Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

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Access Right: Closed AccessAuthor: search.filters.author.Özbek, Nükhet

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  • Article
    Time-Efficient Evaluation of Adaptation Algorithms for Dash With Svc: Dataset, Throughput Generation and Stream Simulator
    (Springer, 2021) Çalı, Mehmet; Özbek, Nükhet
    Bitrate adaptation algorithms have received considerable attention recently. In order to evaluate these algorithms objectively, multiple DASH datasets have been proposed. However, only few of them are compatible to SVC-based adaptation algorithms. Apart from the dataset, to fully implement and evaluate an adaptation algorithm, many time-consuming steps are required such as MPD parser design, adaptation logic design and network environment setup. In this paper, a dash simulator which assesses the performance of SVC-based adaptation algorithms without the requirement of any additional implementation steps is proposed. Also, an SVC dataset that includes both CBR and VBR encoded videos is designed. Demonstration is performed as evaluation of an SVC-based adaptation algorithm under several throughput scenarios using the designed dataset. Results show that the proposed system considerably reduces time requirement compared to real-time assessment. Dataset, throughput generation tool and simulator are all publicly available so that the researchers can test their implementation and compare with the results presented in this paper.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 6
    Ssim-Based Adaptation for Dash With Svc in Mobile Networks
    (Springer Verlag, 2020) Çalı, Mehmet; Özbek, Nükhet
    Dynamic Adaptive Streaming over HTTP (DASH) depends on adjustment of the quality of a video stream to the available network conditions. In order to increase Quality of Experience, average video quality should be maximized, while keeping the quality switching frequency at low levels. However, achieving high average quality with low switching frequency in highly fluctuating mobile network conditions is a tricky optimization problem. In order to overcome this problem, dynamic structure of Scalable Video Coding (SVC) is utilized in this paper. Another challenge in the quality adaptation algorithms is to proper assessment of the video quality. Most of the adaptation algorithms takes either bitrate or representation level as the input that is used to evaluate the quality of the video. However, bitrate is not strongly correlated with the quality, as it depends on the content of the video. Likewise, representation quality relationship entirely bound to encoding. In this paper, in order to have a more reliable adaptation input, SSIM is used while representing the quality of the video stream. The proposed adaptation is compared with a successful SVC DASH adaptation algorithm using both subjective and objective tests. As a result, considerably higher scores are achieved in terms of both switching frequency and average quality.