• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.942-951
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• 2018

In these days, 360 degree videos, which is provided via VR, have high resolution and quality of 8K. These kinds of videos inevitably require streaming technology which guarantees QoS. Therefore, we suggest MPEG DASH HTTP protocol which stably provides streaming services of high quality videos in 8K, which are 360 degree tile-encoded, on low-spec devices such as OTT and IPTV Settop and Tile Segment Cache management structure for servers operating streaming services.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.43-52
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• 2019

360 Virtual Reality(VR) service is getting attention in the domestic streaming market as 5G era is upcoming. However, existing IPTV-based 360 VR video services use upto 4K 360 VR video which is not enough to satisfy customers. It is generally required that over 8K resolution is necessary to meet users' satisfaction level. The bit rate of 8K resolution video exceeds the bandwidth of single QAM channel(38.817mbps), which means that it is impossible to provide 8K resolution video via the IPTV broadcast network environment. Therefore, we suggest and implement the edge streaming system for low-latency streaming to the display devices in the local network. We conducted experiments and confirmed that 360 VR streaming with a viewport switching delay less than 500ms can be achieved while using less than 100mbps of the network bandwidth.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.189-196
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• 2010

Peer-to-Peer (P2P) has attracted attention as an alternative way to enable streaming videos on the Internet. Although P2P systems depend on bandwidth contribution from peers, peers are likely to refuse to contribute their bandwidth. In this paper, we proposed a P2P streaming system that encourages peers to contribute their upstream bandwidth by maintaining fairness among peers and providing different video quality between cooperative peers and selfish peers with a manageable way. Our proposed system determines if peers are cooperative or selfish by a rating mechanism based on their contributed upstream bandwidth, and offers a high quality video to cooperative peers as an incentive. Also we propose a tree reconstruction algorithm to make the system work effectively. Through simulation, we show that the tree reconstruction algorithm works effectively, and our incentive mechanism allocates more downstream bandwidth to cooperative peers and punished selfish peers with low quality video.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.957-966
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• 2014

N-Screen service has experienced rapid business expansion recently, since consumers' watching patterns have been diversified; also business stakeholders including broadcasting companies, internet service providers, and device manufacturers have joined this field. In order to operate N-Screen service in a stable manner, development of advertisement system where it generates continuous advertisement profit is needed. Especially for a streaming service that delivers live TV programs, the new advertising system has to deliver ads in conjunction with the live streaming system that is in use. In this paper, video advertising system that is congenial to N-Screen is proposed. Both real time video/ad converting scheme and direct video ads delivery function were developed and tested. In addition, ad contents management and statistics management functions have been developed for advertisement managers. This system was implemented in a commercial N-Screen service and it is currently being used for delivering video advertisements.

• The KIPS Transactions:PartC
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• v.19C no.2
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• pp.145-148
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• 2012

In a distributed streaming system using an advanced coding scheme that encodes a video into multiple substreams, the capacity of the system depends on the amount of contribution of participating peers. Thus, an incentive mechanism for peers to contribute voluntarily is needed to increase system capacity. In addition, since peers are not only a provider but also a consumer in the system (i.e. prosumer), the overall capacity of the system must be allocated fairly among the peers while it must be allocated in a way that can maximize the net quality of experience of peers to increase system efficiency. In this paper, we propose a substream allocation method to solve the problems taking an optimization approach. Unlike the other optimization approaches, the proposed method is verified quantitatively in a simulation study that it can use the capacity of video streaming system efficiently while allocating fair amount of substreams among peers because it considers explicitly the prosumer characteristics of peers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1768-1789
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• 2016

In contemporary video streaming systems based on HTTP protocol, video players at the client side are responsible for adjusting video quality to network conditions and user expectations. However, when multiple video clips are streamed simultaneously, an intricate application logic implemented in the video players overlays the TCP mechanism which is responsible for a balanced access to a shared network link. As a result, some video players may not obtain a fair share of network throughput and may be vulnerable to an unstable video bit-rate. Therefore, we propose to simplify the algorithms implemented in the video players, which are responsible for the adjustment of video quality and constrain their functionality only to sending feedback to a server about a state of the player buffer. The main logic of the system is shifted to the server, which is now responsible for bit-rate selection and prioritisation of the video streams transmitted to multiple clients. To verify our proposition, we performed several experiments in a laboratory environment which show that when the server cooperates with the clients, the video players experience fewer quality switches and the system achieves better fairness when allocating network throughput among the video players. However, this comes at the cost of worse utilisation of network bandwidth.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4A
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• pp.421-430
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• 2006

In this paper, we propose a practical implementation of network-adaptive HD(high definition) MPEG-2 video streaming with a cross-layered channel monitoring(CLM) over the IEEE 802.11a WLAN(wireless local area network). For wireless channel monitoring, AP(access point) periodically measures the MAC(medium access control) layer transmission information and sends the monitoring information to a streaming server. This makes that the streaming server reacts more quickly as well as efficiently to the fluctuated wireless channel than that of the end-to-end monitoring(E2EM) scheme for the video adaptation. The streaming sewer dynamically performs the priority-based frame dropping to adjust the video sending rate according to the measured wireless channel condition. For this purpose, our streaming system nicely provides frame-based prioritized packetization by using a real-time stream parsing module. Various evaluation results over an IEEE 802.11a WLAM testbed are provided to verify the intended QoS adaptation capability The experimental results show that the proposed system can effectively mitigate the quality degradation of video streaming caused by the fluctuations of time-varying wireless channel condition.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.145-152
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• 2012

Due to the large sizes of streaming media, previous delivery techniques are not providing optimal performance. For this purpose, video proxy server is employed for reducing the bandwidth consumption, network congestion, and network traffic. This paper proposes a fast distributed network file system using state transition model in the media streaming system for efficient utilization of video proxy server. The proposed method is composed of three steps: step 1. Training process using state transition model, step 2. base and decision probability generation, and step 3. storing and deletion based on probability. In addition, storage space of video proxy server is divided into each segment area in order to store the segments efficiently and to avoid the fragmentation. The simulation results show that the proposed method performs better than other methods in terms of hit rate and number of deletion. Therefore, the proposed method provides the lowest user start-up latency and the highest bandwidth saving significantly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.886-895
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• 2005

As the networked media technology have been grown in recent, there have been many research works to deliver high-quality video such as HDV and HDTV over the Internet. To realize high-quality media service over the Internet, however, the network adaptive streaming scheme is required to adopt to the dynamic fluctuation of underlying networks. In this paper, we design and implement the network-adaptive HD(high definition) MPEG-2 streaming system employing the frame-based prioritized packetization. Delivered video is inputted from the JVC HDV camera to the streaming sewer in real-time. It has a bit-rate of 19.2 Mbps and is multiplexed to the MPEG-2 TS (MPEG-2 MP@HL). For the monitoring of network status, the packet loss rate and the average jitter are measured by using parsing of RTP packet header in the streaming client and they are sent to the streaming server periodically The network adaptation manager in the streaming server estimates the current network status from feedback packets and adaptively adjusts the sending rate by frame dropping. For this, we propose the real-time parsing and the frame-based prioritized packetization of the TS packet. The proposed system is implemented in software and evaluated over the LAN testbed. The experimental results show that the proposed system can enhance the end-to-end QoS of HD video streaming over the best-effort network.