Deep Reinforcement Learning Based Routing Scheduling Scheme for Joint Optimization of Energy Consumption and Network Throughput
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Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-5692-7_10
Reference10 articles.
1. Jia, Z., Sun, Y., Liu, Q., Dai, S., Liu, C.: cRretor: an SDN-based routing scheme for data centers with regular topologies. IEEE Access 8, 116866–116880 (2020)
2. Andrews, M., Anta, A.F., Zhang, L., Zhao, W.: Routing for energy minimization in the speed scaling model. In: 2010 Proceedings IEEE INFOCOM, pp. 1–9. IEEE (2010)
3. Pointurier, Y., Brandt-Pearce, M., Subramaniam, S., Xu, B.: Cross-layer adaptive routing and wavelength assignment in all-optical networks. IEEE J. Sel. Areas Commun. 26(6), 32–44 (2008)
4. Wang, F., et al.: Traffic load balancing based on probabilistic routing in data center networks. In: 2020 International Conference on Optical Network Design and Modeling (ONDM), pp. 1–3. IEEE (2020)
5. Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (2018)
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