• Journal of Korea Multimedia Society
• /
• v.18 no.7
• /
• pp.853-863
• /
• 2015

In this paper, we proposed cross-layered approach of video codec and communication system for the efficient video streaming service. Conventional video streaming is served by divided system which consist of video codec layer and communication layer. Its disintegration causes the limitation of the performance of video streaming service. With the cross-layered design, each layer could share the information and the service is able to enhance the performance. And we proposed the selective retransmission method in communication system based on the cross-layered system that reflect the information of encoded video data. Selective retransmission method which consider the characteristics of video data improves the performance of video streaming services. We verified the proposed method with raw format full HD test sequence with H.264/AVC codec and MATLAB simulation. The simulation results show that the proposed method improves about 10% PSNR performance.

• Journal of Korea Multimedia Society
• /
• v.20 no.1
• /
• pp.1-9
• /
• 2017

Explosive deployment of smart mobile devices such as smart phones, and tablets along with expansion of wireless internet bandwidth have enabled the deployment of mobile video streaming such that video traffic becomes the most important service in wireless networks. Recently, for more efficient video streaming services, the ISO MPEG group standardized a protocol called DASH (Dynamic Adaptive Streaming over HTTP) and the standard has been quickly adopted by many service providers such as YouTube and Netflix. Despite of the convenience of mobile streaming services, users also suffer from low QoE(Quality of Experience) due to dynamic channel fluctuations and unnecessary downloading due to high churning rates. This paper proposes a noble efficient video rate selection algorithm considering user buffer level, channel condition and churning rate. Computer simulation based performance study showed that the proposed algorithm improved the QoE significantly compared to a method that determines the video rate based on current channel conditions. Especially, the proposed method reduced the rebuffering rate, one of the most important performance factors of the QoE, to a nonnegligible level.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.11
• /
• pp.3775-3788
• /
• 2014

With the increasing number of the wireless and mobile networks, the way that people use the Internet has changed substantively. Wireless multimedia services, such as wireless video streaming, mobile video game, and mobile voice over IP, will become the main applications of the future wireless Internet. To accommodate the growing volume of wireless data traffic and multimedia services, cognitive radio (CR) and Information-Centric Network (ICN) have been proposed to maximize the utilization of wireless spectrum and improve the network performance. Although CR and ICN have high potential significance for the future wireless Internet, few studies have been conducted on collaborative operations of CR and ICN. Due to the lack of infrastructure support in multi-hop ad hoc CR networks, the problem is more challenging for video streaming services. In this paper, we propose a Cross-layer Video Streaming Mechanism (CLISM) for Cognitive Radio Ad Hoc Information Centric Networks (CRAH-ICNs). The CLISM included two distributed schemes which are designed for the forwarding nodes and receiving nodes in CRAH-ICNs. With the cross-layer approach, the CLISM is able to self-adapt the variation of the link conditions without the central network controller. Experimental results demonstrate that the proposed CLISM efficiently adjust video transmission policy under various network conditions.

• ETRI Journal
• /
• v.36 no.2
• /
• pp.253-263
• /
• 2014

In the near future, traditional narrow and fixed viewpoint video services will be replaced by high-quality panorama video services. This paper proposes a visual-attention-aware progressive region of interest (RoI) trick mode streaming service (VA-PRTS) that prioritizes video data to transmit according to the visual attention and transmits prioritized video data progressively. VA-PRTS enables the receiver to speed up the time to display without degrading the perceptual quality. For the proposed VA-PRTS, this paper defines a cutoff visual attention metric algorithm to determine the quality of the encoded video slice based on the capability of visual attention and the progressive streaming method based on the priority of RoI video data. Compared to conventional methods, VA-PRTS increases the bitrate saving by over 57% and decreases the interactive delay by over 66%, while maintaining a level of perceptual video quality. The experiment results show that the proposed VA-PRTS improves the quality of the viewer experience for interactive panoramic video streaming services. The development results show that the VA-PRTS has highly practical real-field feasibility.

• Asia pacific journal of information systems
• /
• v.31 no.1
• /
• pp.17-42
• /
• 2021

This study examines the adoption of subscription-based video on demand (SVOD) streaming services among consumers. Primarily, we explore the moderating effect of the two models of streaming services, standalone streaming services and bundled streaming services, on the users' adoption. We employ the Unified Theory of Acceptance and Use of Technology (UTAUT2) model in this study. We utilize the data collected from 337 Indian respondents and find that all constructs of the UTAUT2 model act as motivators of adoption. Gender, age, and experience of the respondent also play a moderating role in the adoption of streaming services. We also find that providing bundled streaming service positively moderates price-value and hedonic motivation of adoption. The study is perhaps the first of its kind that aims to understand the motivations for adoption of SVOD services, particularly in the Indian context, which has the fastest-growing base of internet users in the world.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.670-672
• /
• 2021

The video streaming technologies are used in diverse areas including aerospace. UAV (Unmanned Aerial Vehicle) is still being developed so that we are able to use the UAV not only in military areas but also in civil areas. Remotely monitoring and observing a certain area is possible via using video streaming service based on the UAV nowadays. However, UAV is vulnerable to weather conditions, plane's weight, battery capacity and so on, which makes many restrictions of flight time and video streaming services. In order to prolong the video streaming services, we can use a number of UAVs, fly them one by one, and switch video streaming channels. In the paper, we propose the methods how to interchange UAVs' missions and their video streaming channels to provide seamless video stream services.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.8
• /
• pp.3804-3819
• /
• 2018

The increasing popularity of HTTP adaptive video streaming services has dramatically increased bandwidth requirements on operator networks, which attempt to shape their traffic through Deep Packet inspection (DPI). However, Google and certain content providers have started to encrypt their video services. As a result, operators often encounter difficulties in shaping their encrypted video traffic via DPI. This highlights the need for new traffic classification methods for encrypted HTTP adaptive video streaming to enable smart traffic shaping. These new methods will have to effectively estimate the quality representation layer and playout buffer. We present a new machine learning method and show for the first time that video quality representation classification for (YouTube) encrypted HTTP adaptive streaming is possible. The crawler codes and the datasets are provided in [43,44,51]. An extensive empirical evaluation shows that our method is able to independently classify every video segment into one of the quality representation layers with 97% accuracy if the browser is Safari with a Flash Player and 77% accuracy if the browser is Chrome, Explorer, Firefox or Safari with an HTML5 player.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.26 no.6
• /
• pp.1505-1511
• /
• 2016

Live streaming is a method to provide media service by sending recoded media to a user's video player. In order to provide video and audio contents in real-time for a large number of users simultaneously, live streaming compatible protocols such as RTMP (Real Time Messaging Protocol), HLS (Http Live Streaming), are required. In this paper, we analyzed vulnerability of paid live streaming services with the captured packets from the applications used by six major OTT (over-the-top) companies in Korea supporting live streaming services. We found that streaming channels were not encrypted and access control mechanisms were not properly used. Thus, guest users can freely use paid live streaming services.

• Journal of Korea Multimedia Society
• /
• v.21 no.10
• /
• pp.1182-1194
• /
• 2018

The Dynamic Adaptive Streaming over HTTP(DASH) is envisioned to evolve to meet an increasing demand on providing seamless video streaming services in the near future. The DASH performance heavily depends on the client's adaptive quality selection algorithm that is not included in the standard. The existing conventional algorithms are basically based on a procedural algorithm that is not easy to capture and reflect all variations of dynamic network and traffic conditions in a variety of network environments. To solve this problem, this paper proposes a novel quality selection mechanism based on the Deep Q-Network(DQN) model, the DQN-based DASH Adaptive Bitrate(ABR) mechanism. The proposed mechanism adopts a new reward calculation method based on five major performance metrics to reflect the current conditions of networks and devices in real time. In addition, the size of the consecutive video segment to be downloaded is also considered as a major learning metric to reflect a variety of video encodings. Experimental results show that the proposed mechanism quickly selects a suitable video quality even in high error rate environments, significantly reducing frequency of quality changes compared to the existing algorithm and simultaneously improving average video quality during video playback.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.10
• /
• pp.1814-1829
• /
• 2011

In this paper, we present a model-based video bit rate estimation scheme for reducing the bit rate while maintaining a given target quality in many video streaming services limited by network bandwidth, such as IPTV services. Each item of video content can be stored on a video streaming server and delivered with the estimated bit rate using the proposed scheme, which consists of the following two steps: 1) In the first step, the complexity of each intra-frame in a given item of video content is computed as a frame feature to extract a group of candidate frames with a lot of bits. 2) In the second step, the bit rate of the video content is determined by applying statistical analysis and hypothesis testing to that group. The experimental results show that our scheme can reduce the bit rate by up to 78% with negligible degradation of subjective quality, especially with the low-complexity videos commonly used in IPTV services.