pdf, 2015-06-21

Part 3: Car-­‐to-­‐X Networking BEACONING OR 1-­‐HOP BROADCAST [C2X] Summer 2015 Beaconing 1 Let’s Recap ² 
Coopera?ve Awareness Message ª 
ª 
Periodic (up to 10Hz) safety message Informa?on on state of surrounding vehicles: §  Speed, loca?on, … ª 
Message age highly relevant for safety §  Need mechanisms to discard old messages ² 
Same for SOTIS ² 
… but [C2X] Summer 2015 Beaconing 2 Beaconing ² 
Open issues 1. 
2. 
3. 
² 
Real networks are heterogeneous 1. 
2. 
3. 
² 
Infrastructure-­‐less opera?on: needs high marked penetra?on Required/tolerable beacon interval highly dependent on scenario Design needs dedicated channel capacity Roadside infrastructure present vs. absent Freeway scenario vs. inner city Own protocol ⇔ other, future, and legacy protocols How to do beYer? 1. 
2. 
3. 
Dynamically incorporate op?onal infrastructure Dynamically adapt beacon interval Dynamically use all free(!) channel capacity [C2X] Summer 2015 Beaconing 3 Adap?ve Traffic Beacon (ATB) ² 
Adap?ve use of infrastructure  
+ 
+ 
Independent opera?on Road Side Units Traffic Informa?on Center uplink [1] C. Sommer, O. K. Tonguz, F. Dressler, "Traffic Information Systems: Efficient Message Dissemination via Adaptive Beaconing,"
IEEE Communications Magazine, vol. 49 (5), pp. 173-179, May 2011
[C2X] Summer 2015 Beaconing 4 Adap?ve Traffic Beacon (ATB) Adap?ve selec?on of beacon interval ΔI ª 
ª 
Choose interval from range Imin to Imax
ª 
Use factor wI to increase weight of C (ex. wI=0.75) ΔI = ((1 – wI) × P 2 + (wI × C 2)) × (Imax – Imin) + Imin
1
0.75
I 0.5
0.25
0
P
[C2X] Summer 2015 Beaconing 0
0.2
0.4
0.6
0.8
1
ª 
0.2
² 
Consider message u?lity P Consider channel quality C 1
0.8
0.6
0.4
² 
C
5 Adap?ve Traffic Beacon (ATB) ² 
Adap?ve selec?on of beacon interval ΔI ª 
Calcula?on of message u?lity P based on metrics of (ex.) § 
§ 
§ 
§ 
ª 
A: age of informa?on De: distance to source of informa?on Dr: distance to closest Road Side Unit (RSU) B: ra?o of beacon contents received from Road Side Unit (RSU) Calcula?on of channel quality C based on metrics of (ex.) §  N: (es?mated) number of neighbors (à future )
§  S: (observed) signal-­‐to-­‐noise ra?o (à present ) §  K: (measured) collisions on channel (à past )
P=
[C2X] Summer 2015 A + De + Dr
×B
3
Beaconing C=
N + wC (S + K ) / 2
1+ wC
6 Envisioned Scenario ² 
Highly dynamic network [C2X] Summer 2015 Beaconing 7 Simula?ve Performance Analysis ² 
Comparison with regular beaconing ª 
Latency: [C2X] Summer 2015 Beaconing 8 Simula?ve Performance Analysis ² 
Comparison with regular beaconing ª 
Channel load: [C2X] Summer 2015 Beaconing 9 ETSI ITS G5 ² 
DCC ª 
ª 
ª 
Core feature of ETSI ITS G5 Adap?ve parameteriza?on to avoid overload Configurable parameters per AC: § 
§ 
§ 
§ 
ª 
TX power Minimum packet interval Sensi?vity of CCA (Clear Channel Assessment) Data rate State machine determines which parameters are selected; available states: §  Relaxed §  Ac?ve (mul?ple sub states) §  Restric?ve [C2X] Summer 2015 Beaconing 10 ETSI ITS G5 ² 
DCC ª 
State machine for Control Channel: ª 
min/maxChannelLoad(x): record frac?on of ?me in [tnow-­‐x .. tnow] that channel was sensed busy subdivide interval into equal parts (e.g. 50 ms), take min/max Channel busy ⬄ measured received power (signal or noise) above configured sensibility ª 
[C2X] Summer 2015 Beaconing 11 ETSI ITS G5 ² 
DCC ª 
ª 
State machine for Service Channel: Ac?ve state subdivided into up to 4 sub states [C2X] Summer 2015 Beaconing 12 ETSI ITS G5 ² 
DCC Selec?on of parameters when changing states Example: Control Channel ª  “ref”: Value remains unchanged ª 
State
Relaxed
Active
Restrictive
AC_VI
AC_VO
AC_BE
AC_BK
33dBm
ref
25dBm
20dBm
15dBm
-10dBm
0,04s
ref
ref
ref
ref
1s
Data rate
3Mbit/s
ref
ref
ref
ref
12 Mbit/s
Sensitivity
-95 dBm
ref
ref
ref
ref
-65 dBm
TX power
Min pkt interval
[C2X] Summer 2015 Beaconing 13 ETSI ITS G5: Analysis and Problems ² 
Oscilla?ng channel load (both local and global!) ª 
…caused by channel access being too restric?ve (standard parameters) [1] David Eckhoff, Nikoletta Sofra and Reinhard German, "A Performance Study of Cooperative Awareness in ETSI ITS G5 and IEEE WAVE," Proceedings of 10th IEEE/
IFIP Conference on Wireless On demand Network Systems and Services (WONS 2013), Banff, Canada, March 2013.
[C2X] Summer 2015 Beaconing 14 ETSI ITS G5: Analysis and Problems ² 
Latencies ª 
Choosing minimum packet intervals (TRC) too high can introduce high latencies [1] David Eckhoff, Nikoletta Sofra and Reinhard German, "A Performance Study of Cooperative Awareness in ETSI ITS G5 and IEEE WAVE," Proceedings of 10th IEEE/
IFIP Conference on Wireless On demand Network Systems and Services (WONS 2013), Banff, Canada, March 2013.
[C2X] Summer 2015 Beaconing 15 ETSI ITS G5: Analysis and Problems ² 
Update frequency ª 
ª 
Standard parameters are too restric?ve Channel ressources are not used op?mally [1] David Eckhoff, Nikoletta Sofra and Reinhard German, "A Performance Study of Cooperative Awareness in ETSI ITS G5 and IEEE WAVE," Proceedings of 10th IEEE/
IFIP Conference on Wireless On demand Network Systems and Services (WONS 2013), Banff, Canada, March 2013.
[C2X] Summer 2015 Beaconing 16 Problem Solved? ² 
Maybe we all overlooked some issues! ² 
Antenna characteris?cs Radio signal shadowing ² 
[C2X] Summer 2015 Beaconing 17 Experimental Valida?on [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
[C2X] Summer 2015 Beaconing 18 Establishment of New Models ² 
² 
Models allow taking into considera?on (a) sta?c and (b) moving obstacles Research ques?on: What is their impact on beaconing? [C2X] Summer 2015 Beaconing 19 Towards new Beaconing Concepts ² 
DynB – Dynamic Beaconing ² 
Considering all the radio shadowing effects to adapt very quickly to the current channel quality Main idea: con?nuously observe the load of the wireless channel to calculate the current beacon interval ² 
² 
I = Ides + r (Imax – Ides)
with Imax = (N+1) Ides (N is the number of neighbors) and r = (bt / bdes) - 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
[C2X] Summer 2015 Beaconing 20 How Busy Can/Should the Channel Be? ² 
Assuming a payload of l = 512 bit (at 18 Mbit/s), we obtain tbusy = Tpreamble + Tsignal + Tsym [(16 + l + 6) / NDBPS] = 104 µs
Using a minimum AIFS and an average ini?al backoff counter, we get a maximum bt bt = tbusy / (tbusy + taifs + tidle) = 0.64
[C2X] Summer 2015 Beaconing 21 Freeway
Comparing DynB to TRC Received beacons
Suburban
Channel busy ratio
[C2X] Summer 2015 Beaconing bdes=0.25, Ides=0.01
22 Handling Dynamics in the Environment ² 
Assuming two larger clusters of vehicles mee?ng spontaneously (e.g., at intersec?ons in suburban or when two big trucks leave the freeway) [C2X] Summer 2015 Beaconing 23 Main Takeaways ² 
Beaconing ª 
² 
ATB ª 
ª 
² 
Sta?c beaconing Basic mechanism for adap?vity Conges?on control + fairness DCC ª 
ª 
State machine Conges?on control techniques §  TRC, TPC ² 
DynB ª 
Gemng more aggressive [C2X] Summer 2015 Beaconing 24