Nevil Brownlee, University of Auckland, New Zealand

Position Statement for
NSF Workshop on Internet Statistics Measurement and Analysis

Measurement of network traffic flows using the Internet Accounting Model, RFC 1272

Traffic flows between two 'end' points, 'source' and 'destination.' Each end point is specified as a set of attribute values. End-point attributes include adjacent, peer and transport addresses, peer and transport protocol type, etc. Every flow also has 'general' attributes such as byte and packet totals for each direction, time the flow's first and last packets were seen, etc. Traffic is measured by a meter. The set of flows of interest to a meter is specified by a 'rule set.' Flows are bi-directional, with the rule set specifying which end-point is the source. The rule set also specifies how flows are to be aggregated; this data reduction can significantly reduce the volume of data to be collected from a meter. Flow data is recovered from a meter by one or more 'collectors.' One or more collectors may retrieve data from a meter asynchronously, and the set of attribute values retrieved may be different for different collectors. A collector may collect data from any number of meters. Meters and collectors are co-ordinated by a manager. The manager is responsible for downloading rule sets to meters, and for configuring collectors.

NeTraMet: a Public-Domain implementation of the Accounting Model

NeTraMet has been available since October 1993, and is now in widespread use. It provides a combined manager/collector (NeMaC) which runs on Unix systems, and a meter (NeTraMet) which runs on Unix systems or DOS PCs. NeTraMet's hardware requirements are modest - a 40 MHz 386 with 640 KB of memory can cope with 3,000 Ethernet packets per second, and a Unix workstation can measure traffic on an FDDI ring. Although most sites use fairly simple rule sets, some have reported using rule sets containing between 600 and 1700 rules. Most sites use Netramet to collect traffic data for management purposes such as planing and cost recovery, but it has also proved useful for other purposes such as:

Challenges for Traffic Measurement

Update, 11 march 96

Since we've started weekly time-series and distributions plots, we've noticed that the Auckland data is a lot `spikier' than that from most other sites. We think this is because we have our access rate and CIRs a lot higher than our average load, so we don't see any limiting imposed by the Frame Relay PVC management. The other universities tend to run their PVCs closer to their CIRs. Over the last month or two Canterbury has increased its CIR significantly, and we believe that their time-series plots have got spikier. We're looking into this further - stay tuned!