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Explicit allocation of best-effort packet delivery service
IEEE/ACM Transactions on Networking (TON)
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IEEE/ACM Transactions on Networking (TON)
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MRTG: The Multi Router Traffic Grapher
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FlowScan: A Network Traffic Flow Reporting and Visualization Tool
LISA '00 Proceedings of the 14th USENIX conference on System administration
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ATEC '00 Proceedings of the annual conference on USENIX Annual Technical Conference
A framework for alternate queueing: towards traffic management by PC-UNIX based routers
ATEC '98 Proceedings of the annual conference on USENIX Annual Technical Conference
A parameterizable methodology for Internet traffic flow profiling
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In Search of Torrents: Automatic Detection of Logical Sets Flows in Network Traffic
DNIS '02 Proceedings of the Second International Workshop on Databases in Networked Information Systems
ProgME: towards programmable network measurement
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A programmable architecture for scalable and real-time network traffic measurements
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PeekKernelFlows: peeking into IP flows
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ProgME: towards programmable network measurement
IEEE/ACM Transactions on Networking (TON)
Digging into ip flow records with a visual kernel method
CISIS'11 Proceedings of the 4th international conference on Computational intelligence in security for information systems
Detecting anomalies in netflow record time series by using a kernel function
AIMS'12 Proceedings of the 6th IFIP WG 6.6 international autonomous infrastructure, management, and security conference on Dependable Networks and Services
Efficient multidimensional aggregation for large scale monitoring
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Journal of Network and Computer Applications
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Aguri is an aggregation-based traffic profiler targeted for near real-time, long-term, and wide-area traffic monitoring. Aguri adapts itself to spatial traffic distribution by aggregating small volume flows into aggregates, and achieves temporal aggregation by creating a summary of summaries applying the same algorithm to its outputs. A set of scripts are used for archiving and visualizing summaries in different time scales. Aguri does not need a predefined rule set and is capable of detecting an unexpected increase of unknown protocols or DoS attacks, which considerably simplifies the task of network monitoring.Once aggregates are identified and profiled, it becomes possible to make use of the profile records to control the aggregates in best-effort traffic. As a possible solution, we propose a technique to preferentially drop packets from aggregates whose volume is more than the fairshare. Our prototype implementation demonstrates its ability to protect the network from DoS attacks and to provide rough fairness among aggregates.