TY - GEN
T1 - Cost-Efficient Edge Cloud Deployment Method for Autonomous Driving
AU - Park, Changyu
AU - Ko, Haneul
AU - Kyung, Yeunwoong
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - When edge clouds are deployed at all road side unit (RSU), autonomous vehicles (AVs) can offload the tasks and receive the results of the tasks with low latency. However, too excessive deployment of edge clouds can lead significant capital expenditure (CAPEX) of an offloading service provider. In this paper, we propose a cost-efficient edge cloud deployment method where the deployment locations of edge clouds are minimally decided by considering task offloading rates of road segments. To minimize the number of deployed edge clouds while supporting all generated traffic volumes, we formulate an integer non-linear programming (INLP) problem. For the practical deployment even at a huge target area, we propose a low-complexity heuristic algorithm called traffic-aware deployment algorithm (TADA). Evaluation results demonstrate that TADA can achieve a similar deployment cost with the optimal solution while handling all generated traffic.
AB - When edge clouds are deployed at all road side unit (RSU), autonomous vehicles (AVs) can offload the tasks and receive the results of the tasks with low latency. However, too excessive deployment of edge clouds can lead significant capital expenditure (CAPEX) of an offloading service provider. In this paper, we propose a cost-efficient edge cloud deployment method where the deployment locations of edge clouds are minimally decided by considering task offloading rates of road segments. To minimize the number of deployed edge clouds while supporting all generated traffic volumes, we formulate an integer non-linear programming (INLP) problem. For the practical deployment even at a huge target area, we propose a low-complexity heuristic algorithm called traffic-aware deployment algorithm (TADA). Evaluation results demonstrate that TADA can achieve a similar deployment cost with the optimal solution while handling all generated traffic.
KW - autonomous driving
KW - capital expenditure (CAPEX)
KW - deployment
KW - Edge cloud
KW - integer non-linear programming
UR - http://www.scopus.com/inward/record.url?scp=85143252616&partnerID=8YFLogxK
U2 - 10.1109/ICTC55196.2022.9952764
DO - 10.1109/ICTC55196.2022.9952764
M3 - Conference contribution
AN - SCOPUS:85143252616
T3 - International Conference on ICT Convergence
SP - 789
EP - 792
BT - ICTC 2022 - 13th International Conference on Information and Communication Technology Convergence
PB - IEEE Computer Society
T2 - 13th International Conference on Information and Communication Technology Convergence, ICTC 2022
Y2 - 19 October 2022 through 21 October 2022
ER -