• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.47-53
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• 2012

In general, it is essential that contents are to be provided with proper bitrate according to network conditions in order to support higher quality of video streaming services over wired and wireless networks. Recently, DASH is adopted by the MPEG as the standard for HTTP based adaptive streaming technology and consists of the server and clients. The clients should parse XML files from the server and play contents after accessing the finely divided segments into various bitrates. In this paper, we designed a Smart AP(Access Point) which exists between DASH contents server and Non-DASH clients enables provide DASH services to Non-DASH clients. In addition, proposed Smart AP provides DASH service to various types of clients as maintaining the existing environment without additional development costs.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.549-558
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• 2018

We designed and implemented streaming server based on MEPG DASH, which is able to provide high quality video with low-latency live streaming service like 360 VR video on the existing cable network via low-spec media service devices such as IPTV and OTT(Over the Top) SettopBox. We also designed and applied management process which is cable of supporting services by cashing streaming video file(MPD, Segment Files) to reduce the server response delay time. Further more, we confimred that it is also able to provide high quality of tiled video streaming with over 50,000kbps bitrate and 8K@60P through the experiment.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.47-55
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• 2019

Free-viewpoint video (FVV) service provides multi viewpoints of contents and synthesizes intermediate video files which are not captured on some view angles so that enables users to watch as they choose wherever they want. Synthesizing video is necessary technique to provide FVV video service, because every video of the FVV contents for different view angles cannot be stored to the content server physically. For the reason, fast view synthesis can improve the quality of video service and increase user's satisfaction. One of the studies for FVV service, a method was proposed to transmit FVV service based on DASH (Dynamic Adaptive Streaming over HTTP). There is big advantage on using DASH that it is commonly used to transport video service. However, the method was only a conceptual proposal, so it is difficult to implement the system using the proposal. In this paper, we propose an implementation method to provide real-time FVV service smoothly. We suggest a system structure and operation method on the server and client side in detail, which is to be applicable to synthesize video quickly. Also, we suggest generating FVV service map additionally which controls a FVV service overall. We manage real-time information of the whole service through the service map. The service can be controlled by reducing the possible delay from network situation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.203-206
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• 2012

본 논문은 HTTP protocol을 이용한 미디어 Streaming 서비스 표준인 MPEG-DASH(Dynamic Adaptive Streaming over HTTP)를 기반으로 한 N-Screen 서비스 동기화 방안을 제시한다. N-Screen 서비스란 다수의 미디어 Device를 이용하여 하나의 콘텐츠들을 공유 및 전송하는 서비스를 뜻한다. 이는 MPEG-DASH 표준 기술을 활용함으로써 보다 효율적인 서비스 이용이 가능하다. DASH는 다수의 품질의 같은 영상들을 시간별로 분할하여 Server에서 보유하여 한 Device에게 네트워크 환경에 맞춰 가장 적합한 Segment들을 전달 및 전환함으로써 끊기지않는 Streaming 서비스가 가능하다. 하지만 현재 MPEG-DASH 표준기술에서는 N-Screen 서비스에 대한 활용방안 시나리오가 재정되어 있지 않아 다수의 Device에서 Segment를 끊김없는 Media Streaming 서비스를 지원하기 위한 방안이 필요하다. 이를 위해 본 논문에서는 한 Device가 다른 Device에게 N-screen을 위한 동기화 정보를 전송함으로써 특정 콘텐츠가 끊기지 않고 연이어 볼 수 있는 동기화를 이룰 수 있는 방안을 대한 서비스 시나리오를 제시한다.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.33-48
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• 2020

By Digital Transformation, new technologies like ML (Machine Learning), Big Data, Cloud, VR/AR are being used to video streaming technology. We choose ML to provide optimal QoE (Quality of Experience) in various network conditions. In other words, ML helps DASH in providing non-stopping video streaming. In DASH, the source video is segmented into short duration chunks of 2-10 seconds, each of which is encoded at several different bitrate levels and resolutions. We built and compared the performances of five prototypes after applying five different machine learning algorithms to DASH. The prototype consists of a dash.js, a video processing server, web servers, data sets, and five machine learning models.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.548-560
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• 2022

Video based Point Cloud Compression (V-PCC) is one of the compression methods for compressing point clouds, and shows high efficiency in dynamic point cloud compression with movement due to the feature of compressing point cloud data using an existing video codec. Accordingly, V-PCC is drawing attention as a core technology for immersive content services such as AR/VR. In order to effectively service these V-PCC contents through a media streaming platform, it is necessary to encapsulate them in the existing media file format, ISO based Media File Format (ISOBMFF). However, in order to service through an adaptive streaming platform such as Dynamic Adaptive Streaming over HTTP (DASH), it is necessary to encode V-PCC contents of various qualities and store them in the server. Due to the size of the 2D media, it causes a great burden on the encoder and the server compared to the existing 2D media. As a method to solve such a problem, it may be considered to configure a streaming platform based on content obtained through V-PCC content encoding based on SHVC. Therefore, this paper encapsulates the SHVC-based V-PCC bitstream into ISOBMFF suitable for DASH service and proposes a configuration method to service it. In addition, in this paper, we propose ISOBMFF encapsulation and DASH configuration method to effectively service SHVC-based V-PCC contents, and confirm them through verification experiments.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.5
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• pp.297-307
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• 2022

The simple procedural segment selection algorithm commonly used in Dynamic Adaptive Streaming over HTTP (DASH) reveals severe weakness to provide high-quality streaming services in the integrated mobile networks of various wired and wireless links. A major issue could be how to properly cope with dynamically changing underlying network conditions. The key to meet it should be to make the segment selection algorithm much more adaptive to fluctuation of network traffics. This paper presents a system architecture that replaces the existing procedural segment selection algorithm with a deep reinforcement learning algorithm based on the Asynchronous Advantage Actor-Critic (A3C). The distributed A3C-based deep learning server is designed and implemented to allow multiple clients in different network conditions to stream videos simultaneously, collect learning data quickly, and learn asynchronously, resulting in greatly improved learning speed as the number of video clients increases. The performance analysis shows that the proposed algorithm outperforms both the conventional DASH algorithm and the Deep Q-Network algorithm in terms of the user's quality of experience and the speed of deep learning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.527-530
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• 2014

DASH is a well-known streaming technology, which was proposed in 2010 by MPEG and standardized in 2011. Major multimedia contents service providers, including Apple, Microsoft, and Adobe are all using this technology to support their media streaming services. Whenever a new service is requested to the server, the DASH technology helps servicing the multimedia streaming to client by recognizing the capacity of network and by adapting the quality of the multimedia contents. In DASH, the quality of multimedia contents will be automatically lowered to meet the fluctuating network status, when undesirable breaks interrupt the network. In this paper, we classified and analysed the advantages and disadvantages of DASH researches in three aspects: bit-rate measurement method, bandwidth aggregation method; rate adaptation metrics, algorithms and logics; user's experiences and QoE.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.42-52
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• 2017

DASH (Dynamic Adaptive Streaming over HTTP) is an adaptive streaming technique that enables transmission of multimedia content when clients request the multimedia contents to server. In this system, to ensure the best quality of the content to satisfy users, it is necessary to precisely measure the residual bandwidth. However, the measured residual bandwidth by the DASH, which is not considering the transmission features of TCP, varies by the size of previous media segment, which makes it hard to ensure QoE to users. In this paper, we excluded the TCP Slow start range from measurement of residual bandwidth and suggested the new DASH bandwidth measuring method to decrease the error. Then, we realized the method in DASH system based on open source, and compared the existing measuring method. The new method showed that the accuracy of result has increased by 20%. Also, it could improve the QoE of users in terms of service quality and number of changes of segment quality.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.94-104
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• 2020

Currently media consumption over fixed/mobile Internet is mostly conducted by adaptive media streaming technology such as DASH (Dynamic Adaptive Streaming over HTTP), which is an ISO/IEC MPEG (Moving Picture Experts Group) standard, or some other technologies similar to DASH. All these heavily depend on the HTTP caches that ISPs (Internet Service Providers) are obliged to provide sufficiently to make sure fast enough Web services. As a result, as the number of media streaming users increases, ISPs' burden for HTTP cache has been greatly increased rather than CDN (Content Delivery Network) providers' server burden. Hence ISPs charge traffic cost to CDN providers to compensate for the increased cost of HTTP caches. Recently in order to reduce the traffic cost of CDN providers, P2P (Peer-to-Peer)-assisted DASH system was proposed and a peer selection algorithm that maximally reduces CDN provides' traffic cost was investigated for this system. This algorithm, however, tends to concentrate the burden upon the selected peer. This paper proposes a new peer selection algorithm that distributes the burden among multiple peers while maintaining the proper reduction level of the CDN providers' cost. Through implementation of the new algorithm in a Web-based media streaming system using WebRTC (Web Real-Time Communication) standard APIs, it demonstrates its effectiveness with experimental results.