Page 68 - ITU Journal Future and evolving technologies Volume 3 (2022), Issue 2 – Towards vehicular networks in the 6G era

ITU Journal on Future and Evolving Technologies, Volume 3 (2022), Issue 2

480 480
460 TACA 460 TACA
440 Probabilistic (0.3) 440 Probabilistic (0.3)
Generate-at-will Generate-at-will
420 420
TAC 400 TAC 400
380
380
360 360
340 340
320 320
300 300
50 75 100 125 150 50 75 100 125 150
τ g (s) τ g (s)
(a) Uniform time interval (b) Poisson time interval

Fig. 15 – Performance comparisons under dynamic duration of red/green light ( + = 200) in crossroads

direction is too small or too large, it will always lead to Science and Technology Achievements Transformation
a large proportion of the red light duration in one Demonstration Project of Sichuan Province of China No.
direction at the intersection. To optimize the overall AoI, 2018CC0094; and the Fundamental Research Funds for
the overall transmission time will increase, resulting in the Central Universities No. ZYGX2019J075.
the increase of TAC. The TAC when the green light
duration is 50s and 75s is different from that when the REFERENCES
green light duration is 125s and 150s, which will affect
the transmission time of updates and which affects the
[1] Weijing Qi, Qian Li, Qingyang Song, Lei Guo, and Ab‑
TAC. In addition, no matter the proportion of green light
bas Jamalipour. “Extensive edge intelligence for fu‑
and red light duration, the TAC obtained by our method ture vehicular networks in 6G”. In: IEEE Wireless
TACA is always the smallest, which is superior to the Communications (2021), pp. 128–135.
other two update generation poli‑ cies.
[2] NHTSA. U.S. Department of Transportation
on
(RFC)
Comment
6. CONCLUSION Releases Request for (V2X) Communications.
Vehicle‑to‑Everything
In vehicular networks, the mobility of the vehicles is af‑ https://www.nhtsa.gov/press‑releases/us‑
fected by traf ic lights. We investigate the in luence of the department‑transportation‑releases‑request‑
comment‑rfc‑vehicle‑everything‑v2x.
traf ic lights on data delivery in vehicular networks with
the metric of AoI. The AoI and transmission cost is mo‑ [3] National Highway ic Safety
deled as the Total Average Cost (TAC), which is affected Administration. Vehicle‑to‑vehicle
by the generation rate at the source. Moreover, TAC is communication.
also affected by the traf ic light, since the traf ic hole https://www.nhtsa.gov/technology‑ innovation/
problem blocks the old updates and the new updates vehicle‑vehicle‑communication.
will catch up. By considering the trade‑off between AoI
[4] Biplav Choudhury, Vijay Kumar Shah, Avik Dayal,
and trans‑ mission cost, we propose a TAC‑aware
and Jeffrey H. Reed. “Joint Age of Information and
generation rate Algorithm (TACA) for the generation
Self Risk Assessment for Safer 802.11p based V2V
interval time at the source. Our intensive simulations
Networks”. In: Proc. of IEEE INFOCOM (2021).
verify the proposed algorithm, and evaluate the in luence
of the traf ic lights on AoI. In the future, we will extend [5] Yifeng Shao, Cong Liu, and Jie Wu. “Vehicular Net‑
the V2V scenario to a straight road or mesh road with works: From Theory to Practice”. In: Chapman
more traf ic lights. & Hall, 2009. Chap. Delay‑tolerant networks in
VANETs.
ACKNOWLEDGMENT [6] Sanjit Krishnan Kaul, Roy D. Yates, and Marco
Gruteser. “Real‑time status: How often should one
This work is supported by the National Key R&D
update?” In: Proc. of IEEE INFOCOM (2012).
Program of China under Grant 2021YFB3101302 and
2021YFB3101303; the National Natural Science Foun‑ [7] Kumar Saurav and Rahul Vaze. “Minimizing the
dation of China under Grant No. 62020106013 and Sum of Age of Information and Transmission Cost
61572113; Sichuan Science and Technology Program under Stochastic Arrival Model”. In: Proc. of IEEE
under Grants 2020JDTD0007 and 2020YFG0298; the INFOCOM (2021).

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