• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.1
• /
• pp.374-395
• /
• 2017

Users quite often experience volatile channel conditions which negatively influence multimedia transmission. HTTP adaptive streaming has emerged as a new promising technology where the video quality can be adjusted to variable network conditions. Nevertheless, the new technology does not remain without drawbacks. As it has been observed, multiple video players sharing the same network link have often problems with achieving good efficiency and stability of play-out due to a mutual interference and competition among video players. Our investigation indicates that there may be another cause for under-performance of the streamed video. In an emulated environment, we implemented three algorithms of adaptive video play-out based on bandwidth or buffer assessment. As we show, traffic generated by players employing the same or similar play-out strategies is positively correlated and synchronised (clustered), whereas traffic originated from different play-out strategies shows negative or no correlations. However, when some of the parameters of the play-out strategies are randomised, the correlation and synchronisation diminish what has a positive impact on the smoothness of the traffic and on the video quality perceived by end users. Our research shows that non-correlated traffic flows generated by play-out strategies improve efficiency and stability of streamed adaptive video.

• Journal of KIISE
• /
• v.44 no.4
• /
• pp.423-432
• /
• 2017

Recently, the video quality control schemes for the improvement of the QoE (Quality of Experience) of video streaming services that are based on DASH (Dynamic Adaptive Streaming over HTTP), which is a standard of HTTP adaptive streaming (HAS) services, have been studied. However, the problem of the existing schemes is the degradation that is due to unnecessary quality changes because the VBR (Variable Bitrate) characteristics of the video are not considered. In this paper, we propose a SC-DASH (Segment Characteristics-based DASH) which controls the video quality based on the segment characteristics. The SC-DASH can prevent the occurrence of the unnecessary quality changes by controlling the video quality based on the size of the next segment, the segment throughput, and the buffer occupancy. The experiment results showed that the SC-DASH improves the QoE by reducing the unnecessary quality changes compared with the existing quality control schemes.

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

• 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.16 no.4
• /
• pp.1249-1265
• /
• 2022

Video streaming has become one of the most popular applications for mobile devices. The network bandwidth required for video streaming continues to exponentially increase as video quality increases and the user base grows. Multi-Path TCP (MPTCP), which allows devices to communicate simultaneously through multiple network interfaces, is one of the solutions for providing robust and reliable streaming of such high-definition video. However, mobile video streaming over MPTCP raises new concerns, e.g., power consumption and cellular data usage, since mobile device resources are constrained, and users prefer to minimize such costs. In this work, we propose a mobile video streaming framework over MPTCP (mDASH) to reduce the costs of energy and cellular data usage while preserving feasible streaming quality. Our evaluation results show that by utilizing knowledge about video behavior, mDASH can reduce energy consumption by up to around 20%, and cellular usage by 15% points, with minimal quality degradation.

• KIISE Transactions on Computing Practices
• /
• v.21 no.7
• /
• pp.458-463
• /
• 2015

These days, streaming users are using ABR (Adaptive Bitrate) technique services by requesting the most adequate video rate selectively based on their own channel states. Most ABR related video rate adaptation techniques are only focused on real-time bitrate adaptations based on their own channel state, and misses energy limited characteristics that come from a mobile device's battery dependence. In other words, the mobile device's important characteristics and accompanying energy consumption are not being considered and causes dissatisfaction over streaming services. In this paper, we propose energy efficient prefetching based dynamic adaptive video streaming techniques, which saves unnecessary consumed energy while providing video rates of the same performance. Our scheme continuously turns off energy modules with enough streaming in the buffer and turns on in case of the opposite situation to save energy. Through the performance evaluation, this study's proposed scheme is 60% better than the previous work at global average mobile download speed.

• Journal of KIISE
• /
• v.44 no.1
• /
• pp.95-106
• /
• 2017

HTTP adaptive streaming has recently emerged to handle the rapidly growing traffic and to provide high quality multimedia contents. To improve the QoE (Quality of Experience) for HTTP adaptive streaming service, the average video bitrate should be maximized, and the video switching frequency (difference of bitrate between adjacent segments) and video stalling events need to be minimized. The recently proposed quality adaptation algorithms for HTTP adaptive streaming do not provide high QoE, since detailed QoE factors such as video switching frequency and bitrate difference of adjacent segments, are not considered. In this paper, we propose a SQA (Smooth Quality Adaptation) algorithm to improve the user QoE. The proposed algorithm provides the smoothed QoE, such that it minimizes the unnecessary video switching events by maintaining the quality in a certain period, thus minimizing the bitrate difference of adjacent segments. Through simulation, we confirm that the proposed algorithm reduces the unnecessary switching events, and prevents the sudden decrease in video quality.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.4
• /
• pp.784-799
• /
• 2013

This paper presents an adaptive rate control scheme for streaming-based content sharing service. This scheme delivers multimedia contents from a user device to another device or seamlessly redirects streaming service across heterogeneous user devices. In the proposed scheme, a streaming server adjusts video quality level according to the network and client status. Our scheme is different from other rate control schemes, because the video quality at the server is decided not only based on the available bandwidth, but also based on the device characteristics and bandwidth requirement at the access network. We also propose a bandwidth estimation method to achieve more equitable bandwidth allocations among streaming flows competing for the same narrow link with different Round Trip Times (RTTs). Through the simulation, we prove that our scheme improves the network stability and the quality of streaming service by appropriately adjusting the quality of the video stream. The simulation results also demonstrate the ability of the proposed scheme in ensuring RTT-fairness while remaining throughput efficient.

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

• Journal of KIISE
• /
• v.41 no.10
• /
• pp.824-831
• /
• 2014

HTTP (Hypertext Transfer Protocol) Adaptive Streaming is gaining attention because it changes bitrates to adapt changing network conditions. Since HAS (HTTP Adaptive Streaming) client downloads the video data based on TCP (Transmission Control Protocol), it estimates incorrectly the available bandwidth and leads to an unnecessary video quality change in long-delay networks. In this paper, we propose a buffer-based quality control scheme in order to improve the service quality and smooth playback in the HAS. The proposed scheme estimates accurately the available bandwidth based on a modified streaming model that considers network delay. It also calculates the sustainability of the video quality to prevent an unnecessary quality change and determines the inter-request time on the basis of the buffer status. Through the simulation, we prove that our scheme improves the QoS (Quality of Service) of the HAS service and controls the video quality smoothly in long-delay networks.