Deep Reinforcement Learning-Based Multi-node Collaborative Task Offloading Optimization in 6G Space-Air-Ground Integrated Networks
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63989-0_16
Reference14 articles.
1. Cao, X., et al.: Edge-assisted multi-layer offloading optimization of LEO satellite-terrestrial integrated networks. IEEE J. Sel. Areas Commun. 41(2), 381–398 (2023)
2. Gong, Y., Yao, H., Xiong, Z., Guo, S., Yu, F.R., Niyato, D.: Computation offloading and energy harvesting schemes for sum rate maximization in space-air-ground networks. In: GLOBECOM 2022 - 2022 IEEE Global Communications Conference, pp. 3941–3946 (2022)
3. He, L., Li, J., Wang, Y., Zheng, J., He, L.: Balancing total energy consumption and mean makespan in data offloading for space-air-ground integrated networks. IEEE Trans. Mob. Comput. 23(1), 209–222 (2024)
4. Jin, X., Hua, W., Wang, Z., Chen, Y.: A survey of research on computation offloading in mobile cloud computing. Wireless Netw. 28(4), 1563–1585 (2022)
5. Liu, H., Cao, G.: Deep reinforcement learning-based server selection for mobile edge computing. IEEE Trans. Veh. Technol. 70(12), 13351–13363 (2021)
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