• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1768-1789
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• 2016

In contemporary video streaming systems based on HTTP protocol, video players at the client side are responsible for adjusting video quality to network conditions and user expectations. However, when multiple video clips are streamed simultaneously, an intricate application logic implemented in the video players overlays the TCP mechanism which is responsible for a balanced access to a shared network link. As a result, some video players may not obtain a fair share of network throughput and may be vulnerable to an unstable video bit-rate. Therefore, we propose to simplify the algorithms implemented in the video players, which are responsible for the adjustment of video quality and constrain their functionality only to sending feedback to a server about a state of the player buffer. The main logic of the system is shifted to the server, which is now responsible for bit-rate selection and prioritisation of the video streams transmitted to multiple clients. To verify our proposition, we performed several experiments in a laboratory environment which show that when the server cooperates with the clients, the video players experience fewer quality switches and the system achieves better fairness when allocating network throughput among the video players. However, this comes at the cost of worse utilisation of network bandwidth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2177-2193
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• 2018

This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.197-200
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• 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)
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• v.5 no.3
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• pp.592-606
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• 2011

Currently, the development of multimedia communication has progressed so rapidly that the video program service has become a requirement for ordinary customers. The quality of experience (QoE) for the visual signal is of the fundamental importance for numerous image and video processing applications, where the goal of video quality assessment (VQA) is to automatically measure the quality of the visual signal in agreement with the human judgment of the video quality. Considering the codec effect to the video quality, in this paper an efficient non-reference (NR) VQA algorithm is proposed which estimates the video quality (VQ) only by utilizing the distorted video signal at the destination. The VQA feature vectors (FVs) which have high relationships with the subjective quality of the distorted video are investigated, and a hybrid NR VQA (HNRVQA) function is established by considering the multiple FVs. The simulation results, testing on the SDTV programming provided by VCEG Phase I, show that the proposed algorithm can represent the VQ accurately, and it can be used to replace the subjective VQA to measure the quality of the video signal automatically at the destinations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2544-2557
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• 2019

Adaptive bitrate streaming is a crucial element in the implementation of high-quality streaming of media content over the Internet. Dynamic adaptive streaming over HTTP (MPEG-DASH) has lately emerged as the de facto solution for over-the-top (OTT) video streaming services. In this paper, we perform macro-level analysis on a real-world MPEG-DASH-based Internet live broadcasting service to gain insight into its behavior throughout the end-to-end service-provision chain, from broadcasters to viewers. Based on this analysis, we propose methods to improve the quality-of-experience (QoE) of MPEG-DASH-based services, particularly with regard to reducing broadcasting delays between recording and viewing of videos, as well as synchronizing client terminals.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.410-412
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• 2011

영상 서비스에서 사용자가 시청하는 비디오 화질을 측정하는 것은 사용자의 QoE(Quality of Experience)를 추정할 수 있는 중요한 작업 중 하나이다. 이를 위해 가장 널리 쓰이는 측정 방법 중 PSNR이 있다. PSNR은 원본영상과 시청영상간의 각 픽셀 값의 차이를 계산하여 화질을 측정하는 객관적인 평가 방법이다. 본 논문에서는 객관적 평가 방법인 PSNR에 시청자가 영상 측정 시 느낄 수 있는 시선 인식 집중도를 접목시킨 품질 측정방법을 제안한다. 이는 사용자의 시각적 특성이 고려되기 때문에 보다 사용자에게 맞는 영상 품질을 측정할 수 있게 된다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.331-338
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• 2019

Video services over Internet is getting important. Since the service quality of the video service provided by streaming over Internet may be degraded, the quality assessment and management are very important. Currently the objective method based on the measured values of parameters is being widely used for video services. The subjective assessment, however, is more ideal in that the quality that is experienced by human. This paper, therefore, proposes a subjective quality management scheme for video service in a mobile environment that overcomes the limitations of the subjective method. The proposed scheme is expected to contribute to implement a more efficient quality management system for video services in a mobile environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1373-1392
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• 2017

WiFi Direct (WD) is a state of the art technology for a Device-to-Device (D2D) communication in 802.11 networks. The performance of the WD system can be significantly affected by some key factors such as the type of application, specifications of MAC and PHY layer parameters, and surrounding environment etc. It is, therefore, important to develop a system model that takes these factors into account. In this paper, we focus on investigating the design parameters of the PHY layer that could maximize the efficiency of the WD 802.11 system. For this purpose, a basic theoretical model is formulated for a WD network under a 2x2 Multiple In Multiple Out (MIMO) TGn channel B model. The design level parameters such as input symbol rate and antenna spacing, as well as the effects of the environment, are thoroughly examined in terms of path gain, spectral density, outage probability and Packet Error Rate (PER). Thereafter, a novel adaptive algorithm is proposed to choose optimal parameters in accordance with the Quality of Experience (QoE) for a targeted application. The simulation results show that the proposed method outperforms the standard method thereby achieving an optimal performance in an adaptive manner.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3090-3102
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• 2015

The accuracy of an augmented reality (AR) application is highly dependent on the resolution of the object's image and the device's computational processing capability. Naturally, a mobile smart device equipped with a high-resolution camera becomes the best platform for portable AR services. AR applications require significant energy consumption and very fast response time, which are big burdens to the smart device. However, there are very few ways to overcome these burdens. Computation offloading via mobile cloud computing has the potential to provide energy savings and enhance the performance of applications executed on smart devices. Therefore, in this paper, adaptive mobile computation offloading of mobile AR applications is considered in order to determine optimal offloading points that satisfy the required quality of experience (QoE) while consuming minimum energy of the smart device. AR feature extraction based on SURF algorithm is partitioned into sub-stages in order to determine the optimal AR cloud computational offloading point based on conditions of the smart device, wireless and wired networks, and AR service cloud servers. Tradeoffs in energy savings and processing time are explored also taking network congestion and server load conditions into account.

• 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.