Choosing a minimum-cost link topology for a network, given a set of nodes and given the node-to-node traffic that must be routed, is a difficult combinatorial problem. In the network design literature, many different approaches, based on a variety of assumptions, have been proposed for this type of problem. The unique features of Internet Protocol (IP) networks make the link topology design problem especially challenging. In this paper, we discuss some of these features and explain why assumptions commonly found in the link topology design literature often fail to capture the behavior of IP traffic. We discuss possible heuristic approaches to link topology selection that take the particular features of IP into account.
It is common, either for a telecommunications service provider or for a corporate enterprise, to have multiple data networks. For example, both an IP network and an ATM or Frame Relay network could be in operation to serve different applications. This can result in parallel transport links between the same two locations, each carrying data traffic under a different protocol. In this paper, we consider some practical engineering rules, for particular situations, to evaluate whether or not it is advantageous to combine these parallel traffic streams onto a single transport link. Combining the streams requires additional overhead (a so-called "cell tax" ) but, in at least some situations, can result in more efficient use of modular transport capacity. Simple graphs can be used to summarize the analysis. Some interesting, and perhaps unexpected, observations can be made.
A design methodology for an optical mesh network has recently been developed. For a given backbone packet network, we assume that a traffic matrix and an underlying optical fiber network are given. It is necessary to establish logical links between backbone nodes using optical wavelengths over the fiber network. The methodology chooses and sizes logical backbone links, chooses the physical paths for these logical links, and determines traffic routings over logical links under both normal and failure conditions. The methodology utilizes a linear programming engine embedded within a heuristic framework. This work presumes an optical networking environment utilizing dense wavelength division multiplexing (DWDM) and intelligent optical switch (lOS) equipment. It can be used to study potential future networks with high levels of traffic, e.g., in which demand entering the network at any given instant may be measured in terabits per second. In this paper, we describe the optical mesh network design problem that is addressed, outline the solution methodology and discuss some computational experience.
We propose solution techniques for the problem of determining how many access rings are required, which locations should be served by each ring, and to which hub each access ring should be connected. We take into account the cost per mile of the optical fiber used to form the Wavelength Division Multiplexing (WDM) rings, the cost associated with exchanging traffic, the capacity of the WDM rings, the set of demands for wavelengths and the distances between locations. These techniques are based on `joining' algorithms used in statistical clustering. Initially, each location is assumed to be served by its own WDM ring. Using a particular metric to determine candidate pairs of rings, an iterative procedure is used to combine locations served by two rings onto a single ring. We compare different metrics in order to evaluate their performance on a study network based on data from a major U.S. city.
Developments in synchronous (SDH/SONET) transmission products has led to increased use of ring structures in telecommunication networks, on account of their `self- heating' properties. Often, a set of nodes is interconnected by a `family' of such rings, which all follows the same fiber route. In this situation, each node is served by a subset of the rings in the family. For a given set of nodes and a given matrix of point-to-point traffic, we describe a design methodology that determines which rings should serve each node, and how traffic should be routed on the rings. The objective is to minimize the amount of equipment required. Whereas earlier work has addressed this problem for the case of uni-directional rings, the methodology described here can be applied to bi-directional rings as well.
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