A parameterizable methodology for Internet traffic flow profiling. - Claffy, K.C.
We present a parameterizable methodology for profiling Internet traffic flows at a variety of granularities. Our methodology differs from many previous studies that have concentrated on end-point definitions of flows in terms of state derived from observing the explicit opening and closing of TCP connections. Instead, our model defines flows based on traffic satisfying various temporal and spatial locality conditions, as observed at internal points of the network. This approach to flow characterization helps address some central problems in networking based on the Internet model. Among them are route caching, resource reservation at multiple service levels, usage based accounting, and the integration of IP traffic over an ATM fabric. We first define the parameter space and then concentrate on metrics characterizing both individual flows as well as the aggregate flow profile. We consider various granularities of the definition of a flow, such as by destination network, host-pair, or host and port quadruple. We include some measurements based on case studies we undertook, which yield significant insights into some aspects of Internet traffic, including demonstrating (i) the brevity of a significant fraction of IP flows at a variety of traffic aggregation granularities, (ii) that the number of host-pair IP flows is not significantly larger than the number of destination network flows, and (iii) that schemes for caching traffic information could significantly benefit from using application information
Keywords: ATM fabric; IP traffic; Internet model; Internet traffic flow profiling; TCP connections; Aggregate flow profile; Application information; Destination network; Destination network flows; End-point definitions; Host quadruple; Host-pair.; Measurements; Multiple service levels; Networking; Parameter space; Parameterizable methodology; Port quadruple; Resource reservation; Route caching; Traffic flow granularities; Usage based accounting