Abstract

The new generation of packet-switching networks is expected to support a wide range of communication-intensive real-time multimedia applications. A key issue in the area is how to devise reasonable packet-switching network design methodologies that allow the choice of the most adequate set of network resources for the delivery of a given mix of services with the desired level of end-to-end Quality of Service (e2e QoS) and, at the same time, consider the traffic dynamics of today’s packet-switching networks. In this paper, we focus on problems that arise when dealing with this subject, namely Buffer Assignment (BA), Capacity Assignment (CA), Flow and Capacity Assignment (FCA), Topology, Flow and Capacity Assignment (TCFA) problems. Our proposed approach maps the end-user’s performance constraints into transport-layer performance constraints first, and then into network-layer performance constraints. This mapping is then considered together with a refined TCP/IP traffic modeling technique, that is both simple and capable of producing accurate performance estimates, for general-topology packet-switching design networks subject to realistic traffic patterns. Subproblems are derived from a general design problem and a collection of heuristic algorithms are introduced for compute approximate solutions. We illustrate examples of network planning/dimensioning considering Virtual Private Networks (VPNs).

Keywords: Packet-switching networks design and planning; TCP/IP; Queueing theory; Mathematical programming/optimization; Heuristic methods

Article Outline

1. Introduction

2. QoS translation and models

2.1. QoS translators

2.1.1. Application-layer QoS translator

2.1.2. Transport-layer QoS translators

2.2. Traffic and queueing models

2.3. Virtual private networks

3. Problem statement

3.1. The Capacity Assignment problem

3.1.1. Suboptimal solution to the CA problem

3.2. The Buffer Assignment problem

3.2.1. Numerical examples and simulations

3.3. The capacity and flow assignment problem

3.4. The Greedy Weight Flow Deviation method

3.4.1. Numerical examples

3.5. The Topology, Capacity and Flow Assignment problem

3.5.1. Numerical examples and simulations

4. Conclusion

Acknowledgements

Appendix A. Applying meta heuristic algorithms to network design

A.1. Genetic algorithms

A.2. Tabu search algorithm

References

Vitae