Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction
With the rapid deployment of edge base stations and the widespread application of 5G technology, Mobile Edge Computing (MEC)has gradually transitioned from a theoretical concept to practical implementation, playing a key role in emerging human-machine interactions and innovative mobile applications....
Saved in:
| Main Authors: | Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/10/3025 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Joint optimization strategy of service cache and resource allocation in mobile edge network
by: Long LONG, et al.
Published: (2023-01-01) -
Data-intensive service deployment based on edge computing
by: Yongmei GAO, et al.
Published: (2019-07-01) -
Data-intensive service deployment based on edge computing
by: Yongmei GAO, et al.
Published: (2019-07-01) -
Microservice selection approach for mobile users in edge computing environment
by: ZHAO Shuxu, et al.
Published: (2025-05-01) -
Energy-efficient device selection and resource allocation for edge-driven hierarchical federated learning
by: Yongwen Liu, et al.
Published: (2025-09-01)