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Large scientific data transfers often occur at high rates causing increased burstiness in Internet traffic. To limit the adverse effects of these high-rate large-sized flows, which are referred to as $$\alpha $$ α flows, on delay-sensitive audio/video flows, a network management system called Alpha Flow Traffic Engineering System (AFTES) is proposed for intra-domain traffic engineering. An...
Parallel TCP connections are used for large scientific dataset transfers to increase throughput. Therefore, to accurately characterize big-data movement, it is important to reconstruct parallel flowsets from traffic measurements. In this work, we start with NetFlow records collected in an operational research-and-education network across which large scientific datasets are moved routinely, reconstruct...
High-rate, large-sized (α) flows are of interest to providers for various reasons, e.g., they have the potential to degrade service quality for real-time flows, and users are sensitive to the throughput variance of these flows. In this paper, we present characteristics, such as size, duration, average rate, of α flows computed from NetFlow records collected over a 7-month period from 4 ESnet routers...
High-rate large-sized (α) flows have adverse effects on delay-sensitive flows. Research-and-education network providers are interested in identifying such flows within their networks, and directing these flows to traffic-engineered QoS-controlled virtual circuits. To achieve this goal, a design is proposed for a hybrid network traffic engineering system (HNTES) that would run on an external server,...
This paper describes traffic analysis undertaken to answer certain questions needed to design a hybrid network traffic engineering system (HNTES). The hybrid network in question consists of an IP-routed network and a dynamic virtual-circuit network, and the role of HNTES is to identify and redirect α-flows, which are defined as flows in which the number of bytes exceeds a threshold H (1 GB) over at...
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