Abstract
Multi-access edge computing (MEC) system consisting of geographically-distributed heterogeneous servers can provide low-latency virtualized resource to support computation offloading of smart devices. When bulk offloading requests comes to an MEC system, how to dispatch requests to servers so as to maximize divergent objectives of MEC service providers and users is challenging. The problem further involves money transfer when different MEC service providers can share resource to each other. In this paper, we address request dispatch issues in a standalone MEC and among federated MEC systems using matching game theory. We have adapted several classical matching algorithms to our problem. Simulation results show that we can serve more requests while still meeting latency constraints. For federated MEC systems, we can also have high revenue.
Original language | English |
---|---|
Title of host publication | 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538676462 |
DOIs | |
State | Published - 04 2019 |
Externally published | Yes |
Event | 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019 - Marrakesh, Morocco Duration: 15 04 2019 → 19 04 2019 |
Publication series
Name | IEEE Wireless Communications and Networking Conference, WCNC |
---|---|
Volume | 2019-April |
ISSN (Print) | 1525-3511 |
Conference
Conference | 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019 |
---|---|
Country/Territory | Morocco |
City | Marrakesh |
Period | 15/04/19 → 19/04/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Edge Computing
- Matching Theory
- Resource Allocation