The multi-source model for dimensioning data networks

Abstract

Traffic modeling is key to the dimensioning of data networks. Usual models rely on the implicit assumption that each user generates data flows in series, one after the other, the ongoing flows sharing equitably the considered network link. We relax this assumption and consider the more realistic case where users may generate several data flows in parallel, these flows having to share the user's access line as well. We qualify this model as multi-source since each user now behaves as an independent traffic source. Usual performance metrics like mean throughput and congestion rate must now be defined at user level rather than at flow level. We derive explicit expressions for these performance metrics under the assumption that flows share bandwidth according to balanced fairness. These results are compared with those obtained by simulation when max-min fairness is imposed, either at flow level or at user level.

New fluid approaches for studying the performance of elastic traffic under class based weighed fair queuing system

“…The complex underlying packet‐level mechanisms (congestion control algorithms, packet scheduling, buffer management, etc), at short timescales, are then simply represented by a long‐term bandwidth‐sharing policy between ongoing flows . The flow‐level models of data networks can be considered as the analogs for the Erlang model of telephone networks and its extensions to multirate circuit‐switched networks, which have proved its effectiveness for both dimensioning and traffic engineering …”

Poly-symmetry in processor-sharing systems

“…, r K in bit/s. This corresponds to the model introduced in [1] to predict some performance metrics in Internet service provider access networks, where the individual access lines represent subscriber lines which are connected to the aggregation link by the digital subscriber line access multiplexer (DSLAM). 6 gives a toy example with K = 2 possible access rates r 1 and r 2 .…”