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Benchmarking of AQM methods of network congestion control based on extension of interval type-2 trapezoidal fuzzy decision by opinion score method

Author

Listed:
  • Mahmood M. Salih

    (Universiti Pendidikan Sultan Idris
    Tikrit University)

  • O. S. Albahri

    (Universiti Pendidikan Sultan Idris)

  • A. A. Zaidan

    (Universiti Pendidikan Sultan Idris
    Sultan Azlan Shah Campus, Universiti Pendidikan Sultan Idris)

  • B. B. Zaidan

    (Universiti Pendidikan Sultan Idris
    Sultan Azlan Shah Campus, Universiti Pendidikan Sultan Idris
    Future Technology Research Center, National Yunlin University of Science and Technology)

  • F. M. Jumaah

    (Universiti Pendidikan Sultan Idris)

  • A. S. Albahri

    (Universiti Pendidikan Sultan Idris
    Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI))

Abstract

This study presents a benchmarking and evaluation approach for active queue management (AQM) network congestion control methods, which are considered as a problem of multi-criteria decision-making (MCDM). In recent years, the development of MCDM methods has been studied from various perspectives. The latest one called fuzzy decision by opinion score method (FDOSM) has proved its efficiency in solving the concerns faced by other methods. However, the approach of FDOSM and its extension is based on fuzzy type-1, which suffers from issues, especially minimising the effect of data uncertainties. Therefore, this study extended FDOSM into a fuzzy type-2 environment that utilises interval type-2 trapezoidal (IT2T) membership, and then discusses the effectiveness of such membership on AQM method benchmarking. The methodology of this study involves two consecutive phases. The first phase is the construction of a decision matrix utilised in AQM method benchmarking based on a list of AQM methods and multiple evaluation criteria. The second phase is regarding the new method (IT2T-FDOSM), which illustrated two main stages, namely, data transformation unit and data processing. The findings of this study are the following: (1) Individual results of benchmarking which used six decision-makers are almost similar, with the AQM fuzzy GRED method ranked as the best. (2) The group benchmarking results show that a relatively similar order and fuzzy GRED method is the best as well. (3) IT2T-FDOSM can deal with the uncertainty problem properly. (4) The results show significant differences amongst the groups’ scores, which indicate the validity of the IT2T-FDOSM results.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:telsys:v:77:y:2021:i:3:d:10.1007_s11235-021-00773-2
    DOI: 10.1007/s11235-021-00773-2
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    References listed on IDEAS

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    1. O. H. Salman & A. A. Zaidan & B. B. Zaidan & Naserkalid & M. Hashim, 2017. "Novel Methodology for Triage and Prioritizing Using “Big Data” Patients with Chronic Heart Diseases Through Telemedicine Environmental," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1211-1245, September.
    2. R. T. Mohammed & R. Yaakob & A. A. Zaidan & N. M. Sharef & R. H. Abdullah & B. B. Zaidan & K. A. Dawood, 2020. "Review of the Research Landscape of Multi-Criteria Evaluation and Benchmarking Processes for Many-Objective Optimization Methods: Coherent Taxonomy, Challenges and Recommended Solution," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(06), pages 1619-1693, November.
    3. Pei, Lijun & Wu, Fanxin, 2021. "Periodic solutions, chaos and bi-stability in the state-dependent delayed homogeneous Additive Increase and Multiplicative Decrease/Random Early Detection congestion control systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 871-887.
    4. F. M. Jumaah & A. A. Zaidan & B. B. Zaidan & R. Bahbibi & M. Y. Qahtan & A. Sali, 2018. "Technique for order performance by similarity to ideal solution for solving complex situations in multi-criteria optimization of the tracking channels of GPS baseband telecommunication receivers," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(3), pages 425-443, July.
    5. 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.
    6. Mohammed Talal & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem & A. S. Albahri & A. H. Alamoodi & M. L. M. Kiah & F. M. Jumaah & Mussab Alaa, 2019. "Comprehensive review and analysis of anti-malware apps for smartphones," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(2), pages 285-337, October.
    7. Karrar Hameed Abdulkareem & Nureize Arbaiy & A. A. Zaidan & B. B. Zaidan & O. S. Albahri & M. A. Alsalem & Mahmood M. Salih, 2020. "A Novel Multi-Perspective Benchmarking Framework for Selecting Image Dehazing Intelligent Algorithms Based on BWM and Group VIKOR Techniques," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 909-957, May.
    8. A. A. Zaidan & B. B. Zaidan & M. A. Alsalem & Fayiz Momani & Omar Zughoul, 2020. "Novel Multiperspective Hiring Framework for the Selection of Software Programmer Applicants Based on AHP and Group TOPSIS Techniques," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 775-847, May.
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    2. 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.

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