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Related Experiment Video

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A Do-it-yourself System for Scheduled Feeding of Laboratory Rodents in Their Home Cage
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Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms.

Jianwu Wang1, Prakashan Korambath2, Ilkay Altintas1

  • 1San Diego Supercomputer Center, UCSD, La Jolla, CA, U.S.A.

Procedia Computer Science
|February 6, 2018
PubMed
Summary
This summary is machine-generated.

Managing cloud-based workflows is challenging. This study introduces a Workflow as a Service (WFaaS) architecture with four heuristic scheduling algorithms to optimize workflow execution, cost, and performance in cloud environments.

Keywords:
CloudWorkflowWorkflow as a Service (WFaaS) architectureworkflow scheduling algorithms

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Area of Science:

  • Computer Science
  • Cloud Computing
  • Distributed Systems

Background:

  • Cloud computing adoption for workflow systems presents challenges in managing workflows, virtual machines (VMs), and execution efficiency.
  • Scalability and extensibility are key considerations for cloud-based workflow management architectures.

Purpose of the Study:

  • To design a scalable and extensible Workflow as a Service (WFaaS) architecture.
  • To develop and evaluate heuristic workflow scheduling algorithms for efficient cloud execution.

Main Methods:

  • Proposed a Workflow as a Service (WFaaS) architecture with independent services.
  • Developed four heuristic workflow scheduling algorithms tailored for different objectives.
  • Conducted experimental studies to analyze algorithm performance, cost, and price/performance ratio.

Main Results:

  • The proposed WFaaS architecture facilitates efficient management of cloud-based workflows.
  • Experimental results demonstrate varying efficiencies of the four heuristic algorithms across performance, cost, and price/performance metrics.
  • Identified optimal usage scenarios for each algorithm based on specific targets.

Conclusions:

  • The WFaaS architecture provides a robust framework for cloud workflow management.
  • The heuristic scheduling algorithms offer effective strategies for optimizing cloud workflow execution.
  • Algorithm selection should be based on specific performance, cost, or combined objectives.