• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.308-324
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• 2018

HTTP adaptive streaming (HAS) is a promising technology for delivering video content over the Internet. HAS-based video streaming solutions rely on bandwidth estimation to select the appropriate video bitrate. Video streaming solutions that consider network conditions provide users with seamless video playback. However, when multiple clients compete for a common bottleneck link, conventional bandwidth estimation schemes that consider only one client overestimate the network bandwidth due to the ON-OFF traffic pattern. The bandwidth overestimation can cause Quality of Experience (QoE) degradation, such as unnecessary changes in video quality, and unfairness of video quality. In this paper, we propose a client-side bandwidth estimation scheme to obtain a better QoE of HAS in the multiple-client environment. The proposed scheme differentiates the client buffer status according to the buffer occupancy, and then estimates the available network bandwidth based on the buffer status and segment throughput. We evaluate the performance of HAS implemented in the ns-3 network simulator. Simulation results show that compared with the conventional schemes, the proposed scheme can enhance the QoE.

• KIISE Transactions on Computing Practices
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• v.21 no.12
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• pp.780-785
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• 2015

Recently HTTP (Hypertext Transfer Protocol) adaptive streaming services have been the subject of much attention. The video quality control scheme of conventional HTTP adaptive streaming services estimates bandwidth using segment throughput and smooths out the sample of segment throughput. However, the conventional scheme has the problem of QoE (Quality of experience) degradation occurring with buffer underflow and frequent quality change due to the fixed number of samples. In order to solve this problem, we propose a video quality control scheme based on segment throughput and buffer occupancy. The proposed scheme determines the number of samples according to the variation of segment throughput. The proposed scheme also controls video quality based on the threshold of bitrate to keep stable buffer occupancy. The simulation results show that proposed scheme improves QoE by preventing buffer underflow and decreasing quality change when compared with the conventional scheme.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.1-9
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• 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)
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• v.15 no.7
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• pp.2513-2530
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• 2021

With the fast development of information and communication technologies, video streaming services and applications are increasing rapidly. However, the network condition is volatile. In order to provide users with better quality of service, it is necessary to develop an accurate and low-complexity model for Quality of Experience (QoE) prediction of time-varying video. Memory effects refer to the psychological influence factor of historical experience, which can be taken into account to improve the accuracy of QoE evaluation. In this paper, we design subjective experiments to explore the impact of Short-Term Memory (STM) on QoE. The experimental results show that the user's real-time QoE is influenced by the duration of previous viewing experience and the expectations generated by STM. Furthermore, we propose analytical models to determine the relationship between intrinsic video quality, expectation and real-time QoE. The proposed models have better performance for real-time QoE prediction when the video is transmitted in a fluctuate network. The models are capable of providing more accurate guidance for improving the quality of video streaming services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4519-4533
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• 2015

Hypertext Transfer Protocol (HTTP) adaptive streaming has become a new trend in video delivery. An HTTP adaptive streaming client needs to effectively estimate resource availability and demand. However, due to the bitrate of the video encoded in variable bitrate (VBR) mode, a bitrate mismatch problem occurs. With the rising demand for mobile devices, the likelihood of cases where two or more HTTP adaptive streaming clients share the same network bottleneck and competing for available bandwidth will increase. These mismatch and competition issues lead to network congestion, which adversely affects the Quality of Experience (QoE). To solve these problem, we propose a video rate adaptation scheme for the HTTP video streaming to guarantee and optimize the QoE. The proposed scheme estimates the available bandwidth according to the bitrate of each segment and also schedules the segment request time to expedite the response to the bandwidth variation. We used a multi-client simulation to prove that our scheme can effectively cope with drastic changes in the connection throughput and video bitrate.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.188-198
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• 2018

With recent development of high-speed wide-area wireless networks and wide spread of highperformance wireless devices, the demand on seamless video streaming services in Long Term Evolution (LTE) network environments is ever increasing. To meet the demand and provide enhanced Quality of Experience (QoE) with mobile users, the Dynamic Adaptive Streaming over HTTP (DASH) has been actively studied to achieve QoE enhanced video streaming service in dynamic network environments. However, the existing DASH algorithm to select the quality of requesting video segments is based on a procedural algorithm so that it reveals a limitation to adapt its performance to dynamic network situations. To overcome this limitation this paper proposes a novel quality selection mechanism based on a Deep Q-Network (DQN) model, the DQN-based DASH ABR($DQN_{ABR}$) mechanism. The $DQN_{ABR}$ mechanism replaces the existing DASH ABR algorithm with an intelligent deep learning model which optimizes service quality to mobile users through reinforcement learning. Compared to the existing approaches, the experimental analysis shows that the proposed solution outperforms in terms of adapting to dynamic wireless network situations and improving QoE experience of end users.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1811-1818
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• 2013

As the broadband network are being deployed recently, the IPTV (Internet Protocol TV) has appeared and become a most representative service that incorporates audio, video, etc. In spite of the long-period efforts, however, no standardized method exists to measure and evaluate the quality of video that is experienced through TV in the customer's premises. Therefore, before developing a method to measure and evaluate the quality of experience (QoE) for video that is the ultimate goal, this paper reviews the outcomes from the past standardization activities and drive a few important implications that would be reflected to the method to measure and evaluate QoE for video.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8B
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• pp.751-759
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• 2009

Due to the advance of WLAN technology, the use of the multimedia service such as the video streaming service has been increased in the home network. However, we need to study the method which decreases the transmission delay and the frame loss rate to provide QoS of the video streaming service. Therefore, this paper proposes an active buffer management mechanism to guarantee QoS of the streaming service in IEEE 802.11e EDCA. The proposed protocol discards the frame in the HoL of the buffer based on the importance of each frame and the virtual transmission delay of frame newly arriving at the buffer. In the simulation results, the proposed algorithm not only decreases the frame loss probability of important I and P frames but also stabilizes the transmission delay. It may increase the QoS of video streaming services.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.334-344
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• 2010

Recently, due to the prevalence of various mobile devices and broadband wireless networks, a significant interests and demands for multimedia streaming services over the Internet have been increasing. However, it is difficult to transmit continuous multimedia stream when mobile terminals are moving. Therefore, in order to deploy mobile IPTV service in the broadband wireless network, efficient wireless resource utilization and seamless QoE (Quality of Experience) offers to the users are an important issue. In this paper, we propose a network based adaptive streaming scheme, called MARC (Mobile Adaptive Rate Control), which controls the quality of the video and rate of the video based on the status of the wireless channel. The proposed scheme uses awareness information of the wireless channel status and controls transmitting streaming video which is suitable for the wireless channel status and mobile station location, in order to provide a seamless video playback for mobile environment in addition to improving the quality of a streaming service. The proposed MARC scheme alleviates the discontinuity of video playback and allocates suitable client buffer in broadband wireless network. Simulation results demonstrate the effectiveness of our proposed scheme.

• The Journal of Information Technology
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• v.12 no.3
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• pp.49-57
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• 2009

This Paper provides perceptual metrics for video quality based on properties of human visual system, and audio quality based on human audition. All metrics work without reference signals, allowing non-intrusive, in-service measurements. A simple and easy-to-learn user interface displays the metrics and saves them in popular file formats like CSV. In this paper, proposed method was able to various and corrective measurement for the multimedia service video quality. As that it was able to application to set up service guide line and the methode of measurement and system for the set up standardization of the high quality video service.