• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.245-250
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• 2010

To support various bandwidth requirements for many kinds of devices such as PC, notebook, PDA, cellular phone, a transcoding proxy is usually necessary to provide not only adapting multimedia streams to the client by transcoding, but also caching them for later use. Due to huge size of streaming media, we proposed the 3 kinds of segmentation - PT-2, uniform, bitrate-based segmentation. And to reduce the CPU cost of transcoding video, we proposed the DQS service policy. In this paper, we simulate the combined our previous two researches that are bitrate-based segmentation and DQS(Degraded Quality Service) policy. Experimental results show that the combined policy outperforms companion schemes in terms of the byte-hit ratios and delay saving ratios.

• KIISE Transactions on Computing Practices
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• v.22 no.7
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• pp.310-314
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• 2016

Currently, several research studies are looking to improve the quality of DASH (Dynamic Adaptive Streaming over HTTP) based live streaming services. However, conventional DASH based streaming schemes cannot provide seamless playback while maintaining the low buffering and it adversely affects the QoE (Quality of Experience). To address this problem, we propose the QoE driven segment scheduling scheme. The proposed scheme adaptively schedules the segment request message according to the time and variation of segment fetching. Simulation results indicate that the proposed scheme improves the QoE of live streaming service by maintaining the low buffering delay and reducing the buffer underflow events.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.1-9
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• 2017

Explosive deployment of smart mobile devices such as smart phones, and tablets along with expansion of wireless internet bandwidth have enabled the deployment of mobile video streaming such that video traffic becomes the most important service in wireless networks. Recently, for more efficient video streaming services, the ISO MPEG group standardized a protocol called DASH (Dynamic Adaptive Streaming over HTTP) and the standard has been quickly adopted by many service providers such as YouTube and Netflix. Despite of the convenience of mobile streaming services, users also suffer from low QoE(Quality of Experience) due to dynamic channel fluctuations and unnecessary downloading due to high churning rates. This paper proposes a noble efficient video rate selection algorithm considering user buffer level, channel condition and churning rate. Computer simulation based performance study showed that the proposed algorithm improved the QoE significantly compared to a method that determines the video rate based on current channel conditions. Especially, the proposed method reduced the rebuffering rate, one of the most important performance factors of the QoE, to a nonnegligible level.

• International Journal of Contents
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• v.17 no.2
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• pp.1-8
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• 2021

Online streaming wars are intensifying. Netflix is known as the market leader in the streaming business. However, since 2019, Netflix has been losing subscribers in the United States and is at a turning point where it needs to reassess its current position in the market. While Netflix is losing dominance, rivals Amazon Prime and Hulu continue to gain market shares. Studies from Deloitte and PricewaterhouseCoopers indicated a new shift in the streaming landscape caused by the abundance of streaming options and rising subscription costs. Recent surveys showed that consumers are excited about new streaming services, such as Disney +. Nearly two-thirds of consumers intend to terminate or downgrade one or more of their current subscriptions to make room for a new service. Moreover, it seems that consumers want ad-supported options. In Deloitte's latest Digital Media Trends survey, 65% responded that they would watch ads to eliminate or reduce subscription costs. Seventy percent of Hulu's subscribers choose its lower-priced ad-supported plan. NBC recently launched its own streaming service, Peacock, with a free ad-supported option. This opposes Netflix's brand identity of "no ads" and premium differentiation. With increasing pressure from competition and the growing risk of subscriber loss, Netflix needs to diversify its price plans. The company could try implementing the lower-priced mobile-only plan they are currently testing or plan to test in other regions. Netflix should also consider features or benefits for loyal subscribers to maintain a stronger consumer base.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.53-60
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• 2023

Recently, the demand and traffic volume for various multimedia contents are rapidly increasing through real-time streaming platforms. In this paper, we predict real-time streaming traffic to improve the quality of service (QoS). Statistical models have been used to predict network traffic. However, since real-time streaming traffic changes dynamically, we used recurrent neural network-based deep learning models rather than a statistical model. Therefore, after the collection and preprocessing for real-time streaming data, we exploit vanilla RNN, LSTM, GRU, Bi-LSTM, and Bi-GRU models to predict real-time streaming traffic. In evaluation, the training time and accuracy of each model are measured and compared.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.75-78
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• 2002

In this paper, we present the design and implementation of a Fault Tolerant VOD system. The system uses the double striping policy that a original file is sequentially striped to multiple streaming server with constant data block size and the data block of one streaming server is re-striped to the other streaming server. When a fault occurs in one streaming server, automatically the other streaming server will service.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.355-363
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• 2011

Transcoding in the wireless mobile network is an important mechanism that reduces the delay time and improves the stream processing capacity. Wireless mobile streaming media services, however, have such problems as congestion, interference and delay due to narrow network bandwidth and limited resources. These problems degrade not only Quality of Service (QoS) but also responsiveness of the streaming media service. To solve this problem, this paper proposes a object version transcoding method. The proposed method analyzes the object versions to construct the transcoding graph. This paper utilizes a reference rate-based control function for an efficient streaming, and measures MVDS(Multiple Version Delay Saving) for an efficient delay savings. The simulation results show that the proposed mechanism achieves improved performance in delay rate and cache hit rate compared with those of other existing methods.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.287-292
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• 2001

Multimedia service systems should have efficient capacity to serve the growing clients and new data. In the general streaming services, users can endure the small amount of time delay at the beginning of service. But they want to have good quality of service. A streaming server tries to transfer video files to clients from a repository of files in real time. The server must guarantee concurrent and uninterrupted delivery of each video stream requested from clients. To achieve its purpose, many stream servers adopt multi-processors, sufficient memory, and RAID or SAN in their systems. In this paper, we propose a Linux-based parallel media streaming server. It is superior to the other systems in the storing structure, fault-tolerance, and service capacity. Since this system supports the web interlace, users can operate easily through the www. This system uses unique striping policy to distribute multimedia files into the parallel storage nodes. If a service request occurs, each storage node transmits striped files concurrently to the client. Its performance is better than the single media streaming service because of the parallel architecture.

• ETRI Journal
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• v.32 no.6
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• pp.863-870
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• 2010

In recent years, the development of multimedia devices has meant that a wider multimedia streaming service can be supported, and there are now many ways in which TV channels can communicate with different terminals. Generally, scalable video streaming is known to provide more efficient channel capacity than simulcast video streaming. Simulcast video streaming requires a large network bandwidth for all resolutions, but scalable video streaming needs only one flow for all resolutions. In previous research, scalable video streaming has been compared with simulcast video streaming for network channel capacity, in two user simulation environments. The simulation results show that the channel capacity of SVC is 16% to 20% smaller than AVC, but scalable video streaming is not efficient because of the limit of the present network framework. In this paper, we propose a new network framework with an SVC extractor. The proposed network framework shows a channel capacity 50% (maximum) lower than that found in previous research studies.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.373-375
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• 2004

본 논문에서는 클라이언트가 NSS서버에서 제공하는 패키지를 네트워크 스트리밍을 통하여 실시간으로 이용 가능하게 해주는 리눅스[1]기반의 NSS(Network Streaming Service) 시스템 상에서 패키지 prefetching 기능을 제공하는 부분에 대한 효율적인 알고리즘의 설계를 다룬다.