Optimal capacity and buffer size estimation under generalized Markov Fluids models and QoS parameters

Abstract

Quality of service (QoS) for internet traffic management requires good traffic models and good estimation of sharing network resource. A link of a network processes all traffic and it is designed with certain capacity C and buffer size B. A Generalized Markov Fluid model (GMFM), introduced by Marrón (2012), is assumed for the sources because it describes in a versatile way the traffic, allows estimation based on traffic traces, and also consistent effective bandwidth (EB) estimation can be done. QoS, interpreted as buffer overflow probability, can be estimated for GMFM through the EB estimation and solving the optimization problem presented in Courcoubetis and Siris [ Perform. Eval. 48:5–23, 2002], the so-called inf-sup formulas. In this work, we implement a code to solve the inf-sup problem and other optimization related with it, that allow us to do traffic engineering in links of data networks to calculate both, minimum capacity required when QoS and buffer size are given or minimum buffer size required when QoS and capacity are given.