Monitoring network traffic more efficiently

In today’s data networks, traffic analysis — determining which links are getting congested and why — is usually done by computers at the network’s edge, which try to infer the state of the network from the times at which different data packets reach their destinations.
If the routers inside the network could instead report on their own circumstances, network analysis would be much more precise and efficient, enabling network operators to more rapidly address problems. To that end, router manufacturers have begun equipping their routers with counters that can report on the number of data packets a router has processed in a given time interval.
But raw number counts are only so useful, and giving routers a special-purpose monitoring circuit for every new measurement an operator might want to make isn’t practical. The alternative is for routers to ship data packets to outside servers for more complex analysis, but that technique doesn’t scale well. A data center with 100,000 servers, for instance, might need another 40,000 to 50,000 servers just to keep up with the flood of router data.
Researchers at MIT, Cisco Systems, and Barefoot Networks have come up with a new approach to network monitoring that provides great flexibility in data collection while keeping both the circuit complexity of the router and the number of external analytic servers low. They describe the work in a paper they’re presenting this week at the annual conference of the Association for Computing Machinery’s Special Interest Group on Data Communication.
Dubbed Marple, the system consists of a programming language that enables network operators to specify a wide range of network-monitoring tasks and a small set of simple circuit elements that can execute any task specified in the language. Simulations using actual data center traffic statistics suggest that, in the data center setting, Marple should require only one traffic analysis server for every 40 or 50 application servers.”

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