Scheduling for energy efficiency and throughput maximization in a faulty cloud environment

Huda Alrammah, Yi Gu, Chase Wu, Shiguang Ju

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

There is an increasingly prominent trend in many big data scientific applications to move a substantial portion of or even all of the computing workflow executions to a cloud environment, which calls for an effective and efficient solution to optimize the performance of such workflow applications. We focus on computing workflows of streaming applications, and consider a faulty cloud environment where both nodes and links may fail at a certain probability. We tackle a triobjective optimization problem that reduces the total energy consumption while enforcing a bound on the throughput, and a constraint on the reliability. A layer-based mapping algorithm is proposed to schedule each subtask in the workflow to an appropriate node in the cloud in order to achieve three objectives (energy, throughput, and reliability) in a distributed manner. The proposed scheme automatically recomputes a mapping solution adapting to the network changes after a certain period. The performance superiority of the proposed scheme is illustrated by an extensive set of comparisons with other existing methods.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 23rd International Conference on Parallel and Distributed Systems, ICPADS 2017
PublisherIEEE Computer Society
Pages561-569
Number of pages9
ISBN (Electronic)9781538621295
DOIs
StatePublished - May 29 2018
Event23rd IEEE International Conference on Parallel and Distributed Systems, ICPADS 2017 - Shenzhen, China
Duration: Dec 15 2017Dec 17 2017

Publication series

NameProceedings of the International Conference on Parallel and Distributed Systems - ICPADS
Volume2017-December
ISSN (Print)1521-9097

Other

Other23rd IEEE International Conference on Parallel and Distributed Systems, ICPADS 2017
CountryChina
CityShenzhen
Period12/15/1712/17/17

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

Keywords

  • Cloud computing
  • Energy efficiency
  • Reliability
  • Throughput
  • Workflow scheduling

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