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Task Classification Based Energy-Aware Consolidation in Clouds

Authors:

EunYoung LeeAuthors Info & Claims

Scientific Programming, Volume 2016

Page 8

https://doi.org/10.1155/2016/6208358

Published: 01 August 2016 Publication History

Abstract

We consider a cloud data center, in which the service provider supplies virtual machines (VMs) on hosts or physical machines (PMs) to its subscribers for computation in an on-demand fashion. For the cloud data center, we propose a task consolidation algorithm based on task classification (i.e., computation-intensive and data-intensive) and resource utilization (e.g., CPU and RAM). Furthermore, we design a VM consolidation algorithm to balance task execution time and energy consumption without violating a predefined service level agreement (SLA). Unlike the existing research on VM consolidation or scheduling that applies none or single threshold schemes, we focus on a double threshold (upper and lower) scheme, which is used for VM consolidation. More specifically, when a host operates with resource utilization below the lower threshold, all the VMs on the host will be scheduled to be migrated to other hosts and then the host will be powered down, while when a host operates with resource utilization above the upper threshold, a VM will be migrated to avoid using 100% of resource utilization. Based on experimental performance evaluations with real-world traces, we prove that our task classification based energy-aware consolidation algorithm (TCEA) achieves a significant energy reduction without incurring predefined SLA violations.

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Cited By

Swain CShankar RSahu A(2024)Edge data distribution as a network Steiner tree estimation in edge computingComputing10.1007/s00607-024-01259-0106:5(1585-1609)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1007/s00607-024-01259-0
Li GXu SWu JDing H(2018)Resource Scheduling Based on Improved Spectral Clustering Algorithm in Edge ComputingScientific Programming10.1155/2018/68603592018Online publication date: 8-Jul-2018
https://dl.acm.org/doi/10.1155/2018/6860359
Moon YYu HGil JLim J(2017)A slave ants based ant colony optimization algorithm for task scheduling in cloud computing environmentsHuman-centric Computing and Information Sciences10.1186/s13673-017-0109-27:1(1-10)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1186/s13673-017-0109-2

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Published In

cover image Scientific Programming

Scientific Programming Volume 2016, Issue

August 2016

ISSN:1058-9244

EISSN:1875-919X

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Copyright © Copyright © 2016 HeeSeok Choi et al.

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Hindawi Limited

London, United Kingdom

Publication History

Published: 01 August 2016

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Cited By

Swain CShankar RSahu A(2024)Edge data distribution as a network Steiner tree estimation in edge computingComputing10.1007/s00607-024-01259-0106:5(1585-1609)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.1007/s00607-024-01259-0
Li GXu SWu JDing H(2018)Resource Scheduling Based on Improved Spectral Clustering Algorithm in Edge ComputingScientific Programming10.1155/2018/68603592018Online publication date: 8-Jul-2018
https://dl.acm.org/doi/10.1155/2018/6860359
Moon YYu HGil JLim J(2017)A slave ants based ant colony optimization algorithm for task scheduling in cloud computing environmentsHuman-centric Computing and Information Sciences10.1186/s13673-017-0109-27:1(1-10)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1186/s13673-017-0109-2

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