• 디지털융복합연구
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• 제17권2호
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• pp.399-404
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• 2019

본 연구는 국내외 활발히 이용되고 있는 OTT, 온라인 동영상 서비스, 그 중 넷플릭스와 왓챠플레이를 중심으로 사용자의 서비스 이용 현황에 관해 연구하여 K-콘텐츠 동영상 서비스를 통한 한국 엔터테인먼트 발전 전략을 제시하는데 그 목적이 있다. 연구 방법으로는 1차 사례연구를 통해 국내의 동영상 스트리밍 서비스와 국외의 OTT서비스의 특징 및 한국 콘텐츠 제공성을 조사하였다. 그리고 2차로 넷플릭스와 왓챠플레이 이용자 8명을 대상으로 하는 심층 인터뷰를 통해 사용자 경험과 한국엔터테인먼트 동영상 스트리밍 서비스의 수요를 파악하였다. 그 결과, 전략에 관한 두 가지 포인트를 도출해낼 수 있었다. 첫째, 단독화 채널 전략. 둘째, 콘텐츠의 다양화와 개인화 전략. 이 연구는 넷플릭스와 왓챠플레이를 통해 한국 엔터테인먼트 산업의 방향성에 관한 전략을 제시했다는 점에 의의가 있다. 후속 연구를 통해 한국 엔터테인먼트 산업의 개선 방안을 보완하고, 한국 엔터테인먼트 발전 전략 수립에 도움이 되기를 기대한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.308-324
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• 2018

HTTP adaptive streaming (HAS) is a promising technology for delivering video content over the Internet. HAS-based video streaming solutions rely on bandwidth estimation to select the appropriate video bitrate. Video streaming solutions that consider network conditions provide users with seamless video playback. However, when multiple clients compete for a common bottleneck link, conventional bandwidth estimation schemes that consider only one client overestimate the network bandwidth due to the ON-OFF traffic pattern. The bandwidth overestimation can cause Quality of Experience (QoE) degradation, such as unnecessary changes in video quality, and unfairness of video quality. In this paper, we propose a client-side bandwidth estimation scheme to obtain a better QoE of HAS in the multiple-client environment. The proposed scheme differentiates the client buffer status according to the buffer occupancy, and then estimates the available network bandwidth based on the buffer status and segment throughput. We evaluate the performance of HAS implemented in the ns-3 network simulator. Simulation results show that compared with the conventional schemes, the proposed scheme can enhance the QoE.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4585-4603
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• 2015

Video streaming services make up a large proportion of Internet traffic on both fixed and mobile access throughout the world. Adaptive streaming allows for dynamical adaptation of the bitrate with varying network conditions, to guarantee the best user experience. Adaptive bitrate algorithms face a significant challenge in correctly estimating the throughput as it varies widely over time. In this paper, we first evaluate the throughput estimation techniques and show that the method that we have used offers stable response to throughput fluctuations while maintaining a stable playback buffer. Then, we propose an adaptive bitrate scheme that intelligently selects the video bitrates based on the estimated throughput and buffer occupancy. We show that the proposed scheme improves viewing experience by achieving a high video rate without taking unnecessary risks and by minimizing the frequency of changes in the video quality. Furthermore, we show that it offers a stable response to short-term fluctuations and responds swiftly to large fluctuations. We evaluate our algorithm for both constant bitrate (CBR) and variable bitrate (VBR) video content by taking into account the segment sizes and show that it significantly improves the quality of video streaming.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3804-3819
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• 2018

The increasing popularity of HTTP adaptive video streaming services has dramatically increased bandwidth requirements on operator networks, which attempt to shape their traffic through Deep Packet inspection (DPI). However, Google and certain content providers have started to encrypt their video services. As a result, operators often encounter difficulties in shaping their encrypted video traffic via DPI. This highlights the need for new traffic classification methods for encrypted HTTP adaptive video streaming to enable smart traffic shaping. These new methods will have to effectively estimate the quality representation layer and playout buffer. We present a new machine learning method and show for the first time that video quality representation classification for (YouTube) encrypted HTTP adaptive streaming is possible. The crawler codes and the datasets are provided in [43,44,51]. An extensive empirical evaluation shows that our method is able to independently classify every video segment into one of the quality representation layers with 97% accuracy if the browser is Safari with a Flash Player and 77% accuracy if the browser is Chrome, Explorer, Firefox or Safari with an HTML5 player.

• 정보처리학회논문지A
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• 제13A권3호
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• pp.211-222
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• 2006

일반적인 비 공유 저장장치를 가진 시스템에서는 특정 컨텐츠에 대한 편향된(skewed) 요청 문제를 피할 수 없다. 본 논문에서는 비 공유 저장장치 모델로 설계/구현된 클러스터 기반의 스트리밍 서버에서 사용자의 편향된 컨텐츠 요청에 대처할 수 있고 스트리밍 서비스 중인 서버 또는 NS 카드에 문제가 생기더라도 스트리밍 서비스가 중단되지 않도록 다중 스트리밍 방법인 MDC(Multiple Description Coding)를 적용한 스트리밍 전송방법을 제안한다. 제안하는 방법은 클러스터 시스템에서 단일 세션으로 스트리밍 서비스를 제공하는 것이 아니라 MDC를 활용하여 다중 세션을 통한 스트리밍 서비스를 제공함으로써 모든 서버의 부하가 같아지고, 특정 서버에 문제가 발생하더라도 스트리밍 서비스가 끊어지지 않으면서 MDC의 특성인 적응형 서비스도 가능하게 되는 장점이 있다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.830-832
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• 2013

휴대폰은 이제 단순한 통화 기능 이외에 PC와 함께 동영상 콘텐츠를 시청할 수 있는 효과적인 멀티미디어 기기로 발전하고 있다. 따라서 동영상 콘텐츠의 실효성은 스마트폰으로 스트리밍(Streaming)할 수 있는지 여부와 목적한 내용을 효과적으로 전달 할 수 있는지 여부에 의해 결정된다. 여기서 목적한 내용을 효과적으로 전달 할 수 있는지 여부란 교재 영상과 발언자의 영상이 함께 제공되어야만 효과적인 내용 전달이 됨을 의미한다. 본 논문은 위 두 가지 요건을 충족하는 동영상 콘텐츠 인코딩(encoding) 시스템으로 멀티소스(Multi-Source)의 오디오-비디오를 입력받아 인터넷 상에 실시간 및 VOD 서비스 할 수 있는 비디오 통합 관리 시스템을 제안하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.276-284
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• 2022

In this paper, we implemented cloud rendering using WebRTC for high-quality AR and VR services. Cloud rendering is an applied technology of cloud computing. It efficiently handles the rendering of large volumes of 3D content. The conventional VR and AR service is a method of downloading 3D content. The download time is delayed as the 3D content capacity increases. Cloud rendering is a streaming method according to the user's point of view. Therefore, stable service is possible regardless of the 3D content capacity. In this paper, we implemented cloud rendering using WebRTC and analyzed its performance. We compared latency of 100MB, 300MB, and 500MB 3D AR content in 100Mbps and 300Mbps internet environments. As a result of the analysis, cloud rendering showed stable latency regardless of data volume. On the other hand, the conventional method showed an increase in latency as the data volume increased. The results of this paper quantitatively evaluate the stability of cloud rendering. This is expected to contribute to high-quality VR and AR services

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3635-3654
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• 2015

With the rapid development of smart devices and mobile Internet, the video application plays an increasingly important role on mobile devices. Understanding user behavior patterns is critical for optimized operation of mobile live streaming systems. On the other hand, volume based billing models on cloud services make it easier for video service providers to scale their services as well as to reduce the waste from oversized service capacities. In this paper, the watching behaviors of a commercial mobile live streaming system are studied in a content-centric manner. Our analysis captures the intrinsic correlation existing between popularity and watching intensity of programs due to the synchronized watching behaviors with program schedule. The watching pattern is further used to estimate traffic volume generated by the program, which is useful on data volume capacity reservation and billing strategy selection in cloud services. The traffic range of programs is estimated based on a naive popularity prediction. In cross validation, the traffic ranges of around 94% of programs are successfully estimated. In high popularity programs (>20000 viewers), the overestimated traffic is less than 15% of real happened traffic when using upper bound to estimate program traffic.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3856-3872
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• 2018

HTTP-based adaptive streaming (HAS) has recently been widely deployed on the Internet. In the HAS system, a video content is encoded at multiple bitrates and the encoded video content is segmented into small parts of fixed durations. The HAS client requests a video segment and stores it in the playout buffer. The rate adaptation algorithm employed in HAS clients dynamically determines the video bitrate depending on the time-varying bandwidth. Many studies have shown that an efficient rate adaptation algorithm is critical to ensuring quality-of-experience in HAS systems. However, existing algorithms have problems estimating the network bandwidth because bandwidth estimation is performed on the client-side application stack. Without the help of transport layer protocols, it is difficult to achieve accurate bandwidth estimation due to the inherent segment-based transmission of the HAS. In this paper, we propose an alternative approach that utilizes the playout buffer occupancy rather than using bandwidth estimates obtained from the application layer. We start with a queueing analysis of the playout buffer. Then, we present a buffer-aware rate adaptation algorithm that is solely based on the mean buffer occupancy. Our simulation results show that compared to conventional algorithms, the proposed algorithm achieves very smooth video quality while delivering a similar average video bitrate.

• 반도체디스플레이기술학회지
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• 제15권2호
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• pp.66-69
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• 2016

Recently, augmented reality and virtual reality in the ICT sector have been highlighted. So also interested in related HMD areas to facilitate contact with the VR content is being attend. This paper proposes a method for implementing to the virtual reality through the mobile HMD device with the real time 360 image. This system is required the real time 360 image streaming server configuration and image processing for augmented reality and virtual reality. The configuration of the streaming server is configured the DB server to store images and the relay server that can relay images to other devices. Augmented image processing module is composed based on markerless tracking, and there are four modules that are recognition, tracking, detecting and learning module. Also, the purpose of this paper is shown the augmented 360 image processing through the Mobile HMD.