Opnet Technologies, Inc.

Bublup, Inc.

Other

Riverbed Technology, Inc.

Stefan Znam

Alain J Cohen

Pradeep Singh

Marc Andrew Cohen

Alberto Morales

Ryan McKeown

Arun Pasupathy

Paul Janes

Karthikeyan Chandrashekar

David Boyd

Marius Popa

A computer-implemented content suggestion engine provides content suggestions to a requesting user based on information about content items that other users may have independently categorized or organized into folders within a content repository. Embodiments of the method comprise a content repository having a plurality of content items, where each content item is associated with one or more user-created folders. Embodiments further comprise receiving, via a network, a suggestion request for suggested content, where the suggestion request identifies a first content item for which suggestions are sought. Other content items in the content repository are then identified as potential suggestions based on the application of a formal relationship between the first content item and the potential suggested content items. One or more of the potential suggested content items may then be provided in response to the suggestion request via the network.

Deriving semantic relationships based on empirical organization of content by users

In a network that includes static bandwidth and dynamic bandwidth links, traffic flow at the OSI network layer is simulated at a traffic-flow level at interfaces to fixed bandwidth links, and simulated at a discrete-packet level at interfaces to dynamic bandwidth links. The resultant discrete-packet reception events at the receiving interface(s) of the dynamic bandwidth link are processed to determine the effective bandwidth/throughput of the link, as well as the allocation of this bandwidth among the individual flows through the link. The discrete-packet level receptions are used to reconstruct the parameters of the traffic flow at the network layer of the receiving interface, and this determined traffic flow is simulated accordingly at the next link, depending upon whether the next link is a static or dynamic bandwidth link.

Modeling and simulating flow propagation in dynamic bandwidth systems

A sub-system is provided to a discrete event simulator (DES) to expedite simulation execution by first detecting a non-quiescent steady-state condition in the simulated system, and when the steady-state condition is detected, the simulator determines a state, and subsequently simulates the system at a skip-ahead time using this determined state, or a predicted state based on the determined state. Convergence analysis is used to determine whether the system is at, or approaching, a steady-state condition. This convergence skip-ahead process achieves faster analysis by avoiding the computation that would conventionally be required to simulate the system behavior during the time interval that is skipped.

Simulation with convergence-detection skip-ahead

A method and system for flow propagation analysis uses 'tracers' that are iteratively propagated through a simulated network between source and destination elements. These tracers are structured to contain traffic flow information from source to destination, and to reflect changes as the flow is affected by each element along the path from source to destination. The resultant flow information at the destination corresponds to the effective throughput from the source to the destination, and the flow information at the output of each intermediate element in the network corresponds to the potentially achievable throughput through that element for the given source-to-destination flow.

Flow propagation analysis using iterative signaling

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Rockville, MD, United States of America

Stefan Znam