TY - GEN
T1 - A Lightweight and Secure Vehicular Edge Computing Framework for V2X Services
AU - Ramneek,
AU - Pack, Sangheon
N1 - Funding Information:
ACKNOWLEDGMENT This work is supported by National Research Foundation (NRF) grant funded by the Korean Government (No. 2020R1I1A1A01066031 and 2020R1A2C3006786).
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Vehicle-to-everything (V2X) communications over cellular networks have a great potential for enabling intelligent transportation systems (ITSs), and supporting advanced services such as autonomous driving. However, such services have stringent QoS and security/privacy requirements. Even though the use of blockchain can ensure security and privacy for V2X services, blockchain-based solutions suffer from the issues of high latency, low scalability, and high computation power for mining. To overcome these challenges, we propose a lightweight and secure vehicular edge computing framework. The LS-VEC framework leverages directed acyclic graphs (DAGs) for recording transactions for edge resource allocation and micro-transactions for pricing VEC resources. In addition, an auction theory-based game-theoretic approach is proposed for allocation and pricing of edge resources used for supporting computation offloading.
AB - Vehicle-to-everything (V2X) communications over cellular networks have a great potential for enabling intelligent transportation systems (ITSs), and supporting advanced services such as autonomous driving. However, such services have stringent QoS and security/privacy requirements. Even though the use of blockchain can ensure security and privacy for V2X services, blockchain-based solutions suffer from the issues of high latency, low scalability, and high computation power for mining. To overcome these challenges, we propose a lightweight and secure vehicular edge computing framework. The LS-VEC framework leverages directed acyclic graphs (DAGs) for recording transactions for edge resource allocation and micro-transactions for pricing VEC resources. In addition, an auction theory-based game-theoretic approach is proposed for allocation and pricing of edge resources used for supporting computation offloading.
KW - 5G
KW - DAG
KW - V2X
KW - VEC
UR - http://www.scopus.com/inward/record.url?scp=85140931025&partnerID=8YFLogxK
U2 - 10.1109/ICDCS54860.2022.00146
DO - 10.1109/ICDCS54860.2022.00146
M3 - Conference contribution
AN - SCOPUS:85140931025
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 1316
EP - 1317
BT - Proceedings - 2022 IEEE 42nd International Conference on Distributed Computing Systems, ICDCS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 42nd IEEE International Conference on Distributed Computing Systems, ICDCS 2022
Y2 - 10 July 2022 through 13 July 2022
ER -