• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2268-2283
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• 2013

Scalable video coding can handle peer heterogeneity of P2P streaming applications, but there is still a lack of comprehensive studies on how to use it to improve video playback quality. In this paper we propose a capacity aware scalable video coding mechanism for P2P on demand streaming system. The proposed mechanism includes capacity based neighbor selection, adaptive data scheduling and streaming layer adjustment, and can enable each peer to select appropriate streaming layers and acquire streaming chunks with proper sequence, along with choosing specific peers to provide them. Simulation results show that the presented mechanism can decrease the system's startup and playback delay, and increase the video playback quality as well as playback continuity, and thus it provides a better quality of experience for users.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.352-354
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• 2005

As further Studies on 4th generation mobile telecommunication are progressed, the importance of a Cross-Layer is being increased. However, it has focused on coordination model only between MAC layer and PHY layer. It is necessary to expand into II' layer and upper layers. In this paper, we introduce a Cross-layer optimization which can be used to transmit video data with effect by managing resources among layers. It can gives further more adaptive method to solve QoS model problem than single layer.

• 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.

• 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.

• 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.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.

• 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.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.50-53
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• 2002

There are increasing needs to deliver the multimedia streaming over heterogeneous networks. When considering network environments and equipment accessed by user, delivery of video streaming must be scalable. There are many kinds of scalable video coding: spatial, temporal, SNR, and hybrid. The SNR scalable and spatial resolution, but different SNR quality with respect to layers. The 1-layer SNR scalable encoder produces SNR scalable video streams with ease. But, there is drift problem. Modified 1-layer approach does not have this problem but coding inefficiency, and is not MPEG-compliant. The present MPEG-compliant 2-layer encoder comes out to reduce coding rate. But it still use only base layer to encode whole layer. In this paper, we propose adaptive MPEG-compliant 2-layer encoder. Using linear combination algorithm, encoder use 1 motion vector to encode the sequences efficiently. By dong this, we can achieve the coding efficiency of SNR scalable coding.