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Tobias Beckerwerth - IEEE Xplore Author Profile

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Tobias Beckerwerth

Also published under: T. Beckerwerth

Publications

17

Citations

81

Publications by Year

20162024

Co-Authors:

J. AldamaRobert BehrendsArbnor BerishaHendrik BoermaL. Castelvero

Show All Co-Authors (32)

Tobias Beckerwerth

Also published under: T. Beckerwerth

Affiliation

Fraunhofer Heinrich Hertz Institute, Berlin, Germany

Publication Topics

Avalanche Photodiode,
Dark Current,
Coherent Detection,
Epitaxial Structure,
Optical Power,
Reverse Bias Voltage,
Baud Rate,
Bias Voltage,
Digital Signal Processing,
Direct Detection,
Epitaxial Layer,
High Bandwidth

Biography

Tobias Beckerwerth received the B.Sc. and M.Sc. degrees in physics from Freie Universität Berlin, Germany, and Technische Universität Berlin, Germany, in 2012 and 2015, respectively. Since 2015, he has been with Fraunhofer Heinrich Hertz Institute (HHI), Berlin, Germany, and is currently working toward the Ph.D. degree. His research focuses on the development of photodetectors in InP technology.(Based on document published on 29 March 2019).

Publications

17

Citations

81

Publications by Year

20162024

Co-Authors:

J. Aldama
Robert Behrends
Arbnor Berisha
Hendrik Boerma
L. Castelvero

Show All Co-Authors (32)

Author's Published Works

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Showing 1-8 of 8 results

Conferences (5)

Journals (3)

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Tongyu Zong(8)
Yong Liu(6)
Liyang Sun(4)
Yao Wang(3)
Xiaoyang Zeng(2)
Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA(3)
China North Industries Group Corporation, Beijing, China(2)
State Key Lab of ASIC & System, Fudan University, Shanghai, China(1)
Electrical and Computer Engineering Department, Tandon School of Engineering, New York University, Brooklyn, NY, USA(1)
Futurewei Technologies(1)
2018 IEEE International Conference on Consumer Electronics (ICCE)(2)
IEEE/ACM Transactions on Networking(2)
2019 IEEE 27th International Conference on Network Protocols (ICNP)(1)
2021 IEEE International Conference on Robotics and Automation (ICRA)(1)
IEEE INFOCOM 2021 - IEEE Conference on Computer Communications(1)
IEEE(8)
Media(1)
Las Vegas, NV, USA(2)
Chicago, IL, USA(1)
Vancouver, BC, Canada(1)
Xi'an, China(1)
Optimal Control(4)
Deep Reinforcement Learning(3)
Deep Reinforcement Learning Model(3)
Live Streaming(3)
Model Predictive Control(3)

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Cocktail Edge Caching: Ride Dynamic Trends of Content Popularity With Ensemble Learning

Tongyu Zong;Chen Li;Yuanyuan Lei;Guangyu Li;Houwei Cao;Yong Liu

IEEE/ACM Transactions on Networking

Year: 2023 | Volume: 31, Issue: 1 | Journal Article |

Cited by: Papers (23)

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Edge caching will play a critical role in facilitating the emerging content-rich applications. However, it faces many new challenges, in particular, the highly dynamic content popularity and the heterogeneous caching configurations. In this paper, we propose Cocktail Edge Caching, that tackles the dynamic popularity and heterogeneity through ensemble learning. Instead of trying to find a single do...Show More

Cocktail Edge Caching: Ride Dynamic Trends of Content Popularity With Ensemble Learning

Tongyu Zong;Chen Li;Yuanyuan Lei;Guangyu Li;Houwei Cao;Yong Liu

IEEE/ACM Transactions on Networking

Year: 2023 | Volume: 31, Issue: 1 | Journal Article |

Live 360 Degree Video Delivery Based on User Collaboration in a Streaming Flock

Liyang Sun;Yixiang Mao;Tongyu Zong;Yong Liu;Yao Wang

IEEE Transactions on Multimedia

Year: 2023 | Volume: 25 | Journal Article |

Cited by: Papers (7)

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Streaming of live 360-degree video allows users to follow a live event from any view point and has already been deployed on some commercial platforms. However, the current systems can only stream the video at relatively low-quality because the entire 360-degree video is delivered to the users under limited bandwidth. Streaming video falling into user field of view (FoV) can improve bandwidth effic...Show More

Live 360 Degree Video Delivery Based on User Collaboration in a Streaming Flock

Liyang Sun;Yixiang Mao;Tongyu Zong;Yong Liu;Yao Wang

IEEE Transactions on Multimedia

Year: 2023 | Volume: 25 | Journal Article |

Reinforced iLQR: A Sample-Efficient Robot Locomotion Learning

Tongyu Zong;Liyang Sun;Yong Liu

2021 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2021 | Conference Paper |

Cited by: Papers (9)

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Robot locomotion is a major challenge in robotics. Model-based approaches are vulnerable to model errors, and incur high computation overhead resulted from long control horizon. Model-free approaches are trained with a large number of training samples, which are expensive to obtain. In this paper, we develop a hybrid control and learning framework, called Reinforced iLQR (RiLQR), which combines th...Show More

Reinforced iLQR: A Sample-Efficient Robot Locomotion Learning

Tongyu Zong;Liyang Sun;Yong Liu

2021 IEEE International Conference on Robotics and Automation (ICRA)

Year: 2021 | Conference Paper |

Cocktail Edge Caching: Ride Dynamic Trends of Content Popularity with Ensemble Learning

Tongyu Zong;Chen Li;Yuanyuan Lei;Guangyu Li;Houwei Cao;Yong Liu

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications

Year: 2021 | Conference Paper |

Cited by: Papers (14)

HTML

Edge caching will play a critical role in facilitating the emerging content-rich applications. However, it faces many new challenges, in particular, the highly dynamic content popularity and the heterogeneous caching configurations. In this paper, we propose Cocktail Edge Caching, that tackles the dynamic popularity and heterogeneity through ensemble learning. Instead of trying to find a single do...Show More

Cocktail Edge Caching: Ride Dynamic Trends of Content Popularity with Ensemble Learning

Tongyu Zong;Chen Li;Yuanyuan Lei;Guangyu Li;Houwei Cao;Yong Liu

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications

Year: 2021 | Conference Paper |

Towards Optimal Low-Latency Live Video Streaming

Liyang Sun;Tongyu Zong;Siquan Wang;Yong Liu;Yao Wang

IEEE/ACM Transactions on Networking

Year: 2021 | Volume: 29, Issue: 5 | Journal Article |

Cited by: Papers (19)

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Low-latency is a critical user Quality-of-Experience (QoE) metric for live video streaming. It poses significant challenges for streaming over the Internet. In this paper, we explore the design space of low-latency live streaming by developing dynamic models and optimal adaptation strategies to establish QoE upper bounds as a function of the allowable end-to-end latency. We further develop practic...Show More

Towards Optimal Low-Latency Live Video Streaming

Liyang Sun;Tongyu Zong;Siquan Wang;Yong Liu;Yao Wang

IEEE/ACM Transactions on Networking

Year: 2021 | Volume: 29, Issue: 5 | Journal Article |

Optimal Strategies for Live Video Streaming in the Low-latency Regime

Liyang Sun;Tongyu Zong;Yong Liu;Yao Wang;Haihong Zhu

2019 IEEE 27th International Conference on Network Protocols (ICNP)

Year: 2019 | Conference Paper |

Cited by: Papers (13)

HTML

Low-latency is a critical user Quality-of-Experience (QoE) metric for live video streaming. It poses significant challenges for streaming over the Internet. In this paper, we explore the design space of low-latency live video streaming by developing dynamic models and optimal control strategies. We further develop practical live video streaming algorithms within the Model Predictive Control (MPC) ...Show More

Optimal Strategies for Live Video Streaming in the Low-latency Regime

Liyang Sun;Tongyu Zong;Yong Liu;Yao Wang;Haihong Zhu

2019 IEEE 27th International Conference on Network Protocols (ICNP)

Year: 2019 | Conference Paper |

Panoramic video delivery based on Laplace compensation and Sphere-Markov probability model

Tongyu Zong;Zhengzhong Tu;Li Ai;Xueliang Xi;Yize Jin;Xiaoyang Zeng;Yibo Fan

2018 IEEE International Conference on Consumer Electronics (ICCE)

Year: 2018 | Conference Paper |

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Virtual Reality (VR) is on the rise nowadays. To save bandwidth and ensure high quality at the same time, only the tiles within field of view (FOV) of the user should be transmitted in high quality while other tiles in low quality or even not transmitted. However, if a user's viewpoint moves fast while watching a panoramic video, low-quality content will always appear in the FOV because of the rou...Show More

Panoramic video delivery based on Laplace compensation and Sphere-Markov probability model

Tongyu Zong;Zhengzhong Tu;Li Ai;Xueliang Xi;Yize Jin;Xiaoyang Zeng;Yibo Fan

2018 IEEE International Conference on Consumer Electronics (ICCE)

Year: 2018 | Conference Paper |

Content adaptive tiling method based on user access preference for streaming panoramic video

Zhengzhong Tu;Tongyu Zong;Xueliang Xi;Li Ai;Yize Jin;Xiaoyang Zeng;Yibo Fan

2018 IEEE International Conference on Consumer Electronics (ICCE)

Year: 2018 | Conference Paper |

Cited by: Papers (6)

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Tiled streaming has been proposed for delivering ultra-high resolution videos such as zoomable online lectures or panoramas. In tiled streaming, the source video is first partitioned into grid of small rectangular tile groups. Each tile group is independently encoded and compressed. When an user asks for a certain viewport at a time, the server only streams the viewed tiles to save up bandwidth. H...Show More

Content adaptive tiling method based on user access preference for streaming panoramic video

Zhengzhong Tu;Tongyu Zong;Xueliang Xi;Li Ai;Yize Jin;Xiaoyang Zeng;Yibo Fan

2018 IEEE International Conference on Consumer Electronics (ICCE)

Year: 2018 | Conference Paper |

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