• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.668-672
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• 2009

In wireless ad-hoc network, knowing the available bandwidth of the time varying channel is imperative for live video streaming applications. This is because the available bandwidth is varying all the time and strictly limited against the large data size of video streaming. Additionally, adapting the encoding rate to the suitable bit-rate for the network, where an overlarge encoding rate induces congestion loss and playback delay, decreases the loss and delay. While some effective rate controlling methods have been proposed and simulated well like VTP (Video Transport Protocol) [1], implementing to cooperate with the encoder and tuning the parameters are still challenging works. In this paper, we show our result of the implementation experiment of VTP based encoding rate controlling method and then introduce some techniques of our parameter tuning for a video streaming application over wireless environment.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.81-93
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• 2023

The popularity of short-form video platforms like TikTok has increased recently. Short-form videos are significantly shorter than traditional videos, and viewers regularly switch between different types of content to watch. Therefore, a successful prefetching strategy is essential for this novel type of video. This study provides a resource-effective prefetching technique for streaming short-form videos. The suggested solution dynamically adjusts the quantity of prefetched video data based on user viewing habits and network traffic conditions. The results of the experiments demonstrate that, in comparison to baseline approaches, our method may reduce data waste by 21% to 83%, start-up latency by 50% to 99%, and the total time of Re-buffering by 90% to 99%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.341-349
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• 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 Broadcast Engineering
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• v.23 no.1
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• pp.104-114
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• 2018

Recently, as HTTP-based video streaming traffic continues to increase, Dynamic Adaptive Streaming over HTTP(DASH), which is one of the HTTP-based adaptive streaming(HAS) technologies, is receiving attention. Accordingly, many video quality control techniques have been proposed to provide a high quality of experience(QoE) to clients in a DASH environment. In this paper, we propose a new quality control method using ANFIS(Adaptive Network based Fuzzy Inference System) which is one of the neuro-fuzzy system structure. By using ANFIS, the proposed scheme can find fuzzy parameters that selects the appropriate segment bitrate for clients. Also, considering the characteristic of VBR video, the next segment download time can be more accurately predicted using the actual size of the segment. And, by using this, it adjusts video quality appropriately in the time-varying network. In the simulation using NS-3, we show that the proposed scheme shows higher average segment bitrate and lower number of bitrate-switching than the existing methods and provides improved QoE to the clients.

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

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.559-572
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• 2020

As internet technology advances, users can share content online, and many sharing services exist. According to a recently published digital forensic study, when playing an online streaming service, you can restore the played video by reconstructing the Chrome cache file left on local device such as a PC. This can be seen as evidence that the user watched illegal video content. From a different point of view, copyright infringement occurs when a malicious user restores video stream and share it to another site. In this paper, we selected 23 online streaming services that are widely used both at home and abroad. After streaming videos, we tested whether we can recover original video using cache files stored on the PC or not. As a result, the paper found that in most sites we can restore the original video by reconstructing cache files. Furthermore, this study also discussed methodologies for preventing copyright infringement in online streaming service.

• Journal of KIISE
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• v.45 no.2
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• pp.187-194
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• 2018

Recently, Hypertext Transfer Protocol (HTTP) adaptive streaming service is attracting attention. The existing quality adaptive scheme of HTTP adaptive streaming service adjusts the video quality according to the network bandwidth or the client buffer size. However, the problem with the existing quality adaptive scheme is the QoE (Quality of Experience) degradation caused by the unnecessary quality change that occurs due to frequent bandwidth change or fixed buffer threshold. We propose a video quality maintenance scheme that improves average video quality and minimizes unnecessary quality change in order to improve the QoE of HTTP adaptive streaming service in the changing network environment. The proposed scheme maintains high quality for a long time by setting the quality maintenance duration to be long when buffer occupancy and video quality are high. The experimental results show that the proposed scheme improves QoE by improving the average video quality and minimizing the quality change.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.43-52
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• 2019

360 Virtual Reality(VR) service is getting attention in the domestic streaming market as 5G era is upcoming. However, existing IPTV-based 360 VR video services use upto 4K 360 VR video which is not enough to satisfy customers. It is generally required that over 8K resolution is necessary to meet users' satisfaction level. The bit rate of 8K resolution video exceeds the bandwidth of single QAM channel(38.817mbps), which means that it is impossible to provide 8K resolution video via the IPTV broadcast network environment. Therefore, we suggest and implement the edge streaming system for low-latency streaming to the display devices in the local network. We conducted experiments and confirmed that 360 VR streaming with a viewport switching delay less than 500ms can be achieved while using less than 100mbps of the network bandwidth.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.458-463
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• 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
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• v.44 no.1
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• pp.95-106
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• 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.