• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.341-349
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• 2014

Dynamic adaptive streaming over HTTP (DASH) is the most recent and promising technology to support high quality streaming services. In dynamic adaptive streaming over HTTP (DASH), a client consecutively estimates the available network bandwidth and decides the transmission rate for the forthcoming video chunks to be downloaded. In this paper, we propose a novel rate adaptation algorithm called quality of experience QoE-enhanced adaptation algorithm over DASH (QAAD), which preserves the minimum buffer length to avoid interruption and minimizes the video quality changes during the playback. We implemented a DASH test bed and conducted extensive experiments. Experimental results demonstrate that under fluctuating network conditions, QAAD provides seamless streaming with stabilized video quality while the previous buffer-aware algorithm (i.e., QDASH[9]) frequently changes the video quality and undergoes the interruption.

• ETRI Journal
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• v.38 no.6
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• pp.1064-1073
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• 2016

An adaptive speech streaming method to improve the perceived speech quality of a software-based multipoint control unit (SW-based MCU) over IP networks is proposed. First, the proposed method predicts whether the speech packet to be transmitted is lost. To this end, the proposed method learns the pattern of packet losses in the IP network, and then predicts the loss of the packet to be transmitted over that IP network. The proposed method classifies the speech signal into different classes of silence, unvoiced, speech onset, or voiced frame. Based on the results of packet loss prediction and speech classification, the proposed method determines the proper amount and bitrate of redundant speech data (RSD) that are sent with primary speech data (PSD) in order to assist the speech decoder to restore the speech signals of lost packets. Specifically, when a packet is predicted to be lost, the amount and bitrate of the RSD must be increased through a reduction in the bitrate of the PSD. The effectiveness of the proposed method for learning the packet loss pattern and assigning a different speech coding rate is then demonstrated using a support vector machine and adaptive multirate-narrowband, respectively. The results show that as compared with conventional methods that restore lost speech signals, the proposed method remarkably improves the perceived speech quality of an SW-based MCU under various packet loss conditions in an IP network.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.525-528
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• 2005

Adaptive streaming algorithm for the realtime video decoder that can be dynamically adaptable to the network channel status or terminal environment is described and performance analyzed. An LMS filter is used to predict the bitrate and predicted bitrate is used to optimize based prediction filter is used to adapt and optimize the quality of the decoded pictures. The quality of the output pictures are about 48dB.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.549-558
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• 2018

We designed and implemented streaming server based on MEPG DASH, which is able to provide high quality video with low-latency live streaming service like 360 VR video on the existing cable network via low-spec media service devices such as IPTV and OTT(Over the Top) SettopBox. We also designed and applied management process which is cable of supporting services by cashing streaming video file(MPD, Segment Files) to reduce the server response delay time. Further more, we confimred that it is also able to provide high quality of tiled video streaming with over 50,000kbps bitrate and 8K@60P through the experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2144-2159
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• 2015

CISCO VNI predicted an average annual growth rate of 66% for mobile video traffic between 2014 and 2019 and accordingly much academic research related to video streaming has been initiated. In video streaming, Adaptive Bitrate (ABR) is a streaming technique in which a source video is stored on a server at variable encoding rates and each streaming user requests the most appropriate video encoding rate considering their channel capacity. However, these days, ABR related studies are only focusing on real-time rate adaptation omitting energy efficiency though it is one of the most important requirement for mobile devices, which may cause dissatisfaction for streaming users. In this paper, we propose an energy efficient prefetching based dynamic adaptive streaming technique by considering the limited characteristics of the batteries used in mobile devices, in order to reduce the energy waste and provide a similar level of service in terms of the average video rate compared to the latest ABR streaming technique which does not consider the energy consumption. The simulation results is showing that our proposed scheme saves 65~68% of energy at the average global mobile download speed compared to the latest high performance ABR algorithm while providing similar rate adaptation performance.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2544-2557
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• 2019

Adaptive bitrate streaming is a crucial element in the implementation of high-quality streaming of media content over the Internet. Dynamic adaptive streaming over HTTP (MPEG-DASH) has lately emerged as the de facto solution for over-the-top (OTT) video streaming services. In this paper, we perform macro-level analysis on a real-world MPEG-DASH-based Internet live broadcasting service to gain insight into its behavior throughout the end-to-end service-provision chain, from broadcasters to viewers. Based on this analysis, we propose methods to improve the quality-of-experience (QoE) of MPEG-DASH-based services, particularly with regard to reducing broadcasting delays between recording and viewing of videos, as well as synchronizing client terminals.

• 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 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.12 no.1
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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.