When a massive network disruption occurs, repair of the damaged network takes time, and the recovery process involves multiple stages. We previously proposed a multi-stage network recovery method for determining the pareto-optimal recovery order of failed physical components, reflecting the balance requirement between maximizing the total amount of traffic on all logical paths, called total network flow, and providing adequate logical path flows to meet traffic demand. The pareto-optimal problem is formulated by mixed integer linear programming (MILP). In this paper, we propose a heuristic algorithm, called grouped-stage recovery (GSR), to solve the problem which cannot be solved with our previous method in a large-scale failure within a practical time. We numerically evaluated the effectiveness of our method with GSR. The results show that our method with GSR is applicable to large-scale failures because a nearly optimal recovery with less than 10% difference rate can be determined within practical computation time.
['Kouichi Genda', 'Shohei Kamamura']
Multi-stage network recovery considering traffic demand after a large-scale failure