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A synthesized heuristic task scheduling algorithm.

Yanyan Dai1, Xiangli Zhang1

  • 1Institute of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China.

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A new heuristic task scheduling algorithm, HCPPEFT, improves performance in heterogeneous environments by prioritizing critical tasks and using task duplication to cut communication costs. This approach enhances static task scheduling efficiency.

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Algorithm Design

Background:

  • Static task scheduling in heterogeneous computing environments presents significant challenges.
  • Existing algorithms like HEFT, PEFT, and STDH have limitations in optimizing performance.

Purpose of the Study:

  • To propose a novel heuristic task scheduling algorithm, HCPPEFT, for static task scheduling problems in heterogeneous environments.
  • To improve scheduling performance by optimizing task prioritization and resource selection.

Main Methods:

  • The HCPPEFT algorithm employs a three-level task prioritization strategy: critical tasks, tasks with longer path to exit, and tasks with fewer predecessors.
  • Resource selection in HCPPEFT utilizes task duplication to minimize inter-resource communication costs.
  • The algorithm forecasts the impact of task assignments on child tasks for improved decision-making.

Main Results:

  • HCPPEFT demonstrated superior scheduling performance compared to STDH, PEFT, and HEFT algorithms.
  • Experiments were conducted using randomly generated task graphs and task graph sets.

Conclusions:

  • The proposed HCPPEFT algorithm offers enhanced scheduling performance for static task scheduling in heterogeneous environments.
  • Task prioritization and intelligent resource selection, including task duplication, are key to HCPPEFT's effectiveness.