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首页> 外文期刊>International Journal of Intelligent Systems >Multidimensional benchmarking of the active queue management methods of network congestion control based on extension of fuzzy decision by opinion score method
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Multidimensional benchmarking of the active queue management methods of network congestion control based on extension of fuzzy decision by opinion score method

机译：基于意见分数法的模糊决策延伸的网络拥塞控制有效队列管理方法的多维基准

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This study evaluated the benchmarking process of active queue management (AQM) methods, which consider a multicriteria decision-making (MCDM) problem using multidimensional criteria. Academic studies have benchmarked the AQM methods using MCDM techniques. However, these studies have used existing MCDM techniques, which face considerable theoretical challenges. The latest MCDM method called fuzzy decision by opinion score (FDOSM) was published in the Journal of Applied Soft Computing in 2020 to address the theoretical challenges of the existing MCDM methods. However, FDOSM continues to encounter serious issues. That is, it exclusively depends on the direct aggregation MCDM approach based on arithmetic mean (AM) operator. However, performing other operators (i.e., geometric mean, harmonic mean, and root mean square), in addition to applying other MCDM approaches (i.e., distance measurement and compromise rank), may result in different ranking results. Hence, this study mainly proposes an extension of FDOSM through the following aspects: (1) application of different aggregation techniques in the direct aggregation MCDM approach, (2) discussion of the effectiveness of each type on the final AQM benchmarking, and (3) use of varying MCDM approaches on FDOSM to reach the optimum result when benchmarking the AQM methods. The current research methodology is based on two sequential phases. The first phase provides the decision matrix used in benchmarking the AQM methods. The decision matrix was constructed based on the AQM evaluation criteria and a list of AQM methods. The second phase presents two stages, namely, data transformation unit and data processing. Findings of the AQM benchmarking are as follows. (1) In the individual FDOSM, two main configurations are recommended when using the AQM benchmarking: direct aggregation MCDM approach with AM operator and compromise rank approach. Benchmarking results of both configurations based on six decision makers are nearly similar, with the AQM BLUE method being ranked the best. The exception is for the results of the compromise rank approach based on the third decision maker, which revealed that the AQM ERED method is the best. (2) Results of the group FDOSM showed a relatively similar order for the AQM methods in both configurations, with the AQM BLUE method being the best. (3) Lastly, significant differences were found among the groups' scores, thereby indicating the validity of the FDOSM-based AQM benchmarking results.
机译：本研究评估了主动队列管理（AQM）方法的基准过程，其考虑了使用多维标准的多轨道决策（MCDM）问题。学术研究使用MCDM技术基准测试了AQM方法。然而，这些研究使用了现有的MCDM技术，这面临着相当大的理论挑战。最新的MCDM方法称为意见分数（FDOSM）在2020年的应用软计算期刊上发表，以解决现有MCDM方法的理论挑战。然而，FDOSM继续遇到严重的问题。也就是说，它专门取决于基于算术平均值（AM）运算符的直接聚合MCDM方法。然而，除了应用其他MCDM方法（即，距离测量和折衷等级）之外，执行其他运营商（即，几何平均值，谐均值和根均线），可能导致不同的排名结果。因此，本研究主要提出通过以下几个方面的FDOSM的延伸：（1）在直接聚合MCDM方法中应用不同的聚合技术，（2）对最终AQM基准测试的每种类型的有效性，（3）在FDOSM上使用不同的MCDM方法在基准测试AQM方法时达到最佳结果。目前的研究方法基于两个连续阶段。第一阶段提供了用于基准测试AQM方法的决策矩阵。基于AQM评估标准和AQM方法列表构建决策矩阵。第二阶段呈现两个阶段，即数据转换单元和数据处理。 AQM基准测试的结果如下。 （1）在各个FDOSM中，在使用AQM基准测试时建议使用两种主要配置：直接聚合MCDM方法与AM运算符和折衷等级方法。基于六个决策者的两种配置的基准结果几乎相似，AQM蓝色方法排名最佳。例外是基于第三决策者的折衷等级方法的结果，这揭示了AQM ered方法是最好的。 （2）组FDOSM的结果显示了两种配置中AQM方法的相对相似的订单，AQM蓝色方法是最好的。 （3）最后，群体分数中发现了显着的差异，从而表明基于FDOSM的AQM基准测试结果的有效性。

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