• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4519-4533
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• 2015

Hypertext Transfer Protocol (HTTP) adaptive streaming has become a new trend in video delivery. An HTTP adaptive streaming client needs to effectively estimate resource availability and demand. However, due to the bitrate of the video encoded in variable bitrate (VBR) mode, a bitrate mismatch problem occurs. With the rising demand for mobile devices, the likelihood of cases where two or more HTTP adaptive streaming clients share the same network bottleneck and competing for available bandwidth will increase. These mismatch and competition issues lead to network congestion, which adversely affects the Quality of Experience (QoE). To solve these problem, we propose a video rate adaptation scheme for the HTTP video streaming to guarantee and optimize the QoE. The proposed scheme estimates the available bandwidth according to the bitrate of each segment and also schedules the segment request time to expedite the response to the bandwidth variation. We used a multi-client simulation to prove that our scheme can effectively cope with drastic changes in the connection throughput and video bitrate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.476-481
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• 2012

Recently, QoS/QoE technology as a part of the HTTP-based adaptive streaming technology has attracted attention. In this paper, we find out HTTP-based adaptive and dynamic streaming technology. It is based on a dynamic adaptive streaming system over HTTP, which is designed and implemented. The system consist of conversion by the bit rate of MPEG2-TS files, division of segment, creation of MPD(Media Presentation Description) and bitrate's player through analysis of MPD File between servers and clients in network environments of dynamic and adaptive. This diverse network environments, continuous and smooth playback of video will be used in various multimedia fields.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.104-114
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• 2018

Recently, as HTTP-based video streaming traffic continues to increase, Dynamic Adaptive Streaming over HTTP(DASH), which is one of the HTTP-based adaptive streaming(HAS) technologies, is receiving attention. Accordingly, many video quality control techniques have been proposed to provide a high quality of experience(QoE) to clients in a DASH environment. In this paper, we propose a new quality control method using ANFIS(Adaptive Network based Fuzzy Inference System) which is one of the neuro-fuzzy system structure. By using ANFIS, the proposed scheme can find fuzzy parameters that selects the appropriate segment bitrate for clients. Also, considering the characteristic of VBR video, the next segment download time can be more accurately predicted using the actual size of the segment. And, by using this, it adjusts video quality appropriately in the time-varying network. In the simulation using NS-3, we show that the proposed scheme shows higher average segment bitrate and lower number of bitrate-switching than the existing methods and provides improved QoE to the clients.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.859-867
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• 2004

To provide high-quality media streaming service over the best-effort Internet, a streaming methodology is required to response to the dynamic fluctuation of underlying networks. In this paper, we implement the MPEG-4 streaming system with adaptive transport based on priorities of media packets. The implemented system is composed of the common MPEG-4 streaming components such as elementary stream provider, sync and DMIF layer, and adaptive transport module including data prioritization and FEC control. More specifically, the prioritized sync layer packets (based on object level) are delivered to the transport module and then are encoded by an adaptive FEC encoder to help reliable transport. The FEC combination is dynamically adjusted by the feedback information from the receiver. In addition, low priority packets are selectively dropped to meet the limitation of available bandwidth. The experimental results over the emulation-based testbed show that the Proposed system can mitigate the impact of network fluctuation and thus improve the quality of streaming.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1416-1428
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• 2016

In this paper, we address the channel zapping time problem of video streaming services based on HTTP Live Streaming (HLS) on smart Over-The-Top Set-Top Boxes (OTT STBs). Experimental analysis of the channel zapping time, show that smart OTT STBs inevitably suffer from the accumulated zapping time through channel change request, Internet Group Management Protocol (IGMP) leave/join, synchronization delay, video buffer delay, and STB processing delay when providing HLS services. As a practical solution for the zapping time reduction, an adaptive buffering method is proposed. The proposed method exploits two adaptive buffers added to the basic HLS player. These two adaptive buffers are responsible for constantly buffering previous and next channels relative to the current channel. Implementation and test results show that a stable zapping time less than one second can be achieved even under diverse video bitrate changes and varying network conditions by the proposed adaptive buffering method.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.207-222
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• 2012

Recently, many consumer electronics manufacturers have produced 3D devices such as 3DTVs and 3D monitors as interests in a stereoscopic video service are getting increased. However, most of 3D services are focused on local storage or bandwidth guaranteed service since 3D stereoscopic video service require bandwidth more stable and larger. This property causes difficulties in seamless stereoscopic video streaming services under IP based open network environment that cannot guarantee quality of services. In order to achieve a seamless video streaming service the international standard organization MPEG (Moving Pictures Experts Group) has developed the adaptive HTTP streaming technology called as DASH (Dynamic Adaptive Streaming over HTTP). However, the DASH doesn't have obvious scheme which can express the two elementary video streams based service-compatible stereoscopic contents in one segment. Therefore, this paper proposes a scheme of efficient 3D adaptive streaming service based on the DASH, which covers not only frame-packing stereoscopic contents but also service-compatible ones. The 3D adaptive HTTP streaming scheme introduced in this paper is able to provide 3D contents with various qualities to user and also has benefit that single 3D content can be applied to a variety of devices.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.166-172
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• 2020

Video streaming application such as YouTube is one of the most popular mobile applications. To adjust the quality of video for available network bandwidth, a streaming server provides multiple representations of video of which bit rate has different bandwidth requirements. A streaming client utilizes an adaptive bit rate scheme to select a proper video representation that the network can support. The download behavior of video streaming client player is governed by several parameters such as maximum buffer size. Especially, the size of the maximum playback buffer in the client player can greatly affect the user experience. To tackle this problem, in this paper, we propose the maximum buffer size optimization according to available network bandwidth and buffer status. Our simulation study shows that our proposed buffer size optimization scheme successfully mitigates playback stalls while preserving the similar quality of streaming video compared to existing ABR schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.784-799
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• 2013

This paper presents an adaptive rate control scheme for streaming-based content sharing service. This scheme delivers multimedia contents from a user device to another device or seamlessly redirects streaming service across heterogeneous user devices. In the proposed scheme, a streaming server adjusts video quality level according to the network and client status. Our scheme is different from other rate control schemes, because the video quality at the server is decided not only based on the available bandwidth, but also based on the device characteristics and bandwidth requirement at the access network. We also propose a bandwidth estimation method to achieve more equitable bandwidth allocations among streaming flows competing for the same narrow link with different Round Trip Times (RTTs). Through the simulation, we prove that our scheme improves the network stability and the quality of streaming service by appropriately adjusting the quality of the video stream. The simulation results also demonstrate the ability of the proposed scheme in ensuring RTT-fairness while remaining throughput efficient.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1182-1194
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• 2018

The Dynamic Adaptive Streaming over HTTP(DASH) is envisioned to evolve to meet an increasing demand on providing seamless video streaming services in the near future. The DASH performance heavily depends on the client's adaptive quality selection algorithm that is not included in the standard. The existing conventional algorithms are basically based on a procedural algorithm that is not easy to capture and reflect all variations of dynamic network and traffic conditions in a variety of network environments. To solve this problem, this paper proposes a novel quality selection mechanism based on the Deep Q-Network(DQN) model, the DQN-based DASH Adaptive Bitrate(ABR) mechanism. The proposed mechanism adopts a new reward calculation method based on five major performance metrics to reflect the current conditions of networks and devices in real time. In addition, the size of the consecutive video segment to be downloaded is also considered as a major learning metric to reflect a variety of video encodings. Experimental results show that the proposed mechanism quickly selects a suitable video quality even in high error rate environments, significantly reducing frequency of quality changes compared to the existing algorithm and simultaneously improving average video quality during video playback.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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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.