Live migration of virtual machines with their local persistent storage in a data intensive cloud

Modi, Abhinit; Achar, Raghavendra; Thilagam, P. Santhi

doi:10.1504/ijhpcn.2017.083213

Cited by 4 publications

(1 citation statement)

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“…Concerning VM live migration, [48,58] presented surveys that the reader could refer to. We would like to highlight among them [18,51] who studied live migration of the VM storage along with its memory. Very few research work has investigated VM storage live migration because it increases the VM downtime.…”

Section: Page Trackingmentioning

confidence: 99%

Intel Page Modification Logging, a hardware virtualization feature: study and improvement for virtual machine working set estimation

Bitchebe,

Mvondo,

Tchana

et al. 2020

Preprint

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Intel Page Modification Logging (PML) is a novel hardware feature for tracking virtual machine (VM) accessed memory pages. This task is essential in today's data centers since it allows, among others, checkpointing, live migration and working set size (WSS) estimation. Relying on the Xen hypervisor, this paper studies PML from three angles: power consumption, efficiency, and performance impact on user applications. Our findings are as follows. First, PML does not incur any power consumption overhead. Second, PML reduces by up to 10.18% both VM live migration and checkpointing time. Third, PML slightly reduces by up to 0.95% the performance degradation on applications incurred by live migration and checkpointing. Fourth, PML however does not allow accurate WSS estimation because read accesses are not tracked and hot pages cannot be identified. A naive extension of PML for addressing these limitations could lead to severe performance degradation (up to 34.8%) for the VM whose WSS is computed.This paper presents Page Reference Logging (PRL), a smart extension of PML for allowing both read and write accesses to be tracked. It does this without impacting user VMs. The paper also presents a WSS estimation system which leverages PRL and shows how this algorithm can be integrated into a data center which implements memory overcommitment. We implement PRL and the WSS estimation system under Gem5, a very popular hardware simulator. The evaluation results validate the accuracy of PRL in the estimation of WSS. They also show that PRL incurs no performance degradation for user VMs.

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