Performance models of storage contention in cloud environments
Software and Systems Modeling (SoSyM)
Virtual machine workloads: the case for new benchmarks for NAS
FAST'13 Proceedings of the 11th USENIX conference on File and Storage Technologies
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In this paper, we propose simple performance models to predict the impact of consolidation on the storage I/O performance of virtualized applications. We use a measurement-based approach based on tools such as blktrace and tshark for storage workload characterization in a commercial virtualized solution, namely VMware ESX server. Our approach allows a distinct characterization of read/write performance attributes on a per request level and provides valuable information for parameterization of storage I/O performance models. In particular, based on measures of quantities such as the mean queue-length seen upon arrival by requests, we define simple linear prediction models for the throughput, response times, and mix of read/write requests in consolidation based only on information collected in isolation experiments for the individual virtual machines.