Network Latency Estimation and Low-Rank Matrix Completion
Introduction
Predict network latencies between nodes in a network is critical to real-time applications. Traditional algorithms is not suitable for mobile network due to the time-varying network condition. This project collected network latency data from the Seattle platform and developed new algorithms for network latency prediction. The proposed approaches significantly outperform various state-of-the-art latency prediction techniques. The paper based on this project is accepted by IEEE INFOCOM 2015 and IEEE/ACM Transactions on Networking (TON).
Relevant Materials
Publications
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Rui Zhu, Bang Liu, Di Niu, Zongpeng Li, H. Vicky Zhao. (2016).
Network Latency Estimation for Personal Devices: a Matrix Completion Approach,
IEEE/ACM Transactions on Networking, 25(2), 724-737.
(Download)
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Bang Liu, Di Niu, Zongpeng Li, H. Vicky Zhao. (2015).
Network Latency Prediction for Personal Devices: Distance-Feature Decomposition from 3D Sampling,
in INFOCOM 2015.
(Download)
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Yaochen Hu, Yushi Wang, Bang Liu, Di Niu, Cheng Huang. (2017).
Latency reduction and load balancing in coded storage systems,
in SoCC 2017.
(Download)