• ETRI Journal
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• v.32 no.6
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• pp.863-870
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• 2010

In recent years, the development of multimedia devices has meant that a wider multimedia streaming service can be supported, and there are now many ways in which TV channels can communicate with different terminals. Generally, scalable video streaming is known to provide more efficient channel capacity than simulcast video streaming. Simulcast video streaming requires a large network bandwidth for all resolutions, but scalable video streaming needs only one flow for all resolutions. In previous research, scalable video streaming has been compared with simulcast video streaming for network channel capacity, in two user simulation environments. The simulation results show that the channel capacity of SVC is 16% to 20% smaller than AVC, but scalable video streaming is not efficient because of the limit of the present network framework. In this paper, we propose a new network framework with an SVC extractor. The proposed network framework shows a channel capacity 50% (maximum) lower than that found in previous research studies.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.413-417
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• 2009

The use of scalable video coding scheme has been regarded as a promising solution for guaranteeing the quality of service of the video streaming over the Internet because it is a capable coding scheme to perform quality adaptation depending on network conditions. In this paper, we use a streaming model that transmits base layer using TCP and enhancement layers using DCCP, which try to provide transmission reliability of the BL and TCP friendliness. Unlike pervious works, the proposed algorithm performs rate adaptation based on playout buffer status. The PoB status of the client is sent back periodically to the server and serves as a network congestion indicator. Experimental results show that our scheme improves streaming quality comparing with pervious scheme in the case of not only constant/dynamic background flows but also VBR-encoded video sequence.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.516-528
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• 2015

In this paper, we propose mobile ad hoc network configuration and its autonomous network construction method for efficiency and scalability of media streaming for mobile smart devices. To provide scalable network configuration for streaming traffic distribution, an IEEE 802.11 infrastructure network and ad hoc networks are hierarchically built. The proposed method autonomously configures a hierarchical streaming network by competition based on performance and states of devices and the wireless network, not depending on any specific nodes. Finally, we conduct performance measurement for the proposed configuration and analyze the experimental result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4B
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• pp.368-376
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• 2009

Over recent years, the development of multimedia devices has meant that a wider multimedia streaming service can be supported, and there are now many ways in which TV channels can communicate with different terminals. Generally, scalable video streaming is known to provide more efficient channel capacity than simulcast video streaming. Simulcast video streaming requires a large network bandwidth for all resolutions, but scalable video streaming needs only one flow for all resolutions. On the contrary, to preserve the same video quality, SVC(Sealable Video Coding) needs a higher bit-rate than AVC(non-layered Video Coding) due to the coding penalty($10%{\sim}30%$). In previous research, scalable video streaming has been compared with simulcast video streaming for network channel capacity, in two-user simulation environments. The simulation results show that the channel capacity of SVC is $16{\sim}20%$ smaller than AVC, but scalable video streaming is not efficient because of the limit of the present network framework. In this paper, we propose a new network framework with a new router using EDE(Extraction Decision Engine) and SVC Extractor to improve network performance. In addition, we compare the SVC environment in the proposed framework with previous research on the same way subject. The proposed network framework shows a channel capacity 50%(maximum) lower than that found in previous research studies.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.318-327
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• 2002

This paper Introduces a new scanning method for network-adaptive scalable streaming video coding methodologies such as the MPEG-4 Fine Granular Scalable (FGS) Coding. Proposed scanning method can guarantee the subjectively improved picture quality of the region of the interest in the decoded video by managing the image information of that interested region to be encoded and transmitted most-preferentially, and also to be decoded most-preferentially. Proposed scanning method can lead the FGS coding method to achieve improved picture quality, in about 1dB ~ 3dB better, especially on the region of interest.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.975-979
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• 2010

Existing quality adaptation schemes are useful for improving network stability in a congested network, but these schemes do not guarantee the quality of experience on video streaming due to the frequent variations in playback quality for a streaming service. In this paper, we propose a network-adaptive quality adaptation scheme to guarantee the quality of experience on SVC(Scalable Video Coding) video streaming. The proposed scheme estimates the available bandwidth by bandwidth measurement scheme using media characteristic, and then smoothly adjusts the quality level of SVC video stream according to the estimated bandwidth. Through the simulation, we prove that our scheme guarantees the quality of experience for video streaming by minimizing quality variation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2001.11a
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• pp.335-354
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• 2001

.Next Generation Multimedia Streaming Technology Massive Scale Support $\rightarrow$ Clustered Solution Adaptive to Heterogeneous Network daptive to Heterogeneous Terminal Capability Presentation Technique .SMART Server Architecture .HERMES File System .Clustered Solution . High Speed Storage Interconnect .' Content Partitioning . Load Management . Support for Heterogeniety . Adaptive End to End Streaming Transport: Unicast vs. Multicast '. Scalable Encoding

• Journal of information and communication convergence engineering
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• v.14 no.4
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• pp.240-245
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• 2016

Scalable video streaming over wireless networks has many challenges. The most significant challenge is related to packet loss. To overcome this problem, in this paper, we propose an unequal loss protection (ULP) method using a new forward error correction (FEC) mechanism for robust scalable video streaming over wireless networks. For an efficient FEC assignment considering video quality, we first introduce a simple and efficient performance metric, the layer-based recovery rate (LRR), for quantifying the unequal error propagation effects of the temporal and quality layers on the basis of packet losses. LRR is based on the unequal importance in both the temporal and the quality layers of a hierarchical scalable video coding structure. Then, the proposed ULP-LRR method assigns an appropriate number of FEC packets on the basis of the LRR to protect the video layers against packet lossy network environments. Compared with conventional ULP algorithms, the proposed ULP-LRR algorithm demonstrates a higher performance for various error-prone wireless channel statuses.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5B
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• pp.517-525
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• 2009

We propose a quality guaranteed scalable video streaming service over the Internet using a new rate adaptation algorithm. Because video data requires much more bandwidth rather than other types of service, therefore, quality of video streaming service should be guaranteed while providing friendliness with other service flows over the Internet. To successfully provide this, we propose a framework for providing quality-guaranteed streaming service using two-channel transport layer and rate adaptation of scalable video stream. In this framework, baseline layer for scalable video is transmitted using TCP transport for minimum qualify service. Enhancement layers are delivered using TFRC transport with layer adaptation algorithm. The proposed framework jointly uses the status of playout buffer in the client and the encoding rate of layers in media contents. Therefore, the proposed algorithm can remarkably guarantee minimum quality of streaming service rather than conventional approaches regardless of network congestion and the encoding rate variation of media content.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.257-260
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• 2006

In Video streaming environment, we must consider terminal and network characteristics, such as display resolution, frame rate, computational resource, network bandwidth, etc. The JVT (Joint Video Team) by ISO/IEC MPEG and ITU-TVCEG is currently standardizing Scalable Video Coding (SVC). This can represent video bitstreams in different sealable layers for flexible adaptation to terminal and network characteristics. This characteristic is very useful in video streaming applications. One fully scalable video can be extracted with specific target spatial resolution, temporal frame rate and quality level to match the requirements of terminals and networks. Besides, the extraction process is fast and consumes little computational resource, so it is possible to extract the partial video bitstream online to accommodate with changing network conditions etc. With all the advantages of SVC, we design and implement a network-adaptive SVC streaming system with an SVC extractor and a streamer to extract appropriate amounts of bitstreams to meet the required target bitrates and spatial resolutions. The proposed SVC extraction is designed to allow for flexible switching from layer to layer in SVC bitstreams online to cope with the change in network bandwidth. The extraction is made in every GOP unit. We present the implementation of our SVC streaming system with experimental results.