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The authors have implemented vPerfGuard as a combination of three modules: a sensor module, a model building module, and a model updating module. They evaluate its effectiveness using different benchmarks and different workload types, specifically focusing on various resource (CPU, memory, disk I/O) contention scenarios that are caused by work-load surges or "Noisy neighbors". The results show that vPerfGuard automatically points to the correct performance bottleneck in each scenario, including the type of the contended resource and the host where the contention occurred.
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