VANETs. When applications drive communications. Institute of Telematics, University of Karlsruhe. Decentralized Systems and Network Services
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1 VANETs When applications drive communications Marc Torrent-Moreno, Prof. Hannes Hartenstein Decentralized Systems and Network Services Institute of Telematics, University of Karlsruhe Marc Torrent Moreno 1
2 Communications can make a difference * Source: DaimlerChrysler AG where other technologies can not help.» Annual economic impact of traffic-related accidents: >$200 billion Marc Torrent Moreno 2
3 Structure of this talk» VANETs, a brief overview Projects and Activities Key points VANETs: our perspective» D-FPAV About keeping the load on the channel under control» Packet Level Incoordination About understanding the effect of probabilistic models on higher layers Marc Torrent Moreno 3
4 VANETs, Intro» Vehicular Ad-Hoc Network comes from well known concept MANET, but commonly considers: Vehicle-to-Vehicle Vehicle-to-Infrastructure» Currently both industry and academia involved in ambitious projects motivated by governmental sponsorships Marc Torrent Moreno 4
5 Ongoing Projects Over The World Vehicle Infrastructure Integration (VII) Standardization DSRC Advanced Safety Vehicle program Car 2 Car Communication Consortium (C2CCC) Network on Wheels (NoW) Marc Torrent Moreno 5
6 Related Activities and some publicity ACM International Workshop on Vehicular Ad Hoc Networks (VANET) with MOBICOM Los Angeles, CA September And also: Vehicle-to-Vehicle Communications Workshop (V2VCOM), IEEE Intelligent Transportation Systems (ITS), IEEE Vehicular Technology Conference (VTC), IEEE Intelligent Vehicles Symposium (IV), ITS World Congress, International Workshop on Intelligent Transportation (WIT), Marc Torrent Moreno 6
7 VANETs Keypoints» USA dedicated 75MHz at 5,9Ghz band. 7 Channels of 10Mhz» OFDM decided as the lower layer technology -> p» USA is taking decisions faster: FCC defined 3 priorities in its report : Safety-of-Life, Safety, Non-Safety 1 Control channel where safety applications should reside 6 Service channels to support non-safety traffic» For car manufacturers costs are a major concern: All cars will have GPS receiver Only one transceiver? Base system without Digital Map? Marc Torrent Moreno 7
8 VANETs: Our Focus Triangle inequality Unicast 1/multi-hop: Inform. Dissemination: Safety: Ex: map-download, internet, chat Not main driver for governments Ex: traffic information Relatively easy to implement Existing competitors Ex: Coop. collision warning, inters. collision warning C2C comm. is the key enabler Highest benefit Most challenging Marc Torrent Moreno 8
9 So, how can safety be increased? Marc Torrent Moreno 9
10 In the control channel Beaconing messages: Periodically transmitted (few/s) 1-Hop Broadcast Advertise status information Position, speed Event-driven messages: Disseminate information about an unsafe situation Mutli-hop geo-broadcast Marc Torrent Moreno 10
11 First Challenge» IEEE DCF for broadcast messages is inefficient» Limited channel capacity» Potential fast moving heavy vehicular traffic conditions High number of collisions Low safety level Proposed solution: Adjust transmission power of Beacons Marc Torrent Moreno 11
12 Which power adjustment strategy addresses safety? Capacity? Marc Torrent Moreno 12
13 Which power adjustment strategy addresses safety? Capacity Connectivity? Marc Torrent Moreno 13
14 Which power adjustment strategy addresses safety? Capacity Connectivity Fairness Every vehicle needs a good estimation of the state of all closer vehicles A vehicle without a fair portion of the resources becomes a danger Marc Torrent Moreno 14
15 Which power adjustment strategy addresses safety? Max-Min Capacity Connectivity Fairness Fairness D-FPAV, Distributed Fair Tx Power Adjustment for Vehicular Environments Marc Torrent Moreno 15
16 D-FPAV, Problem Statement BL(PA) MBL BL=2 BL=3 PA: Power Assignment PA(i) Pmax: Transmission Power where PA(i) [0,1] CS range PA(1) PA(2) PA(3) PA(n)» Goal: Beaconing Max-Min Tx Power Marc Torrent Moreno 16
17 D-FPAV, Algorithm Input: Status of all nodes in CS max (pggiback status information in beacons) Step 1. Compute common maximum tx power Pi of all nodes, so BL < MBL (max-min water filling) Step 2a. Broadcast Pi to all nodes in CSmax Step 2b. Receive messages with Pi from nodes in CSmax Step 3. Compute final power level as the minimum of the received Pi Marc Torrent Moreno 17
18 D-FPAV, Scenario D-FPAV-ON 500m TRG-CRITICAL D-FPAV-OFF 500m TRG-CRITICAL D-FPAV-ON 500m Nak-CRITICAL D-FPAV-OFF 500m Nak-CRITICAL D-FPAV-ON 500m Shad-CRITICAL D-FPAV-OFF 500m Shad-CRITICAL NodeID Marc Torrent Moreno 18 Channel Busy Time Rate
19 D-FPAV, Results Probability of Message Reception D-FPAV-ON 500m TRG-CRITICAL D-FPAV-ON 500m TRG-BEACON D-FPAV-OFF 500m TRG-CRITICAL D-FPAV-OFF 500m TRG-BEACON 0.2 D-FPAV-ON 500m Shad-CRITICAL D-FPAV-ON 500m Shad-BEACON D-FPAV-OFF 500m Shad-CRITICAL D-FPAV-OFF 500m Shad-BEACON Distance [m] Distance [m] Distance [m] Distance [m] Increase of reception rates of event-driven messages at all distances Maintaining good reception rates at distances close to the sender for beaconing messages Marc Torrent Moreno 19 Probability of Message Reception Probability of Message Reception
20 Why simulation results with probabilistic propagation models look so different? Marc Torrent Moreno 20
21 IEEE Broadcast Ad Hoc Network C B A CS New flavor of the hidden terminal problem Marc Torrent Moreno 21
22 We want to understand PLI Formalization» Packet Level Incoordination, receiver perspective: In case a node A has sensed two frames from nodes B and C, i.e., the messages from B and C arrive at A s location with power greater than CS Th, we will account B s packet as uncoordinated if: t B + t PBC < t C < t B + t PBC + l B + DIFS Marc Torrent Moreno 22
23 Simulation Scenario 1200m CS = 156m Marc Torrent Moreno 23
24 Relation to Broadcast Reception Rates (Preliminary Results) 2pckts/s, CR=100m, CS=156m 4pckts/s, CR=141m, CS=212m Marc Torrent Moreno 24
25 Thank you very much for your attention! Marc Torrent Moreno 25
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