Later
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Bit Torrent review

• Swarming Parallel downloads among a mesh of
  cooperating peers
• Scalable System capacity increases with increase
  in number of peers
• Tracker
• Handles peer discovery
• Centralized Tracker, single point of failure
• Observation Might not work for Wireless
  scenarios, because of intermittent connectivity
• Issue Mobility increases churn of nodes
  participating in a download

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BitTorrent. A picture..
Uploader/downloader
Uploader/downloader
Uploader/downloader
Tracker
Uploader/downloader
Uploader/downloader
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Experimental Evaluation
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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
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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.

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Impact of Selection Strategy
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Analytical Model
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Why is the Car-Torrent solution attractive?

• Bandwidth at the infostation is limited and not
  convenient
• It can become congested if all vehicles stop
• It is a nuisance as I must stop and waste time
• GPRS and 3G bandwidth is also limited and
  expensive
• The car to car bandwidth on the freeway is huge
  and practically unlimited!
• Car to car radios already paid for by safe
  navigation requirement
• CarTorrent transmissions are reliable - they
  involve only few hops (proximity routing)

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AdTorrent Digital BillBoards for Vehicular
Networks

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

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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.

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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)

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AdTorrent Features

• Keyword Set Indexing to reduce Communication
  Overhead
• Epidemic Scoped Query Data Dissemination
  optimized for vehicular ad hoc setting
• Broadcast medium leveraged for communication
  efficiency of gossip messaging
• Torrent Ranking Algorithm
• Swarming in actual content delivery
• Discourage Selfishness

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Modeling Approach

• What is the impact of scope of epidemic
  dissemination on query hit rates?
• Model the network of caches, from the perspective
  of a single file i
• LRU-managed caches
• Model Local requests
• Model Remote requests
• i file id, k Number of hops, B cache size
• Plocal(i,j,k) probability of finding the file in
  the local cache in the top j positions when the
  hop-limit is k
• Given plocal(i,B,k) we can compute the hit rate
  for k-hop neighborhood as follows
• P(i,B,k) 1-(1 -plocal(i,B,k))M(k) we used
  M(k) k1.4
• M(k) derived from real-track mobility model

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Neighborhood Model
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Hit Rate vs. Hop Count with LRU
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Car to car on-line gamesClaudio Palazzi (UCLA)
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Massive Multiplayer Online Games

• Exploding market
• Tot Games industry revenues 40 billion in 2003
• MMOG revenues 1 billion in 2003, expected 10
  billion in 2009

Tot MMOG Subscribers
MMOG Revenue by Region 2003
8 millions
Jan-98
Jan-05
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Design Challenges in On Line Games

• Consistency
• contemporary uniformity of game state view in all
  nodes
• Responsiveness
• multiplayer gaming is extremely delay-sensitive
• Scalability
• the number of contemporary players should not be
  bounded
• Resilience to network conditions
• players performance should not depend on network
  conditions (Fairness)

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New challenges in car to car on-line games

• Frequent changes in routing handoffs
• Highly variable latency
• Highly variable bandwidth
• Intermittent connectivity
• Packet loss

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Proposed Approach Mirrored Game Server
Architecture Car-networking Scenario
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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

1. Fixed Infrastructure 2. Processing and
storage
Infostation
Car to Infostation
1. On-board black box 2. Processing and
storage
Car-Car multi-hop
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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
CRASH
Meta-data Img, -. (10,10), VID10
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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

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Epidemic diffusion
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VSN Mobility-Assist Data Harvesting
Relay its Event to Neighbors Listen and
store others relayed events
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VSN Mobility-Assist Data Harvesting

• Agent (Police) harvests situation specific data
  from its neighbors
• Nodes return the relevant datathey have
  collected so far

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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
• ? network density of disseminating nodes
• Discrete time analysis (time step ?t)
• Metrics
• Average event percolation delay
• Average delay until all relevant data is harvested

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VSN Simulation

• Simulation Setup
• Implemented using NS-2
• 802.11a 11Mbps, 250m transmission range
• Average speed 10 m/s
• Network 2400m x 2400m
• Mobility Models
• Random waypoint (RWP)
• Road-track model (RT) Group mobility model with
  merge and split at intersections
• Westwood map is used for a realistic simulation

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Road Track Mobility Model
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Event diffusion delayRandom Way Point
K2,m10
Fraction of Infected Nodes
K1,m10
K2,m1
K1,m1
1. k-hop relaying2. m event sources
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Event diffusion delay Route Tracks
Fraction of Infected Nodes
1. k-hop relaying2. m event sources
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Data harvesting delay with RWP
Agent
Regular Nodes
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Data harvesting results with RT
AGENT
REGULAR
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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

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The End

• Thank You