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Robust Deadline-Constrained Resource Provisioning and Workflow Scheduling Algorithm for Handling Performance Uncertainty in IaaS Clouds

Published: 05 December 2017 Publication History

Abstract

Scheduling the execution of scientific applications expressed as workflows on Infrastructure as a Service (IaaS) Clouds involves many uncertainties due to the variable and unpredictable performance of Cloud resources. These uncertainties are modeled by probability distribution functions in past researches or totally ignored in some cases. In this paper, we propose a novel deadline constrained workflow scheduling algorithm which handles the uncertainties in scheduling workflows in the IaaS Clouds. Our proposed model addresses the uncertainties related to: the estimation of task execution times, and the delay in provisioning computational Cloud resources. The workflow scheduling problem is considered as a cost-optimized, deadline-constrained optimization problem. In our model, we consider knowledge of the interval of uncertainty for modeling the execution time rather than using a known probability distribution function or precise estimations which are very sensitive to variations. Simulation results from experiments with synthetic workflows show that our proposal is robust to fluctuations in estimates of task runtimes and is able to produce high quality schedules that have deadline guarantees with minimal penalty cost trade-off depending on the length of the interval of uncertainty.

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Cited By

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  • (2021)Clockwork: A Delay-Based Global Scheduling Framework for More Consistent Landing Times in the Data WarehouseProceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining10.1145/3447548.3467119(3627-3637)Online publication date: 14-Aug-2021
  • (2020)Adaptive Workflow Scheduling Using Evolutionary Approach in Cloud ComputingVietnam Journal of Computer Science10.1142/S219688882050010407:02(179-196)Online publication date: 26-Feb-2020
  • (2018)A Robust Algorithm for Deadline Constrained Scheduling in IaaS Cloud EnvironmentIEICE Transactions on Information and Systems10.1587/transinf.2018PAP0016E101.D:12(2942-2957)Online publication date: 1-Dec-2018

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cover image ACM Conferences
UCC '17 Companion: Companion Proceedings of the10th International Conference on Utility and Cloud Computing
December 2017
252 pages
ISBN:9781450351959
DOI:10.1145/3147234
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 05 December 2017

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Author Tags

  1. deadline-constrained scheduling
  2. iaas clouds
  3. resource provisioning
  4. robust scheduling
  5. workflow application

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Overall Acceptance Rate 38 of 125 submissions, 30%

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Cited By

View all
  • (2021)Clockwork: A Delay-Based Global Scheduling Framework for More Consistent Landing Times in the Data WarehouseProceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining10.1145/3447548.3467119(3627-3637)Online publication date: 14-Aug-2021
  • (2020)Adaptive Workflow Scheduling Using Evolutionary Approach in Cloud ComputingVietnam Journal of Computer Science10.1142/S219688882050010407:02(179-196)Online publication date: 26-Feb-2020
  • (2018)A Robust Algorithm for Deadline Constrained Scheduling in IaaS Cloud EnvironmentIEICE Transactions on Information and Systems10.1587/transinf.2018PAP0016E101.D:12(2942-2957)Online publication date: 1-Dec-2018

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