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Virtual machine consolidation for cloud data centers using parameter-based adaptive allocation

Published: 31 August 2017 Publication History

Abstract

Cloud computing enables cloud providers to offer computing infrastructure as a service (IaaS) in the form of virtual machines (VMs). Cloud management platforms automate the allocation of VMs to physical machines (PMs). An adaptive VM allocation policy is required to handle changes in the cloud environment and utilize the PMs efficiently In the literature, adaptive VM allocation is typically performed using either reservation-based or demand-based allocation. In this work, we have developed a parameter-based VM consolidation solution that aims to mitigate the issues with the reservation-based and demand-based solutions. This parameter-based VM consolidation exploits the range between demand-based and reservation-based finding VM to PM allocations that strike a delicate balance according to cloud providers' goals. Experiments conducted using CloudSim show how the proposed parameter-based solution gives a cloud provider the flexibility to manage the trade-off between utilization and other requirements.

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  • (2022)Adaptive Computational Solutions to Energy Efficiency in Cloud Computing Environment Using VM ConsolidationArchives of Computational Methods in Engineering10.1007/s11831-022-09852-230:3(1789-1818)Online publication date: 27-Nov-2022
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cover image ACM Other conferences
ECBS '17: Proceedings of the Fifth European Conference on the Engineering of Computer-Based Systems
August 2017
177 pages
ISBN:9781450348430
DOI:10.1145/3123779
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 ACM 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: 31 August 2017

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Author Tags

  1. cloud data centers
  2. efficient data center utilization
  3. virtual machine consolidation
  4. virtual machine mapping

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ECBS '17

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Overall Acceptance Rate 25 of 49 submissions, 51%

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  • (2024)Efficient Virtual Machine Placement Strategy Based on Enhanced Genetic ApproachSN Computer Science10.1007/s42979-024-02832-25:5Online publication date: 20-Apr-2024
  • (2023)A Hybrid Approach for Improving Task Scheduling Algorithm in the CloudIntelligent Computing and Optimization10.1007/978-3-031-50151-7_18(181-193)Online publication date: 15-Dec-2023
  • (2022)Adaptive Computational Solutions to Energy Efficiency in Cloud Computing Environment Using VM ConsolidationArchives of Computational Methods in Engineering10.1007/s11831-022-09852-230:3(1789-1818)Online publication date: 27-Nov-2022
  • (2021)Classification-Based and Energy-Efficient Dynamic Task Scheduling Scheme for Virtualized Cloud Data CenterIEEE Transactions on Cloud Computing10.1109/TCC.2019.29182269:4(1376-1390)Online publication date: 1-Oct-2021
  • (2021)Usage Trends Aware VM Placement in Academic Research Computing Clouds2021 IEEE 14th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD53861.2021.00088(688-697)Online publication date: Sep-2021
  • (2021) Load Aware Hotspot Selection for SLA Improvement in Cloud Computing and Protect Environment by Reduction In CO 2 Emissions IOP Conference Series: Earth and Environmental Science10.1088/1755-1315/889/1/012028889:1(012028)Online publication date: 1-Nov-2021
  • (2020)A Multi-Weight Strategy for Container Consolidation2020 IEEE 4th International Conference on Fog and Edge Computing (ICFEC)10.1109/ICFEC50348.2020.00009(11-18)Online publication date: May-2020
  • (2020)PAPSO: A Power-Aware VM Placement Technique Based on Particle Swarm OptimizationIEEE Access10.1109/ACCESS.2020.29908288(81747-81764)Online publication date: 2020
  • (2019)Residual Capacity-Aware Virtual Machine Assignment for Reducing Network Loads in Multi-tenant Data Center NetworksJournal of Network and Systems Management10.1007/s10922-019-09492-127:4(949-971)Online publication date: 1-Oct-2019
  • (2019)GWMA Algorithm for Host Overloading Detection in Cloud Computing EnvironmentAdvances in E-Business Engineering for Ubiquitous Computing10.1007/978-3-030-34986-8_26(358-370)Online publication date: 28-Nov-2019
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