System Revenue Maximization for Offloading Decisions in Mobile Edge Computing

被引:0
作者
Zhang, Juan [1 ]
Wu, Yulei [1 ]
Min, Geyong [1 ]
机构
[1] Univ Exeter, Coll Engn Math & Phys Sci, Exeter EX4 4QF, Devon, England
来源
IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021) | 2021年
关键词
Revenue maximization; offloading; mobile edge computing; energy consumption; game theory; ENERGY; MODEL;
D O I
10.1109/ICC42927.2021.9500485
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Offloading decisions in mobile edge computing have been extended with multiple objectives, such as revenue maximization, energy conservation and latency reduction. Revenues of network/service operators, as the realistic and ultimate goal at intensive competitive markets, have not been thoroughly studied under a pricing scheme in combination with offloading decisions, especially with the aims of reducing and restricting energy consumption and latency. To bridge this important gap, this paper studies the revenue maximization of network operators through a pricing scheme in mobile edge computing, by explicitly formulating energy consumption and latency into the offloading strategy. A two-stage game-theory framework based on the Stackelberg game is established, through which the optimal price for both the network operator and the customer can be reached. The offloading data size can be dynamically adjusted according to the agreed price. The existence of equilibrium in the Stackelberg game is proved, and experiments are conducted to verify the effectiveness of our proposed model.
引用
收藏
页数:6
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