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Time-efficient evaluation of adaptation algorithms for DASH with SVC: dataset, throughput generation and stream simulator

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Abstract

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.

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Notes

  1. In the rest of the paper, we describe the process with a window length of 30 samples which is the same value used in [34].

  2. The average omitted video chunk size of corresponding adaptation algorithm for all throughput waveforms.

  3. sDASH term will be used to refer this implementation in the rest of the paper.

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Correspondence to Nükhet Özbek.

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Çalı, M., Özbek, N. Time-efficient evaluation of adaptation algorithms for DASH with SVC: dataset, throughput generation and stream simulator. SIViP 15, 1477–1485 (2021). https://doi.org/10.1007/s11760-021-01880-y

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