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The Impact on the Performance of Co-running Virtual Machines in a Virtualized Environment

Published: 25 July 2016 Publication History

Abstract

The success of cloud computing technologies heavily depends on the underlying hardware as well as the system software support for virtualization. As hardware resources become more abundant with each technology generation, the complexity of managing the resources of computing systems has increased dramatically. Past research has demonstrated that contention for shared resources in modern multi-core multithreaded microprocessors (MMMP) can lead to poor and unpredictable performance. In this paper we conduct a performance degradation study targeting virtualized environment. Firstly, we present our findings of the possible impact on the performance of virtual machines (VMs) when managed by the default Linux scheduler as regular host processes. Secondly, we study how the performance of virtual machines can be affected by different ways of co-scheduling at the host level. Finally, we conduct a correlation study in which we strive to determine which hardware event(s) can be used to identify performance degradation of the VMs and the applications running within. Our experimental results show that if not managed carefully, the performance degradation of individual VMs can be as high as 135%. We believe that low-level hardware information collected at runtime can be used to assist the host scheduler in managing co-running virtual machines in order to alleviate contention for resources, therefore reducing performance degradation of individual VMs as well as improving the overall system throughput.

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  • (2023)A Distributed Virtual-Machine Placement and Migration Approach Based on Modern Portfolio TheoryJournal of Network and Systems Management10.1007/s10922-023-09775-832:1Online publication date: 25-Oct-2023
  • (2020)High Frequency Performance Monitoring via Architectural Event Measurement2020 IEEE International Symposium on Workload Characterization (IISWC)10.1109/IISWC50251.2020.00020(114-122)Online publication date: Oct-2020
  • (2019)SoK: The Challenges, Pitfalls, and Perils of Using Hardware Performance Counters for Security2019 IEEE Symposium on Security and Privacy (SP)10.1109/SP.2019.00021(20-38)Online publication date: May-2019
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  1. The Impact on the Performance of Co-running Virtual Machines in a Virtualized Environment

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    cover image ACM Conferences
    ARMS-CC'16: Proceedings of the Third International Workshop on Adaptive Resource Management and Scheduling for Cloud Computing
    July 2016
    66 pages
    ISBN:9781450342278
    DOI:10.1145/2962564
    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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    Publication History

    Published: 25 July 2016

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    Author Tags

    1. Cloud Computing
    2. Hardware Performance Counters
    3. Kernel Virtual Machine
    4. Virtual Machine Management

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    View all
    • (2023)A Distributed Virtual-Machine Placement and Migration Approach Based on Modern Portfolio TheoryJournal of Network and Systems Management10.1007/s10922-023-09775-832:1Online publication date: 25-Oct-2023
    • (2020)High Frequency Performance Monitoring via Architectural Event Measurement2020 IEEE International Symposium on Workload Characterization (IISWC)10.1109/IISWC50251.2020.00020(114-122)Online publication date: Oct-2020
    • (2019)SoK: The Challenges, Pitfalls, and Perils of Using Hardware Performance Counters for Security2019 IEEE Symposium on Security and Privacy (SP)10.1109/SP.2019.00021(20-38)Online publication date: May-2019
    • (undefined)A Distributed Virtual-Machine Placement and Migration Approach Based on Modern Portfolio TheorySSRN Electronic Journal10.2139/ssrn.4170520

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