FSO (Free Space Optics) is a well established wireless optical transmission technology considered as an alternative to radio communications, for example in metropolitan wireless mesh networks. An FSO link is established by means of a laser beam connecting the transmitter and the receiver placed in the line of sight. A major disadvantage of FSO links (with respect to fiber links) is their sensitivity to weather conditions such as fog, rain and snow, causing substantial loss of the transmission power over the optical channel due mostly to absorption and scattering. Thus, although the FSO technology allows for fast and low-cost deployment of broadband networks, its operation will be affected by this sensitivity, manifested by substantial losses in links' transmission capacity with respect to the nominal capacity. Therefore, a proper approach to FSO network dimensioning should take such losses into account so that the level of carried traffic is satisfactory under all observed weather conditions. In the paper we describe such an approach. We introduce a relevant dimensioning problem and present a robust optimization algorithm for such enhanced dimensioning. A substantial part of the paper is devoted to present a numerical study of two FSO network instances that illustrates the promising effectiveness of the proposed approach.
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Flow thinning (FT) is a traffic routing and protection strategy for communication networks whose links experience fluctuations in available capacity (as, e.g., in wireless networks). To cope with this phenomenon, end-to-end traffic demands are assigned dedicated tunnels (e.g., MPLS tunnels) whose nominal capacity is subject to thinning in order to account for variable capacity of the links, fluctuating below their nominal values. Consequently, the instantaneous traffic sent between the demand's end nodes must accommodate to the current total capacity available on its dedicated tunnels. In the paper we present a path generation-based approach to network dimensioning for a practical version of FT applying affine flow thinninga fairly complicated issue not yet considered. We derive a relevant pricing problem and present a numerical study illustrating efficiency of the optimization algorithm.
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