References
- Lim, D., I. Joe. A DRL-Based Task Offloading Scheme for Server Decision-Making in Multi-Access Edge Computing. – Electronics, Vol. 12, 2023, No 18, 3882.
- Wu, Z., Z. Jia, X. Pang, S. Zhao. Deep Reinforcement Learning-Based Task Offloading and Load Balancing for Vehicular Edge Computing. – Electronics, Vol. 13, 2024, No 8, 1511.
- Tütüncüoğlu, F. G. Dán. Joint Resource Management and Pricing for Task Offloading in Serverless Edge Computing. – IEEE Transactions on Mobile Computing, Vol. 23, 2023, No 6, pp. 7438-7452.
- Hao, H., C. Xu, W. Zhang, S. Yang, G. M. Muntean. Joint Task Offloading, Resource Allocation, and Trajectory Design for Multi-Uav Cooperative Edge Computing with Task Priority. – IEEE Transactions on Mobile Computing, Vol. 23, 2024, No 9, pp. 8649-8663.
- Li, N., L. Zhai, Z. Ma, X. Zhu, Y . Li . Lyapunov-Guided Deep Reinforcement Learning for Service Caching and Task Offloading in Mobile Edge Computing. – Computer Networks, Vol. 250, 2024, 110593.
- An, X., Y. Li, Y. Chen, T. Li. Joint Task Offloading and Resource Allocation for Multi-User Collaborative Mobile Edge Computing. – Computer Networks, Vol. 250, 2024, 110604.
- Cheng, C., L. Zhai, X. Zhu, Y. Jia, Y. Li. Dynamic Task Offloading and Service Caching Based on Game Theory in Vehicular Edge Computing Networks. – Computer Communications, Vol. 224, 2024, pp. 29-41.
- Zhang, Z., F. Zhang, M. Cao, C. Feng, D. Chen. Enhancing UAV-Assisted Vehicle Edge Computing Networks through a Digital Twin-Driven Task Offloading Framework. – Wireless Networks, Vol. 31, 2024, No 1, pp. 965-981.
- Liu, X., J. Zheng, Y. Li, M. Zhang, R. Wang, Y. He. Multi-Path Serial Tasks Offloading Strategy and Dynamic Scheduling Optimization in Vehicular Edge Computing Networks. – Vehicular Communications, Vol. 49, 2024, 100827.
- Min, H., A. M. Rahmani, P. Ghaderkourehpaz, K. Moghaddasi, M. Hosseinzadeh. A Joint Optimization of Resource Allocation Management and Multi-Task Offloading in High-Mobility Vehicular Multi-Access Edge Computing Networks. – Ad Hoc Networks, Vol. 166, 2025, 103656.
- Ju, T., L. Li, S. Liu, Y. Zhang. A Multi-UAV-Assisted Task Offloading and Path Optimization for Mobile Edge Computing via Multi-Agent Deep Reinforcement Learning. – Journal of Network and Computer Applications, Vol. 229, 2024, 103919.
- Liu, J., Y. Wang, D. Pan, D. Yuan. QoS-Aware Task Offloading and Resource Allocation Optimization in Vehicular Edge Computing Networks via MADDPG. – Computer Networks, Vol. 242, 2024, 110282.
- Wang, S., S. Zhao, H. Gui, X. He, Z. Lu, B. Chen, Z. Fan, S. Pang. Energy-Efficient Collaborative Task Offloading in Multi-Access Edge Computing Based on Deep Reinforcement Learning. – Ad Hoc Networks, Vol. 169, 2025, 103743.
- Zhang, S. H., J. S. Wang, S. W. Zhang, Y. X. Xing, X. T. Wang, X. F. Sui. MOSO: Multi-Objective Snake Optimizer with Density Estimation and Grid Indexing Mechanism for Edge Computing Task Offloading and Scheduling Optimization. – Cluster Computing, Vol. 28, 2025, No 4, 244.
- Tolba, B., M. Abo-Zahhad, M. Elsabrouty, A. Uchiyama, A. H. AbdEl-Malek. Joint User Association, Service Caching, and Task Offloading in Multi-Tier Communication/Multi-Tier Edge Computing Heterogeneous Networks. – Ad Hoc Networks, Vol. 160, 2024, 103500.
- Wang, J., M. Zhang, Q. Yin, L. Yin, Y. Peng. Multi-Agent Reinforcement Learning for Task Offloading with Hybrid Decision Space in Multi-Access Edge Computing. – Ad Hoc Networks, Vol. 166, 2025, 103671.
- Su, X., X. Fang, Z. Cheng, Z. Gong, C. Choi. Deep Reinforcement Learning Based Latency-Energy Minimization in Smart Healthcare Network. – Digital Communications and Networks, Vol. 11, 2025, No 3, pp. 795-805.
- Zhai, L., Z. Lu, J. Sun, X. Li. Joint Task Offloading and Computing Resource Allocation with DQN for Task-Dependency in Multi-Access Edge Computing. – Computer Networks, Vol. 263, 2025, 111222.
- Huang, Z., X. Wu, S. Dong. Multi-Objective Task Offloading for Highly Dynamic Heterogeneous Vehicular Edge Computing: An Efficient Reinforcement Learning Approach. – Computer Communications, Vol. 225, 2024, pp. 27-43.
- Zhu, K., S. Li, X. Zhang, J. Wang, C. Xie, F. Wu, R. Xie. An Energy-Efficient Dynamic Offloading Algorithm for Edge Computing Based on Deep Reinforcement Learning. – IEEE Access, Vol. 12, 2024, pp. 127489-127506.
- Lin, H., L. Yang, H. Guo, J. Cao. Decentralized Task Offloading in Edge Computing: An Offline-to-Online Reinforcement Learning Approach. – IEEE Transactions on Computers, Vol. 73, 2024, No 6, pp. 1603-1615.
- Alsadie, D. Efficient Task Offloading Strategy for Energy-Constrained Edge Computing Environments: A Hybrid Optimization Approach. – IEEE Access, Vol. 12, 2024, pp. 85089-85102.
- Alhartomi, M., A. Salh, L. Audah, S. Alzahrani, A. Alzahmi. Enhancing Sustainable Edge Computing Offloading via Renewable Prediction for Energy Harvesting. – IEEE Access, Vol. 12, 2024, pp. 74011-74023.
- AlAssaf, M. M., M. Qatawneh, A. AlRadhi. A Cost-Benefit Model for Feasible IoT Edge Resources Scalability to Improve Real-Time Processing Performance. – Cybernetics and Information Technologies, Vol. 24, 2024, No 4, pp. 59-77.
- Sherif, H., E. Ahmed, A. M. Kotb. Energy-Efficient and Accelerated Resource Allocation in O-RAN Slicing Using Deep Reinforcement Learning and Transfer Learning. – Cybernetics and Information Technologies, Vol. 24, 2024, No 3, pp. 132-150.