At+t Corp.

Mei Deng

David James Houck, Jr

David Frederick Lynch

James Anthony Schmitt

Peter M Dollard

Luiz Antonio Vitoria

Ken Ambs

Z Ming Ma

Sebastian Cwilich

Dicky Chi Kwong Yan

A network that is architectured to distributively be responsible for remedying failures achieves advantageous operation. This is accomplished by algorithmically and distributively assigning the responsibility for recovery from all failures to different network nodes and by re-routing traffic at the failed point though network elements in close topological proximity to the failed point. Each node maintains an awareness of the spare resources in its neighborhood and pre-plans re-route plans for each of the failures for which it is responsible. It maintains the created re-route plans and, upon detection of a failure, transmits a re-route plan to particular nodes that participate in the re-routing recovery planned for such a failure. Alternatively, it transmits re-route plans to the nodes that need them, and upon detection of a failure, the network node broadcasts an ID of the re-route plan that needs to be executed. Nodes that receive a plan ID that corresponds to a plan that they possess execute the relevant plan. Whenever the spare resources change in a manner that suggests that a re-route plan needs to be revisited, the network node initiates a new re-route preplanning process.

Local information-based restoration arrangement

A method and system are provided for computing an optimal restoration capacity and/or optimal restoration paths for a network to resolve a restoration scenario by solving a linear program (LP) model. The LP model includes decision variables corresponding to restoration capacity and restoration paths and constraints requiring restoration of traffic and conservation of capacity in the network. For example, the system determines a set of network paths that need to be restored in the network, preprocesses network data corresponding to the network to reduce LP processing workload and time; generates possible restoration paths and solves the LP model, preferably through column generation methods, to determine the optimal restoration capacity and/or the optimal restoration paths to resolve the restoration scenario; changes the LP solution into integer form, as necessary, and changes the LP solution in integer form to the original format of the network data or an equivalent thereof.

Optimizing restoration capacity

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Holmdel, NJ, United States of America

Mei Deng