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EN
An available bandwidth at a link is an unused capacity. Its measuring and/or estimation is not simple in practice. On the other hand, we know that its continuous knowledge is crucial for the operation of almost all networks. Therefore, there is a continuous effort in improving the existing and developing new methods of available bandwidth measurement and/or estimation. This paper deals with these problems. Network calculus terminology allows to express an available bandwidth in terms of a service curve. The service curve is a function representing a service available for a traffic flow which can be measured/estimated in a node as well as at an end-to-end connection of a network. An Internet traffic is highly unpredictable what hinders to a large extent an execution of the tasks mentioned above. This paper draws attention to pitfalls and difficulties with application of the existing network calculus methods of an available bandwidth estimation in a real Internet Service Provider (ISP) network. The results achieved in measurements have been also confirmed in simulations performed as well as by mathematical considerations presented here. They give a new perspective on the outcomes obtained by other authors and on their interpretations.
EN
The network calculus provides a theoretical background for description of traffic in computer networks. Using this tool in explanation of the so-called pathchirp method of measuring the available bandwidth, the validity and range of application of some relationships exploited are verified in this paper. The derivations are carried out in a wider context than that considered in a recent paper by Liebeherr et al. published in IEEE/ACM Transactions on Networking on network bandwidth estimation, providing thereby new insights and outcomes. These results, summarized in a table, show a means of bounding the service curve, depending upon its convexity or non-convexity property assumed and upon the linearity or non-linearity of a network considered. Moreover, it is shown here that the nonlinear network example analyzed by Liebeherr et al. can be viewed equivalently as a linear parametric network. For this network, the behaviour of the cross traffic is considered in a more detail, too.
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