• KNOM Review
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• v.22 no.1
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• pp.52-59
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• 2019

As the video streaming service are supported by various devices, the amount of usage increases and efforts to improve the service from the viewpoint of users have continued. When a user watches a video, a response time occurs from input to playback, and if this response time becomes longer, the user's service satisfaction decreases. In this paper, we are proposing a method prefetching each user's preference video data obtained by analyzing user's past history record to the device for reducing the response time. We will show the result that prefetching data can improve the response time to 41% at most. And we analyzed real-video streaming viewing record and got each user's preferred video list. We investigated the change of response time according to a hit-ratio and amount of overhead data that was prefetched to the device, but not viewed. It was shown that as the hit-ratio grows bigger, the improvement of response time becomes more effective.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.179-184
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• 2022

With the development of information and communication technology, the production and distribution of digital contents is rapidly increasing, and the distribution of illegally copied contents also increases, causing various problems. In order to prevent illegal distribution of contents, a DRM (Digital Rights Management)-based approach can be used, but in a situation where the contents are already copied and distributed, a method of searching and detecting the duplicated contents is required. In this paper, a duplication detection method based on the contents of video content is proposed. The proposed method divides the video into scene units using the visual rhythm extracted from the video, and hierarchically applies the playback time and color feature values of each divided scene to quickly and efficiently detect duplicate videos in a large database. Through experiments, it was shown that the proposed method can reliably detect various replication modifications.

• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.17-27
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• 2024

Video frame interpolation is an important technique used in the field of video and media, as it increases the continuity of motion and enables smooth playback of videos. In the study of video frame interpolation using deep learning, Kernel Based Method captures local changes well, but has limitations in handling global changes. In this paper, we propose a new U-Net structure that applies feature map differentiation and two directions to focus on capturing major changes to generate intermediate frames more accurately while reducing the number of parameters. Experimental results show that the proposed structure outperforms the existing model by up to 0.3 in PSNR with about 61% fewer parameters on common datasets such as Vimeo, Middle-burry, and a new YouTube dataset. Code is available at https://github.com/Go-MinSeong/SF-AdaCoF.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.5
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• pp.213-217
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• 2001

Excessive memory buffer requirement in continuous media playback is a serious impediment of wide spread usage of on-line multimedia service. Skewed access frequency of available video files provides an opportunity of re-using the date blocks which has been loaded by one session for later usage. We present novel algorithm which minimizes the buffer requirement in multiple sessions of multimedia playbacks. In continuous media playback originated from the disk, a certain amount of memory buffer is required to synchronize asynchronous disk. Read operation and synchronous playback operation. As aggregate playback bandwodth increases, larger amount of buffer needs to be allocated for this synchronization purpose. The focus of this work is to study the asymptotic behavior of the synchronization buffer requirement and to develop an algorithm coping with this excessive buffer requirement under bandwidth congestioon. We argue that in a large scale continuous media server, it may not be necessary to read the blocks for each session directly from the disk. The beauty of our work lies in the fact that it dynamically adapts to disk utilization of the server and finds the optimal way of servicinh the individual sessions while minimizing the overall buffer space requirement. Optimality of the proposed algorithm is shown by proof. The effectiveness and performance of the proposed scheme is examined via simulation.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.11
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• pp.1296-1304
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• 1999

본 논문은 다수의 고객들에게 실시간 재생 서비스를 제공하는 주문형 비디오 서버에서 데이타 검색의 효율을 높이기 위한 저장 시스템의 구조와 그에 따른 배치 정책을 제안한다. 주문형 비디오 저장 서버에서 동시에 보다 많은 고객들에게 그들이 원하는 서비스를 제공하기 위해서는 여러 분야에서의 다양한 정책들이 고려될 수 있으나, 특히 저장 매체들을 어떤 구조로 구성하고 여기에 비디오 객체들을 어떻게 배치할 것인가는 검색 효율과 직접 관계되는 중요한 문제이다. 본 논문에서는 디스크 배열 형태로 구성된 저장 시스템을 디스크 성능을 고려하여 재구성하고, 비디오 객체들을 저장할 때 저장하고자 하는 데이타의 특성들과 저장 구조를 함께 고려하여 검색 효율을 극대화할 수 있는 배치 방법을 제안한다. 마지막으로 제안된 정책의 검색 효율을 검증하기 위해 다양한 실험을 통하여 기존의 배치 정책들과 비교하고 성능을 평가한다.Abstract In this paper, we propose the structure of storage system and a placement policy to provide many clients with real-time playback services efficiently in VOD(video-on-demand) server. Though policies in various areas being considered to provide more clients with services of degree requested by them simultaneously in VOD storage server, it is important how to construct storage media and to place video objects on it for retrieval efficiency. In this paper, we reorganize a large disk array with disks performance and place video objects using the placement policy considering both characteristics of video data and the structure of storage system for maximizing retrieval efficiency. Lastly, we simulate the proposed policy and conventional policies through various environments, compare our policy with others n evaluate the performance of our policy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.341-349
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• 2014

Dynamic adaptive streaming over HTTP (DASH) is the most recent and promising technology to support high quality streaming services. In dynamic adaptive streaming over HTTP (DASH), a client consecutively estimates the available network bandwidth and decides the transmission rate for the forthcoming video chunks to be downloaded. In this paper, we propose a novel rate adaptation algorithm called quality of experience QoE-enhanced adaptation algorithm over DASH (QAAD), which preserves the minimum buffer length to avoid interruption and minimizes the video quality changes during the playback. We implemented a DASH test bed and conducted extensive experiments. Experimental results demonstrate that under fluctuating network conditions, QAAD provides seamless streaming with stabilized video quality while the previous buffer-aware algorithm (i.e., QDASH[9]) frequently changes the video quality and undergoes the interruption.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.9-16
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• 2002

As existing analog video surveillance systems could save and retrieve data only in a limited space within short distance, it had many constraints in developing into various application systems. However, on the back of development of the Internet and computer technologies, digital video surveillance systems can be controlled from a remote location by web browser without space limits. Moreover, data compression and management technologies with Index Search algorithm make it possible to efficiently handling, storing, and retrieving a large amount of data and further motion detection algorithm enhances a recording speed and efficiency for a practical application, that is, a practical remote recordable video surveillance system using our efficient algorithms as mentioned, called WebCam. The WebCam server system can intelligently record and save video images digitized through efficient database management, monitor and control cameras in a remote place through user authentication, and search logs.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.775-782
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• 2005

In this paper, we propose multicast technique in order to reduce the required network bandwidth by n times, by merging the adjacent multicasts depending on the number of HENs (Head-End-Nodes) n that request the same video. Allowing new clients to immediately join an existing multicast through patching improves the efficiency of the multicast and offers services without any initial latency. A client might have to download data through two channels simultaneously, one for multicast and the other for patching. The more the frequency of requesting the video is, the higher the probability of caching it among HENs increases. Therefore, the requests for the cached video data can be served by HENs. Multicast from server is generated when the playback time exceeds the amount of cached video data. Since the interval of multicast can be dynamically expanded according to the popularity of videos, it can be reduced the server's workload and the network bandwidth. We perform simulations to compare its performance with that of conventional multicast. From simulation results, we confirm that the Proposed multicast technique offers substantially better performance.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.223-231
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• 2003

Video-on-Demand (VOD) service needs high resource consumption because of high bandwidth and long playback duration which are characteristics of multimedia. Various techniques such as Patching and Channel-Reserving Patching have been proposed to reduce the demand on the network-I/O bandwidth. Patching allows new clients to join an existing multicast for realization of true VOD, and Channel-Reserving Patching reserves the part of total channel capacity of video server in order to serve the requests for popular videos on which requests of users concentrate. To improve the performance of Channel-Reserving Patching, we propose the method that determines the reserved channel capacity of video server for the popular videos in this paper. The performance of our method is evaluated in terms of average servile latency, defection ratio and fairness through simulation, and is compared with those of Patching and another Channel-Reserving Patching.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4207-4222
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• 2016

In a P2P (Peer-to-Peer) VoD (video-on-Demand) streaming system, the nodes' load is an important factor which affects the system performance. In the system, some nodes may receive too many requests, which leads to overload. On the other hand, some other nodes may receive too few requests, which leads to low utilization. Therefore, designing a reasonable load balancing strategy is important. However, existing related studies cannot handle this problem effectively, because they don't have an efficient dynamic load information management mechanism, and they don't distinguish the difference of requests when transfer the nodes' load. In this paper, to manage the dynamic load information efficiently, we design a load management table for each node. Based on the load information, we propose a load balancing strategy which uses a request migration algorithm (LBRM). Through simulations, our scheme can handle the load imbalance problem effectively and improve the users' playback fluency.