A QoS-based scheduling algorithm for instance-intensive workflows in cloud environment

Huifang Li, Siyuan Ge, Lu Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

Along with the rapid development of the Internet, especially the advent of cloud computing era, instance-intensive workflow applications will play an increasingly important role in people's daily life. Most of the existing scheduling algorithms are designed just for a single complex workflow instance. This paper takes cloud workflow as a research background, completely generalizes and describes the instance-intensive workflow scheduling optimization problems based on QoS (Quality of Service) under the current architecture of cloud workflows. Then this paper classifies workflow tasks based on user's QoS preference, and combines with staggered sub-deadlines allocation criteria, proposes a QDA scheduling algorithm suitable for instance-intensive workflows in cloud environment. Simulation results show that, compared to other algorithms, QDA algorithm can better meets the different requirements from users, and also has a much better load balancing rate.

Original languageEnglish
Title of host publication26th Chinese Control and Decision Conference, CCDC 2014
PublisherIEEE Computer Society
Pages4094-4099
Number of pages6
ISBN (Print)9781479937066
DOIs
Publication statusPublished - 2014
Event26th Chinese Control and Decision Conference, CCDC 2014 - Changsha, China
Duration: 31 May 20142 Jun 2014

Publication series

Name26th Chinese Control and Decision Conference, CCDC 2014

Conference

Conference26th Chinese Control and Decision Conference, CCDC 2014
Country/TerritoryChina
CityChangsha
Period31/05/142/06/14

Keywords

  • Cloud workflows
  • Quality of Service
  • instance-intensive workflows
  • workflow scheduling algorithm

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Li, H., Ge, S., & Zhang, L. (2014). A QoS-based scheduling algorithm for instance-intensive workflows in cloud environment. In 26th Chinese Control and Decision Conference, CCDC 2014 (pp. 4094-4099). Article 6852898 (26th Chinese Control and Decision Conference, CCDC 2014). IEEE Computer Society. https://doi.org/10.1109/CCDC.2014.6852898