Optimization method of task uninstallation in mobile edge computing environment combining improved deep Q-learning and transmission learning
Abstract Traditional task uninstallation methods are difficult to cope with the continuous changes in network environment and device status, therefore a more intelligent solution is urgently needed. This article studied the optimization method of task uninstallation in mobile edge computing (MEC) en...
        Saved in:
      
    
          | Main Authors: | Lihong Zhao, Shuqin Wang, Xiaomei Ding | 
|---|---|
| Format: | Article | 
| Language: | English | 
| Published: | Springer
    
        2024-12-01 | 
| Series: | Discover Applied Sciences | 
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-024-06396-x | 
| Tags: | Add Tag 
      No Tags, Be the first to tag this record!
   | 
Similar Items
- 
                
                    A deep Q-learning model for sequential task offloading in edge AI systems        
                          
 by: Dong Liu, et al.
 Published: (2024-09-01)
- 
                
                    Research on task offloading algorithm of mobile edge computing based on deep reinforcement learning in SDCN        
                          
 by: Shouhua JIANG, et al.
 Published: (2024-02-01)
- 
                
                    Efficient task migration and resource allocation in cloud–edge collaboration: A DRL approach with learnable masking        
                          
 by: Yang Wang, et al.
 Published: (2025-01-01)
- 
                
                    Maritime mobile edge computing offloading method based on deep reinforcement learning        
                          
 by: Xin SU, et al.
 Published: (2022-10-01)
- 
                
                    Task offloading optimization in mobile edge computing based on a deep reinforcement learning algorithm using density clustering and ensemble learning        
                          
 by: Yi Qin, et al.
 Published: (2025-01-01)
 
       