Implementation of multi-format adaptive streaming server

Fimic, Nemanja; Tanackovic, Sreten; Kovačević, Jelena; Temerinac, Miodrag

doi:10.1109/icce-berlin.2015.7391239

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…Agar prinsip layanan adaptive streaming dipenuhi, maka file video di dalam server di-encode ke berbagai format bitrate dan sebuah file manifest digeneralisasi [4,8]. File manifest berisi informasi dari representasi media yang berupa bandwitdh, ukuran frame, lokasi file video, segment base dan initial range.…”

Section: Pendahuluanunclassified

Adaptive Streaming Server dengan FFMPEG dan Golang

Kristiadi¹,

Marwiyati²

2021

RESTI

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Quality of experience (QoE) when accessing video streaming becomes a challenge in varieties of network bandwidth/speed. Adaptive streaming becomes an answer to gain good QoE. An architecture system of the adaptive streaming server with Dynamic Adaptive Streaming over HTTP (DASH) was proposed. The system was consists of two services e.g transcoding and streaming. Transcoding service encodes an audio file, multi-bitrates video files, and manifest.mpd files. Streaming service serves client streaming requests that appropriate to client network profiles. The system is built using the Golang programming environment and FFMPEG. Transcoding service has some execution mode (serial and concurrent) and passing mode (1 pass and 2 passes). The transcoding service test results show that concurrent execution is faster 11,5% than the serial execution and transcoding using 1 pass is faster 46,95% than 2 passes but the bitrate of output video lower than the determinate bitrate parameter. The streaming service has a good QoE. In the 5 scenarios, buffer level=0 happens 5 times, and its total duration is 64 seconds. Buffer level=0 happens when extreme changes happen in network speed from fast to too slow.

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Section: Pendahuluanunclassified

Adaptive Streaming Server dengan FFMPEG dan Golang

Kristiadi¹,

Marwiyati²

2021

RESTI

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“…The fact that figures for such an application reveal an enormous rise in 3DTV and Ultra High Definition (UHD) availability (or IP traffic share) that is proclaimed to reach over 20% of the total, annual, global video IP traffic by the year 2020, may be very motivating. As a derivative of dynamic bandwidth and network management schemes, more and more multimedia services are deployed nowadays relying on adaptive bitrate streaming mechanisms, competing with different approaches, such as HTTP Live Streaming (HLS) or Motion Pictures Experts Group -Dynamic Adaptive Streaming over HTTP (MPEG-DASH) [2]. Introduction of such streaming technology mechanics implies multiple quality measurement-related considerations.…”

Section: Introductionmentioning

confidence: 99%

Stereoscopic 3DTV Video Quality Metric: the Compressed Average Image Intensity

Wilczewski¹

2018

JTIT

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This paper presents a newly designed stereoscopic video quality metric. Overall insights towards the creation of mechanisms utilized within the genuine metric are presented herein. Delivery of the core information and motivation behind the features implemented, as well as functionality of the Compressed Average Image Intensity (CAII) quality metric are of utmost importance. The mechanisms created might be characterized as an objective, reliable and versatile quality evaluation tool for advanced analysis of the content delivery chain within stereoscopic video services.

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Implementation of multi-format adaptive streaming server

Cited by 2 publications

References 5 publications

Adaptive Streaming Server dengan FFMPEG dan Golang

Adaptive Streaming Server dengan FFMPEG dan Golang

Stereoscopic 3DTV Video Quality Metric: the Compressed Average Image Intensity

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