A passive available bandwidth estimation methodology

The Available Bandwidth (AB) of an end-to-end path is its remaining capacity and it is an important metric for several applications such as overlay routing and P2P networking. That is why many AB estimation tools have been published recently. Most of these tools use the Probe Rate Model, which requi...

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Detalhes bibliográficos
Autores: Cabellos Aparicio, Alberto|||0000-0001-9329-7584, Thompson, John, García, Francisco J., Domingo Pascual, Jordi|||0000-0001-6277-7542
Formato: informe técnico
Fecha de publicación:2009
País:España
Recursos:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/14354
Acesso em linha:https://hdl.handle.net/2117/14354
Access Level:acceso abierto
Palavra-chave:Telecommunication -- Traffic
Passive
Measurement
Available bandwidth
Telecomunicació -- Tràfic
Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
Descrição
Resumo:The Available Bandwidth (AB) of an end-to-end path is its remaining capacity and it is an important metric for several applications such as overlay routing and P2P networking. That is why many AB estimation tools have been published recently. Most of these tools use the Probe Rate Model, which requires sending packet trains at a rate matching the AB. Its main issue is that it congests the path under measurement. We present a different approach: a novel passive methodology to estimate the AB that does not introduce probe traffic. Our methodology, intended to be applied between two separate nodes, estimates the path’s AB by analyzing specific parameters of the traffic exchanged. The main challenge is that we cannot rely on any given rate of this traffic. Therefore we rely on a different model, the Utilization Model. In this paper we present our passive methodology and a tool (PKBest) based on it. We evaluate its applicability and accuracy using public NLANR data traces. Our results -more than 300Gb- show that our tool is more accurate than pathChirp, a state-of-the-art active PRM-based tool. At the best of the authors’ knowledge this is the first passive AB estimation methodology.