2021/10/29(Fri.) 14:20- 李奇育教授 (Prof. Chi-Yu Li) 國立陽明交通大學 資訊工程學系 (Dept. of Computer Science, NYCU) - An Experience Driven Design for IEEE 802.11ac Rate Adaptation based on Reinforcement Learning

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Date&Time : 

2021 / 10 / 29 (Fri) 14:20 - 16:20

 

Location : 

Online Course

 

Speaker : 

 李奇育教授 (Prof. Chi-Yu Li)

國立陽明交通大學 資訊工程學系 (Dept. of Computer Science, NYCU) 

 

Topic : 

An Experience Driven Design for IEEE 802.11ac Rate Adaptation based on Reinforcement Learning

 

Abstract : 

The IEEE 802.11ac supports gigabit speeds by extending 802.11n air-interface features and increases the number of rate options by more than two times. Enabling so many rate options can be a challenge to rate adaptation (RA) solutions. Particularly, they need to adapt rates to various fast-changing channels; they would suffer without scalability. In this work, we identify three limitations of current 802.11ac RAs on commodity network interface cards (NICs): no joint rate and bandwidth adaptation, lack of scalability, and no online learning capability. To address the limitations, we apply deep reinforcement learning (DRL) into designing a scalable, intelligent RA, designated as experience driven rate adaptation (EDRA). DRL enables the online learning capability of EDRA, which not only automatically identifies useful correlations between important factors and performance for the rate search, but also derives low-overhead avenues to approach highest-goodput (HG) rates by learning from experience. It can make EDRA scalable to timely locate HG rates among many rate options over time. We implement and evaluate EDRA using the Intel Wi-Fi driver and Google TensorFlow on Intel 802.11ac NICs. The evaluation result shows that EDRA can outperform the Intel and Linux default RAs by up to 821.4% and 242.8%, respectively, in various cases.

 

Bio :

Chi-Yu Li is currently an Associate Professor with the Department of Computer Science, National Yang Ming Chiao Tung University (NYCU). He received his PhD degree in computer science from University of California, Los Angeles (UCLA) in 2015. Before joining UCLA, he received his Master and Bachelor degrees from the Department of Computer Science, NCTU. His research interests include wireless networking, mobile networks and systems, and network security. He has published many papers in top-tier academic conferences of both networking and security areas, such as ACM MobiCom, IEEE INFOCOM, ACM MobiSys, and ACM CCS. He received the Award of MTK Young Chair Professor (2016), MOST Young Scholar Research Award (2017, 2020), MOST FutureTex Award (2020, 2021), and the Best Paper Award in IEEE CNS 2018.