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Virtual Machine Workloads: The Case for New NAS Benchmarks

Authors: 

Vasily Tarasov, Stony Brook University; Dean Hildebrand, IBM Research—Almaden; Geoff Kuenning, Harvey Mudd College; Erez Zadok, Stony Brook University

Abstract: 

Network Attached Storage (NAS) and Virtual Machines (VMs) are widely used in data centers thanks to their manageability, scalability, and ability to consolidate resources. But the shift from physical to virtual clients drastically changes the I/O workloads seen on NAS servers, due to guest file system encapsulation in virtual disk images and the multiplexing of request streams from different VMs. Unfortunately, current NAS workload generators and benchmarks produce workloads typical to physical machines.

This paper makes two contributions. First, we studied the extent to which virtualization is changing existing NAS workloads. We observed significant changes, including the disappearance of file system meta-data operations at the NAS layer, changed I/O sizes, and increased randomness. Second, we created a set of versatile NAS benchmarks to synthesize virtualized workloads. This allows us to generate accurate virtualized workloads without the effort and limitations associated with setting up a full virtualized environment. Our experiments demonstrate that the relative error of our virtualized benchmarks, evaluated across 11 parameters, averages less than 10%.

Vasily Tarasov, Stony Brook University

Dean Hildebrand, IBM Research—Almaden

Geoff Kuenning, Harvey Mudd College

Erez Zadok, Stony Brook University

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BibTeX
@inproceedings {180740,
author = {Vasily Tarasov and Dean Hildebrand and Geoff Kuenning and Erez Zadok},
title = {Virtual Machine Workloads: The Case for New {NAS} Benchmarks},
booktitle = {11th {USENIX} Conference on File and Storage Technologies ({FAST} 13)},
year = {2013},
isbn = {978-1-931971-99-7},
address = {San Jose, CA},
pages = {307--320},
url = {https://www.usenix.org/conference/fast13/technical-sessions/presentation/tarasov},
publisher = {{USENIX} Association},
month = feb,
}
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