Learning-Based Task Offloading for Mobile Edge Computing
Author:
Affiliation:
1. University of Quebec at Montreal,Department of Computer Science,QC,Canada
2. University of Carthage,National Institute of Applied Sciences and Technology,Tunis,Tunisia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9837954/9838246/09838831.pdf?arnumber=9838831
Reference18 articles.
1. Cache-Aided NOMA Mobile Edge Computing: A Reinforcement Learning Approach
2. Deep Reinforcement Learning-based Task Offloading Decision in the Time Varying Channel
3. Delay-Sensitive Task Offloading for Internet of Things in Nonorthogonal Multiple Access MEC Networks;dat tuong;Proc IEEE ICTC,2020
4. Adaptive Task Partitioning at Local Device or Remote Edge Server for Offloading in MEC
5. Offloading Schemes in Mobile Edge Computing for Ultra-Reliable Low Latency Communications;jianhui;IEEE Access,2018
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1. MOGR: Multi-task Offloading via Graph Representation in Heterogeneous Computing Network;ICC 2024 - IEEE International Conference on Communications;2024-06-09
2. Efficient End–Edge–Cloud Task Offloading in 6G Networks Based on Multiagent Deep Reinforcement Learning;IEEE Internet of Things Journal;2024-06-01
3. Optimizing Task Processing Efficiency in MEC Networks Through Cooperative Offloading and Resource Allocation;2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE);2024-05-10
4. Road Side Unit-Assisted Learning-Based Partial Task Offloading for Vehicular Edge Computing System;IEEE Transactions on Vehicular Technology;2023
5. $\mu$-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning Technique for Service Offloading in Fog computing Environments;IEEE Transactions on Services Computing;2023
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