Quality of service specification in video databases

Bertino, Elisa; Catarci, Tiziana; Elmagarmid, Ahmed K.; Hacid, Mohand-Saïd

doi:10.1109/mmul.2003.1237552

Cited by 2 publications

(1 citation statement)

References 22 publications

(22 reference statements)

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“…Jitter is a considerable issue in video streaming and can degrade QoS [81], [82]. Jitter requirements vary as per application ranging from 10ms˘50ms e.g., VoD streaming (≤ 50ms) [83], videoconferencing and interactive video streaming (≤ 30ms) [84].…”

Section: Video Streaming Challengesmentioning

confidence: 99%

A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges

et al. 2022

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5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive multimedia applications (e.g., ultra high definition video conferencing, 3D and multiview video streaming, crowdsourced video streaming, cloud gaming, virtual and augmented reality) are becoming more ambitious with high volume and low latency video streams putting strict demands on the already congested networks. Mobile Edge Computing (MEC) is an emerging paradigm that extends cloud computing capabilities to the edge of the network i.e., at the base station level. To meet the latency requirements and avoid the end-toend communication with remote cloud data centers, MEC allows to store and process video content (e.g., caching, transcoding, pre-processing) at the base stations. Both video on demand and live video streaming can utilize MEC to improve existing services and develop novel use cases, such as video analytics, and targeted advertisements. MEC is expected to reshape the future of video streaming by providing ultrareliable and low latency streaming (e.g., in augmented reality, virtual reality, and autonomous vehicles), pervasive computing (e.g., in real-time video analytics), and blockchain-enabled architecture for secure live streaming. This paper presents a comprehensive survey of recent developments in MEC-enabled video streaming bringing unprecedented improvement to enable novel use cases. A detailed review of the state-ofthe-art is presented covering novel caching schemes, optimal computation offloading, cooperative caching and offloading and the use of artificial intelligence (i.e., machine learning, deep learning, and reinforcement learning) in MEC-assisted video streaming services.

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Section: Video Streaming Challengesmentioning

confidence: 99%