Riverbed Technology, Inc.

Other

Mazu Networks, Inc.

Dimitri Stratton Vlachos

Christopher James White

Steven McCanne

Loris Degioanni

Massimiliano Antonio Poletto

David Paul Doyle

Robert Nader Nazzal

Network traffic information from multiple sources, at multiple time scales, and at multiple levels of detail are integrated so that users may more easily identify relevant network information. The network monitoring system stores and manipulates low-level and higher-level network traffic data separately to enable efficient data collection and storage. Packet traffic data is collected, stored, and analyzed at multiple locations. The network monitoring locations communicate summary and aggregate data to central modules, which combine this data to provide an end-to-end description of network traffic at coarser time scales. The network monitoring system enables users to zoom in on high-level, coarse time scale network performance data to one or more lower levels of network performance data at finer time scales. When high-level network performance data of interest is selected, corresponding low-level network performance data is retrieved from the appropriate distributed network monitoring locations to provide additional detailed information.

Distributed network traffic data collection and storage

An automated service discovery and monitoring utility employs automatically generated policies (rules) for monitoring network health of a service based on network discovery using flow data derived from transmissions sent over segments between computing components defining the service. An interactive discovery application employs flow data based on transmissions associated with a service. Analysis of the flow data identifies associated components from inspection of the transmissions. Iterative component selection allows network traversal of components based on flow data of the segments used for providing the service. The interactive service discovery therefore identifies associated components (servers) and segments based on flow data, rather than topology, rendering the flow data to allow a user to make an informed selection of segments and components for inclusion in a service, and generates a set of policies (rules) based on the discovered service dependencies for monitoring various metrics for the components providing the monitored service.

Service network discovery

An arrangement is disposed in a network. The arrangement includes a device that is logically disposed adjacent logically nearby routers having a first type of probe that are disposed to sample traffic, and that is has second type of probe that is disposed in-line during an attack by modifying router tables on the nearby routers.

Architecture to thwart denial of service attacks

A monitoring device disposed for thwarting denial of service attacks on the data center is described. The monitoring device includes a plurality of probe devices that are disposed to collect statistical information on packets that are sent between the network and the data center and a cluster head coupled to each of the plurality of probe devices, the cluster head receiving collected statistical information from the probe devices and determining from the collected information whether the data center is under a denial of service attack.

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Lexington, MA, United States of America

Dimitri Stratton Vlachos