Despite the growing popularity of enterprise virtual desktop infrastructure (VDI), little is known about its storage traffic characteristics. In addition, no prior work has considered the detailed characteristics of virtual machine (VM) behavior on VDI. In this paper, we analyze the enterprise storage traffic on commercial office VDI using designated VMs. For 28 consecutive days, we gathered various types of traces, including a usage questionnaire and active and passive measurements. To characterize the storage traffic, we focused on two perspectives: fibre channel (FC) traffic and VM behavior. From the FC traffic perspective, we found that read traffic is dominant, although the applications are similar to those in a previous small-scale VDI. In particular, the write response time of large transactions, e.g.,128 KiB, is strongly affected by a slight decrease in cache hits during an update storm. From the VM behavior, we found that all active user VMs generate only 25% of traffic. Although a few VMs generate massive traffic, their impact is small. These characteristics are unique in comparison with the small-scale VDI. Our results have significant implications for designing the next generation of VDI and improving its performance.

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SUMMARYNetwork testbeds have been used for network measurement and experiments. In such testbeds, resources, such as CPU, memory, and I/O interfaces, are shared and virtualized to maximize node utility for many users. A few studies have investigated the impact of virtualization on precise network measurement and understood Internet traffic characteristics on virtualized testbeds. Although scheduling latency and heavy loads are reportedly affected in precise network measurement, no clear conditions or criteria have been established. Moreover, empirical-statistical criteria and methods that pick out anomalous cases for precise network experiments are required on userland because virtualization technology used in the provided testbeds is hardly replaceable. In this paper, we show that 'oversize packet spacing', which can be caused by CPU scheduling latency, is a major cause of throughput instability on a virtualized network testbed even when no significant changes occur in well-known network metrics. These are unusual anomalies on virtualized network environment. Empirical-statistical analysis results accord with results at previous work. If network throughput is decreased by the anomalies, we should carefully review measurement results. Our empirical approach enables anomalous cases to be identified. We present CPU availability as an important criterion for estimating the anomalies.