A cooperative approach to virtual machine based fault injection

Thomas Naughton; Christian Engelmann; Geoffroy Vallée; Ferrol Aderholdt; Stephen L. Scott

doi:10.1007/978-3-319-58943-5_54

A cooperative approach to virtual machine based fault injection

Thomas Naughton, Christian Engelmann, Geoffroy Vallée, Ferrol Aderholdt, Stephen L. Scott

Intelligent Systems and Facilities

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target context is increased due to the separation between host and guest (VM). We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target’s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof-of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.

Original language	English
Title of host publication	Euro-Par 2016
Subtitle of host publication	Parallel Processing Workshops - Euro-Par 2016 International Workshops, Revised Selected Papers
Editors	Pierre-Francois Dutot, Frederic Desprez
Publisher	Springer Verlag
Pages	671-682
Number of pages	12
ISBN (Print)	9783319589428
DOIs	https://doi.org/10.1007/978-3-319-58943-5_54
State	Published - 2017
Event	22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016 - Grenoble, France Duration: Aug 24 2016 → Aug 26 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10104 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016
Country/Territory	France
City	Grenoble
Period	08/24/16 → 08/26/16

Funding

T. Naughton—This manuscript has been authored by UT-Battelle, LLC under Contract No.DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ). This material is based upon work supported by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research program.

Keywords

Fault injection
Resilience tools
Virtual machine introspection
Virtualization

Access to Document

10.1007/978-3-319-58943-5_54

Cite this

Naughton, T., Engelmann, C., Vallée, G., Aderholdt, F., & Scott, S. L. (2017). A cooperative approach to virtual machine based fault injection. In P.-F. Dutot, & F. Desprez (Eds.), Euro-Par 2016: Parallel Processing Workshops - Euro-Par 2016 International Workshops, Revised Selected Papers (pp. 671-682). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10104 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-58943-5_54

Naughton, Thomas ; Engelmann, Christian ; Vallée, Geoffroy et al. / A cooperative approach to virtual machine based fault injection. Euro-Par 2016: Parallel Processing Workshops - Euro-Par 2016 International Workshops, Revised Selected Papers. editor / Pierre-Francois Dutot ; Frederic Desprez. Springer Verlag, 2017. pp. 671-682 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A cooperative approach to virtual machine based fault injection",

abstract = "Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target context is increased due to the separation between host and guest (VM). We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target{\textquoteright}s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof-of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.",

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Naughton, T , Engelmann, C, Vallée, G, Aderholdt, F & Scott, SL 2017, A cooperative approach to virtual machine based fault injection. in P-F Dutot & F Desprez (eds), Euro-Par 2016: Parallel Processing Workshops - Euro-Par 2016 International Workshops, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10104 LNCS, Springer Verlag, pp. 671-682, 22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016, Grenoble, France, 08/24/16. https://doi.org/10.1007/978-3-319-58943-5_54

A cooperative approach to virtual machine based fault injection. / Naughton, Thomas ; Engelmann, Christian; Vallée, Geoffroy et al.
Euro-Par 2016: Parallel Processing Workshops - Euro-Par 2016 International Workshops, Revised Selected Papers. ed. / Pierre-Francois Dutot; Frederic Desprez. Springer Verlag, 2017. p. 671-682 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10104 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A cooperative approach to virtual machine based fault injection

AU - Naughton, Thomas

AU - Engelmann, Christian

AU - Vallée, Geoffroy

AU - Aderholdt, Ferrol

AU - Scott, Stephen L.

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target context is increased due to the separation between host and guest (VM). We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target’s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof-of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.

AB - Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target context is increased due to the separation between host and guest (VM). We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target’s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof-of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.

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KW - Virtual machine introspection

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DO - 10.1007/978-3-319-58943-5_54

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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ER -

Naughton T , Engelmann C, Vallée G, Aderholdt F, Scott SL. A cooperative approach to virtual machine based fault injection. In Dutot PF, Desprez F, editors, Euro-Par 2016: Parallel Processing Workshops - Euro-Par 2016 International Workshops, Revised Selected Papers. Springer Verlag. 2017. p. 671-682. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-58943-5_54

A cooperative approach to virtual machine based fault injection

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