Cooperative Server-Client HTTP Adaptive Streaming System for Live Video Streaming

Han, Sang-Wook; Go, Yunmin; Noh, Hyunmin; Song, Hwangjun

doi:10.1109/icoin.2019.8718151

Cited by 12 publications

(7 citation statements)

References 6 publications

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“…As mentioned previously, the work in [57] conirmed the improvement of the clients' bandwidth utilization and simultaneously minimizes the luctuation of video quality based on the cooperative serverśclient HTTP in ABS-based LVS services. Meanwhile, [169] and [190] demonstrated that the bandwidth consumption of the LVS experience was reduced signiicantly by invoking edge/fog architectures.…”

Section: Resource Consumptionsupporting

confidence: 54%

“…A higher video bitrate is expected to achieve a higher video quality for the LVS experience. Owing to the unstable characteristics of many parameters afected by video quality, many authors have attempted to adopt the ABS concept [5,57,102,149] to guarantee video quality as high as possible by adapting to bandwidth/throughput luctuations owing to changes in network condition. In the ABS method, a transmitted video is simultaneously encoded at various levels of bitrates, from which these streams are divided into multiple segments and stored on an HTTP server, and the client will be assigned appropriate bitrate segments considering the network conditions [16,104].…”

Section: Video Bitratementioning

confidence: 99%

“…In the ABS method, a transmitted video is simultaneously encoded at various levels of bitrates, from which these streams are divided into multiple segments and stored on an HTTP server, and the client will be assigned appropriate bitrate segments considering the network conditions [16,104]. In particular, Han et al proposed a cooperative client server based on HTTP adaptive streaming to provide a high-quality LVS service by improving bandwidth utilization [57]. The proposed model designs system operations as (i) the server adaptively encodes a live transmitted video into multiple video segments and (ii) the client chooses an appropriate segment bitrate by taking into account the quality, bandwidth, and bufered playback duration.…”

Section: Video Bitratementioning

confidence: 99%

“…The proposed model designs system operations as (i) the server adaptively encodes a live transmitted video into multiple video segments and (ii) the client chooses an appropriate segment bitrate by taking into account the quality, bandwidth, and bufered playback duration. Preliminary results in [57] showed that the LVS system can achieve higher bandwidth utilization and lower levels of adaptive bitrates than existing schemes. In addition, in [149], CDN has been considered as another key enabler to improve the quality of content delivered by LVS services, where the CDN infrastructure is responsible for providing fast delivery of Internet content via a geographically distributed group of servers that work together and the HLS protocol is further performed for LVS content.…”

Section: Video Bitratementioning

confidence: 99%

See 3 more Smart Citations

A Contemporary Survey on Live Video Streaming from a Computation-Driven Perspective

Dao

Tran

et al. 2022

ACM Comput. Surv.

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Live video streaming services have experienced significant growth since the emergence of social networking paradigms in recent years. In this scenario, adaptive bitrate streaming communications transmitted on web protocols provide a convenient and cost-efficient facility to serve various multimedia platforms over the Internet. In these communication models, video content is delivered optimally, possibly transcoded, edited automatically, and cached temporarily by network elements along the path. To this end, the computational capabilities of various network elements are considered as major resources to be optimized for service quality improvements. This paper provides a contemporary survey of cutting-edge live video streaming studies from a computation-driven perspective. First, an overview of the global standards, system architectures, and streaming protocols is presented. Next, hierarchical computation-driven models of live video streaming are anatomized, including cloud-, edge-, and peer-to-peer-based solutions. Cutting-edge studies are then reviewed to discover the advances they have made in improving system performance in multiple aspects. Finally, open challenges are presented to direct future research in this field.

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Section: Resource Consumptionsupporting

confidence: 54%

Section: Video Bitratementioning

confidence: 99%

Section: Video Bitratementioning

confidence: 99%

Section: Video Bitratementioning

confidence: 99%

See 2 more Smart Citations

A Contemporary Survey on Live Video Streaming from a Computation-Driven Perspective

Dao

Tran

et al. 2022

ACM Comput. Surv.

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“…Ketika proses streaming dimulai, klien menerima file manifest dan menganalisis file tersebut untuk mengetahui segment bitrate yang tersedia di server. Kemudian klien memberikan request segment ke server yang video sesuai dengan kondisi jaringan [9,10]. [5], libdash [11], dan MP4Box dari GPAC [12].…”

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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An Adaptive QP Adjustment of Multimedia over Heterogeneous Wireless Networks

Xie

Tian

2020

IOP Conf. Ser.: Mater. Sci. Eng.

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Cooperative Server-Client HTTP Adaptive Streaming System for Live Video Streaming

Cited by 12 publications

References 6 publications

A Contemporary Survey on Live Video Streaming from a Computation-Driven Perspective

A Contemporary Survey on Live Video Streaming from a Computation-Driven Perspective

Adaptive Streaming Server dengan FFMPEG dan Golang

An Adaptive QP Adjustment of Multimedia over Heterogeneous Wireless Networks

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