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Type :article
Subject :Q Science (General)
Main Author :Albahrey, Shihab Ahmed
Additional Authors :Al-Juboori, A. Z. Ansaef
Zaidan, Bilal Bahaa
Maimuna Khatari
Alsalem, Mohammed Assim
Title :Multi-criteria evaluation and benchmarking for active queue management methods: open issues, challenges and recommended pathway solutions
Place of Production :Tanjong Malim
Publisher :Fakulti Seni, Komputeran dan Industri Kreatif
Year of Publication :2019
Corporate Name :Universiti Pendidikan Sultan Idris

Abstract : Universiti Pendidikan Sultan Idris
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 speci¯c 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 con°icting issues and benchmarking techniques to identify weak points, and possible solutions are discussed. The ¯ndings of this study are as follows: (1) The limitations and problems of existing AQM evaluation and benchmarking methods, such as multi-evaluation criteria, criteria tradeo®, benchmarking and criteria signi¯cance, are presented and emphasized. (2) Multi-criteria decision-making using multiple criteria, such as performance, processing overhead and con¯guration, can be used to benchmark numerous AQM methods to determine solutions for future directions.  

References

1. B. Abbasov and S. Korukoglu, E®ective RED: An algorithm to improve RED's performance by reducing packet loss rate, Journal of Network and Computer Applications 32(3) (2009) 703–709, doi: http://dx.doi.org/10.1016/j.jnca.2008.07.001.

2. H. Abdel-Jaber, J. Ababneh, F. Thabtah, M. A. Daoud and M. Baklizi, Performance analysis of the proposed adaptive gentle random early detection method under noncongestion and congestion situations, Digital Enterprise and Information Systems (Springer, Berlin, 2011), pp. 592–603.

3. H. Abdel-Jaber, M. Mahafzah, F. Thabtah and M. Woodward, Fuzzy logic controller of Random Early Detection based on average queue length and packet loss rate, in Int. Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2008 (IEEE, 2008), pp. 428–432.

4. B. N. Abdullateef, N. F. Elias, H. Mohamed, A. Zaidan and B. Zaidan, An evaluation and selection problems of OSS-LMS packages, SpringerPlus 5(1) (2016) 248.

5. M. M. Abualhaj, A. A. Abu-Shareha and M. M. Al-Tahrawi, FLRED: An e±cient fuzzy logic based network congestion control method, Neural Computing and Applications 30 (2016) 1–11, doi: 10.1007/s00521-016-2730-9.

6. R. Adams, Active queue management: A survey, IEEE Communications Surveys & Tutorials 15(3) (2013) 1425–1476, doi: 10.1109/SURV.2012.082212.00018.

7. G. F. Ahammed and R. Banu, Analyzing the performance of active queue management algorithms, International Journal of Computer Networks and Communications 2(2) (2010).

8. H. Ahmadi, M. Nilashi and O. Ibrahim, Organizational decision to adopt hospital information system: An empirical investigation in the case of Malaysian public hospitals, International Journal of Medical Informatics 84(3) (2015) 166–188.

9. M. Al-Diabat, H. Abdel-Jaber, F. Thabtah, O. Abou-Rabia and M. Kishta, Analytical models based discrete-time queueing for the congested network, International Journal of Modeling, Simulation, and Scienti¯c Computing 3(1) (2012) 1150004.

10. A. Albahri, A. Zaidan, O. Albahri, B. Zaidan and M. Alsalem, Real-time fault-tolerant mhealth system: comprehensive review of healthcare services, opens issues, challenges and methodological aspects, Journal of Medical Systems 42(8) (2018) 137.

11. A. S. Albahri, et al., Based multiple heterogeneous wearable sensors: A smart real-time health monitoring structured for hospitals distributor, IEEE Access 7 (2019) 37269–37323, doi: 10.1109/ACCESS.2019.2898214.

12. O. Albahri, A. Zaidan, B. Zaidan, M. Hashim, A. Albahri and M. Alsalem, Real-time remote health-monitoring systems in a medical centre: A review of the provision of healthcare services-based body sensor information, open challenges and methodological aspects, Journal of Medical Systems 42(9) (2018) 164.

13. A. S. Alfa, Queueing Theory for Telecommunications (Springer, Boston, MA, 2010).

14. A. G. Ali, M. Woodward and M. Etbega, Two di®erent approaches of active queue management, in 2007 IEEE Int. Conf. Networking, Sensing and Control (IEEE, 2007), pp. 579–583.

15. E. M. Almahdi, A. A. Zaidan, B. B. Zaidan, M. A. Alsalem, O. S. Albahri and A. S. Albahri, Mobile-based patient monitoring systems: A prioritization framework using multi-criteria decision-making techniques, Journal of Medical Systems 43(7) (2019) 207.

16. M. Alsalem, et al., Systematic review of an automated multiclass detection and classi- ¯cation system for acute Leukaemia in terms of evaluation and benchmarking, open challenges, issues and methodological aspects, Journal of Medical Systems 42(11) (2018) 204.

17. M. A. Alsalem, A. A. Zaidan, B. B. Zaidan, O. S. Albahri, A. H. Alamoodi, A. S. Albahri, A. H. Mohsin and K. I. Mohammed, Multiclass benchmarking framework for automated acute leukaemia detection and classi¯cation based on BWM and Group-VIKOR,Journal of Medical Systems 43(7) (2019) 212. doi: 10.1007/s10916-019-1338-x.

18. H. AlSattar, et al., MOGSABAT: A metaheuristic hybrid algorithm for solving multiobjective optimisation problems, Neural Computing and Applications 31 (2018) 1–15.

19. A. H. Ismail, A. El-Sayed, Z. Elsaghir and I. Z. Morsi, Enhanced random early detection (ENRED), International Journal of Computer Applications 92(9) (2014).

20. J. R. Annette, A. Banu and S. P. Chandran, Comparison of multi criteria decision making algorithms for ranking cloud renderfarm services, Indian Journal of Science and Technology 9(31) (2016).

21. I. M. Ar and A. Kurtaran, Evaluating the relative e±ciency of commercial banks in Turkey: An integrated AHP/DEA approach, International Business Research 6(4) (2013) 129.

22. M. Aruldoss, T. M. Lakshmi and V. P. Venkatesan, A survey on multi criteria decision making methods and its applications, American Journal of Information Systems 1(1) (2013) 31–43.

23. S. Athuraliya, S. H. Low, V. H. Li and Q. Yin, REM: Active queue management, IEEE Network 15(3) (2001) 48–53.

24. G. Attiya and H. El-Khobby, Improving internet quality of service through active queue management in routers, IJCSI International Journal of Computer Science Issues 9(1) (2012) 279.

25. J. Aweya, M. Ouellette and D. Y. Montuno, A control theoretic approach to active queue management, Computer Network 36(2–3) (2001) 203–235, doi: 10.1016/s1389- 1286(00)00206-1.

26. M. Baklizi, H. Abdel-Jaber, M. M. Abu-Alhaj, N. Abdullah, S. Ramadass and A. Almomani, Dynamic stochastic early discovery: A new congestion control technique to improve networks performance, International Journal of Innovative Computing, Information and Control 9(3) (2013) 1118–1126.

27. M. Baklizi, H. Abdel-Jaber, M. M. Abu-Alhaj, N. Abdullah, S. Ramadass and A. Almomani, Dynamic stochastic early discovery: A new congestion control technique to improve networks performance, ICIC International 9(3) (2013) 1113–1126.

28. M. Baklizi, H. Abdel-jaber, A. A. Abu-Shareha, M. M. Abualhaj and S. Ramadass, Fuzzy logic controller of gentle random early detection based on average queue length and delay rate, International Journal of Fuzzy Systems 16(1) (2014) 9–19.

29. M. Baklizi, H. Abdel-Jaber, S. Ramadass, N. Abdullah and M. Anbar, Performance assessment of AGRED, RED and GRED congestion control algorithms, Information Technology Journal 11(2) (2012) 255.

30. R. Baltussen and L. Niessen, Priority setting of health interventions: The need for multicriteria decision analysis, Cost E®ectiveness and Resource Allocation 4(1) (2006) 1.

31. B. Briscoe, Insights from Curvy Random Early Detection (RED) (2015).

32. X. Changbiao and L. Fengfeng, A congestion control algorithm of fuzzy control in routers, in 4th Int. Conf. Wireless Communications, Networking and Mobile Computing(2008), pp. 1–4.

33. S. Chebli, A. El Akkary, N. Se¯ani and N. Elalami, PI stabilization for congestion control of AQM routers with tuning parameter optimization, International Journal of Interactive Multimedia and Arti¯cial Inteligence 4(1) (2016) 52–55.

34. C.-K. Chen, T.-L. Liao and J.-J. Yan, Active queue management controller design for TCP communication networks: Variable structure control approach, Chaos, Solitons & Fractals 40(1) (2009) 277–285

35. J. Chen, C. Hu and Z. Ji, Self-tuning random early detection algorithm to improve performance of network transmission, Mathematical Problems in Engineering 2011 (2010) 872347.

36. W. Chen, Y. Li and S.-H. Yang, An average queue weight parameterization in a network supporting TCP °ows with RED, in 2007 IEEE Int. Conf. Networking, Sensing and Control (IEEE, 2007), pp. 590–595.

37. W. Chen and S.-H. Yang, The mechanism of adapting RED parameters to TCP tra±c, Computer Communications 32(13) (2009) 1525–1530.

38. K. Chitra and G. D. Padamavathi, Adaptive CHOKe: An algorithm to increase the fairness in Internet Routers, International Journal of Advanced Networking and Applications 1(6) (2010) 382–386.

39. C. Chrysostomou, A. Pitsillides, G. Hadjipollas, A. Sekercioglu and M. Polycarpou, Fuzzy explicit marking for congestion control in di®erentiated services networks, in Proc. Eighth IEEE Int. Symposium on Computers and Communication (ISCC 2003) (IEEE, 2003), pp. 312–319.

40. A. Chydzinski and L. Chrost, Analysis of AQM queues with queue size based packet dropping, International Journal of Applied Mathematics and Computer Science 21(3) (2011) 567–577.

41. D. Claudio, O. E. G. Kremer, W. Bravo-Llerena and A. Freivalds, A dynamic multiattribute utility theory–based decision support system for patient prioritization in the emergency department, IIE Transactions on Healthcare Systems Engineering 4(1) (2014) 1–15.

42. G. Da-Gang, A new adaptive BLUE algorithm, in 2010 Int. Conf. Electrical and Control Engineering (ICECE) (IEEE, 2010), pp. 2601–2605.

43. Y. Dong, Q. Zha, H. Zhang, G. Kou, H. Fujita, F. Chiclana and E. Herrera-Viedma, Consensus reaching in social network group decision making: Research paradigms and challenges, Knowledge-Based Systems 162 (2018) 3–13.

44. O. Enaizan, A. Zaidan, M. N. Alwi, B. Zaidan, M. Alsalem, O. Albahri and A. Albahri, Electronic medical record systems: Decision support examination framework for individual, security and privacy concerns using multi-perspective analysis, Health and Technology 10 (2018) 1–28.

45. E. M. Almahdi, A. A. Zaidan, B. B. Zaidan, M. A. Alsalem, O. S. Albahri and A. S. Albahri, Mobile patient monitoring systems from a benchmarking aspect: Challenges, open issues and recommended solutions, Journal of Medical Systems 43(7) (2019) 207.

46. M. H. Etbega, M. Woodward, H. Abdel-Jaber and G. A. Ali, A new version of adaptive red with reduced dependency on parameterisation, Citeseer (2004).

47. A. Fakharian and A. Abbasi, Design of congestion controller for TCP networks based on LMI formulation, Journal of Optimization in Industrial Engineering 8(17) (2015) 51–56.

48. W.-C. Feng, D. D. Kandlur, D. Saha and K. G. Shin, Stochastic fair blue: A queue management algorithm for enforcing fairness, in Proc. IEEE INFOCOM 2001. Twentieth Annual Joint Conf. IEEE Computer and Communications Societies (Cat. No. 01CH37213), Vol. 3 (IEEE, 2001), pp. 1520–1529.

49. W.-C. Feng, K. G. Shin, D. D. Kandlur and D. Saba, The BLUE active queue management algorithms, IEEE/ACM Transactions on Networking 10(4) (2002) 513–528, doi: 10.1109/tnet.2002.801399.

50. S. Floyd, Recommendation on using the gentle variant of RED (2000). www.icir.org/ °oyd/red/gentle.html.

51. S. Floyd, Recommendations on using the gentle variant of RED (2000). http://www. aciri.org/°oyd/red/gentle.html.

52. S. Floyd, R. Gummadi and S. Shenker, Adaptive RED: An algorithm for increasing the robustness of RED's active queue management (2001), pp. 518–522.

53. S. Floyd, R. Gummadi and S. Shenker, Adaptive RED: An algorithm for increasing the robustness of RED's active queue management (2001), pp. 518–522.

54. S. Floyd and V. Jacobson, Random early detection gateways for congestion avoidance, IEEE/ACM Transaction on Networking 1(4) (1993) 397–413, doi: 10.1109/90.251892.

55. K. Govindan and M. B. Jepsen, ELECTRE: A comprehensive literature review on methodologies and applications, European Journal of Operational Research 250(1) (2016) 1–29.

56. Y. Hadjadj-Aoul, Towards AQM cooperation for congestion avoidance in Di®Serv/MPLS networks, Recent Patents on Computer Science 2(1) (2009) 1–13.

57. W. Henderson, C. Pearce, G. P. Taylor and N. M. van Dijk, Closed queueing networks with batch services, Queueing Systems 6(1) (1990) 59–70.

58. C. V. Hollot, V. Misra, D. Towsley and W. B. Gong, On designing improved controllers for AQM routers supporting TCP °ows, in Proc. IEEE INFOCOM 2001. Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No. 01CH37213), Vol. 3 (IEEE, 2001), pp. 1726–1734.

59. J. Hong, C. Joo and S. Bahk, Active queue management algorithm considering queue and load states, Computer Communications 30(4) (2007) 886–892.

60. C.-L. Hwang and K. Yoon, Multiple Attribute Decision Making: Methods and Applications a State-of-the-Art Survey, Vol. 186 (Springer Science & Business Media, 2012).

61. N. S. Ingoley and M. Nashipudi, A review: Fuzzy logic in congestion control of computer network, in Int. Conf. Recent Trends in Information Technology and Computer Science (ICRITITCS, 2012), pp. 0975–8887.

62. M. Joshi, A. Mansata, S. Talauliker and C. Beard, Design and analysis of multi-level active queue management mechanisms for emergency tra±c, Computer Communications 28(2) (2005) 162–173.

63. F. Jumaah, A. Zadain, B. Zaidan, A. Hamzah and R. Bahbibi, Decision-making solution based multi-measurement design parameter for optimization of GPS receiver tracking channels in static and dynamic real-time positioning multipath environment. Measurement 118 (2018) 83–95.

64. F. Jumaah, A. Zaidan, B. Zaidan, R. Bahbibi, M. Qahtan and A. Sali, Technique for order performance by similarity to ideal solution for solving complex situations in multicriteria optimization of the tracking channels of GPS baseband telecommunication receivers, Telecommunication Systems 68 (2017) 1–19.

65. N. Kalid, A. Zaidan, B. Zaidan, H. O. Salman, M. Hashim, O. Albahri and A. Albahri, Based on real time remote health monitoring systems: A new approach for prioritization \Large Scales Data" patients with chronic heart diseases using body sensors and communication technology, Journal of Medical Systems 42(4) (2018) 69.

66. N. Kalid, A. Zaidan, B. Zaidan, H. O. Salman, M. Hashim and H. Muzammil, Based real time remote health monitoring systems: A review on patients prioritization and related \Big Data" using body sensors information and communication technology, Journal of Medical Systems 42(2) (2018) 30.

67. A. C. Kapadia and W.-C. Feng, GREEN: A TCP equation-based approach to active queue management (2004).

68. G. J. Klir, Fuzzy logic, IEEE Potentials 14(4)(1995) 10–15, doi: 10.1109/45.468220.

69. J. Koo, S. Ahn and J. Chung, A comparative study of queue, delay, and loss characteristics of AQM schemes in QoS-enabled networks, Computing and Informatics 23(4) (2004) 317–335.

70. G. Kou, D. Ergu, C. Lin and Y. Chen, Pairwise comparison matrix in multiple criteria decision making, Technological and Economic Development of Economy 22(5) (2016) 738–765.

71. S. Kunniyur and R. Srikant, End-to-end congestion control schemes: Utility functions, random losses and ECN marks, IEEE/ACM Transactions on Networking 11(5) (2003) 689–702.

72. S. S. Kunniyur and R. Srikant, An adaptive virtual queue (AVQ) algorithm for active queue management, IEEE/ACM Transactions on Networking (ToN) 12(2) (2004) 286–299.

73. K. Lam and X. Zhao, An application of quality function deployment to improve the quality of teaching, International Journal of Quality & Reliability Management 15(4) (1998) 389–413.

74. D. Lapsley and S. Low, Random early marking: An optimisation approach to internet congestion control, in Proc. IEEE Int. Conf. Networks ICON '99 (Cat. No. PR00243) (IEEE, 1999), pp. 67–74.

75. K. M. Lee, J. H. Yang and B. S. Suh, Congestion control of active queue management routers based on LQ-Servo control, Engineering Letters 16(3) (2008) 332–338.

76. G. Li, G. Kou and Y. Peng, A group decision making model for integrating heterogeneous information, IEEE Transactions on Systems, Man, and Cybernetics: Systems 48(6) (2018) 982–992.

77. J.-S. Li and Y.-S. Su, Random early detection with °ow number estimation and queue length feedback control, Journal of Systems Architecture 52(6) (2006) 359–372.

78. L. B. Lim, L. Guan, A. Grigg, I. W. Phillips, X. G. Wang and I. U. Awan, Controlling mean queuing delay under multi-class bursty and correlated tra±c, Journal of Computer and System Sciences 77(5) (2011) 898–916, doi: http://dx.doi.org/10.1016/j.jcss.2010.08.007.

79. S. Liu, T. Ba?ar and R. Srikant, TCP-Illinois: A loss-and delay-based congestion control algorithm for high-speed networks, Performance Evaluation 65(6) (2008) 417–440.

80. C. Long, B. Zhao, X. Guan and J. Yang, The Yellow active queue management algorithm, Computer Networks 47(4) (2005) 525–550.

81. L. Rossides, A. Sekercioglu, A. Pitsillides, A. Vasilakos, S. Kohler and P. Tran-Gia, Fuzzy RED: Congestion control for TCP/IP Di®-Serv, in Advances in Computational Intelligence and Learning (Springer, Dordrecht, 2002), pp. 343–352.

82. J. Malczewski, GIS and Multicriteria Decision Analysis (John Wiley & Sons, New York, 1999).

83. A. Marin, S. Rossi, A. Bujari and C. Palazzi, Performance evaluation of AQM techniques with heterogeneous tra±c, in 2016 13th IEEE Annual Consumer Communications & Networking Conf. (CCNC) (IEEE, 2016), pp. 194–199.

84. S. S. Masoumzadeh, G. Taghizadeh, K. Meshgi and S. Shiry, Deep blue: A fuzzy Q-learning enhanced active queue management scheme, in Int. Conf. Adaptive and Intelligent Systems (ICAIS'09) (IEEE, 2009), pp. 43–48.

85. M. H. Y. Moghaddam, A fuzzy active queue management mechanism for internet congestion control, in 2010 Third International Workshop on Advanced Computational Intelligence (IWACI) (2010).

86. S. Mohammadi, H. M. Pour, M. Jafari and A. Javadi, Fuzzy-based PID active queue manager for TCP/IP networks, in 10th Int. Conf. Information Sciences Signal Processing and Their Applications (ISSPA 2010) (IEEE, 2010), pp. 434–439.

87. D. C. Montgomery, Design and Analysis of Experiments (John Wiley & Sons, New York, 2008).

88. J. Morente-Molinera, G. Kou, K. Samuylov, R. Ureña and E. Herrera-Viedma, Carrying out consensual group decision making processes under social networks using sentiment analysis over comparative expressions, Knowledge-Based Systems 165 (2019) 335–345.

89. J. A. Morente-Molinera, G. Kou, Y. Peng, C. Torres-Albero and E. Herrera-Viedma, Analysing discussions in social networks using group decision making methods and sentiment analysis, Information Sciences 447 (2018) 157–168.

90. X. Naixue, V. V. Athanasios, T. Y. Laurence, W. Cheng-Xiang, K. Rajgopal, C. ChinChen and P. Yi, A novel self-tuning feedback controller for active queue management supporting TCP °ows, Information Science 180(11) (2010) 2249–2263, doi: 10.1016/j. ins.2009.12.001.

91. G. Nakhaeizadeh and A. Schnabl, Development of multi-criteria metrics for evaluation of data mining algorithms, in KDD (1997), pp. 37–42.

92. C. N. Nyirenda and D. S. Dawoud, Multi-objective particle swarm optimization for fuzzy logic based active queue management, in Int. Conf. Fuzzy Systems (IEEE, 2006), pp. 2231–2238.

93. M. Oliveira, D. B. Fontes and T. Pereira, Multicriteria decision making: A case study in the automobile industry, Annals of Management Science 3(1) (2014) 109.

94. T. J. Ott, T. V. Lakshman and L. Wong, SRED: Stabilized RED, in IEEE INFOCOM'99 Conference on Computer Communications Proc. Eighteenth Annual Joint Conf. IEEE Computer and Communications Societies (Cat. No. 99CH36320), Vol. 3 (IEEE, 1999), pp. 1346–1355.

95. S. Patel and S. Bhatnagar, Adaptive mean queue size and its rate of change: Queue management with random dropping (2016), arXiv:1602.02241.

96. S. Petrovic-Lazarevic and A. Abraham, Hybrid fuzzy-linear programming approach for multi criteria decision making problems (2004), arXiv:cs/0405019.

97. M. Qader, B. Zaidan, A. Zaidan, S. Ali, M. Kamaluddin and W. Radzi, A methodology for football players selection problem based on multi-measurements criteria analysis, Measurement 111 (2017) 38–50.

98. B. Rahmatullah, A. Zaidan, F. Mohamed and A. Sali, Multi-complex attributes analysis for optimum GPS baseband receiver tracking channels selection, in 2017 4th Int. Conf. Control, Decision and Information Technologies (CoDIT) (IEEE, 2017), pp. 1084–1088.

99. L. Rossides, A. Sekercioglu, A. Pitsillides, A. Vasilakos, S. Kohler and P. Tran-Gia, Fuzzy RED: Congestion control for TCP/IP di®-serv, Advances in Computational Intelligence and Learning (Springer, New York, 2002), pp. 343–352.

100. S. Ryu, C. Rump and C. Qiao, Advances in internet congestion control, IEEE Communications Surveys & Tutorials 5(1) (2003) 28–39.

101. T. L. Saaty, A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology 15(3) (1977) 234–281.

102. T. L. Saaty, The Analytic Hierarchical Process (McGrow-Hill, New York, 1980).

103. M. M. Salih, B. Zaidan, A. Zaidan and A. M. Ahmed, Survey on fuzzy TOPSIS state-ofthe-art between 2007–2017, Computers & Operations Research 104(April) (2018) 207– 227. doi: 10.1016/J.COR.2018.12.019

104. O. Salman, A. Zaidan, B. Zaidan, Naserkalid and M. Hashim, Novel methodology for triage and prioritizing using \big data" patients with chronic heart diseases through telemedicine environmental, International Journal of Information Technology & Decision Making 16(5) (2017) 1211–1245.

105. O. Seifaddini, A. Abdullah and A. H. Vosough, Red, gred, agred congestion control algorithms in heterogeneous tra±c types, in Int. Conf. Computing and Informatics (2013), pp. 139–144.

106. H.-S. Shih, H.-J. Shyur and E. S. Lee, An extension of TOPSIS for group decision making, Mathematical and Computer Modelling 45(7) (2007) 801–813.

107. G. J. Silva, A. Datta and S. P. Bhattacharyya, PI stabilization of ¯rst-order systems with time delay, Automatica 37(12) (2001) 2025–2031.

108. R. Stanojevic, R. N. Shorten and C. M. Kellett, Adaptive tuning of drop-tail bu®ers for reducing queueing delays, IEEE Communications Letters 10(7) (2006) 570–572.

109. J. Sun and M. Zukerman, RaQ: A robust active queue management scheme based on rate and queue length, Computer Communications 30(8) (2007) 1731–1741.

110. J. Sun, M. Zukerman and M. Palaniswami, Stabilizing RED using a fuzzy controller, in 2007 IEEE Int. Conf. Communications (IEEE, 2007), pp. 266–271.

111. S. Suthaharan, Reduction of queue oscillation in the next generation internet routers, Computer Communications 30(18) (2007) 3881–3891.

112. G. Tamea, M. Biagi and R. Cusani, Soft multi-criteria decision algorithm for vertical handover in heterogeneous networks, IEEE Communications Letters 15(11) (2011) 1215–1217.

113. L. Tsavlidis, P. Efraimidis and R.-A. Koutsiamanis, Prince: An e®ective router mechanism for networks with sel¯sh °ows, Journal of Internet Engineering 6(1) (2016) 355–362.

114. B. Wang, B. Kasthurirangan and J. Xu, Subsidized RED: An active queue management mechanism for short-lived °ows, Computer Communications 28(5) (2005) 540–549.

115. H. Wang, Z. Tian and Q. Zhang, Self-tuning price-based congestion control supporting TCP networks, in 2010 Proc. 19th Int. Conf. Computer Communications and Networks (IEEE, 2010), pp. 1–6.

116. P. Wang, H. Chen, X. Yang and X. Lu, Active queue management of delay network based on constrained model predictive control, in 2011 Chinese Control and Decision Conference (CCDC) (IEEE, 2011), pp. 814–818.

117. Y. Wind and T. L. Saaty, Marketing applications of the analytic hierarchy process, Management Science 26(7) (1980) 641–658.

118. M. E. Woodward, Communication and Computer Networks: Modelling with Discrete-Time Queues (Wiley-IEEE Computer Society Press, Los Alanitos, CA, 1993).

119. M. H. Yaghmaee, M. Menhaj and H. Amintoosi, A fuzzy extension to the blue active queue management algorithm, IAEEE, Journal of Iranian Association of Electrical and Electronics Engineers 1(3) (2005) 3–14.

120. T. Yamaguchi and Y. Takahashi, A queue management algorithm for fair bandwidth allocation, Computer Communications 30(9) (2007) 2048–2059.

121. Q. M. Yas, A. Zadain, B. Zaidan, M. Lakulu and B. Rahmatullah, Towards on develop a framework for the evaluation and benchmarking of skin detectors based on arti¯cial intelligent models using multi-criteria decision-making techniques, International Journal of Pattern Recognition and Arti¯cial Intelligence 31(3) (2017) 1759002.

122. Q. M. Yas, A. Zaidan, B. Zaidan, B. Rahmatullah and H. A. Karim, Comprehensive insights into evaluation and benchmarking of real-time skin detectors: Review, open issues & challenges, and recommended solutions, Measurement 114 (2018) 243–260.

123. Z. Yu-Hong, Z. Xue-Feng and T. Xu-Yan, Research on the improved way of RED algorithm S-RED, International Journal of u-and e-Service, Science and Technology9(2) (2016) 375–384.

124. A. Zaidan, B. Zaidan, A. Al-Haiqi, M. L. M. Kiah, M. Hussain and M. Abdulnabi, Evaluation and selection of open-source EMR software packages based on integrated AHP and TOPSIS, Journal of Biomedical Informatics 53 (2015) 390–404.

125. A. Zaidan, B. Zaidan, O. Albahri, M. Alsalem, A. Albahri, M. Q. Yas and M. Hashim, A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking Coherent taxonomy, open issues and recommendation pathway solution, Health and Technology 8 (2018) 1–16.

126. A. Zaidan, B. Zaidan, M. Hussain, A. Haiqi, M. M. Kiah and M. Abdulnabi, Multicriteria analysis for OS-EMR software selection problem: A comparative study. Decision Support Systems 78 (2015) 15–27.

127. A. A. Zaidan, Based multi-agent learning neural network and bayesian for real-time IoT skin detectors: A new evaluation and benchmarking methodology. Neural Computing and Applications 32 (2019).

128. B. Zaidan and A. Zaidan, Software and hardware FPGA-based digital watermarking and steganography approaches: Toward new methodology for evaluation and benchmarking using multi-criteria decision-making techniques, Journal of Circuits, Systems and Computers 26(7) (2017) 1750116.

129. B. Zaidan and A. Zaidan, Comparative study on the evaluation and benchmarking information hiding approaches based multi-measurement analysis using TOPSIS method with di®erent normalisation, separation and context techniques, Measurement 117 (2018) 277–294.

130. B. Zaidan, A. Zaidan, H. Abdul Karim and N. Ahmad, A new approach based on multidimensional evaluation and benchmarking for data hiding techniques, International Journal of Information Technology & Decision Making 19 (2017) 1–42.

131. B. Zaidan, A. Zaidan, H. A. Karim and N. Ahmad, A new digital watermarking evaluation and benchmarking methodology using an external group of evaluators and multicriteria analysis based on `large-scale data', Software: Practice and Experience 47(10) (2017) 1365–1392.

132. S. T. Zargar, H. M. Yaghmaee and A. M. Fard, Fuzzy proactive queue management technique, in 2006 Annual IEEE India Conf. (IEEE, 2006), pp. 1–6.

133. Z.-Q. Zhan, Z. Jie and X. Di, Stability analysis in an AVQ model of internet congestion control algorithm, The Journal of China Universities of Posts and Telecommunications 19(4) (2012) 22–28.

134. H. Zhang, G. Kou and Y. Peng, Soft consensus cost models for group decision making and economic interpretations, European Journal of Operational Research 277(3) (2019) 964–980. doi: 10.1016/J.EJOR.2019.03.009.

135. J. Zhang, W. Xu and L. Wang, An improved adaptive active queue management algorithm based on nonlinear smoothing, Procedia Engineering 15 (2011) 2369–2373.

136. S. Zionts, MCDM-If not a roman numeral, then what?Interfaces 9(4) (1979) 94–101.

 


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