Optimal capacity and flow assignment for self-healing ATM networks based on line and end-to-end restoration

This paper addresses an optimal link capacity design problem for self-healing asynchronous transfer mode (ATM) networks based on two different restoration schemes: line restoration and end-to-end restoration. Given a projected traffic demand, capacity and flow assignment is jointly optimized to find an optimal capacity placement. The problem can be formulated as a large-scale linear programming. The basis matrix can be readily factorized into an LU form by taking advantage of its special structure, which results in a substantial reduction on the computation time of the revised simplex method. A row generation and deletion mechanism is developed to cope with the explosive number of constraints for the end-to-end restoration-based networks. In self-healing networks, end-to-end restoration schemes have been considered more advantageous than line restoration schemes because of a possible reduction of the redundant capacity to construct a fully restorable network. A comparative analysis is presented to clarify the benefit of end-to-end restoration schemes quantitatively in terms of the minimum resource installation cost. Several networks with diverse topological characteristics as well as multiple projected traffic demand patterns are employed in the experiments to see the effect of various network parameters. The results indicate that the network topology has a significant impact on the required resource installation cost for each restoration scheme. Contrary to a wide belief in the economic advantage of the end-to-end restoration scheme, this study reveals that the attainable gain could be marginal for a well-connected and/or unbalanced network