This paper focuses on the selection of bandwidth-guaranteed channels for communication sessions that require it. The basic idea comes from minimum interference routing: select a feasible path that puts the least possible restriction on the available transmission capacity of other communicating parties. This is achieved by circumventing some critical bottleneck links. The main contribution of the paper is a novel characterization of link criticality, the criticality threshold, which can be readily precompiled for routing dozens of subsequent calls. Based on this finding we define a generic precomputation framework for minimum interference routing, the least-critical-path-first routing algorithm. We show by means of extensive simulations that efficient route precomputation is possible even in the case, when accurate resource availability information is not immediately available.

Recently, a new working group - Next Steps In Signalling (NSIS) - was established within the IETF to develop a general signalling protocol primarily to support QoS resource reservation. Two main operation modes have been clarified: stateful and reduced state. The first mode relies on per flow-state information in all interior nodes while the other uses aggregated states. Stateful operation is based on the resource reservation protocol (RSVP), while reduced state operation will be similar to the resource management in a Diffserv (RMD) framework. With the use of aggregated states instead of per-flow granularity, one looses fine control over resources but derives a scalable and more efficient protocol. However, some problems need new handling mechanisms. In this paper, we discuss the problem of re-routing from the aspect of reduced state resource reservation. We show how quickly and easily RSVP handles such situations but reduced state solutions like RMD require new mechanisms for a quick reaction. We propose and analyse several solutions.

Dynamic traffic engineering requires the operation of load balanced routing. Load sharing, however, implies a thus far neglected, currently hidden problem: insufficient path integrity. Since load balancing requires changing the routes of traffic in order to achieve proper load distribution, path changes of ongoing communications go hand in hand with dynamic traffic engineering. Frequent path changes will not only degrade the performance of current TCP based applications but they will also dramatically influence the grade of service experienced by future QoS critical applications. To overcome this problem, we present a two level hashing based mechanism for route pinning under load balancing. We analytically formalise the path integrity and convergence time achievable for our routing model, and use these formulas for dimensioning path integrity aware load balancing.

This paper is concerned with the saturation probability of aggregate traffic data arrival rate on a communication link. This performance metric also referred to as the tail distribution of aggregate traffic is essential in traffic control and management algorithms of high speed networks including future QoS Internet. In this paper, efficient closed form upper bounds have been derived for the saturation probability when very little information is available on the aggregate traffic. The performance of these estimators is also investigated via numerical examples.

The paper is concerned with analyzing a time-division multiplexing method with two priority classes. A discrete-time model is established for analyzing the queuing behaviour of low priority traffic streams. The motivation came from dynamic transfer mode (DTM) networks which uses time-division multiplexing of channels, however the results might also be used for other fast circuit switched networks. The model to be investigated is based on the important observation that from the viewpoint of low priority traffic the system behaves as a queuing system subjected to periodic server interruption. The probability generating function (p.g.f.) of the system time and system content of low priority messages is expressed in closed forms from which the first two moments can be calculated in a straightforward manner. Tail probabilities of system content and system time are also derived by applying an efficient approximation technique. Finally, we also give numerical examples as simple illustrations.

This paper addresses the issue of how to solve convex programming problems by analog artificial neural networks (ANNs), with applications in asynchronous transfer mode (ATM) resource management. We first show that the essential and difficult optimization problem of dimensioning the system of virtual subnetworks in ATM networks can be modeled as a convex programming task. Here the transformation of the problem into a convex programming task is a nontrivial step. We also present and analyze an analog ANN architecture that is capable of solving such convex programming tasks with time-varying penalty multipliers. The latter property makes it possible to perform quick sensitivity analysis with respect to the constraints in order to identify the bottleneck capacities in the network or those which give the highest return if we invest in extending them.

A mathematical model is presented that provides a well-defined formulation of the logical configuration problem of ATM networks (the carriers of future B-ISDN) with the objective of maximizing the total expected network revenue, given the physical network parameters and the traffic requirements of each virtual subnetwork. A two-phase solution procedure is developed in which the decision variables are the logical link capacities that specify the logical decomposition into virtual subnetworks, and the load sharing parameters. The first phase of the solution finds a global optimum in a rougher model. The second phase uses this as an initial point for a gradient-based hill climbing that applies the partial derivatives of the network revenue function obtained in a more refined model.>

The amplitude specification can be formulated in a form of a phase specification for prototype or non-prototype lattice Wave Digital Filters (WDF). The approximation problem is solved by generating arbitrary phase polynomials via an interpolation algorithm and by applying the Remez-exchange algorithm. The approximation method results in filters with equiripple amplitude both in the pass band and stop band. The approximation in the pass band and stop band are carried out simultaneously. The iteration is simple, converging in a few steps. Design examples illustrate the efficiency of the proposed design method in the pass band, stop band and transition band.>