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video transcoding for adaptive bitrate streaming over edge-cloud continuum

Digital Communications and Networks 2021年第4期7卷 598-604页

作者： Guanyu Gao Yonggang Wen School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing210094China School of Computer Science and Engineering Nanyang Technological University 639798Singapore

video transcoding is to create multiple representations of a video for content *** is deemed as a core technique in Adaptive BitRate(ABR)*** to manage video transcoding affects the performance of ABR streaming in various aspects,including operational cost,streaming delays,Quality of Experience(QoE),***,the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming *** problems become more worthy of investigation with the emergence of the edge-cloud continuum,which makes the resource allocation for video transcoding more *** this end,this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming,including designing a rate profile for video transcoding,providing resources for video transcoding in clouds,and caching multi-bitrate video contents in networks,*** analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service(QoS)optimization *** goal is to minimize resource consumption while guaranteeing the QoS for ABR *** also discuss some promising research directions for the ABR streaming services.

关键词： video transcoding Adaptive bitrate streaming Quality of service Resource allocation Edge-cloud

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Efficient video downscaling transcoder from MPEG-2 to H.264

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2008年第4期9卷 457-463页

作者： Xiang-wen WANG Jun SUN Rong XIE Song-yu YU Shanghai Key Lab. of Digital Media Processing ＆ Transmissions Institute of lmage Communication ＆ Information Processing Shanghai Jiao Tong University Shanghai 200240 China

The new H.264 video coding standard achieves significantly higher compression performance than MPEG-2. As the MPEG-2 is popular in digital TV, DVD, etc., bandwidth or memory space can be saved by transcoding those streams into H.264 in these applications. Unfortunately, the huge complexity keeps transcoding from being widely used in practical applications. This paper proposes an efficient transcoding architecture with a smart downscaling decoder and a fast mode decision algorithm. Using the proposed architecture, huge buffering memory space is saved and the transcoding complexity is reduced. Performance of the proposed fast mode decision algorithm is validated by experiments.

关键词： video transcoding Mode decision Edge direction analysis

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FSpot:Fast and Efficient video Encoding Workloads Over Amazon Spot Instances

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Computers, Materials & Continua 2022年第6期71卷 5677-5697页

作者： Anatoliy Zabrovskiy Prateek Agrawal Vladislav Kashansky Roland Kersche Christian Timmerer Radu Prodan University of Klagenfurt Klagenfurt9020Austria Lovely Professional University Phagwara144411India Petrozavodsk State University Petrozavodsk185035Russia Bitmovin Klagenfurt9020Austria

HTTP Adaptive Streaming(HAS)of video content is becoming an undivided part of the Internet and accounts for most of today’s network *** compression technology plays a vital role in efficiently utilizing network channels,but encoding videos into multiple representations with selected encoding parameters is a significant ***,video encoding is a computationally intensive and time-consuming operation that requires high-performance resources provided by on-premise infrastructures or public *** turn,the public clouds,such as Amazon elastic compute cloud(EC2),provide hundreds of computing instances optimized for different purposes and clients’***,there is a need for algorithms and methods for optimized computing instance selection for specific tasks such as video encoding and transcoding ***,the encoding speed directly depends on the selected encoding parameters and the complexity characteristics of video *** this paper,we first benchmarked the video encoding performance of Amazon EC2 spot instances using multiple×264 codec encoding parameters and video sequences of varying ***,we proposed a novel fast approach to optimize Amazon EC2 spot instances and minimize video encoding ***,we evaluated how the optimized selection of EC2 spot instances can affect the encoding *** results show that our approach,on average,can reduce the encoding costs by at least 15.8%and up to 47.8%when compared to a random selection of EC2 spot instances.

关键词： EC2 spot instance encoding time prediction adaptive streaming video transcoding clustering HTTP adaptive streaming MPEG-DASH cloud computing optimization Pareto front

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