research-article

A smart intuitionistic fuzzy-based framework for round-robin short-term scheduler

Authors:

Supriya Raheja,

Mohammed Alshehri,

Ahmed A. Mohamed,

Supriya Khaitan,

Thompson StephanAuthors Info & Claims

The Journal of Supercomputing, Volume 78, Issue 4

Pages 4655 - 4679

https://doi.org/10.1007/s11227-021-04052-4

Published: 01 March 2022 Publication History

Abstract

A smart intuitionistic fuzzy-based framework is designed to facilitate adaptability by providing continuous changes in the size of time slice to scheduler at run time. The present work models a round-robin scheduler with its imprecise parameters. To manage the impreciseness among parameters and to improve the performance, an intuitionistic fuzzy-based round-robin scheduler is implemented. IFRR scheduler integrates the two components, namely intuitionistic fuzzy inference system and hybrid round-robin scheduling approach. Intuitionistic fuzzy inference system is implemented to handle the impreciseness of burst time to provide a dynamic time slice to scheduler, whereas hybrid round-robin scheduling approach is used to make a decision on selection of next task to run. The prove the performance, the proposed scheduler is compared with the other baseline round-robin schedulers. The results prove the efficiency of scheduler in terms of average waiting time, average turnaround time, average normalized turnaround time, and number of context switches.

References

[1]

Galvin PB, Gagne G, Silberschatz A (2005) Operating system concepts, vol 10. John Wiley & Sons

[2]

Stallings W Operating systems: internals and design principles 2012 Boston Prentice Hall

[3]

Zaim AH Design of a scheduler: comparison of different scheduling algorithms Istanbul Univ—J Electr Electron Eng 2003 3 2 859-877

[4]

Park M, Yoo HJ, Chae J, Kim CK (2008) Quantum-based fixed priority scheduling. In: Int Conf Adv Comput Theory Eng, pp. 64-68, IEEE.

[5]

Park M, Yoo HJ, Chae J (2009) Integration of preemption threshold and quantum-based scheduling for schedulability enhancement of fixed priority tasks. In: 15th IEEE Int Conf Embed Real-Time Comput Syst Appl, pp. 503-510, IEEE.

[6]

Racu R, Li L, Henia R, Hamann A, Ernst R (2007) Improved response time analysis of tasks scheduled under preemptive round-robin In: Proceed 5th IEEE/ACM Int Conf Hardw/Softw Codesi Syst Synth, pp. 179-184.

[7]

Caprita B, Chan WC, Nieh J, Stein C, Zheng H (2005) Group ratio round-robin: O (1) proportional share scheduling for uniprocessor and multiprocessor systems. In: USENIX Annu Tech Conf, General Track, pp 337-352.

[8]

Raheja S, Dadhich R, and Rajpal S An optimum time quantum using linguistic synthesis for round robin scheduling algorithm Int J Soft Comput 2012 3 1 57-66

[9]

Matarneh RJ Self-adjustment time quantum in round robin algorithm depending on burst time of the now running processes Am J Appl Sci 2009 6 10 1831-1837

[10]

Mostafa SM, Rida SZ, and Hamad SH Finding time quantum of round robin CPU scheduling algorithm in general computing systems using integer programming Int J Res Rev Appl Sci (IJRRAS) 2010 5 1 64-71

[11]

Noon A, Kalakech A, and Kadry S A new round robin based scheduling algorithm for operating systems: dynamic quantum using the mean average Int J Comput Sci Issues 2011 8 3 224-229

[12]

Zouaoui S, Boussaid L, and Mtibaa A Improved time quantum length estimation for round robin scheduling algorithm using neural network Indonesian J Electr Eng Inform (IJEEI) 2019 7 2 190-202

[13]

Gupta C and Sharma K Luhach AK Fluctuating time quantum round robin (FTQRR) CPU scheduling algorithm First international conference on sustainable technologies for computational intelligence 2020 Singapore Springer 467-479

[14]

Shafi U, Shah M, Wahid A, Abbasi K, Javaid Q, Asghar M, and Haider M A novel amended dynamic round robin scheduling algorithm for timeshared systems Int Arab J Inform Technol 2020 17 1 90-98

[15]

Naidu KP, Chelluri VP, Sumahasan S, and Sivaram RDDV Finest round robin scheduling algorithm using effective time quantum J Softw Eng Tools Technol Trends 2020 1 1 4-8

[16]

Oyam NA, Pidlaoan LJ, Baquirin RB, Bayani EF, Fronda RJ (2020) Refining the round robin algorithm using a recomputed time quantum: a comparison. In: Proceed 6th Int Conf Comput Data Eng, pp. 1–4.

[17]

Ali KF, Marikal A, and Kumar KA A hybrid round robin scheduling mechanism for process management Int J Comput Appl 2020 117 36 14-19

[18]

Sinha P, Prabadevi B, Dutta S, Deepa N, Kumari N (2020). Efficient process scheduling algorithm using RR and SRTF. In: 2020 Int Conf Emerg Trends Inform Technol Eng (ic-ETITE), pp. 1-6, IEEE

[19]

Sangwan P, Sharma M, and Kumar A Improved round robin scheduling in cloud computing Adv Comput Sci Tech 2017 10 4 639-644

[20]

Runsungnoen M and Anusas-amornkul T Zhang YD Round robin scheduling based on remaining time and median (RR_RT&M) for cloud computing Smart trends in computing and communications 2020 Singapore Springer 21-29

[21]

Butt MA and Akram M A novel fuzzy decision-making system for CPU scheduling algorithm Neural Comput Appl 2016 27 7 1927-1939

[22]

Kandel A, Zhang YQ, and Henne M On use of fuzzy logic technology in operating systems Fuzzy Sets Syst 1998 99 3 241-251

[23]

Raheja S, Dadhich R, and Rajpal S Designing of vague logic based multilevel feedback queue scheduler Egypt Inform J 2016 17 1 125-137

[24]

Blej M and Azizi M Melliani S and Castillo O Task parameter impacts in fuzzy real time scheduling Recent advances in intuitionistic fuzzy logic systems 2019 Cham Springer 69-78

[25]

Alam B Fuzzy round robin CPU scheduling algorithm JCS 2013 9 8 1079-1085

[26]

Zanjirani DM and Esmaelian M An integrated approach based on fuzzy inference system for scheduling and process planning through multiple objectives J Ind Manag Optim 2020 16 3 1235-1259

[27]

Datta L A new RR scheduling approach for real time systems using fuzzy logic Int J Comput Appl 2015 119 5 27-32

[28]

Trivedi JA and Sajja PS Improving efficiency of round robin scheduling using neuro fuzzy approach Int J Res Rev Comput Sci 2011 2 2 308-311

[29]

Zadeh LA Fuzzy sets Inform Control 1965 8 3 338-353

[30]

Gau WL and Buehrer DJ Vague sets IEEE Trans Syst Man Cybern 1993 23 2 610-614

[31]

Raheja S Designing of vague logic based 2-layered framework for CPU scheduler Adv Fuzzy Syst 2016 2016 1-11

[32]

Raheja S An intuitionistic based novel approach to highest response ratio next CPU scheduler Intell Decis Technol 2019 13 4 523-536

[33]

Butt MA and Akram M A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler SpringerPlus 2016 5 1 1-17

[34]

Zhang X, Deng Y, Chan FT, Xu P, Mahadevan S, and Hu Y IFSJSP: a novel methodology for the job-shop scheduling problem based on intuitionistic fuzzy sets Int J Prod Res 2013 51 17 5100-5119

[35]

Atanassov KT Atanassov Krassimir T Intuitionistic fuzzy sets Intuitionistic fuzzy sets 1999 Heidelberg Physica 1-137

[36]

Atanassov K Intuitionistic fuzzy sets Int J Bioautom 2016 20 1-6

[37]

Alam B, Doja MN, Biswas R (2008) Finding time quantum of Round Robin CPU scheduling algorithm using fuzzy logic. In: 2008 Int Conf Comput Electr Eng, pp. 795-798, IEEE.

[38]

Zahedi MH, Ghazizadeh M, and Naghibzadeh M Sobh T Fuzzy round robin CPU scheduling (FRRCS) algorithm Advances in computer and information sciences and engineering 2008 Dordrecht Springer 348-353

[39]

Behera HS, Mohanty R, and Nayak D A new proposed dynamic quantum with re-adjusted round robin scheduling algorithm and its performance analysis Int J Comput Appl 2011 5 5 10-15

[40]

Nayak D, Malla SK, and Debadarshini D Improved round robin scheduling using dynamic time quantum Int J Comp Appl 2012 38 5 34-38

[41]

Riaz R, Kazmi SH, Kazmi ZH, and Shah SA Randomized dynamic quantum CPU scheduling algorithm J Inform Commun Technol Robot Appl 2018 9 2 19-27

[42]

Biswas D and Samsuddoha M Determining proficient time quantum to improve the performance of round robin scheduling algorithm Int J Mod Educ Comput Sci 2019 11 10 33-40

[43]

Alsulami AA, Al-Haija QA, Thanoon MI, Mao Q (2019) Performance evaluation of dynamic round robin algorithms for CPU scheduling. In: 2019 SoutheastCon IEEE, pp 1–5

Cited By

Saxena ADubey YKumar M(2023)Predictive modeling of drilling operation for optimum MRR, machine power, and estimated tool life using fuzzy logic and regression analysisJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-22276844:5(7613-7627)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-222768

Index Terms

A smart intuitionistic fuzzy-based framework for round-robin short-term scheduler
1. Theory of computation
  1. Design and analysis of algorithms

Index terms have been assigned to the content through auto-classification.

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Published In

cover image The Journal of Supercomputing

The Journal of Supercomputing Volume 78, Issue 4

Mar 2022

1434 pages

ISSN:0920-8542

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© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021. corrected publication 2021.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 March 2022

Accepted: 25 August 2021

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Majmaah University (SA)

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Cited By

Saxena ADubey YKumar M(2023)Predictive modeling of drilling operation for optimum MRR, machine power, and estimated tool life using fuzzy logic and regression analysisJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-22276844:5(7613-7627)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-222768

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