Zoom Session Quality: A Network-Level View

Choi, Albert H.; Karamollahi, Mehdi; Williamson, Carey; Arlitt, Martin

doi:10.1007/978-3-030-98785-5_25

Cited by 9 publications

(2 citation statements)

References 13 publications

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“…With the improvement of Internet high-throughput bandwidth and real-time transmission technology of wireless networks, large-scale online conference learning has become possible (e.g. Zoom) [14]. More advanced multi-sensor devices like VR/AR (augmented reality) have facilitated sensor-based technologies in education [3,6].…”

Section: Roadmap Of Technology Use In Educationmentioning

confidence: 99%

Educational Technology in the Post-Pandemic Era: Current Progress, Potential, and Challenges

Zhang,

Wasie

2023

Preprint

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Information technology has been significantly developed during the past decades. Teachers leverage various technologies to enhance teaching experience and knowledge delivery. Students explore diverse knowledge from numerous learning resources on the Web. Furthermore, the COVID-19 pandemic accelerates processing technology integration in education. During the pandemic, Zoom and Google Classroom were widely used for course content delivery, and they are still presenting their values in the post-pandemic era. Some other applications are also continuously adopted when in-person teaching and learning have been resumed. In this paper, a literature review-based approach is applied to summarize recent achievements in educational technology and present several promising directions for the future of education, including artificial intelligence-powered content generation and metaverse. A roadmap is proposed to illustrate the current and future progress of education technology. Meanwhile, safeguards are also provided to guide schools and parents to be aware of the potential hazards during technology use at the K-12 education level.

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Section: Roadmap Of Technology Use In Educationmentioning

confidence: 99%

Educational Technology in the Post-Pandemic Era: Current Progress, Potential, and Challenges

Zhang,

Wasie

2023

Preprint

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“…Passive network congestion detection [6,7] captures the information of the packets through the detection point and sends it to the server to obtain traffic characteristics and network status, such as NetFlow, sFlow and IPFIX; it does not generate extra bandwidth overhead, but the design of mechanisms such as sampling will also sacrifice accuracy of detection.…”

Section: Network Congestion Detectionmentioning

confidence: 99%

A Fine-Grained Network Congestion Detection Based on Flow Watermarking

Wang

2022

Applied Sciences

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With the rapid development of the network, how to effectively reduce the dynamic delay and improve the performance of the network is an important and challenging problem. Specifically, network congestion is one of the key factors that hurt the network performance, so real-time detection of the network congestion is critical for recovering the network failure quickly. Current research in congestion detection mainly faces the problems of occupying extra bandwidth, decreasing the ratio of the effective payload of the packet, increasing the burden of the switches, etc. In this paper, we apply flow watermarking to network congestion detection and propose a fine-grained network congestion detection method based on flow watermarking. We also combine it with the eBPF (extended Berkeley Packet Filter) to improve the performance of congestion detection. Theoretical analysis and experimental results show that the changes in network status can be reflected in real-time and accurately in the watermark decoding information. The network congestion detection based on flow watermarking can detect network status on a small time scale and realize low-overhead and easily deployed congestion detection.

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