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Right buffer sizing matters: Some dynamical and statistical studies on Compound TCP
Published in Elsevier B.V.
2020
Volume: 139
   
Abstract
Large and unmanaged router buffers could lead to an increase in queuing delays in the Internet, which is a serious concern for network performance and quality of service. Our focus is to conduct a performance evaluation of Compound TCP (C-TCP), in a regime where the router buffer sizes are small (i.e., independent of the bandwidth-delay product), and the queue policy is Drop-Tail. In particular, we provide buffer sizing recommendations for high speed core routers fed by well multiplexed TCP controlled flows. For this, we consider two topologies: a single bottleneck and a multi-bottleneck topology, under different traffic scenarios. The first topology consists of a single bottleneck router, and the second consists of two distinct sets of TCP flows, regulated by two edge routers, feeding into a common core router. We focus on some key dynamical and statistical properties of the underlying system. From a dynamical perspective, we first develop fluid models. A local stability analysis for these models yields a key insight: buffer sizes need to be dimensioned carefully, and smaller buffers favour stability. We also highlight that larger Drop-Tail buffers, in addition to increasing latency, are prone to inducing limit cycles in the system dynamics. These limit cycles in turn induce synchronisation among the TCP flows, which then results in a loss of link utilisation. We then empirically analyse some statistical properties of the bottleneck queues. These statistical analyses serve to validate an important modelling assumption: that in the regime considered, each bottleneck queue may be reasonably well approximated as either an M∕M∕1∕B or an M∕D∕1∕B queue. We also highlight that smaller buffers, in addition to ensuring stability and low latency, would also yield reasonable system-wide performance, in terms of throughput and flow completion times. © 2020 Elsevier B.V.
About the journal
JournalData powered by TypesetPerformance Evaluation
PublisherData powered by TypesetElsevier B.V.
ISSN01665316
Open AccessNo