Resource allocation and performance analysis problems in optical networks

Author: Esa Hyytiä Name of the dissertation Resource Allocation and Performance Analysis Problems in Optical Networks Date of manuscript 10th of November Date of the dissertation 10th December 2004 Monograph × Article dissertation (summary + original articles) Abstract Optical networks pose a rich variety of new design and performance analysis problems. Typically, the static design problems belong to the field of combinatorial optimisation, whereas decision-making and performance analysis problems are best treated using appropriate stochastic models. This dissertation focuses on certain issues in resource allocation and performance evaluation of backbone wavelength-routed (WR) networks and metropolitan area optical burst switching (OBS) networks. The first two parts of the thesis consider heuristic algorithms for the static routing and wavelength assignment (RWA) and logical topology design (LTD) problems that arise in the context of WR networks. In a static RWA problem, one is asked to establish a given set of lightpaths (or light trees) in an optical WR network with given constraints, where the objective often is to minimise the number of wavelength channels required. In LTD problem, the number of wavelength channels is given and one is asked to decide on the set of lightpaths so that, for instance, the mean sojourn time of packets travelling at the logical layer is minimised. In the thesis, several heuristic algorithms for both the RWA and LTD problems are described and numerical results are presented. The third part of the thesis studies the dynamic control problem where connection requests, i.e. lightpath requests, arrive according to a certain traffic pattern and the task is to establish one lightpath at a time in the WR optical network so that the expected revenue is maximised or the expected cost is minimised. Typically, the goal of optimisation is to minimise some infinite time horizon cost function, such as the blocking probability. In this thesis, the dynamic RWA problem is studied in the framework of Markov decision processes (MDP). An algorithmic approach is proposed by which any given heuristic algorithm can be improved by applying the so-called first policy iteration (FPI) step of the MDP theory. Relative costs of states needed in FPI are estimated by on-the-fly simulations. The computational burden of the approach is alleviated by introducing the importance sampling (IS) technique with FPI, for which an adaptive algorithm is proposed for adjusting the optimal IS parameters at the same time as data are collected for the decision-making analysis. …

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