• Journal of KIISE
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• v.44 no.4
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• pp.423-432
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• 2017

Recently, the video quality control schemes for the improvement of the QoE (Quality of Experience) of video streaming services that are based on DASH (Dynamic Adaptive Streaming over HTTP), which is a standard of HTTP adaptive streaming (HAS) services, have been studied. However, the problem of the existing schemes is the degradation that is due to unnecessary quality changes because the VBR (Variable Bitrate) characteristics of the video are not considered. In this paper, we propose a SC-DASH (Segment Characteristics-based DASH) which controls the video quality based on the segment characteristics. The SC-DASH can prevent the occurrence of the unnecessary quality changes by controlling the video quality based on the size of the next segment, the segment throughput, and the buffer occupancy. The experiment results showed that the SC-DASH improves the QoE by reducing the unnecessary quality changes compared with the existing quality control schemes.

• ETRI Journal
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• v.35 no.1
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• pp.27-34
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• 2013

This paper proposes a network-adaptive mechanism for HTTP-based video streaming over wireless/mobile networks. To provide adaptive video streaming over wireless/mobile networks, the proposed mechanism consists of a throughput estimation scheme in the time-variant wireless network environment and a video rate selection algorithm used to increase the streaming quality. The adaptive video streaming system with proposed modules is implemented using an open source multimedia framework and is validated over emulated wireless/mobile networks. The emulator helps to model and emulate network conditions based on data collected from actual experiments. The experiment results show that the proposed mechanism provides higher video quality than the existing system provides and a rate of video streaming almost void of freezing.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.602-612
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• 2019

Various streaming technologies are being studied to guarantee the QoE of viewers due to the development of realistic media. HTTP adaptive streaming is a typical example, and it is based on HTTP / 1.1 and TCP. These protocols have become one of the causes of delaying the image delay and increasing the waiting time of web pages. Therefore, in this paper, we propose a QUIC-DASH system applying the UDP-based transmission protocols QUIC and HTTP / 2 to the MPEG-DASH system after analyzing various transmission protocols and development process of HTTP. Through experiments, the QUIC-DASH system confirmed the possibility of providing optimal performance in terms of transmission speed of LTE environment than existing system. We also suggest various future studies for better performance.

• Journal of KIISE
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• v.43 no.7
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• pp.827-833
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• 2016

HTTP Adaptive Streaming (HAS) is a technique that adapts its video quality to network conditions for providing Quality of Experience. In the HAS approach, a video content is encoded at multiple bitrates and the encoded video content is divided into several video segments. A HAS player estimates the network bandwidth and adjusts the video bitrate based on estimated bandwidth. However, the segment scheduler in the conventional HAS player requests video segments periodically without considering TCP. If the waiting duration for the next segment request is quite long, the TCP connection can be initialized and it restarts slow-start. Slow-start causes the reduction in TCP throughput and consequentially leads to low-quality video streaming. In this study, we propose a TCP-aware segment scheduling scheme to improve performance of HAS service. The proposed scheme adjusts request time for the next video request to prevent initialization of TCP connection and also considers the point of scheduling time. The simulation proves that our scheme improves the Quality of Service of the HAS service without buffer underflow issue.

• 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.

• Journal of KIISE
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• v.45 no.2
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• pp.175-186
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• 2018

Recently, HAS (HTTP Adaptive Streaming) has been the subject of much attention to improve the QoE (Quality of Experience). In a high latency network, HAS degrades the QoE due to the lost RTT cycle since it replies with a response of one segment to the request of one segment. The server-push based HAS schemes of downloading multiple segments in one request cause QoE degradation due to the buffer underflow. In this paper, we propose a VSSDS (Video Streaming Scheme based on Dynamic Server-push) scheme to improve the QoE in a high latency network. The proposed scheme adjust video quality by estimating available bandwidth and determine the number of segments to be downloaded for each segment request cycle. Through the simulation, the proposed scheme not only improves the average video bitrate but also alleviates the buffer underflow.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.3
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• pp.206-211
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• 2014

In this Paper, We proposed the HLS(Http Live Streaming) transmitter which is operated easily and cheap in all networks and client environments compared to the exist video live streaming transmitter. We analyzed the HLS protocol and then implemented for making the HLS transmitter cheaper and portable. After designing the HLS transmitter hardware using the RISC processor of Arm11 core, we ported the Linux Operating System and implemented the HLS protocol using the open source FFmpeg and Segmenter. For the performance evaluation of the developed HLS transmitter, we made the testing environment which is including the notebook, iPhone, and aroid Phone. In this testing environment, we analysed the received video data at the client displayer. As a results of the performance evaluation, we could certify that the proposed HLS transmitter has a higher performance than the Apple company's HLS.

• Journal of KIISE
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• v.45 no.1
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• pp.86-93
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• 2018

When multiple clients share bandwidth and receive a streaming service, HTTP Adaptive Streaming has a problem in that the bandwidth is measured inaccurately due to the ON-OFF pattern of the segment request. To solve the problem caused by the ON-OFF pattern, the proposed PANDA (Probe AND Adapt) determines the quality of the segment to be requested while increasing the target bandwidth. However, since the target bandwidth is increased by a fixed amount, there is a problem in low bandwidth utilization and a slow response to changes in bandwidth. In this paper, we propose a video quality control scheme that improves the low bandwidth utilization and slow responsiveness of PANDA. The proposed scheme adjusts the amount of increase in the target bandwidth according to the bandwidth utilization after judging the bandwidth utilization by comparing the segment download time and the request interval. Experimental results show that the proposed scheme can fully utilize the bandwidth and can quickly respond to changes in bandwidth.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.155-173
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• 2011

Recently, with the digitalization of a broadcasting system and the development of a communication technology, the existing trend of consuming media contents throughout the fixed-displayer and the dedicated channel is being changed. The existing user only could consume media contents under limited time and places because of the fixed-displayer and the dedicated channel. However, with advent of the IP-based terminals and HTTP adaptive streaming which transfer the media sequence according to the user's transmission condition, users become possible to enjoy the media content anytime anywhere. As the result of the alteration of the broadcasting surrounding, users can enjoy the media content while changing his terminals according to their preferences and circumstances. However, in case that users try to consume consecutively the content from last view-point ended in the previous terminal under current HTTP adaptive streaming environment, a user has to remember the last view-point, and then has to apply the view-point to the changed terminal. Thus, for solving this problem, this paper defines "User Profile" for describing the metadata for the chained content consume environment between the terminals. Also, for proving the proposed method, this paper try to demonstrate the proposed method throughout the realization of the system based on Smooth Streaming from Microsoft.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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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.