Cost effective survivable virtual optical network mapping in flexible bandwidth optical networks
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This paper presents a cost-effective solution for survivable virtual optical network mapping in flexible bandwidth optical networks. It introduces an integer linear program model and two mapping approaches, lbsd and lcsd, which significantly reduce network costs while ensuring minimum spectrum usage and regeneration. The results indicate that these methods approach the optimal solutions and outperform a baseline approach in both 6-node and 14-node network simulations.
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Cost effective survivable virtual optical network mapping in flexible bandwidth optical networks
- 1. Cost-Effective Survivable Virtual Optical Network Mapping in Flexible Bandwidth Optical Networks Abstract: This paper addresses the minimum network cost problem for survivable virtual optical network mapping in flexible bandwidth optical networks. For each virtual link, we provide dedicated-path protection, i.e., primary path and backup path, to guarantee high survivability on the physical network. To simplify the virtual links mapping, an extended auxiliary graph is constructed by coordinating the virtual optical network and the physical network. We develop an integer linear program (ILP) model, the LBSD (the largest bandwidth requirement (LB) of virtual links versus the shortest distance (SD)) mapping approach, the LCSD (the largest computing (LC) resources requirement versus the shortest distance) mapping approach to minimize the network cost for a given set of VONs. For comparison, we also introduce one baseline mapping approach, named LCLC (the largest computing resources requirement versus the largest computing resources (LC) provisioning), and the lower bound. Simulation results show that, comparing to the LCLC mapping approach, the ILP model, the LBSD and LCSD mapping approaches not only solve the problem of minimizing the total network cost but also guarantee that the spectrum usage and the number of regenerators are minimum. The ILP model and the LBSD mapping approach are greatly close to a lower bound of network cost and perform the same results as a lower bound of spectrum usage in both the 6-node network and the 14-node network. As a result, our proposed LBSD mapping approach can efficiently reduce the network
- 2. cost, spectrum usage, and the number of regenerators, which is near the optimal solutions of the ILP model.