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Related Experiment Video

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Enhancing task execution: a dual-layer approach with multi-queue adaptive priority scheduling.

Mansoor Iqbal1, Muhammad Umar Shafiq2, Shouzab Khan2

  • 1Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, Cyprus.

Peerj. Computer Science
|December 9, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces the Multi-Queue Adaptive Priority Scheduling (MQAPS) algorithm for efficient task execution. MQAPS optimizes CPU resource utilization and prevents job starvation, outperforming traditional scheduling methods.

Keywords:
Adjustable time quantum processingDynamic priority schedulingJob prioritizationMulti-queue thresholdTime-sensitive systems

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Area of Science:

  • Computer Science
  • Algorithms

Background:

  • Efficient task execution is crucial for optimizing computing resource usage in process scheduling.
  • Existing scheduling algorithms aim for optimized and efficient resource utilization.
  • Task starvation is a common issue in conventional scheduling methods with fixed or undefined priorities.

Purpose of the Study:

  • To introduce an innovative dual-layer scheduling algorithm, Multi-Queue Adaptive Priority Scheduling (MQAPS).
  • To enhance CPU utilization and ensure timely completion of important jobs.
  • To provide a balanced framework for dynamic adjustment of time quantum and priority.

Main Methods:

  • Developed a dual-layer hierarchy with a ready queue (RQ) and a secondary queue (SQ).
  • Implemented dynamic time slice calculation based on process priorities.
  • Prioritized tasks in the RQ based on their priority level, while SQ holds lower-priority tasks.

Main Results:

  • MQAPS demonstrated superior CPU resource and time utilization compared to Round-Robin (RR) and multi-level scheduling.
  • The algorithm effectively prevents starvation of low-priority jobs.
  • Simulation results confirmed MQAPS's optimization, fairness, and efficiency in job scheduling.

Conclusions:

  • MQAPS is a promising scheduling technique for efficient task execution.
  • The algorithm offers a balanced framework for dynamic adjustment of time quantum and priority.
  • MQAPS enhances overall system performance by optimizing resource allocation and ensuring fairness.