On scheduling all-to-all personalized connections and cost-effective designs in WDM rings
IEEE/ACM Transactions on Networking (TON)
Worst-case analysis of dynamic wavelength allocation in optical networks
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
Cost-effective traffic grooming in WDM rings
IEEE/ACM Transactions on Networking (TON)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A novel generic graph model for traffic grooming in heterogeneous WDM mesh networks
IEEE/ACM Transactions on Networking (TON)
A genre perspective on online newspaper front page design
Journal of Web Engineering
Traffic grooming in WDM networks
IEEE Communications Magazine
On optimal traffic grooming in WDM rings
IEEE Journal on Selected Areas in Communications
Traffic grooming in an optical WDM mesh network
IEEE Journal on Selected Areas in Communications
Dynamic traffic grooming algorithms for reconfigurable SONET over WDM networks
IEEE Journal on Selected Areas in Communications
Traffic grooming for survivable WDM networks - shared protection
IEEE Journal on Selected Areas in Communications
Traffic grooming in mesh WDM optical networks - performance analysis
IEEE Journal on Selected Areas in Communications
A Link Bundled Auxiliary Graph Model for Constrained Dynamic Traffic Grooming in WDM Mesh Networks
IEEE Journal on Selected Areas in Communications
Traffic grooming in WDM networks: past and future
IEEE Network: The Magazine of Global Internetworking
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In WDM networks, traffic grooming is a fundamental and important operation for aggregating multiple low-rate channels from the end users into a high-rate wavelength channel. In the literature, several traffic grooming problems were formulated where the common objective is to minimize the number of add-drop multiplexers required, and each of these problems was solved by specific algorithms. In this paper, we propose a network flow approach for solving a class of static and dynamic traffic grooming problems. In this approach, we transform a traffic grooming problem onto the minimum edge-cost flow problem through proper graph transformation and assignment of edge weights, and then solve this resulting network flow problem by an efficient heuristic algorithm. The network flow approach has two main advantages: (1) It is generally applicable to many static and dynamic traffic grooming problems. It can solve some existing traffic grooming problems as well as new problems that cannot be solved by the existing algorithms. (2) It performs at least as good as the best existing algorithm for static traffic grooming and significantly outperforms the existing algorithms for dynamic traffic grooming.