A computing allocation strategy for Internet of things’ resources based on edge computing
In order to meet the demand for efficient computing services in big data scenarios, a cloud edge collaborative computing allocation strategy based on deep reinforcement learning by combining the powerful computing capabilities of cloud is proposed. First, based on the comprehensive consideration of...
Saved in:
Main Author: | Zengrong Zhang |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-12-01
|
Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/15501477211064800 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Cooperative Overbooking-Based Resource Allocation and Application Placement in UAV-Mounted Edge Computing for Internet of Forestry Things
by: Xiaoyu Li, et al.
Published: (2024-12-01) -
Computing Resource Allocation Strategy Using Biological Evolutionary Algorithm in UAV-Assisted Mobile Edge Computing
by: Li Wang, et al.
Published: (2022-01-01) -
Energy-Efficient Distributed Edge Computing to Assist Dense Internet of Things
by: Sumaiah Algarni, et al.
Published: (2025-01-01) -
Joint Resource Allocation Optimization of Wireless Sensor Network Based on Edge Computing
by: Jie Liu, et al.
Published: (2021-01-01) -
An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment
by: Hao Liu
Published: (2022-01-01)