Managing responsiveness of virtual desktops using passive monitoring

Bhowmik, Rajdeep; Kochut, Andrzej; Beaty, Kirk

doi:10.1109/inm.2009.5188831

Cited by 5 publications

(2 citation statements)

References 18 publications

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“…This suggests that the functional form in Equation 1 has intrinsic properties of accurately representing the users' interactivity cycles. We have used this formula in an on-line management algorithm [2].…”

Section: Functional Form For State Duration Modelingmentioning

confidence: 99%

“…We have gathered desktop usage traces covering fine grained (10 seconds averaging) measurements of CPU and memory usage on a sample of 35 workstations for the period of three weeks. The data set is analyzed to determine aggregation properties of desktop workloads as well as to find invariant properties that could be used in dynamic resource management algorithms (an example of such algorithm can be found in [2]). In particular, we explore how variation and autocorrelation of desktop traces change as a function of number of aggregated desktops.…”

Section: Introductionmentioning

confidence: 99%

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Desktop workload study with implications for desktop cloud resource optimization

Kochut

Beaty

Shaikh

et al. 2010

2010 IEEE International Symposium on Parallel &Amp; Distributed Processing, Workshops and PHD Forum (IPDPSW)

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Desktop cloud is a new delivery model in which end users connect to virtual desktops running in remote data centers. This paradigm offers multiple benefits both in terms of manageability as well as efficiency improvements. However, realizing this potential requires better understanding of desktop workload and its implications for desktop consolidation.We analyze CPU and memory usage on a sample of 35 desktops using a fine-grained 10 second averaging interval. Results provide insights into achievable efficiency improvements from desktop consolidation as well as detailed autocorrelation and variability behavior as a function of number of aggregated desktops. We also propose an interactivity classification method leading to functional form suitable for estimating residual durations of interactivity states. This finding can be leveraged in on-line proactive management algorithms for desktop cloud optimization.

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Section: Functional Form For State Duration Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%