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Performance monitoring of data centers provides vital information for dynamic resource provisioning, fault diagnosis, and capacity planning decisions. However, the very act of monitoring a system interferes with its performance, and if the information is transmitted to a monitoring station for analysis and logging, this consumes network bandwidth and disk space. This paper proposes a low-cost monitoring solution using compressive sampling - a technique that allows certain classes of signals to be recovered from the original measurements using far fewer samples than traditional approaches - and evaluates its ability to measure typical signals generated in a data-center setting using a testbed comprising the Trade6 enterprise application.
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