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Journal articles on the topic 'Multilevel feedback queue'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Gupta, Amit Kumar, Narendra Singh Yadav, and Dinesh Goyal. "Design and Performance Evaluation of Smart Job First Multilevel Feedback Queue (SJFMLFQ) Scheduling Algorithm with Dynamic Smart Time Quantum." International Journal of Multimedia Data Engineering and Management 8, no. 2 (2017): 50–64. http://dx.doi.org/10.4018/ijmdem.2017040106.

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Multilevel feedback queue scheduling (MLFQ) algorithm is based on the concept of several queues in which a process moves. In earlier scenarios there are three queues defined for scheduling. The two higher level queues are running on Round Robin scheduling and last level queue is running on FCFS (First Come First Serve). A fix time quantum is defined for RR scheduling and scheduling of process depends upon the arrival time in ready queue. Previously a lot of work has been done in MLFQ. In our propose algorithm Smart Job First Multilevel feedback queue (SJFMLFQ) with smart time quantum (STQ), th

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Candra Pamungkas, Angga Riyandi Saputra, Aditya Ramadhan, Alif Kurniawan, Naufal Abi Pratama, and Wishnu Rindra. "Pernerapan Algoritma Multilevel Feedback Queue (MFQ) & First In First Out (FIFO) pada Studi Kasus di Toko Bunga ARTHA PUSPA." JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital 2, no. 2 (2023): 192–98. http://dx.doi.org/10.55123/jumintal.v2i2.2402.

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Artha Puspa is a flower shop in Madiun which sells plant needs. This very rapid business development encourages every entrepreneur to create a form that is different from other businesses, one of which is the Arta Puspa Flower Shop, a common problem that is often experienced by Artha Puspa, namely direct purchase queues and orders. With that we use a combination of MFQ and FIFO. The application of a combination of Multilevel Feedback Queue (MFQ) and First In First Out (FIFO) algorithms is a strategy that can be used to manage processes that occur in computer systems. MFQ is a scheduling algori

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Raheja, Supriya, Reena Dadhich, and Smita Rajpal. "Designing of vague logic based multilevel feedback queue scheduler." Egyptian Informatics Journal 17, no. 1 (2016): 125–37. http://dx.doi.org/10.1016/j.eij.2015.09.003.

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4

Artia, Fransiska, I Gede Maha, M. Rakhmat Dramaga, and Aqwam Rosadi Kardian. "Implementasi Algoritma Penjadwalan Multilevel Feedback Queue pada Aplikasi Berbasis Flutter." JURNAL MAHAJANA INFORMASI 8, no. 2 (2023): 55–63. http://dx.doi.org/10.51544/jurnalmi.v8i2.4643.

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Application development has experienced a shift towards a cross-platform approach, where developers can write code once for multiple platforms. Flutter, as a fast-growing cross-platform framework with a wide community is one of the most popular cross-platform frameworks today. However, along with that, there is an increase in application complexity which makes the concept of multitasking very important. This article proposes the implementation of the Multilevel Feedback Queue (MLQ) scheduling algorithm in Flutter applications, which can help manage tasks and improve application efficiency. Thi

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M, Arunachalam, and Rajamani V. "MULTILEVEL FEEDBACK QUEUE WAVELENGTH ASSIGNMENT ALGORITHM IN SURVIVABLE OPTICAL WDM NETWORKS." ICTACT Journal on Communication Technology 02, no. 04 (2011): 433–37. http://dx.doi.org/10.21917/ijct.2011.0060.

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6

Luis William C. Meing. "Exploring Multilevel Feedback Queue Combinations and Regression-Based Time Quanta in Scheduling Algorithms." Journal of Information Systems Engineering and Management 10, no. 6s (2025): 56–66. https://doi.org/10.52783/jisem.v10i6s.699.

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Much like day-to-day life, scheduling methods have roles in managing what to do and how much time or resources to invest. Multilevel Feedback Queues (MLFQ) are a widely used algorithm due to its capacity to handle a wide range of task types and execution times. There is increasing interest in exploring dynamic scheduling models that can adapt to live variables solved by machine learning. This study explores an approach to process scheduling by integrating linear regression into the dynamic adjustment of round robin time quanta within MLFQ systems. This paper identifies system resources that ca

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7

Dhruva, R. Rinku, and AshaRani M. "Reinforcement learning based multi core scheduling (RLBMCS) for real time systems." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1805–13. https://doi.org/10.11591/ijece.v10i2.pp1805-1813.

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Embedded systems with multi core processors are increasingly popular because of the diversity of applications that can be run on it. In this work, a reinforcement learning based scheduling method is proposed to handle the real time tasks in multi core systems with effective CPU usage and lower response time. The priority of the tasks is varied dynamically to ensure fairness with reinforcement learning based priority assignment and Multi Core MultiLevel Feedback queue (MCMLFQ) to manage the task execution in multi core system

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Rinku, Dhruva R., and M. AshaRani. "Reinforcement learning based multi core scheduling (RLBMCS) for real time systems." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 2 (2020): 1805. http://dx.doi.org/10.11591/ijece.v10i2.pp1805-1813.

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Embedded systems with multi core processors are increasingly popular because of the diversity of applications that can be run on it. In this work, a reinforcement learning based scheduling method is proposed to handle the real time tasks in multi core systems with effective CPU usage and lower response time. The priority of the tasks is varied dynamically to ensure fairness with reinforcement learning based priority assignment and Multi Core MultiLevel Feedback queue (MCMLFQ) to manage the task execution in multi core system.

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9

Ardani, Rega Listya, and Asrul Sani. "DESIGNING AN ANDROID-BASED FUTSAL BOOKING APP USING FCFS AND MULTILEVEL FEEDBACK QUEUE ALGORITHMS." Jurnal Pilar Nusa Mandiri 20, no. 2 (2024): 155–64. http://dx.doi.org/10.33480/pilar.v20i2.5778.

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The improvement of data innovation has affected the advancement of human life, moving from ordinary strategies to present day computerized strategies. One application of data innovation in everyday life is online planning and booking. This investigate points to design an Android-based futsal field booking application utilizing the Primary Come To begin with Serve (FCFS) and Multilevel Input Line (MLFQ) calculations.This application is expected to energize clients in making futsal field reservations viably and effectively. The modify strategy utilized in this ask generally is Remarkable Program

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10

Wahyu Prasetyo, Tri, Wiharto , -, and Afrizal Doewes. "Pemodelan Penjadwalan Multilevel Feedback Queue Menggunakan Dynamic Time Quantum Pada Kasus Pemesanan Makanan di Restoran." Jurnal Teknologi & Informasi ITSmart 4, no. 2 (2016): 92. http://dx.doi.org/10.20961/its.v4i2.1772.

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11

Putri, Aei Dhelwis Okdhianthy, Fauziah Fauziah, and Agus Iskandar. "ALGORITMA CONTENT-BASED FILTERING DAN ALGORITMA MULTILEVEL FEEDBACK QUEUE PADA PROSES PEMESANAN MAKANAN BERBASIS WEB." JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) 8, no. 1 (2023): 266–80. http://dx.doi.org/10.29100/jipi.v8i1.3426.

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12

AndrianGinting, Dian, S. Si Aristoteles, and Ossy Dwi Endah. "Implementation of Multilevel Feedback Queue Algorithm in Restaurant Order Food Application Development for Android and iOS Platforms." International Journal of Computer Applications 80, no. 13 (2013): 24–30. http://dx.doi.org/10.5120/13922-1824.

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13

Ilyas, Muchammad, R. Dimas Adityo, and Rani Purbaningtyas. "Design and Implementation of Food & Beverage Order Applications Using Multilevel Feedback Queue Method Based Android (case Study : Bonk Cafe Krian)." JEECS (Journal of Electrical Engineering and Computer Sciences) 2, no. 2 (2017): 287–98. http://dx.doi.org/10.54732/jeecs.v2i2.154.

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With the development of information technology that exists today everyone can perform data processing easily, canproduce an information we need accurately and save time, as well as cost. Then we need a menu applicationapplication program using smartphone technology and web based to facilitate the ordering of food and drinks atBonk Cafe Krian. With the features that exist in this application, the user can make the ordering process usingAndroid and from the order will be stored into the database server so that the ordering process will appear on themonitor the kitchen along with the cashier. Thi

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14

Takahashi, Yuma, Takefumi Hiraguri, Kazuki Maruta, et al. "Power–Packet Conversion Methods and Analysis of Scheduling Schemes for Wireless Power Transfer." IoT 6, no. 2 (2025): 28. https://doi.org/10.3390/iot6020028.

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Recently, electromagnetic wireless power transfer (WPT) has emerged as a promising technology for supplying power to multiple terminals. Previous studies have devised packet transmission methods, commonly used in telecommunication, for power analysis. This study develops a simulator that calculates the received power by integrating a power–packet conversion method, based on previous research. The simulator incorporates several scheduling functions to facilitate the investigation of the efficiency of the power-feeding methods. This study analyzes the efficacy of a first-come–first-served (FCFS)

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15

Van Houdt, B., J. Van Velthoven, and C. Blondia. "QBD Markov chains on binomial-like trees and its application to multilevel feedback queues." Annals of Operations Research 160, no. 1 (2007): 3–18. http://dx.doi.org/10.1007/s10479-007-0288-8.

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16

"Multilevel Algorithm Feedback Queue for Restaurant Order System." International Journal of Recent Technology and Engineering 8, no. 3 (2019): 5000–5005. http://dx.doi.org/10.35940/ijrte.c5649.098319.

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The purpose of writing this paper is to advance a restaurant that is have started out or even developing, with this business process will be make it easy and integrated to be as simple as possible so that customers who come to a restaurant no longer need to queue. In order to improve the quality of education on an ongoing basis both input, process and output in a study program, applications are needed that can support business processes[1]. The author makes the analysis of the system running using the UML (Unified Model Language), Multilevel Algorithm method used for analyzing the running syst

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17

Panduranaga Rao, M. V., and K. C. Shet. "A Research in Real Time Scheduling Policy for Embedded System Domain." CLEI Electronic Journal 12, no. 2 (2018). http://dx.doi.org/10.19153/cleiej.12.2.4.

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Scheduling a sequence of jobs released over time when the processing time of a job is only known at its completion is a classical problem in CPU scheduling in time sharing and real time operating systems. Previous approaches to scheduling computer systems have focused primarily on systemlevel abstractions for the scheduling decision functions or for the mechanisms that are used to implement them. This paper introduces a new scheduling concept New Multi Level Feedback Queue (NMLFQ) algorithm. It’s important to get a good response time with interactive tasks w

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18

Pradeep, Kumar Jatav, Nagar Nitin, and Singhai Rahul. "An In-depth Analysis of CPU Scheduling Algorithms in Operating Systems." June 30, 2023. https://doi.org/10.5281/zenodo.8176750.

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CPU scheduling algorithms determine how programs run on a CPU in an operating system. These algorithms optimize the system responsiveness, process equity, and resource use. This study examines the operating system CPU scheduling algorithms. We first explain the preemptive and non-preemptive CPU scheduling algorithms. We examine FCFS, SJN, RR, Priority Scheduling, and Multilevel Queue Scheduling. The reasoning, strengths, flaws, and examples of successes and failures are described. We also study Multilevel Feedback Queue Scheduling, Guaranteed Scheduling, and Lottery Scheduling. These algorithm

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19

Pradeep, Kumar Jatav, Nagar Nitin, and Singhai Rahul. "An In-depth Analysis of CPU Scheduling Algorithms in Operating Systems." June 30, 2023. https://doi.org/10.5281/zenodo.8176778.

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CPU scheduling algorithms determine how programs run on a CPU in an operating system. These algorithms optimize the system responsiveness, process equity, and resource use. This study examines the operating system CPU scheduling algorithms. We first explain the preemptive and non-preemptive CPU scheduling algorithms. We examine FCFS, SJN, RR, Priority Scheduling, and Multilevel Queue Scheduling. The reasoning, strengths, flaws, and examples of successes and failures are described. We also study Multilevel Feedback Queue Scheduling, Guaranteed Scheduling, and Lottery Scheduling. These algorithm

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