• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.79-83
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• 2009

Streaming Technology can support the real-time playback without downloading and storing multimedia data in local HDD. So, client browser or plug-in can represent multimedia data before the end of file transmission using streaming technology. Recently, the demand for efficient real-time playback and transmission of large amounts of multimedia data is growing rapidly. But most users' connections over network are not fast and stable enough to download large chunks of multimedia data. In this paper, we propose an intelligent IP streaming system based on personalized media service. The proposed IP streaming system enables users to get an intelligent recommendation of multimedia contents based on the user preference information stored on the streaming server or the home media server. The supposed intelligent IP streaming system consists of Server Metadata Agent, Pumping Server, Contents Storage Server, Client Metadata Agent and Streaming Player. And in order to implement the personalized media service, the user information, user preference information and client device information are managed under database concept. Moreover, users are assured of seamless access of streamed content event if they switch to another client device by implementing streaming system based on user identification and device information. We evaluate our approach with manufacturing home server system and simulation results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.491-508
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• 2010

In peer-to-peer (P2P) on-demand streaming networks, the alleviation of server load depends on reciprocal stream sharing among peers. In general, on-demand video services enable clients to watch videos from beginning to end. As long as clients are able to buffer the initial part of the video they are watching, on-demand service can provide access to the video to the next clients who request to watch it. Therefore, the key challenge is how to keep the initial part of a video in a peer's buffer for as long as possible, and thus maximize the availability of a video for stream relay. In addition, to address the issues of delivering data on lossy network and providing scalable quality of services for clients, the adoption of multiple description coding (MDC) has been proven as a feasible resolution by much research work. In this paper, we propose a novel caching scheme for P2P on-demand streaming, called Dynamic Buffering. The proposed Dynamic Buffering relies on the feature of MDC to gradually reduce the number of cached descriptions held in a client's buffers, once the buffer is full. Preserving as many initial parts of descriptions in the buffer as possible, instead of losing them all at one time, effectively extends peers’ service time. In addition, this study proposes a description distribution balancing scheme to further improve the use of resources. Simulation experiments show that Dynamic Buffering can make efficient use of cache space, reduce server bandwidth consumption, and increase the number of peers being served.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.360-363
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• 2010

Streaming Technology can support the real-time playback without downloading and storing multimedia data in local HDD. So, client browser or plug-in can represent multimedia data before the end of file transmission using streaming technology. Recently, the demand for efficient real-time playback and transmission of large amounts of multimedia data is growing rapidly. But most users' connections over network are not fast and stable enough to download large chunks of multimedia data. In this paper, we propose an intelligent IP streaming system based on personalized media service. The proposed IP streaming system enables users to get an intelligent recommendation of multimedia contents based on the user preference information stored on the streaming server or the home media server. The supposed intelligent IP streaming system consists of Server Metadata Agent, Pumping Server, Contents Storage Server, Client Metadata Agent and Streaming Player. And in order to implement the personalized media service, the user information, user preference information and client device information are managed under database concept. Moreover, users are assured of seamless access of streamed content event if they switch to another client device by implementing streaming system based on user identification and device information. We evaluate our approach with manufacturing home server system and simulation results.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2
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• pp.93-101
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• 2002

This paper presents the Internet audio broadcasting technology based on the streaming technology. In this paper, we choose the MPEG-2 AAC for multimedia data, and for the streaming of this data we use RTP/RTCP protocol. We use RTSP protocol for the control of streaming data and TCP/IP for the exchange of information between server and client. By using all of these protocols and MPEBG-2 AAC, we explain the implementation method for the unicast/multicast streaming server/client system. Our system was tested by ETRI intranet, which is connected by 2000 researchers. Experimental result show that our system can be process the packet loss and jitter by retransmission and variable length buffer. Multicast streaming server can be used for the audio broadcasting service inside the company, unicast streaming server can be used for the AOD (Audio On Demand) service.

• Journal of Communications and Networks
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• v.15 no.6
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• pp.635-644
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• 2013

Adaptive hypertext transfer protocol (HTTP) streaming has become a new trend to support adaptivity in video delivery. An HTTP streaming client needs to estimate exactly resource availability and resource demand. In this paper, we focus on the most important resource which is bandwidth. A new and general formulation for throughput estimation is presented taking into account previous values of instant throughput and round trip time. Besides, we introduce for the first time the use of bitrate estimation in HTTP streaming. The experiments show that our approach can effectively cope with drastic changes in connection throughput and video bitrate.

• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1052-1062
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• 2020

As the market demand for immersive media increases, an efficient streaming method is required in consideration of network conditions while maintaining the user's immersive experience. Accordingly, transmitting a viewport with relatively high-quality, such as tile-based streaming, is mainly used. But there still remains a lot of technical challenges, such as quickly providing a new viewport in high-quality according to the gaze. To solve the aforementioned problem, in this paper, we propose a method of configuring and transmitting a supplemental tile set through the predicted direction, and a range of stable utilization of the transmitted supplemental tile set.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1152-1168
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• 2010

Recently, due to the prevalence of various mobile devices and wireless broadband networks, there has been a significant increase in interest and demand for multimedia streaming services such as the mobile IPTV. In such a wireless broadband network, transmitting a continuous stream of multimedia data is difficult to achieve due to mobile stations (MSs) movement. Providing Quality of Service (QoS) for multimedia video streaming applications requires the server and/or client to be network-aware and adaptive. Therefore, in order to deploy a mobile IPTV service in wireless broadband networks, offering users efficient wireless resource utilization and seamlessly offering user perceived QoS are important issues. In this paper, we propose a new adaptive streaming scheme, called MARC (Mobile-aware Adaptive Rate Control), which adjusts the quality of bit-stream and transmission rate of video streaming based on the wireless channel status and network status. The proposed scheme can control the rate of multimedia streaming to be suitable for the wireless channel status by using awareness information of the wireless channel quality and the mobile station location. The proposed scheme can provide a seamless multimedia playback service in wireless broadband networks in addition to improving the QoS of multimedia streaming services. The proposed MARC scheme alleviates the discontinuity of multimedia playback and allocates a suitable client buffer to the wireless broadband network. The simulation results demonstrate the effectiveness of our proposed scheme.

• 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.

• ETRI Journal
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• v.35 no.6
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• pp.960-968
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• 2013

To implement a cloud game service platform supporting multiple users and devices based on real-time streaming, there are many technical needs, including game screen and sound capturing, audio/video encoding in real time created by a high-performance server-generated game screen, and real-time streaming to client devices, such as low-cost PCs, smart devices, and set-top boxes. We therefore present a game service platform for the running and management of the game screen, as well as running the sound on the server, in which the captured and encoded game screen and sound separately provide client devices through real-time streaming. The proposed platform offers Web-based services that allow game play on smaller end devices without requiring the games to be installed locally.