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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

Zhiqiang Xie1, Xia Shao1, Yu Xin1

  • 1College of Computer and Technology, Harbin University of Science and Technology, Harbin, Heilongjiang, China.

Plos One
|August 5, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a new cloud computing task scheduling algorithm using the dynamic essential path (DDEP) driver. The DDEP algorithm effectively reduces task completion time (Makespan) and improves overall performance.

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Area of Science:

  • Computer Science
  • Cloud Computing
  • Algorithm Design

Background:

  • Task scheduling in cloud computing is complex due to inter-task dependencies.
  • Existing algorithms may not efficiently handle constraint relations and dynamic costs.

Purpose of the Study:

  • To propose a novel task scheduling algorithm for cloud computing systems.
  • To address task dependency and dynamic cost challenges in scheduling.

Main Methods:

  • Developed a scheduling algorithm based on the dynamic essential path (DDEP) driver.
  • Implemented a predecessor-task layer priority strategy to manage task constraints.
  • Utilized a dynamic essential long path strategy to prioritize tasks with the longest paths based on actual costs.

Main Results:

  • The DDEP algorithm effectively reduces task Makespan in most simulated scenarios.
  • Experimental results demonstrate high-quality performance objectives are met.
  • The algorithm successfully handles constraint relations among task nodes.

Conclusions:

  • The proposed DDEP algorithm offers an effective solution for cloud computing task scheduling.
  • The algorithm improves efficiency by considering dynamic costs and task dependencies.
  • This approach contributes to optimized resource utilization and performance in cloud environments.