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Location-Aware Protocols in Vehicular Networks Marco Gruteser - - PowerPoint PPT Presentation
Location-Aware Protocols in Vehicular Networks Marco Gruteser WINLAB @ Rutgers University IAB Spring 2006 1 Intelligent Transportation System Applications Automotive safety Vehicular networks likely driver Key Applications
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guides, local entertainment
Vehicular networks likely driver
for deployment of wireless ad hoc and sensor systems
Vehicular accidents account for ~40,000 fatalities/yr (in US)
Short Range Communications
vehicular environment
velocity, low-latency environment, privacy, security, reliability
Key Applications Add-on Applications
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Current Automotive
Technology
sensors
V2V Opportunities
Source: GM Press Release 2005 GPS/V2V Blind spot warning GPS/V2V Stalled vehicle warning
Extended Sensing Examples
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(fast-changing obstructions)
Group/Swarm formation
Security & Privacy
Unique addresses enables monitoring of nearby vehicles Criteria for pseudonimity and anonymity of location traces
Performance Evaluation
Not 802.11 + AODV/DSR. Need bottom-up Cross-layer design For vehicular networks
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25000 ms
No TCP changes, full EAP auth, IAPP, DHCPv4 Worst case
1300 ms
6to4, RR, Active scan Average case
150 ms
All fixes Best case 5000 (802.11/CDMA) - 20000 (802.11/GPRS) TCP parameter adjustment (status quo) L4 1-1.5 RTT (CAM) to 2.5 RTT (RR) MN-CN BU L3 1 RTT (IKE w/HA SA), 4 RTT (IKE w/CoA SA) MN-HA BU L3 Optimistic DAD L3 1000 DAD (full) L3 1500 Wait for subsequent RA L3 5 Initial RS/RA L3 1000 DHCPv4 L3 60 Fast handoff (4-way handshake only) L2 250 802.1X authentication (fast resume) L2 1000 802.1X authentication (full) L2 40 802.11 assoc/reassoc (w/ IAPP) L2 2 802.11 assoc/reassoc (no IAPP) L2 40 to 300 ms 802.11 scan (active) L2 0 ms (cached), 1 second (wait for Beacon) 802.11 scan (passive) L2
Time (ms) Item Layer Source: Bernard Aboba, http: / / www.drizzle.com/ ~ aboba/ IEEE/
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Warning messages
must be reliably delivered in both low and high density scenarios
802.11 broadcast
suffers too many collisions in high density case
250m
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senders
Antennas Mini ITX-based SSF PC
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Without rate adaptation (rate fixed to 54Mbps)
Standard MAC Implementation 1: SampleRate Standard MAC implementation 2: Onoe
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Vehicular networks have many properties of conventional ad
Do not scale well to large networks with high node mobility
Key difference: Positioning through GPS already available in
Positioning coverage can be increased through integration with vehicle velocity,
inertial sensors, compass, etc.
Vehicles also travel on (short-term) predictable paths and contain map
information
Enables a set of new protocols
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addressing mechanism
more important than a network address
forwarding within geographic perimeter
different vehicles
Desired message delivery zone (Idealized) Broadcast range
Irrelevant vehicles in radio range for few seconds Passing vehicle, in radio range for tens of seconds Following vehicle, in radio range for minutes
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Packets carry perimeter and
directional information
Location-based assignment of
delay: T_delay = Max_delay * GaussianRV((1- progress), 0.3)
Timer-based suppression of
multiple rebroadcasts
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200 vehicles distributed
DSRC MAC parameters Location-based
forwarding shows improved packet delivery rate and efficiency
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Motivation
Vehicles sporadically disconnected from infrastructure, requires self-organization Storage (e.g., flash) becoming increasingly affordable
Location-based clustering and channel assignment
Vehicles select channel and node cluster based on a predefined geographic
channel map
Allows remote monitoring and management Map can be updated periodically (e.g., daily, weekly)
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John Doe 1234 Main St Anywhere, US (515110X 4300483Y, 13Z)
Geocoded Address Database (TIGER/LINE):
[515110X 4300483Y 13Z]
Identification based
subpoenas not necessary
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MAC
Network Applications On-Device Localization Location Service Location Cloaking
Maximum resolution shared with 1- hop neighbors Medium resolution shared throughout local network Coarse resolution throughout Internet Accuracy reduction
Access Control Silent Periods
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: original location samples : perturbed location samples : perturbation area : path confusion
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real difference and it expose challenging requirements
Location information is an integral part of or can help to solve
Need for a location architecture
architecture