• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.6
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• pp.353-362
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• 2015

In order to provide smart devices with high quality multimedia streaming services, an adaptive streaming technique over HTTP has been received much attention recently and the Dynamic Adaptive Streaming over HTTP (DASH) standard has been established. In DASH, however, the technique to select an appropriate quality of multimedia based on the performance metrics measured in a smart device might have some difficulties to reflect the capabilities of other neighboring smart devices and dynamic network conditions in real time. To solve the problem, this paper proposes a novel software agent approach, called DASH agent (DA), which gathers and analyzes the device capabilities and dynamic network conditions in real time and finally determines the highest achievable quality of segment to meet the best Quality of Experience (QoE) in current situations. The simulation results show that our approach provides higher quality of multimedia segments with less frequency of quality changes to lower quality of multimedia segments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.476-481
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• 2012

Recently, QoS/QoE technology as a part of the HTTP-based adaptive streaming technology has attracted attention. In this paper, we find out HTTP-based adaptive and dynamic streaming technology. It is based on a dynamic adaptive streaming system over HTTP, which is designed and implemented. The system consist of conversion by the bit rate of MPEG2-TS files, division of segment, creation of MPD(Media Presentation Description) and bitrate's player through analysis of MPD File between servers and clients in network environments of dynamic and adaptive. This diverse network environments, continuous and smooth playback of video will be used in various multimedia fields.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.7
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• pp.467-476
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• 2014

Recently, various services which use the fused form of broadcasting and communication are being offered over the Internet globally. To provide various interactive services through connected smart TV on wired or wireless network, the seamless multimedia service is key feature. In this paper, Dynamic Adaptive Streaming over HTTP (DASH)is adopted to develop cost-effective adaptive streaming system for Open Hybrid TV(OHTV) service. This system can provide seamless adaptive streaming service for IP VOD, Video Clips, Ad insertion which are defined in OHTV.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.488-490
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• 2012

Nowadays QoS / QoE using technology as part of HTTP, dynamic adaptive streaming technology that became a big issue. In this paper, using HTTP, dynamic adaptive streaming technology is introduced. This dynamic adaptive streaming using HTTP-based system design and implementation. In this system, a number of MPEG2-TS file bitrate's conversion of image quality, a certain amount of time by the division of Segment, standing before the final note of the files that are used in transmission MPD (Media Presentation Description) File creation and streaming between servers and clients using HTTP to a dynamic and adaptive network environment consists of bitrate's streamers. In a network environment in which an unspecified number of seamless continuous playback of video streaming for a variety of sectors and will be utilized in the field of multimedia.

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

• Journal of KIISE
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• v.42 no.8
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• pp.1039-1048
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• 2015

Recently, the web-based adaptive streaming service, DASH (Dynamic Adaptive Streaming over HTTP), is receiving more attention. However, existing network-based and buffer-based video quality control schemes in DASH environments make oscillation of segment throughput, causing degradation of the quality of experience (QoE) with frequent quality changes and playback interruptions because these schemes do not consider the content characteristics. In this paper, we propose a C-DASH (Content Characteristics based Dynamic Adaptive Streaming over HTTP) scheme in order to improve the QoE in DASH environments. The C-DASH scheme performs seamless and smooth quality control based on the segment throughput, buffer status, and segment size of the content. Based on simulation results, it is confirmed that the C-DASH scheme can improve the QoE, when compared with the existing quality control schemes.

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

• 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.

• 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.