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Multi-Criteria Evaluation and Benchmarking for Active Queue Management Methods: Open Issues, Challenges and Recommended Pathway Solutions

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  • Maimuna Khatari

    (Department of Computing, Faculty of Arts Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Malaysia)

  • A. A. Zaidan

    (Department of Computing, Faculty of Arts Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Malaysia)

  • B. B. Zaidan

    (Department of Computing, Faculty of Arts Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Malaysia)

  • O. S. Albahri

    (Department of Computing, Faculty of Arts Computing and Creative Industry, Universiti Pendidikan Sultan Idris, Tanjong Malim, Malaysia)

  • M. A. Alsalem

    (#x2020;Department of Management, Information Systems, College of Administration and Economic, University of Mosul, Mosul, Iraq)

Abstract

The evaluation and benchmarking processes of active queue management (AQM) methods are complicated and challenging. Several evaluation criteria/metrics must be considered before an AQM method can yield satisfactory performance using specific metric(s). Further investigations are required to highlight the limitations of how criteria/metrics are determined and how their procedures accord with the evaluation and benchmarking processes of AQM. In this paper, we presented comprehensive insights into the multi-criteria evaluation and benchmarking of AQM methods based on two critical directions. First, current AQM evaluation criteria are collected, analyzed and categorized. Second, these AQM evaluation criteria highlight conflicting issues and benchmarking techniques to identify weak points, and possible solutions are discussed. The findings of this study are as follows: (1) The limitations and problems of existing AQM evaluation and benchmarking methods, such as multi-evaluation criteria, criteria trade-off, benchmarking and criteria significance, are presented and emphasized. (2) Multi-criteria decision-making using multiple criteria, such as performance, processing overhead and configuration, can be used to benchmark numerous AQM methods to determine solutions for future directions.

Suggested Citation

  • Maimuna Khatari & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem, 2019. "Multi-Criteria Evaluation and Benchmarking for Active Queue Management Methods: Open Issues, Challenges and Recommended Pathway Solutions," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1187-1242, July.
  • Handle: RePEc:wsi:ijitdm:v:18:y:2019:i:04:n:s0219622019300039
    DOI: 10.1142/S0219622019300039
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    References listed on IDEAS

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    Cited by:

    1. Albahri, A.S. & Alnoor, Alhamzah & Zaidan, A.A. & Albahri, O.S. & Hameed, Hamsa & Zaidan, B.B. & Peh, S.S. & Zain, A.B. & Siraj, S.B. & Alamoodi, A.H. & Yass, A.A., 2021. "Based on the multi-assessment model: Towards a new context of combining the artificial neural network and structural equation modelling: A review," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    2. Mahmood M. Salih & O. S. Albahri & A. A. Zaidan & B. B. Zaidan & F. M. Jumaah & A. S. Albahri, 2021. "Benchmarking of AQM methods of network congestion control based on extension of interval type-2 trapezoidal fuzzy decision by opinion score method," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 77(3), pages 493-522, July.
    3. Noor S. Baqer & A. S. Albahri & Hussein A. Mohammed & A. A. Zaidan & Rula A. Amjed & Abbas M. Al-Bakry & O. S. Albahri & H. A. Alsattar & Alhamzah Alnoor & A. H. Alamoodi & B. B. Zaidan & R. Q. Malik , 2022. "Indoor air quality pollutants predicting approach using unified labelling process-based multi-criteria decision making and machine learning techniques," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 81(4), pages 591-613, December.
    4. Jafar Ababneh, 2020. "Influencing Performance Measurements through Varying Packet Capacities of Queue Nodes - DRED," Modern Applied Science, Canadian Center of Science and Education, vol. 14(4), pages 1-23, April.

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