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The Exact Planning of the GMPLS-based Metro Core Network

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Abstract The continuing rapid increase in the number of wavelengths per fiber will dramatically increase the size of OXCs/ROADMs in the WDM-based metro core networks. This calls for the use of the multi-granular switching concept introduced in Generalized Multiprotocol Label Switching (GMPLS) to avoid the cost explosion of these optical switches. This paper addresses the optimal planning problem of the GMPLS-based (or multi-granular) metro core network by (i) considering the whole traffic flow hierarchy defined in GMPLS, and (ii) maintaining the color-continuity constraint for all optical flows. We call such a planning problem the Routing and Multi-Granular Paths Assignment (RMGPA). The objective of the problem is to minimize the total weighted port count in the metro core network. The problem is formulated as a Mixed Integer Linear Programming (MILP) model. Due to the computational complexity of the problem, the MILP model is solved for small-sized problems.
Walter de Gruyter GmbH
Title: The Exact Planning of the GMPLS-based Metro Core Network
Description:
Abstract The continuing rapid increase in the number of wavelengths per fiber will dramatically increase the size of OXCs/ROADMs in the WDM-based metro core networks.
This calls for the use of the multi-granular switching concept introduced in Generalized Multiprotocol Label Switching (GMPLS) to avoid the cost explosion of these optical switches.
This paper addresses the optimal planning problem of the GMPLS-based (or multi-granular) metro core network by (i) considering the whole traffic flow hierarchy defined in GMPLS, and (ii) maintaining the color-continuity constraint for all optical flows.
We call such a planning problem the Routing and Multi-Granular Paths Assignment (RMGPA).
The objective of the problem is to minimize the total weighted port count in the metro core network.
The problem is formulated as a Mixed Integer Linear Programming (MILP) model.
Due to the computational complexity of the problem, the MILP model is solved for small-sized problems.

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