Conclusion and Future Work

Zehua Guo

doi:10.1007/978-981-19-4874-9_6

Conclusion and Future Work

Zehua Guo^*

^*此作品的通讯作者

自动化学院

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

摘要

In this book, we introduce two critical application scenarios for SDN: SD-WANs and SD-DCNs. To improve network performance of SD-WANs and SD-DCNs, we leverage emerging ML techniques (i.e., DRL, MARL, and GNN) to maintain the load balance, increase the power efficiency, and improve the QoS. This book exhibits the effectiveness of ML for solving networking problems and paves the way for the future research on the usage of DRL, MARL, and GNN for computer networks.

源语言	英语
主期刊名	SpringerBriefs in Computer Science
出版商	Springer
页	67-68
页数	2
DOI	https://doi.org/10.1007/978-981-19-4874-9_6
出版状态	已出版 - 2022

出版系列

姓名	SpringerBriefs in Computer Science
ISSN（印刷版）	2191-5768
ISSN（电子版）	2191-5776

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10.1007/978-981-19-4874-9_6

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Guo, Z. (2022). Conclusion and Future Work. 在 SpringerBriefs in Computer Science (页码 67-68). (SpringerBriefs in Computer Science). Springer. https://doi.org/10.1007/978-981-19-4874-9_6

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Conclusion and Future Work

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