TY - JOUR
T1 - A Proactive Reliable Mechanism-Based Vehicular Fog Computing Network
AU - Dong, Luobing
AU - Ni, Qiufen
AU - Wu, Weili
AU - Huang, Chuanhe
AU - Znati, Taieb
AU - Du, Ding Zhu
N1 - Funding Information:
Manuscript received May 5, 2020; revised June 7, 2020; accepted June 30, 2020. Date of publication July 7, 2020; date of current version December 11, 2020. This work was supported in part by the National Science Foundation under Grant 1747818 and Grant 1907472; in part by the Fundamental Research Funds for Central Universities under Grant JB161004; in part by the Department of Energy under Contract DE-SC0014376; and in part by the National Science Foundation of China under Grant 61772385 and Grant 61572370. (Corresponding author: Luobing Dong.) Luobing Dong is with the School of Computer Science and Technology, Xidian University, Xi’an 710071, China (e-mail: lbdong@xidian.edu.cn).
Publisher Copyright:
© 2014 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - As vehicles are becoming more and more intelligent, mobile data traffic in vehicular ad hoc network (VANET) has been increasing dramatically. This makes the communication capacity of VANET systems and the computing resources of vehicles insufficient. In the meantime, location-aware large-scale distributed services with very low latency and high reliability are demanded by most of the novel functions, such as accident alarming, and congestion warning, in the intelligent transportation system. To meet these claimed characteristics of VANET, we first present a novel architecture that integrates vehicular fog computing and vehicle-to-vehicle (V2V) communication technologies. Lower latency and higher quality services can be supplied to vehicles by nearby fog servers, which are virtualized from vehicles that locate close enough and communicate using the V2V link. However, like all collaborative systems, computing reliability is vital to collaborative VANET. In this article, we design a novel energy-efficient proactive replication mechanism. Follower vehicles calculate with a lazy rate act as backups of host vehicles to ensure the reliability of the system. Considering the time sensitivity of computing requirements in VANET, the upper bound on the total number of failures is proposed through theoretical analysis. Then, the lower bound on the lazy calculating rate of followers is derived by balancing the tradeoffs between delay and energy. A fast algorithm for searching this lower bound based on the discrete Newton method is also proposed. Results of numerical experiments show that our new mechanism is effective in energy saving and reliability enhancing.
AB - As vehicles are becoming more and more intelligent, mobile data traffic in vehicular ad hoc network (VANET) has been increasing dramatically. This makes the communication capacity of VANET systems and the computing resources of vehicles insufficient. In the meantime, location-aware large-scale distributed services with very low latency and high reliability are demanded by most of the novel functions, such as accident alarming, and congestion warning, in the intelligent transportation system. To meet these claimed characteristics of VANET, we first present a novel architecture that integrates vehicular fog computing and vehicle-to-vehicle (V2V) communication technologies. Lower latency and higher quality services can be supplied to vehicles by nearby fog servers, which are virtualized from vehicles that locate close enough and communicate using the V2V link. However, like all collaborative systems, computing reliability is vital to collaborative VANET. In this article, we design a novel energy-efficient proactive replication mechanism. Follower vehicles calculate with a lazy rate act as backups of host vehicles to ensure the reliability of the system. Considering the time sensitivity of computing requirements in VANET, the upper bound on the total number of failures is proposed through theoretical analysis. Then, the lower bound on the lazy calculating rate of followers is derived by balancing the tradeoffs between delay and energy. A fast algorithm for searching this lower bound based on the discrete Newton method is also proposed. Results of numerical experiments show that our new mechanism is effective in energy saving and reliability enhancing.
KW - Fog computing
KW - discrete Newton method
KW - reliability
KW - vehicle-to-vehicle (V2V)
KW - vehicular ad hoc network (VANET)
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U2 - 10.1109/JIOT.2020.3007608
DO - 10.1109/JIOT.2020.3007608
M3 - Article
AN - SCOPUS:85097836126
SN - 2327-4662
VL - 7
SP - 11895
EP - 11907
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 12
M1 - 9134380
ER -