Video Streaming

• Swift: Adaptive Video Streaming with Layered Neural Codecs [NSDI’22]
• SenSei: Aligning Video Streaming Quality with Dynamic User Sensitivity [NSDI’21]
• Learning in situ: a randomized experiment in video streaming [NSDI’20]
• Grad: Learning for Overhead-aware Adaptive Video Streaming with Scalable Video Coding [MM’20]
• PERM: Neural Adaptive Video Streaming with Multi-path Transmission [INFOCOM’20]
• End-to-End Transport for Video QoE Fairness [SIGCOMM’19]
• PiTree: Practical Implementation of ABR Algorithms Using Decision Trees [MM’19] [Code] [Dataset]
• Requet: Real-Time QoE Detection for Encrypted YouTube Traffic [MMSys’19][Data]
• Oboe: Auto-tuning Video ABR Algorithms to Network Conditions [SIGCOMM’18]
• Neural Adaptive Content-aware Internet Video Delivery [OSDI’18]
• ABR Streaming of VBR-encoded Videos: Characterization, Challenges, and Solutions [CoNEXT’18]
• Understanding Video Management Planes [IMC’18]
• From Theory to Practice: Improving Bitrate Adaptation in the DASH Reference Player [MMSys’18]
• VideoNOC: assessing video QoE for network operators using passive measurements [MMSys’18]
• Disk|Crypt|Net: rethinking the stack for high-performance video streaming [SIGCOMM’17]
• Neural Adaptive Video Streaming with Pensieve [SIGCOMM’17][Code]
• Pytheas: Enabling Data-Driven QoE Optimization Using Group-Based Exploration-Exploitation [NSDI’17]
• Dissecting VOD Services for Cellular: Performance, Root Causes and Best Practices [IMC’17]
• CS2P: Improving Video Bitrate Selection and Adaptation with Data-Driven Throughput Prediction [SIGCOMM’16]
• MP-DASH: Adaptive Video Streaming Over Preference-Aware Multipath [CoNEXT’16]
• DASH2M: Exploring HTTP/2 for Internet Streaming to Mobile Devices [MM’16]
• BOLA: Near-Optimal Bitrate Adaptation for Online Videos [INFOCOM’16]
• A Control-Theoretic Approach for Dynamic Adaptive Video Streaming over HTTP [SIGCOMM’15]
• Can Accurate Predictions Improve Video Streaming in Cellular Networks? [HotMobile’15]
• A Buffer-Based Approach to Rate Adaptation: Evidence from a Large Video Streaming Service [SIGCOMM’14]
• Improving Fairness, Efficiency, and Stability in HTTP-based Adaptive Video Streaming with FESTIVE [CoNEXT’12]

NSDI23

• Draco: Towards General-Purpose Acceleration of Retrospective Video Analytics

  Neil Agarwal, Ravi Netravali

• GEMEL: Model Merging for Memory-Efficient, Real-Time Video Analytics at the Edge

  Arthi Padmanabhan, Neil Agarwal, Anand Iyer, Ganesh Ananthanarayanan, Yuanchao Shu, Nikolaos Karianakis, Harry Xu, Ravi Netravali

• RECL: Responsive Resource-Efficient Continuous Learning for Video Analytics

  Mehrdad Khani, Ganesh Ananthanarayanan, Kevin Hsieh, Junchen Jiang, Ravi Netravali, Yuanchao Shu, Mohammad Alizadeh, Victor Bahl

• Enabling High Quality Real-Time Communications with Adaptive Frame-Rate

  Zili Meng, Tingfeng Wang, Yixin Shen, Bo Wang, Mingwei Xu, Rui Han, Honghao Liu, Venkat Arun, Hongxin Hu, Xue Wei