We address the problem of generating physical realistic optical transport network topologies. This type of network has characteristics that differ from scale-free networks, such as the Internet. Based on the analysis of a set of real transport topologies, we identify and assess relevant characteristics. A method to generate realistic topologies is proposed. The proposed method is validated by comparing the characteristics of computer-generated and real-world optical transport networks.

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Due to the increase of bandwidth supported by optical transport networks, it becomes important to identify how reliable the actual real-world network topologies are, and the relationship of reliability with other key factors. Reliability is essential in this context, since the failure of elements such as fiber links and cross connects may cause the outage of several associated optical channels, leading to large data losses. Here we address reliability related to link failures. For a fixed number of nodes, the maximum network reliability could be obtained by maximizing the number of links, but it is prohibitive due to the technological and cost constraints. However, for a given number of nodes and links, there exist a number of topologies that may have different levels of reliability. How can we build the most reliable topologies satisfying these constraints? How reliable are the real-world topologies? In order to answer these questions, we explore a class of topologies that maximize reliability. Such topologies correspond to a subclass of Harary graphs. In this paper, we compare the reliability of the real-world topologies to the most reliable ones. Also, we compare both sets of topologies with respect to cost. Our results show that, in some cases, after maximizing reliability, the resulting topologies may also present lower capital expenditure.

We present a statistical model to estimate the CapEx in multi-layer optical networks. This model allows a fast calculation of the CapEx without complete information. The accuracy of the model was evaluated considering practical optical networks. For all the networks considered an error smaller than 10% was obtained, which shows that is possible to estimate the CapEx with good accuracy even without complete information.

The amount of spare capacity for restoration is usually calculated using network design tools. This task depends on the detailed information about the network topology and traffic model. In order to allow a preliminary evaluation of the networks, we propose an approximation to estimate the spare capacity required to a mesh network recover from any single link failure. The expression is based on statistical methods and does not requires knowledge of the network topology. We also provide experimental results evaluating the performance of the proposed approximation against a previous published one and a network design tool.

This paper compares two path selection strategies for optical burst switching networks: a) the path from source to destination is chosen randomly from the set of the k shortest paths; b) the path selection is based on a probabilistic model for the link demands. In the second strategy, the set of shortest paths from source to destination is ranked according to the probability of their overall link demands. The path selection schemes are evaluated for a specific scenario of grid over OBS networks. Our results show that, in general, the probabilistic model outperforms the random k shortest path routing scheme, this improvement is relevant for small job sizes.