This paper describes our implementation of and initial experiences with DipZoom (for "Deep Internet Performance Zoom"), a novel approach to provide focused, on-demand Internet measurements. Unlike existing a...
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ISBN:
(纸本)1595936394
This paper describes our implementation of and initial experiences with DipZoom (for "Deep Internet Performance Zoom"), a novel approach to provide focused, on-demand Internet measurements. Unlike existing approaches that face a difficult challenge of building a measurement platform with sufficiently diverse measurements and measuring hosts, DipZoom implements a matchmaking service instead, using P2P concepts to bring together experimenters in need of measurements with external measurement providers. DipZoom offers the following two main contributions. First, since it is just a facilitator for an open community of participants, it promises unprecedented availability of diverse measurements and measuring points. Second, by offering programmatic access to the entire platform from the experimenter's local computer, DipZoom simplifies staging and execution of complex measurement experiments and lowers the bar for obtaining high-quality measurements.
Branch taken rate and transition rate have been proposed as metrics to characterize the branch predictability. However, these two metrics may misclassify branches with regular history patterns as hard-to-predict branc...
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ISBN:
(纸本)9781450302623
Branch taken rate and transition rate have been proposed as metrics to characterize the branch predictability. However, these two metrics may misclassify branches with regular history patterns as hard-to-predict branches, causing an inaccurate and ambiguous view of branch predictability. This study uses autocorrelation to analyze the branch history patterns and presents a new metric Degree of Pattern Irregularity (DPI) for branch classification. The proposed metric is evaluated with different branch predictors, and the results show that DPI significantly improves the quality and the accuracy of branch classification over traditional taken rate and transition rate.
Network traffic measurement and workload characterization are key steps in the workload modeling process. Much has been learned through network measurement and workload modeling in the last ten years, but new challeng...
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