Hubungan Antara Ukuran Kuantum (Quantum Size) dan Kinerja Algoritma Round-Robin (Studi Kasus Penjadwalan CPU)

Fillah Anjany; Syifa Fikroh Al Kaamil; Muhammad Ainul Yaqin

doi:10.55382/jurnalpustakadata.v5i2.1395

Penulis

Fillah Anjany Universitas Islam Negeri Maulana Malik Ibrahim Malang
Syifa Fikroh Al Kaamil Universitas Islam Negeri Maulana Malik Ibrahim Malang
Muhammad Ainul Yaqin Universitas Islam Negeri Maulana Malik Ibrahim Malang

DOI:

https://doi.org/10.55382/jurnalpustakadata.v5i2.1395

Kata Kunci:

Round Robin, Time Quantum, Penjadwalan CPU, Context Switch, Turnaround Time

Abstrak

Penjadwalan CPU merupakan salah satu fungsi penting dalam sistem operasi yang menentukan efisiensi dan keadilan penggunaan prosesor. Algoritma Round Robin (RR) dikenal karena kesederhanaannya dan kemampuannya mendistribusikan waktu CPU secara adil kepada setiap proses. Namun, performa algoritma ini sangat dipengaruhi oleh besar kecilnya nilai time quantum. Penelitian ini bertujuan untuk menganalisis hubungan antara ukuran quantum dan kinerja algoritma Round Robin berdasarkan metrik turnaround time (TAT), waiting time (WT), throughput, dan context switch (CS). Simulasi dilakukan pada beberapa skenario dengan variasi quantum (2–100 ms) dan pola kedatangan proses yang berbeda. Hasil menunjukkan bahwa peningkatan nilai quantum menurunkan jumlah context switch secara signifikan hingga titik optimal pada kisaran 10–20 ms, di mana sistem mencapai keseimbangan antara efisiensi dan responsivitas. Analisis regresi menunjukkan hubungan positif antara context switch dan turnaround time dengan koefisien determinasi (R²) mencapai 0,84–0,87. Temuan ini menegaskan bahwa pemilihan time quantum yang tepat sangat krusial dalam menjaga performa sistem operasi time-sharing, dan nilai quantum 10–20 ms dapat dianggap sebagai rentang optimal untuk beban kerja umum.

Unduhan

Data unduhan belum tersedia.

Referensi

H. S. Behera, R. Mohanty, & D. Nayak, “A New Proposed Dynamic Quantum with Re-Adjusted Round Robin Scheduling Algorithm and Its Performance Analysis,” International Journal of Computer Applications, vol. 5, no. 5, pp. 10–15, 2010.

A. R. Dash, S. K. Sahu, & S. K. Samantra, “An Optimized Round Robin CPU Scheduling Algorithm with Dynamic Time Quantum,” International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), vol. 5, no. 1, pp. 7–15, 2015.

T. D. Putra & R. Purnomo, “Analisis Algoritma Round Robin pada Penjadwalan CPU,” Jurnal Ilmiah Teknologi Informasi Asia, vol. 15, no. 2, 2021.

N. A. Patel, “An Improved Priority Dynamic Quantum Time Round Robin Scheduling Algorithm,” International Journal of Advance Research and Innovative Ideas in Education (IJARIIE), vol. 3, no. 5, 2017.

U. Shafi et al., “A Novel Amended Dynamic Round Robin Scheduling Algorithm for Timeshared Systems,” The International Arab Journal of Information Technology, vol. 17, no. 1, pp. 90–97, 2020.

M. A. Rahman and T. Ahmed, “Performance Optimization of Round Robin Scheduling Algorithm Using Dynamic Time Quantum,” Journal of Computer Systems and Informatics Engineering, vol. 6, no. 1, pp. 45–54, 2022.

S. Verma and R. Chauhan, “Adaptive Scheduling Algorithms for Cloud Computing: Comparative Evaluation of RR and Its Variants,” International Journal of Cloud and Distributed Systems, vol. 11, no. 2, pp. 101–116, 2023.

L. Zhang, H. Liu, and Y. Qiao, “Machine Learning-Based Prediction of Optimal Time Quantum for CPU Scheduling,” IEEE Transactions on Parallel and Distributed Systems, vol. 35, no. 4, pp. 890–899, 2024.

P. Singh and K. Sharma, “Regression-driven Tuning of Time Quantum for Improving Multi-Process Scheduling Efficiency,” in Proc. Int. Conf. Computational Intelligence and Systems Engineering (CISE), pp. 221–230, 2024.

A. E. Taha and M. Y. Hassan, “Fairness-Aware Round Robin Scheduling for Multi-Core Systems: A Quantitative Evaluation,” in Proc. 2023 ACM Symposium on Operating Systems Principles (SOSP), pp. 411–423, 2023.

B. Romanov and D. Hwang, “Emerging Trends in CPU Scheduling: A Survey Report,” NVIDIA Research Technical Report, pp. 1–26, 2024.

S. K. Gupta, R. Prasad, and A. Kumar, “Adaptive Quantum CPU Scheduling Based on Workload Prediction Using Neural Networks,” IEEE Access, vol. 12, pp. 58214–58227, 2024.

R. Belferik, “Analisis Average Waiting Time Penjadwalan CPU Menggunakan Round Robin dan First Come First Served,” Journal of Digital Information Systems, vol. 9, no. 1, pp. 55–63, 2025.

K. Alsaadi and Y. H. Jasim, “A Hybrid Predictive Round Robin Scheduling Algorithm Using Burst-Time Forecasting in Cloud Systems,” IEEE Access, vol. 11, pp. 148920–148931, 2023.

J. Navarro, M. F. Amin, and A. Kumar, “Latency-Aware Adjustable Quantum Scheduling for Multi-Core Operating Systems,” in Proc. 2024 IEEE International Conference on Computer Engineering and Intelligent Systems (CEIS), Singapore, pp. 312–320, 2024.