Enhancing traffic sampling scope and efficiency

dc.contributor.author João Marco en
dc.contributor.author Carvalho,P en
dc.contributor.author Lima,SR en
dc.date.accessioned 2018-01-15T17:06:41Z
dc.date.available 2018-01-15T17:06:41Z
dc.date.issued 2013 en
dc.description.abstract Traffic Sampling is a crucial step towards scalable network measurements, enclosing manifold challenges. The wide variety of foreseeable sampling scenarios demands for a modular view of sampling components and features, grounded on a consistent architecture. Articulating the measurement scope, the required information model and the adequate sampling strategy is a major design issue for achieving an encompassing and efficient sampling solution. This is the main focus of the present work, where a layered architecture, a taxonomy of existing sampling techniques distinguishing their inner characteristics and a flexible framework able to combine these characteristics are introduced. In addition, a new multiadaptive technique proposal, based on linear prediction, allows to reduce the measurement overhead significantly, while assuring that traffic samples reflect the statistical behavior of the global traffic under analysis. © 2013 IEEE. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/6213
dc.identifier.uri http://dx.doi.org/10.1109/infcom.2013.6566718 en
dc.language eng en
dc.relation 6946 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Enhancing traffic sampling scope and efficiency en
dc.type conferenceObject en
dc.type Publication en
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