• 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 Information Science Society Conference
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• 2004.10c
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• pp.370-372
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• 2004

본 논문에서는 개방형 운영체제인 리눅스상에서 package streaming service를 제공하는 Network Streaming Service(통칭 NSS)를 설계하는 문제를 다룬다. NSS는 client가 serve 측에 설치된 소프트웨어 package를 마치 client 자신의 local disk상에 이미 인스톨된 패키지를 실행하는 것처럼 동작하도록 해준다. NSS는 client측의 NSS Mounter, Package Streaming Consumer, NSS Configurator와 server측의 NSS Load Balancer, Package Streaming Supplier, NSS Manager, Accounting & Security Manager로 구성되며 local disk caching과 background prefetching 기능을 사용하여 향상된 서비스를 제공한다.

• 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.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.166-172
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• 2020

Video streaming application such as YouTube is one of the most popular mobile applications. To adjust the quality of video for available network bandwidth, a streaming server provides multiple representations of video of which bit rate has different bandwidth requirements. A streaming client utilizes an adaptive bit rate scheme to select a proper video representation that the network can support. The download behavior of video streaming client player is governed by several parameters such as maximum buffer size. Especially, the size of the maximum playback buffer in the client player can greatly affect the user experience. To tackle this problem, in this paper, we propose the maximum buffer size optimization according to available network bandwidth and buffer status. Our simulation study shows that our proposed buffer size optimization scheme successfully mitigates playback stalls while preserving the similar quality of streaming video compared to existing ABR schemes.

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.6-12
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• 2006

Peer-to-Peer (P2P) networks are attracting considerable research interest because of their scalability and high performance relative to cost. One of the important services on a P2P network is the streaming service. However, because each node in the P2P network is autonomous, it is difficult to provide a stable streaming service on the network. Therefore, for a stable streaming service on the P2P network, a fault-tolerant scheme must be provided. In this paper, we propose two new node selection schemes, Playback Node First (PNF) and Playback Node first with Prefetching (PNF-P) that can be used for a service migration-based fault-tolerant streaming service. The proposed schemes exploit the fact that the failure probability of a node currently being served is lower than that of a node not being served. Simulation results show that the proposed schemes outperform traditional node selection schemes.

• Journal of Information Technology Services
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• v.18 no.4
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• pp.115-134
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• 2019

The global music industry has been growing steadily every year. In particular, the proportion of music streaming services in the overall market are expanding. It shows same pattern in domestic market. Also, several companies are providing music streaming services competitively. It is clear that there is growing interest in effective operations of music streaming services. In this study, we examine the impact of customization and network effect on service quality and customer loyalty. We collect survey data and analyze relationships between latent variables using structural equations modeling. We find that customization and network effect of music streaming services positively affect service quality. However, the effect of customization on customer loyalty is not significant and there is a negative effect of network effect on customer loyalty. Finally, we find that service quality works as a mediator between customization and customer loyalty, and service quality also works as a mediator between network effect and customer loyalty.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4572-4586
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• 2019

Mobile Edge Computing (MEC) and Information-Centric Networking (ICN) are essential network architectures for the future Internet. The advantages of MEC and ICN such as computation and storage capabilities at the edge of the network, in-network caching and named-data communication paradigm can greatly improve the quality of video streaming applications. However, the packet loss in wireless network environments still affects the video streaming performance and the existing loss recovery approaches in ICN does not exploit the capabilities of MEC. This paper proposes a Deep Learning based Loss Recovery Mechanism (DL-LRM) for video streaming over MEC based ICN. Different with existing approaches, the Forward Error Correction (FEC) packets are generated at the edge of the network, which dramatically reduces the workload of core network and backhaul. By monitoring network states, our proposed DL-LRM controls the FEC request rate by deep reinforcement learning algorithm. Considering the characteristics of video streaming and MEC, in this paper we develop content caching detection and fast retransmission algorithm to effectively utilize resources of MEC. Experimental results demonstrate that the DL-LRM is able to adaptively adjust and control the FEC request rate and achieve better video quality than the existing approaches.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.95-98
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• 2003

To provide high-quality media streaming service over the best-effort Internet, an efficient streaming system with a network-adaptive transport is essential. By adopting FEC-based adaptive transport and by matching it to the priority of media packets, in this paper, an enhanced MPEG-4 streaming system is implemented. The implemented adaptive transport can complement the existing MPEG-4 streaming server with components such as elementary stream provider, sync layer and DMIF layer. Sync layer packets of each MPEG-4 elementary stream are prioritized and then selectively dropped at the sender to match the currently available bandwidth. Also, with the proposed adaptive transport module, the level of FEC protection is dynamically adjusted based on the underlying network condition. With preliminary verification over the emulated network testbed, it is shown that the proposed implementation can mitigate the impact of network fluctuation and thus improve the quality of streaming.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.597-600
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• 2005

The software streaming technology enables telematics software to be automatically updated through a wireless network. When the software starts running, software streaming system inspects its version and then, automatically download latest one. The software streaming system breaks the software into several pieces that are streamed to the user as needed. In this way, software streaming system can improves the telematics application load time while updating the software through wireless network. In our experiments, the application load time was reduced about 7 times compared to downloading whole software at best case.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.35-42
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• 2018

In this paper, we propose an optimal streaming service method based on Hybrid CDN/P2P architecture. Recently, video streaming utilizes a CDN (Content Delivery Network) operation technique based on a Proxy Server, which is an end node located close to a user. However, since CDN has a fixed network traffic bandwidth and data information exchange among CDNs in the network is not smooth, it is difficult to guarantee traffic congestion and quality of image service. In the hybrid CDN/P2P network, a data selection technique is used to select only the data that is expected to be continuously requested among all the data in order to guarantee the QoS of the user who utilizes the limited bandwidth efficiently. In order to search user requested data, this technique effectively retrieves the storage information of the constituent nodes of CDN and P2P, and stores the new image information and calculates the deletion priority based on the request possibility as needed. Therefore, the streaming service scheme proposed in this paper can effectively improve the quality of the video streaming service on the network.