LEAP-Reference-Cited by-同舟云学术

LEAP

Published:2019-06-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Symposium on Quality of Service
language:
Short-container-title:

Author:

Shi Wanxin¹,Li Qing²,Wang Chao¹,Shen Gengbiao¹,Li Weichao²,Wu Yu²,Jiang Yong¹

Affiliation:

1. Tsinghua University, Shenzhen, China

2. Southern University of Science and Technology, Shenzhen, China

Funder

Guangdong Province Key Area R&D Program

R&D Program of Shenzhen

NSFC

PCL Future Regional Network Facilities for Large-scale Experiments and Applications

Shenzhen Key Lab of Software Defined Networking

Publisher

ACM

Reference34 articles.

1. Adnan Ahmed Zubair Shafiq Harkeerat Bedi and Amir Khakpour. 2017. Suffering from Buffering? Detecting QoE Impairments in Live Video Streams. In IEEE ICNP. Adnan Ahmed Zubair Shafiq Harkeerat Bedi and Amir Khakpour. 2017. Suffering from Buffering? Detecting QoE Impairments in Live Video Streams. In IEEE ICNP.

2. Zahaib Akhtar Yun Seong Nam Ramesh Govindan Sanjay Rao Jessica Chen Ethan Katz-Bassett Bruno Ribeiro Jibin Zhan and Hui Zhang. 2018. Oboe: Auto-Tuning Video ABR Algorithms to Network Conditions. In ACM SIGCOMM. 10.1145/3230543.3230558 Zahaib Akhtar Yun Seong Nam Ramesh Govindan Sanjay Rao Jessica Chen Ethan Katz-Bassett Bruno Ribeiro Jibin Zhan and Hui Zhang. 2018. Oboe: Auto-Tuning Video ABR Algorithms to Network Conditions. In ACM SIGCOMM. 10.1145/3230543.3230558

3. Apache Traffic Server. 2017. https://trafficserver.apache.org/. Apache Traffic Server. 2017. https://trafficserver.apache.org/.

4. Daniel S Berger Ramesh K Sitaraman and Mor Harchol-Balter. 2017. AdaptSize: Orchestrating the Hot Object Memory Cache in a Content Delivery Network. In USENIX NSDI. Daniel S Berger Ramesh K Sitaraman and Mor Harchol-Balter. 2017. AdaptSize: Orchestrating the Hot Object Memory Cache in a Content Delivery Network. In USENIX NSDI.

5. Federico Chiariotti Stefano D'Aronco Laura Toni and Pascal Frossard. 2016. Online Learning Adaptation Strategy for DASH Clients. In ACM MMSys. 10.1145/2910017.2910603 Federico Chiariotti Stefano D'Aronco Laura Toni and Pascal Frossard. 2016. Online Learning Adaptation Strategy for DASH Clients. In ACM MMSys. 10.1145/2910017.2910603

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reinforcement Learning-Based Adaptive Bitrate Caching at MEC Server;IEEE Transactions on Network and Service Management;2024-06

2. Content-Aware Caching at the Mobile Edge Network Using Federated Learning;IEEE Transactions on Emerging Topics in Computational Intelligence;2024

3. On-demand inference acceleration for directed acyclic graph neural networks over edge-cloud collaboration;Journal of Parallel and Distributed Computing;2023-01

4. Joint Optimization of DNN Inference Delay and Energy under Accuracy Constraints for AR Applications;GLOBECOM 2022 - 2022 IEEE Global Communications Conference;2022-12-04

5. Machine Learning at the Mobile Edge: The Case of Dynamic Adaptive Streaming Over HTTP (DASH);IEEE Transactions on Network and Service Management;2022-12