Fast algorithms for computing parsimonious estimates of QoS measures

In recent publications concerning quality of service (QoS) measures in communication networks several attempts have been made to improve the techniques of computing or estimating the quality of data transfer. Many of the promising results are based on the knowledge of only very few parameters on the traffic situation, some of which are known a priory, others are measured. The paper deals with such parsimonious estimation techniques of QoS measures under the bufferless fluid flow multiplexing (bffm) framework, and concentrates on the efficient computation of them. The proposed fixed-point recursive algorithms are actively used to put the implicit formulae or ones containing optimization tasks into real-time environment.