Protocol Design for Adaptive Inter-Vehicle Communication · 2013. 5. 29. · Adaptive Cruise...

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1 Falko Dressler University of Innsbruck JNCT Keynote 2013-05-29 Computer and Communication Systems (Lehrstuhl für Technische Informatik) Protocol Design for Adaptive Inter-Vehicle Communication Falko Dressler University of Innsbruck, Austria [email protected]

Transcript of Protocol Design for Adaptive Inter-Vehicle Communication · 2013. 5. 29. · Adaptive Cruise...

Page 1: Protocol Design for Adaptive Inter-Vehicle Communication · 2013. 5. 29. · Adaptive Cruise Control . Warning . Messages . Traffic Light Violation . Electronic ... Network Services

1 Falko Dressler University of Innsbruck

JNCT Keynote 2013-05-29

Computer and Communication Systems (Lehrstuhl für Technische Informatik)

Protocol Design for Adaptive Inter-Vehicle Communication

Falko Dressler University of Innsbruck, Austria

[email protected]

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Outline

Inter-Vehicular Communication Communication paradigms Applications

Protocols and Standards

Where do we got from DSRC/WAVE

Traffic Dissemination

One hop broadcast Adaptive beaconing Getting more realistic

Conclusions

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Communication Paradigms

Ad Hoc Multihop Broadcasting

Infrastructure-assisted Data Exchange

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Taxonomy

Wealth of applications [T. L. Willke 2009]

Non-Safety

Comfort

Entertainment Contextual Information

Traffic Information Systems

Optimal Speed Advisory

Congestion, Accident

Information

Safety Situation

Awareness

Blind Spot Warning

Adaptive Cruise Control

Warning Messages

Traffic Light Violation

Electronic Brake Light

Short-Range Radio Broadcast

Range 3G+

Cellular Cost ?

[1] G. T. L. Willke, P. Tientrakool, and N. F. Maxemchuk, "A Survey of Inter-Vehicle Communication Protocols and Their Applications," IEEE Communications Surveys and Tutorials, vol. 11 (2), pp. 3-20, 2009

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3G / 3.5G – aktiv CoCar

aktiv CoCar Goals

Investigate feasibility of Car-to-X over 3G/3.5G networks Establish business case

Cooperation of Telcos, OEMs Car manufacturers Government, automobile association

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3G / 3.5G – aktiv CoCar

Hierarchy of (logical) function blocks Reflector

blind re-broadcast of received data, copy sent upstream to CoCar Aggregator envisioned to be deployed close to roads, e.g. in base stations

Geocast Manager autonomous wide-area dissemination of messages received from upstream

CoCar Aggregator central information broker

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3G / 3.5G – aktiv CoCar

Selected performance measures Using MBMS (multicast service), emergency messages can be handled well using the FTAP (~120 ms end-to-end delay)

[1] C. Sommer, A. Schmidt, R. German, W. Koch, and F. Dressler, "Simulative Evaluation of a UMTS-based Car-to-Infrastructure Traffic Information System," Proceedings of IEEE Global Telecommunications Conference (GLOBECOM 2008), 3rd IEEE Workshop on Automotive Networking and Applications (AutoNet 2008), New Orleans, LA, December 2008

[2] C. Sommer, A. Schmidt, Y. Chen, R. German, W. Koch, and F. Dressler, "On the Feasibility of UMTS-based Traffic Information Systems," Elsevier Ad Hoc Networks, Special Issue on Vehicular Networks, vol. 8 (5), pp. 506-517, July 2010

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DSRC/WAVE

WAVE IEEE 1609.1: “Core System” IEEE 1609.2: Security

TCP / UDP

WAVE PHY

WAVE MAC and Channel Coordination

IPv6 WSMP

Man

agem

ent

Sec

urity

LLC

802.

11p 16

09.4

16

09.3

1609

.2

WAVE PHY

IEEE 1609.3: Network Services IEEE 1609.4: Channel Management

[1] Jiang, D. and Delgrossi, L., "IEEE 802.11p: Towards an international standard for wireless access in vehicular environments," Proceedings of 67th IEEE Vehicular Technology Conference (VTC2008-Spring), Marina Bay, Singapore, May 2008

[2] Uzcátegui, Roberto A. and Acosta-Marum, Guillermo, "WAVE: A Tutorial," IEEE Communications Magazine, vol. 47 (5), pp. 126-133, May 2009

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Access Control and QoS in WAVE

Use of EDCA equivalent to IEEE 802.11e EDCA DCF -> EDCA (Enhanced Distributed Channel Access) Definition of four Access Categories (AC)

AC0 (lowest) to AC3 (highest priority) Introduction of AIFS (Arbitration Inter-Frame Space) ACs define...

CWmin, CWmax, AIFS, TXOP-Limit (max. continuous channel use) Management data are transmitted using DIFS instead of an AIFS

Medium busy Data

Data

Data

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Channel Management

Channel Management Management and safety information on the Control Channel (CCH) single radios have to switch to the CCH at known times Two-way communication on the Service Channel (SCH)

Slot management Synchronization using GPS Standard: 100ms sync interval including 50ms on the CCH Slots start with a guard interval

CCH interval

CCH interval

“SCH” interval

“SCH” interval

[1] IEEE Vehicular Technology Society, "IEEE 1609.4 (Multi-channel Operation)," IEEE Std, November, 2006

t = n × 1s

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Application Layer

Car-2-Car Communication Consortium & ETSI TC ITS Not defined by DSRC/WAVE but frame formats are provided (e.g., WAVE Short Messages)

First application: Cooperative Awareness Messages (CAM)

Periodic beacons containing Time Speed Position Heading …

Fixed interval of 1 to 10 Hz (now considered up to 40 Hz)

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Simple Broadcast-based IVC

Open issues Infrastructure-less operation: needs high marked penetration Required/tolerable beacon interval highly dependent on scenario Design needs dedicated channel capacity

Real networks are heterogeneous

Roadside infrastructure present vs. absent Freeway scenario vs. inner city Own protocol ⇔ other, future, and legacy protocols

How to do better?

Dynamically incorporate optional infrastructure Dynamically adapt beacon interval Dynamically use all free(!) channel capacity

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Fully Distributed: Adaptive Traffic Beacon

Beacon interval: measure of channel quality and message priorities Infrastructure elements: RSUs of different capabilities can be included

Lightweight SSUs (service support unit) Interconnected RSUs

[1] Christoph Sommer, Ozan K. Tonguz and Falko Dressler, "Traffic Information Systems: Efficient Message Dissemination via Adaptive Beaconing," IEEE Communications Magazine, vol. 49 (5), pp. 173-179, May 2011

[2] Christoph Sommer, Ozan K. Tonguz and Falko Dressler, "Adaptive Beaconing for Delay-Sensitive and Congestion-Aware Traffic Information Systems," Proceedings of 2nd IEEE Vehicular Networking Conference (VNC 2010), Jersey City, NJ, December 2010, pp. 1-8

[3] C. Sommer, R. German, and F. Dressler, "Decentralized Traffic Information Systems and Adaptive Rerouting in Urban Scenarios," Proceedings of 29th IEEE Conference on Computer Communications (INFOCOM 2010), Demo Session, San Diego, CA, March 2010

Challenging questions • How frequently can the beacons be sent? • How frequently should the beacons be sent? • Which information should be included into the beacon?

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Beacon Interval

Interval parameter I

I = (1 – wI) x P2 + (wI x C2)

C … channel quality P … message priority wI … interval weighting

Beacon interval ΔI

ΔI = Imin + (Imax – Imin) x I

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Beacon Interval

Parameters influencing the channel quality C Number of neighbors N Observed collisions K Signal to noise ratio S

Message priority estimation P Message age A Distance to event De

Distance to next RSU Dr

Estimated knowledge of local RSU B

= 1;

neighbors # max.neighbors #min

2

N

collisions # 111

+−=K

=

2

SNR max.SNR;0maxS

c

c

w

KSwNC

+

+×+

=1

2

= 1;age messagemin

2

maxIA

−=max

RSU todistance1;0max

IvDr

= 1;

event todistancemin

2

maxIvDe

entriesunknown # 11

+=B

3re DDABP ++

×=

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Grid Scenario

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Intermediate Conclusion

Scenario independence self-organization – no topology detection or maintenance

Infrastructure independence incorporates RSUs on demand

Coexistence makes liberal use of all unused channel capacity, leaves channel “virtually unloaded” for high-priority messages

These concepts also went into standardization ETSI ITS-G5 developed DCC (Decentralized Congestion Control) with TRC (Transmit Rate Control) bt is the “busy ratio” of the channel Coarse grained measurement intervals

[1] Werner, Marc and Lupoaie, Radu and Subramanian, Sundar and Jose, Jubin, "MAC Layer Performance of ITS G5 - Optimized DCC and Advanced Transmitter Coordination," Proceedings of 4th ETSI TC ITS Workshop, Doha, Qatar, February 2012

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Problem Solved?

Maybe we all overlooked some issues! Antenna characteristics Radio signal shadowing

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Experimental Validation

[1] Christoph Sommer, David Eckhoff, Reinhard German and Falko Dressler, "A Computationally Inexpensive Empirical Model of IEEE 802.11p Radio Shadowing in Urban Environments," Proceedings of 8th IEEE/IFIP Conference on Wireless On demand Network Systems and Services (WONS 2011), Bardonecchia, Italy, January 2011, pp. 84-90

[2] David Eckhoff, Christoph Sommer, Reinhard German and Falko Dressler, "Cooperative Awareness At Low Vehicle Densities: How Parked Cars Can Help See Through Buildings," Proceedings of IEEE Global Telecommunications Conference (GLOBECOM 2011), Houston, TX, December 2011

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Establishment of New Models

Models allow taking into consideration (a) static and (b) moving obstacles Research question: What is their impact on beaconing?

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Towards new Beaconing Concepts

DynB – Dynamic Beaconing

Considering all the radio shadowing effects to adapt very quickly to the current channel quality Main idea: continuously observe the load of the wireless channel to calculate the current beacon interval

𝐼 = 𝐼des + 𝑟 𝐼max − 𝐼des with 𝐼max = 𝑁 + 1 𝐼des (𝑁 is the number of neighbors) and 𝑟 = 𝑏𝑡

𝑏𝑑𝑑𝑑− 1 clipped in [0,1]

[1] Christoph Sommer, Stefan Joerer, Michele Segata, Ozan K. Tonguz, Renato Lo Cigno and Falko Dressler, "How Shadowing Hurts Vehicular Communications and How Dynamic Beaconing Can Help," Proceedings of 32nd IEEE Conference on Computer Communications (INFOCOM 2013), Mini-Conference, Turin, Italy, April 2013

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How Busy Can/Should the Channel Be?

Assuming a payload of 𝑙 = 512 bit (at 18 Mbit/s) , we obtain

𝑡busy = 𝑇preamble + 𝑇signal + 𝑇sym16 + 𝑙 + 6𝑁DBPS

= 104 𝜇𝜇

Using a minimum AIFS and an average initial backoff counter, we get a maximum bt

𝑏𝑡 =𝑡busy

𝑡busy + 𝑡aifs + 𝑡idle≈ 0.64

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Comparing DynB to TRC (G5) Fr

eew

ay

Sub

urba

n

Channel busy ratio Received beacons

bdes=0.25, Ides=0.01

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Handling Dynamics in the Environment

Assuming two larger clusters of vehicles meeting spontaneously (e.g., at intersections in suburban or when some big trucks leave the freeway)

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Evaluation

Real-world experiments Outline only limited information about the feasibility and the performance

experiments with roughly 400 cars are planned in a German project Performance evaluation for 2%, 10%, 50%,… penetration?

Simulation Usually using standard network simulation methods

ns2/ns3, OMNeT++, GloMoSim, OPNET, …

Detailed network layers, simple “support” modules Appropriate for VANETs?

Research challenge: appropriate mobility modeling

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Mobility Modeling

Early approaches Random Waypoint Manhattan Grid Traces

Road traffic microsimulation Simulation of individual cars Exact modeling of streets, speed limits, etc.

Coupling with network simulation Pre-computation (or on-demand simulation) of road traffic Incorporation of computed traces into network simulators (can be used for real-world traces as well)

[1] C. Sommer and F. Dressler, "Progressing Towards Realistic Mobility Models in VANET Simulations," IEEE Communications Magazine, vol. 46 (11), pp. 132-137, November 2008 [2] Christoph Sommer, Reinhard German and Falko Dressler, "Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis," IEEE Transactions on Mobile

Computing, vol. 10 (1), pp. 3-15, January 2011 [3] V. Naumov, R. Baumann, and T. Gross, "An evaluation of inter-vehicle ad hoc networks based on realistic vehicular traces," Proceedings of 7th ACM International Symposium on

Mobile Ad Hoc Networking and Computing (ACM Mobihoc 2006), Florence, Italy, March 2006, pp. 108-119 [4] M. Fiore, J. Härri, F. Filali, and C. Bonnet, "Vehicular Mobility Simulation for VANETs," Proceedings of 40th Annual Simulation Symposium (ANSS 2007), March 2007, pp. 301-309

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Veins

Veins – Vehicles in Network Simulation http://veins.car2x.org/

Models

Bidirectionally-coupled simulation Incorporation of real-world street maps Flexible and fast(!) simulation Corrected Two-Ray Interference LOS Sophisticated but fast(!) building shadowing (NLOS) Vehicle shadowing Human-driver behavior

[1] Christoph Sommer, Reinhard German and Falko Dressler, "Bidirectionally Coupled Network and Road Traffic Simulation for Improved IVC Analysis," IEEE Transactions on Mobile Computing, vol. 10 (1), pp. 3-15, January 2011

[2] C. Sommer, I. Dietrich, and F. Dressler, "Realistic Simulation of Network Protocols in VANET Scenarios," Proceedings of 26th IEEE Conference on Computer Communications (INFOCOM 2007): IEEE Workshop on Mobile Networking for Vehicular Environments (MOVE 2007), Poster Session, Anchorage, AK, May 2007, pp. 139-143

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Open Research Issues

Fundamental scalability issues Non-safety data dissemination / traffic information systems

Studied for data aggregation [1] Unclear for distance-based pruning

Safety applications

Channel utilization / overload as the key challenge Partially studied for multi-channel protocols using IEEE 802.11p [2] Partially studied for adaptive beaconing [3]

[1] B. Scheuermann, C. Lochert, J. Rybicki, and M. Mauve, "A Fundamental Scalabiliy Criterion for Data Aggregation in VANETs," Proceedings of 15th ACM International Conference on Mobile Computing and Networking (ACM MobiCom 2009), Beijing, China, September 2009

[2] Intelligent Transportation Systems Committee, "IEEE Trial-Use Standard for Wireless Access in Vehicular Environments (WAVE) - Multi-channel Operation," IEEE, 1609.4, November 2006

[3] C. Sommer, O .K. Tonguz and F. Dressler, "Traffic Information Systems: Efficient Message Dissemination via Adaptive Beaconing," IEEE Communications Magazine, vol. 49 (5), pp. 173-179, May 2011

[4] F. Dressler, C. Sommer, D. Eckhoff and O. K. Tonguz, "Towards Realistic Simulation of Inter-Vehicle Communication: Models, Techniques and Pitfalls," IEEE Vehicular Technology Magazine, 2011. (to appear)

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Conclusions

Today, we studied Traffic Information Systems: Methods and Protocols

Centralized vs. Distributed Routing, P2P vs. Beaconing

Not discussed: security and privacy concerns

Strong debate about privacy vs. security

… as can be seen, there are many open challenges and research issues for another decade of V2V research