On impact of non-conformant flows on a network of DropTail gateways

In this paper we evaluate rate distributions between competing flows in a network of DropTail queues. Specifically we look at the case when some of the flows are non-conformant or mis-behaving and it's effect on conformant flows. Our results show in a network of DropTail queues mis-behaving flows can have significantly higher bandwidth allocations at the cost of conformant flows. Further this unequal sharing worsens in a multi-bottleneck scenario where conformant flows may consistently time-out. However the distribution of rates improves if RED is used at the bottleneck thus suggesting deployment of RED. In this paper we also look at the fairness from the network's perspective rather then end-user's. As such we propose an analytical model for managing non-conformant or mis-behaving flows by manipulating congestion penalties conveyed to them. We show that this penalty transformation can map a user's utility function, U-s, to any objective utility function, U-obi. These penalty transformation modules can be completely implemented at the edge and can also work with DropTail queues. We have analyzed the framework and evaluated it for both single and multi bottleneck scenarios.