Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Blocking analysis of dynamic traffic grooming in mesh WDM optical networks
IEEE/ACM Transactions on Networking (TON)
Traffic grooming in WDM networks
IEEE Communications Magazine
Traffic grooming in an optical WDM mesh network
IEEE Journal on Selected Areas in Communications
Design and provisioning of WDM networks with multicast traffic grooming
IEEE Journal on Selected Areas in Communications - Part Supplement
Traffic grooming in path, star, and tree networks: complexity, bounds, and algorithms
IEEE Journal on Selected Areas in Communications - Part Supplement
A tutorial on decomposition methods for network utility maximization
IEEE Journal on Selected Areas in Communications
Survivable MPLS Over Optical Transport Networks: Cost and Resource Usage Analysis
IEEE Journal on Selected Areas in Communications
Spare Capacity Allocation in Two-Layer Networks
IEEE Journal on Selected Areas in Communications
Traffic grooming in WDM networks: past and future
IEEE Network: The Magazine of Global Internetworking
Computers and Operations Research
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Presently, backbone data networks are converging toward a typical two-layer architecture of an IP/MPLS layer over an optical layer. In this paper, we study the problem of maximizing a utility function for an Internet service provider (ISP) of a two-layer mesh networks and propose an efficient decomposition method based on Lagrange relaxation. Differing from previous works on two-layer mesh networks, our proposed decomposition method decomposes an original two-layer mathematic optimization problem, respectively, into an IP/MPLS-layer and an optical-layer optimization problem by slacking the constraints between the two layers. This decomposition method enables to control the trade-off between running time and quality of the feasible solution. Numerical results for a variety of networks indicate that our proposed decomposition method is attractive to quickly find near optimal solutions.