Wait analysis of virtual machines using host kernel tracing

Hani Nemati, Geneviève Bastien, Michel Dagenais

Communication écrite (2018)

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Résumé

An agent-less method to understand virtual machines (VMs) behavior its evolution during the VM life-cycle is an essential task for IaaS provider. It allows the IaaS provider to better scale the VMs resources by properly allocating the physical resources. On the other hand, because of privacy, security, ease of deployment and execution overhead issues, the method presented limits its data collection to the physical host level, without internal access to the VMs. We propose a host-based, precise method to recover wait states for the virtual CPUs (vCPUs) of a given VM. The Wait Analysis Algorithm (W2A) computes the state of vCPUs through the host kernel trace. The state of vCPUs is displayed in an interactive trace viewer (TraceCompass) for further inspection. Our proposed VM trace analysis algorithm has been open-sourced for further enhancements and to the benefit of other developers. Our new technique is being evaluated with representative workloads, generated by different benchmarking tools. These approaches are based on host hypervisor tracing, which brings a lower overhead (around 0.03%) as compared to other approaches.

Mots clés

Organismes subventionnaires:
CRSNG/NSERC
Numéro de subvention:
CRDPJ468687-14
Adresse URL de PolyPublie:
Nom de la conférence:
IEEE International Conference on Consumer Electronics (ICCE 2018)
Lieu de la conférence:
Las Vegas, États-Unis
Date(s) de la conférence:
2018-01-12 - 2018-01-14
Maison d'édition:
IEEE
OAI:
oai:publications.polymtl.ca:4205
ORCID
Date du dépôt:
17 févr. 2020 12:58
Dernière modification:
14 oct. 2026 10:43
Citer en APA 7:
Nemati, H., Bastien, G., & Dagenais, M. (janvier 2018). Wait analysis of virtual machines using host kernel tracing [Communication écrite]. IEEE International Conference on Consumer Electronics (ICCE 2018), Las Vegas, États-Unis (6 pages). https://doi.org/10.1109/icce.2018.8510984

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