Abstract
Mobile edge computing (MEC) caches data and services from remote cloud to the edge of network. In this way, MEC lets user equipment (UE) more closer to data and services than traditional cloud computing. Service providers (SPs) deploy their own base stations (BSs) to provide high quality services to their subscribers in MEC networks. SPs get their total revenue from their subscribers, but face the cost of energy and acquiring resources. In this paper, we attempt to maximize the final profit of SPs base on a novel resource allocation method to cut down the cost of energy and acquiring resources. The simulation results indicate that our scheme increases the final profit of SPs, compared to the existing methods.
| Original language | English |
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| Title of host publication | Combinatorial Optimization and Applications |
| Subtitle of host publication | 14th International Conference, COCOA 2020, Proceedings |
| Editors | Weili Wu, Zhongnan Zhang |
| Publisher | Springer Nature |
| Pages | 657-668 |
| ISBN (Electronic) | 978-3-030-64843-5 |
| ISBN (Print) | 978-3-030-64842-8 |
| DOIs | |
| Publication status | Published - Dec 2020 |
| Event | 14th International Conference on Combinatorial Optimization and Applications, COCOA 2020 - Virtual, Dallas, United States Duration: 11 Dec 2020 → 13 Dec 2020 https://theory.utdallas.edu/COCOA2020/index.html |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Theoretical Computer Science and General Issues) |
|---|---|
| Volume | 12577 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Conference | 14th International Conference on Combinatorial Optimization and Applications, COCOA 2020 |
|---|---|
| Place | United States |
| City | Dallas |
| Period | 11/12/20 → 13/12/20 |
| Internet address |
Research Keywords
- Mobile edge computing
- Profit maximization
- Resource allocation