Research on Edge Computing Offloading Based on Reinforcement Learning in Multi-user Scenarios
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-31275-5_11
Reference12 articles.
1. Saeik, F., et al.: Task offloading in edge and cloud computing: a survey on mathematical, artificial intelligence and control theory solutions. Comput. Netw. 195, 108177 (2021)
2. Mach, P., Becvar, Z.: Mobile edge computing: a survey on architecture and computation offloading. IEEE Commun. Surv. Tutor. 19(3), 1628–1656 (2017)
3. Zhang, Z., Li, S.: A survey of computational offloading in mobile cloud computing. In: 2016 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud), pp. 81–82. IEEE (2016). https://doi.org/10.1109/MobileCloud.2016.15
4. Zhang, G., Zhang, S., Zhang, W., Shen, Z., Wang, L.: Joint service caching, computation offloading and resource allocation in mobile edge computing systems. IEEE Trans. Wirel. Commun. 20(8), 5288–5300 (2021)
5. Zhan, Y., Guo, S., Li, P., Zhang, J.: A deep reinforcement learning based offloading game in edge computing. IEEE Trans. Comput. 69(6), 883–893 (2020)
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