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VM processes state detection by hypervisor tracing

Hani Nemati and Michel Dagenais

Paper (2018)

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The diagnosis of performance issues in cloud environments is a challenging problem, due to the different levels of virtualization, the diversity of applications and their interactions on the same physical host. Moreover, because of privacy, security, ease of deployment and execution overhead, an agent-less method, which limits its data collection to the physical host level, is often the only acceptable solution. In this paper, a precise host-based method, to recover wait state for the processes inside a given Virtual Machine (VM), is proposed. The virtual Process State Detection (vPSD) algorithm computes the state of processes through host kernel tracing. The state of a virtual Process (vProcess) is displayed in an interactive trace viewer (Trace Compass) for further inspection. Our proposed VM trace analysis algorithm has been open-sourced for further enhancements and for the benefit of other developers. Experimental evaluations were conducted using a mix of workload types (CPU, Disk, and Network), with different applications like Hadoop, MySQL, and Apache. vPSD, being based on host hypervisor tracing, brings a lower overhead (around 0.03%) as compared to other approaches.

Uncontrolled Keywords

wait analysis; virtual process; virtual machine; cloud; performance analysis

Department: Department of Computer Engineering and Software Engineering
Grant number: CRDPJ468687-14
PolyPublie URL: https://publications.polymtl.ca/4204/
Conference Title: Annual IEEE International Systems Conference (SysCon 2018)
Conference Location: Vancouver, Canada
Conference Date(s): 2018-04-23 - 2018-04-26
Publisher: IEEE
DOI: 10.1109/syscon.2018.8369612
Official URL: https://doi.org/10.1109/syscon.2018.8369612
Date Deposited: 17 Feb 2020 12:52
Last Modified: 20 Apr 2023 06:06
Cite in APA 7: Nemati, H., & Dagenais, M. (2018, April). VM processes state detection by hypervisor tracing [Paper]. Annual IEEE International Systems Conference (SysCon 2018), Vancouver, Canada (8 pages). https://doi.org/10.1109/syscon.2018.8369612


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