• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.11
• /
• pp.4585-4603
• /
• 2015

Video streaming services make up a large proportion of Internet traffic on both fixed and mobile access throughout the world. Adaptive streaming allows for dynamical adaptation of the bitrate with varying network conditions, to guarantee the best user experience. Adaptive bitrate algorithms face a significant challenge in correctly estimating the throughput as it varies widely over time. In this paper, we first evaluate the throughput estimation techniques and show that the method that we have used offers stable response to throughput fluctuations while maintaining a stable playback buffer. Then, we propose an adaptive bitrate scheme that intelligently selects the video bitrates based on the estimated throughput and buffer occupancy. We show that the proposed scheme improves viewing experience by achieving a high video rate without taking unnecessary risks and by minimizing the frequency of changes in the video quality. Furthermore, we show that it offers a stable response to short-term fluctuations and responds swiftly to large fluctuations. We evaluate our algorithm for both constant bitrate (CBR) and variable bitrate (VBR) video content by taking into account the segment sizes and show that it significantly improves the quality of video streaming.

• 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.12 no.8
• /
• pp.3856-3872
• /
• 2018

HTTP-based adaptive streaming (HAS) has recently been widely deployed on the Internet. In the HAS system, a video content is encoded at multiple bitrates and the encoded video content is segmented into small parts of fixed durations. The HAS client requests a video segment and stores it in the playout buffer. The rate adaptation algorithm employed in HAS clients dynamically determines the video bitrate depending on the time-varying bandwidth. Many studies have shown that an efficient rate adaptation algorithm is critical to ensuring quality-of-experience in HAS systems. However, existing algorithms have problems estimating the network bandwidth because bandwidth estimation is performed on the client-side application stack. Without the help of transport layer protocols, it is difficult to achieve accurate bandwidth estimation due to the inherent segment-based transmission of the HAS. In this paper, we propose an alternative approach that utilizes the playout buffer occupancy rather than using bandwidth estimates obtained from the application layer. We start with a queueing analysis of the playout buffer. Then, we present a buffer-aware rate adaptation algorithm that is solely based on the mean buffer occupancy. Our simulation results show that compared to conventional algorithms, the proposed algorithm achieves very smooth video quality while delivering a similar average video bitrate.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.6
• /
• pp.2144-2159
• /
• 2015

CISCO VNI predicted an average annual growth rate of 66% for mobile video traffic between 2014 and 2019 and accordingly much academic research related to video streaming has been initiated. In video streaming, Adaptive Bitrate (ABR) is a streaming technique in which a source video is stored on a server at variable encoding rates and each streaming user requests the most appropriate video encoding rate considering their channel capacity. However, these days, ABR related studies are only focusing on real-time rate adaptation omitting energy efficiency though it is one of the most important requirement for mobile devices, which may cause dissatisfaction for streaming users. In this paper, we propose an energy efficient prefetching based dynamic adaptive streaming technique by considering the limited characteristics of the batteries used in mobile devices, in order to reduce the energy waste and provide a similar level of service in terms of the average video rate compared to the latest ABR streaming technique which does not consider the energy consumption. The simulation results is showing that our proposed scheme saves 65~68% of energy at the average global mobile download speed compared to the latest high performance ABR algorithm while providing similar rate adaptation performance.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2017.06a
• /
• pp.197-200
• /
• 2017

퍼지 논리를 기반으로 한 적응형 스트리밍 기법인 FDASH 적응 알고리즘은 빠르게 변하는 네트워크 상황에서 우수한 콘텐츠의 화질을 보장하면서 끊김 없는 서비스를 제공하는 특성을 보이지만 비디오의 화질이 자주 변하기 때문에 최고의 사용자 체감 품질 (QoE: Quality of Experience)을 제공하지 못 할 수도 있다. 본 논문에서는 제한된 버퍼 크기를 가지고 동일한 콘텐츠의 화질을 보장하면서도 비디오 화질의 변화 횟수를 줄여서 최적의 QoE를 제공할 수 있도록 하는 변환된 퍼지 논리 기반의 DASH 적응 알고리즘을 제안하고자 한다. 제안된 방식은 우선 퍼지 논리 제어부(FLC : Fuzzy Logic Controller)의 수정을 통하여 다음 세그먼트의 비트율에 대해 최적의 판단을 하도록 하였고, 세그먼트 비트율 필터링 모듈 (SBFM: Segment Bitrate Filtering Module)을 추가하여 비디오 화질의 변화 횟수가 최소화 될 수 있도록 하였으며, 스트리밍 서비스 시작 시 SBFM에 의해 일정시간 저화질의 비디오를 시청해야 하는 상황을 막기 위한 Start Mechanism을 추가하였고, 마지막으로 버퍼의 오버플로우를 방지하기 위해 Sleeping Mechanism을 추가하였다. NS-3를 이용한 네트워크 모의실험 결과를 통해 제안된 방식이 FDASH 방식에 비하여 제한된 버퍼크기 상황 하에서도 오버플로우가 발생하지 않으며 점대점(Point to Point) 상황에서는 거의 동일 화질 성능을 보이면서도 비디오 화질 변화 횟수를 50% 이상 줄일 수 있음과 일반 Wifi환경에서는 오히려 17.8%정도 더 뛰어난 비디오 화질 성능을 보이면서 비디오 화질변화 횟수 측면에서는 53.1%정도 줄일 수 있음을 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.10
• /
• pp.2430-2447
• /
• 2013

In recent years, HTTP adaptive streaming (HAS) has attracted considerable attention as the state-of-the-art technology for video transport. HAS dynamically adjusts the quality of video streaming according to the network bandwidth and device capability of users. Content-Centric Networking (CCN) has also emerged as a future Internet architecture, which is a novel communication paradigm that integrates content delivery as a native network primitive. These trends have led to the new research issue of harmonizing HAS with the in-network caching provided by CCN routers. Previous research has shown that the performance of HAS can be improved by using the H.264/SVC(scalable video codec) in the in-network caching environments. However, the previous study did not address the misbehavior that causes video freeze when overestimating the available network bandwidth, which is attributable to the high cache hit rate. Thus, we propose a new SVC-based adaptation algorithm that utilizes a drop timer. Our approach aims to stop the downloading of additional enhancement layers that are not cached in the local CCN routers in a timely manner, thereby preventing excessive consumption of the video buffer. We implemented our algorithm in the SVC-HAS client and deployed a testbed that could run Smooth-Streaming, which is one of the most popular HAS solutions, over CCNx, which is the reference implementation of CCN. Our experimental results showed that the proposed scheme (SLA) could avoid video freeze in an effective manner, but without reducing the high hit rate on the CCN routers or affecting the high video quality on the SVC-HAS client.