Distributed path restoration based on optical cross-connects can provide highly capacity-efficient real-time restoration for WDM-based optical networking. However, to obtain an assured restoration level with the theoretically very low amounts of spare capacity that path restoration allows, one must solve, or closely approximate a solution to, the integer multicommodity maximum flow (MCMF) problem, MCMF is, however a hard combinatorial optimization problem due to what is called the "mutual capacity" aspects of the problem: which of many competing origin-destination pairs should be allowed paths over the finite spares on each span? Integer MCMF is further complicated by the nonunimodular nature of the problem, i.e., fractional flows are forbidden but would arise if solved by linear programming. This paper presents a heuristic principle that tests well against integer programming solutions of MCMF routing. The heuristic is first characterized in a centralized program, then adapted for use in a distributed path restoration protocol. In all test cases, the protocol obtains over 97% of the paths found in an optimal MCMF solution in the same network. Via OPNET simulation it is also predicted that the protocol will run in well under 2 seconds which means it could be used directly in real-time, or in distributed prefailure self-planning, for restoration. The significance is that network operators could aggressively optimize their spare capacity, toward theoretical minimums, while still assuring 100% restorability.

The total transmission capacity required by a transport network to satisfy demand and protect it from failures contributes significantly to its cost, especially in long-haul networks. Previously, the spare capacity of a network with a given set of working span sizes has been optimized to facilitate span restoration. Path restorable networks can, however, be even more efficient by defining the restoration problem from an end to end rerouting viewpoint. We provide a method for capacity optimization of path restorable networks which is applicable to both synchronous transfer mode (STM) and asynchronous transfer mode (ATM) virtual path (VP)-based restoration. Lower bounds on spare capacity requirements in span and path restorable networks are first compared, followed by an integer program formulation based on flow constraints which solves the spare and/or working capacity placement problem in either span or path restorable networks. The benefits of path and span restoration, and of jointly optimizing working path routing and spare capacity placement, are then analyzed.