Virtual Topology Design and Reconfiguration of Virtual Private Networks (VPNs) over All-Optical WDM Networks

Abstract

This paper studies the virtual topology design and reconfiguration problem of virtual private networks (VPNs) over all-optical WDM networks. To support VPN service, a set of lightpaths must be established over the underlying WDM network to meet the VPN traffic demands and this set of lightpaths must also be dynamically reconfigurable in response to changing VPN traffic. To achieve good network performance and meet the service requirements of optical virtual private networks (oVPNs), we formulate the problem as an integer programming problem with multi-objectives and present a general formulation of the problem. In the formulation, we take into account the average propagation delay over a lightpath, the maximum link load, and the reconfiguration cost with objectives to minimize the three metrics simultaneously. The formulated problem is NP-hard and is therefore not practical to have exact solutions. For this reason, we use heuristics to obtain approximate optimal solutions and propose a balanced alternate routing algorithm (BARA) based on a genetic algorithm. To make the problem computationally tractable, we approximately divide BARA into two independent stages: route computing and path routing. At the route computing stage, a set of alternate routes is computed for each pair of source and destination nodes in the physical topology. At the path routing stage, an optimal route is decided from a set of alternative routes for each of the lightpaths between a pair of source and destination nodes. A decision is subject to the constraints and objectives in the formulation. To improve the computational efficiency, we use a genetic algorithm in BARA. Through simulation experiments, we show the effectiveness of BARA and the evolution process of the best solution in a population of solutions produced by the genetic algorithm. We also investigate the impact of the number of alternative routes between each pair of source and destination nodes on the optimized solutions.