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Scalable accurate consolidation of passively measured statistical data

Abstract : Passive probes continuously collect a significant amount of traffic volume, and autonomously generate statistics on a large number of metrics. A common statistical output of passive probe is represented by probability mass functions (pmf). The need for consolidation of several pmfs arises in two contexts, namely: (i) whenever a central point collects and aggregates measurement of multiple disjoint vantage points, and (ii) whenever a local measurement processed at a single vantage point needs to be distributed over multiple cores of the same physical probe, in order to cope with growing link capacity. Taking an experimental approach, we study both cases assessing the impact of different consolidation strategies, obtaining general design and tuning guidelines.
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Conference papers
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Submitted on : Thursday, June 19, 2014 - 4:00:55 PM
Last modification on : Tuesday, November 30, 2021 - 2:32:02 PM


  • HAL Id : hal-01010371, version 1


Silvia Colabrese, D. Rossi, M. Mellia. Scalable accurate consolidation of passively measured statistical data. Passive and Active Measurement (PAM), Extended Abstract, Mar 2014, Los Angeles, United States. pp.262-264. ⟨hal-01010371⟩



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