Dynamic tuning for parameter-based virtual machine placement

Tools

Mosa, Abdelkhalik and Sakellariou, Rizos; (2018) Dynamic tuning for parameter-based virtual machine placement. In: 2018 17th International Symposium on Parallel and Distributed Computing (ISPDC). IEEE, Piscataway, NJ, pp. 38-45. ISBN 9781538653319 (https://doi.org/10.1109/ISPDC2018.2018.00015)

[thumbnail of Mosa-Sakellariou-ISPDC2018-Dynamic-tuning-for-parameter-based-virtual-machine-placement]
Preview
 Text. Filename: Mosa_Sakellariou_ISPDC2018_Dynamic_tuning_for_parameter_based_virtual_machine_placement.pdf
Accepted Author Manuscript
License: Strathprints license 1.0
Download (1MB)| Preview

Abstract

Virtual machine (VM) placement is the process that allocates virtual machines onto physical machines (PMs) in cloud data centers. Reservation-based VM placement allocates VMs to PMs according to a (statically) reserved VM size regardless of the actual workload. If, at some point in time, a VM is making use of only a fraction of its reservation this leads to PM underutilization, which wastes energy and, at a grand scale, it may result in financial and environmental costs. In contrast, demand-based VM placement consolidates VMs based on the actual workload's demand. This may lead to better utilization, but it may incur a higher number of Service Level Agreement Violations (SLAVs) resulting from overloaded PMs and/or VM migrations from one PM to another as a result of workload fluctuations. To control the tradeoff between utilization and the number of SLAVs, parameter-based VM placement can allow a provider, through a single parameter, to explore the whole space of VM placement options that range from demand-based to reservation-based. The idea investigated by this paper is to adjust this parameter continuously at run-time in a way that a provider can maintain the number of SLAVs below a certain (predetermined) threshold while using the smallest possible number of PMs for VM placement. Two dynamic algorithms to select a value of this parameter on-the-fly are proposed. Experiments conducted using CloudSim evaluate the performance of the two algorithms using one synthetic and one real workload.

ORCID iDs

Mosa, Abdelkhalik ORCID logoORCID: https://orcid.org/0000-0001-9521-1676 and Sakellariou, Rizos;
  • Item type:Book Section
    ID code:82334
    Dates:
    Date
    Event
    30 August 2018
    Published
    Notes:© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Science > Mathematics
    Department:Faculty of Science > Computer and Information Sciences
    Depositing user: Pure Administrator
    Date deposited:13 Sep 2022 14:18
    Last modified:11 Nov 2024 15:30
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/82334
CORE (COnnecting REpositories)