TY - GEN
T1 - A game theoretical pricing scheme for vehicles in vehicular edge computing
AU - Tang, Chaogang
AU - Zhu, Chunsheng
AU - Wu, Huaming
AU - Wei, Xianglin
AU - Li, Qing
AU - Rodrigues, Joel J.P.C.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - Vehicular edge computing (VEC) brings the computing resources to the edge of the networks and thus provisions better computing services to the vehicles in terms of response latency. Meanwhile, the edge server can earn their revenues by leasing the computing resources. However, a higher price does not always bring forth more benefits for the edge server in VEC, since it may discourage vehicles from renting more computing resources from VEC. To the best of our knowledge, few of previous works have focused on the real-time pricing problem for VEC. We investigate in this paper the pricing problem from the viewpoints of both vehicles and the edge server, so as to optimize the utility values and revenues of vehicles and the edge server, respectively. We resort to the Stackelberg game for modeling the interactions between vehicles and edge server, and a distributed algorithm for this pricing problem is proposed in the paper. Experimental results have displayed the efficiency and effectiveness of the proposed algorithm.
AB - Vehicular edge computing (VEC) brings the computing resources to the edge of the networks and thus provisions better computing services to the vehicles in terms of response latency. Meanwhile, the edge server can earn their revenues by leasing the computing resources. However, a higher price does not always bring forth more benefits for the edge server in VEC, since it may discourage vehicles from renting more computing resources from VEC. To the best of our knowledge, few of previous works have focused on the real-time pricing problem for VEC. We investigate in this paper the pricing problem from the viewpoints of both vehicles and the edge server, so as to optimize the utility values and revenues of vehicles and the edge server, respectively. We resort to the Stackelberg game for modeling the interactions between vehicles and edge server, and a distributed algorithm for this pricing problem is proposed in the paper. Experimental results have displayed the efficiency and effectiveness of the proposed algorithm.
KW - Distributed
KW - Edge server
KW - Pricing
KW - Stackelberg game
KW - Vehicular edge computing
UR - http://www.scopus.com/inward/record.url?scp=85104619377&partnerID=8YFLogxK
U2 - 10.1109/MSN50589.2020.00020
DO - 10.1109/MSN50589.2020.00020
M3 - Conference article published in proceeding or book
AN - SCOPUS:85104619377
T3 - Proceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020
SP - 17
EP - 22
BT - Proceedings - 2020 16th International Conference on Mobility, Sensing and Networking, MSN 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th International Conference on Mobility, Sensing and Networking, MSN 2020
Y2 - 17 December 2020 through 19 December 2020
ER -