System revenue maximization for offloading decisions in mobile edge computing

Juan Zhang, Yulei Wu, Geyong Min

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

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.
Original languageEnglish
Title of host publicationICC 2021 - IEEE International Conference on Communications
Place of PublicationPiscataway, US
PublisherIEEE
Pages2573-2578
Number of pages6
ISBN (Electronic)9781728171227
ISBN (Print)9781728171234
DOIs
Publication statusPublished - 14 Jun 2021
Externally publishedYes
EventICC 2021 - IEEE International Conference on Communications - Montreal, QC, Canada
Duration: 14 Jun 202123 Jun 2021

Publication series

NameIEEE International Conference on Communications
PublisherIEEE
ISSN (Print)1550-3607
ISSN (Electronic)1938-1883

Conference

ConferenceICC 2021 - IEEE International Conference on Communications
Period14/06/2123/06/21

Cite this