VITP and CARS: A Distributed Service Model and Rate Adaptation for VANETs Liviu Iftode Department of Computer Science Rutgers University.

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Presentation transcript:

VITP and CARS: A Distributed Service Model and Rate Adaptation for VANETs Liviu Iftode Department of Computer Science Rutgers University

From Vehicular Applications to Services, Security and Networking VANET Applications based on C2C VANET Applications based on C2C TrafficView (MDM’04, ACM MC2R’04) TrafficView (MDM’04, ACM MC2R’04) EZCab (PerCom’06) EZCab (PerCom’06) Adaptive Traffic Lights (VTC’07) Adaptive Traffic Lights (VTC’07) Highways with Reservation Lanes (ITCS’07) Highways with Reservation Lanes (ITCS’07) Content Sharing for In-Car Entertainment Content Sharing for In-Car Entertainment Vehicular Services Vehicular Services Vehicular Information Transfer Protocol (VITP) (Vanet’05, IEEE JSAC’07)) Vehicular Information Transfer Protocol (VITP) (Vanet’05, IEEE JSAC’07)) Context-aware Migratory Services (IEEE TMC’07) Context-aware Migratory Services (IEEE TMC’07) Security Issues in VANET Security Issues in VANET Probabilistic Validation of Data Aggregation (Vanet’06) Probabilistic Validation of Data Aggregation (Vanet’06) Trusted Application-Centric Ad-Hoc Networks (MASS’07) Trusted Application-Centric Ad-Hoc Networks (MASS’07) Traffic-Driven Cross-Layer Optimization in VANET Traffic-Driven Cross-Layer Optimization in VANET Context-aware Transmission Rate Selection (CARS) Context-aware Transmission Rate Selection (CARS) For more information: For more information: Vehicular Applications Services Security Networking

The TrafficView Application Improve driving safety Improve driving safety Provides driver with a real-time view of the traffic ahead Provides driver with a real-time view of the traffic ahead Prototype demonstrated in real traffic conditions Prototype demonstrated in real traffic conditions

1. Location-Aware Vehicular Services Many VANET applications follow a client-server model Many VANET applications follow a client-server model Centralized vehicular services Centralized vehicular services Expensive to support Expensive to support Limited time and space granularity Limited time and space granularity Distributed services over VANET Distributed services over VANET Based on C2C communication Based on C2C communication Any car can be a client or an ad-hoc server for a request Any car can be a client or an ad-hoc server for a request Stateless or Stateful Stateless or Stateful Require a trusted service architecture Require a trusted service architecture

Vehicular Information Transfer Protocol (VITP) Application-layer protocol similar to HTTP Application-layer protocol similar to HTTP VITP Peers VITP Peers VITP-enabled vehicles VITP-enabled vehicles VITP clients and VITP Servers VITP clients and VITP Servers VITP Messages VITP Messages Carry location-oriented requests and replies between VITP peers Carry location-oriented requests and replies between VITP peers Updated by VITP Servers to store state of VITP transaction Updated by VITP Servers to store state of VITP transaction Examples of VITP URI Examples of VITP URI METHOD VITP/ METHOD VITP/ Target: [rd_id_dest,seg_id_dest] From: [rd_id_src,seg_id_src] with From: [rd_id_src,seg_id_src] with Time: Time: Expires: Expires: Cache-Control: Cache-Control: TTL: TTL: msgID: msgID: Content-Length: Content-Length: CRLF VITP Message Format GET /vehicle/traffic?[cnt=10&tout=2000ms]&tframe=3min GET /service/gas?[cnt=4&tout=1800ms]&price<2USD POST /vehicle/alert?[cnt=*&tout=*]&type=slippery-road

Virtual Ad-Hoc Servers (VAHS) Gas Station Coffee place Dynamic collection of VITP peers in the target location of Q that collaborate to resolve Q until its Return Condition is satisfied Dynamic collection of VITP peers in the target location of Q that collaborate to resolve Q until its Return Condition is satisfied Q

VITP Transactions VITP Peer VANET node VAHS Q Q Intermediary nodes Q1 Q2 Q3 Q4 Q5 Q6 Q7 R R R Dispatch-query phaseVAHS-computation phase Dispatch-Reply phase Reply-delivery phase

Accuracy vs. Return Condition Evaluation of VITP in the IEEE JSAC paper (joint work with University of Cyprus, to appear in 2007) Evaluation of VITP in the IEEE JSAC paper (joint work with University of Cyprus, to appear in 2007)

2. Transmission Rate Adaptation for Vehicular Ad-Hoc Networks Content-sharing applications require good throughput Content-sharing applications require good throughput Higher bitrates + high quality links = transmit more data Higher bitrates + high quality links = transmit more data Higher bitrates + low quality links = higher loss probability Higher bitrates + low quality links = higher loss probability Transmission Rate Adaptation Transmission Rate Adaptation Which bit rate provides the maximum throughput? Which bit rate provides the maximum throughput? When to switch to another bit rate? When to switch to another bit rate? Existing solutions in wireless networks are reactive Existing solutions in wireless networks are reactive Use physical and link layer metrics as estimates of channel quality Use physical and link layer metrics as estimates of channel quality Incur time delay due to sampling interval: slow for VANET Incur time delay due to sampling interval: slow for VANET Do not account for various dynamics in VANETs caused by fading and mobility Do not account for various dynamics in VANETs caused by fading and mobility Idea: Use VANET application context information to select the best transmission rate Idea: Use VANET application context information to select the best transmission rate

Context-Aware Rate Selection (CARS) for Vehicular Ad-Hoc Networks Model the effect of context information on bit error rate starting from real experiments Model the effect of context information on bit error rate starting from real experiments Use current context information (speed, distance between cars, density) to proactively select the best transmission rate Use current context information (speed, distance between cars, density) to proactively select the best transmission rate

CARS vs. SampleRate: Detailed Comparison

Throughput: CARS vs SampleRate