Dr. Hsu-Chen Cheng Profile

Dr. Hsu-Chen Cheng

at Chinese Culture Univ.

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Proceedings Article | 8 February 2005 Paper

A multicast tree aggregation algorithm in wavelength-routed WDM networks

Hsu-Chen Cheng, Chin-Chun Kuo, Frank Lin

Proceedings Volume 5626, (2005) https://doi.org/10.1117/12.572576

KEYWORDS: Magnesium, Wavelength division multiplexing networks, Time division multiplexing, Optical networks, Transmitters, Receivers, Lawrencium, Wavelength division multiplexing, Switching, Mathematical modeling

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Wavelength division multiplexing (WDM) has been considered a promising transmission technology in optical communication networks. With the continuous advance in optical technology, WDM network will play an important role in wide area backbone networks. Optical wavelength switching, compared with optical packet switching, is a more mature and more cost-effective choice for optical switching technologies. Besides, the technology of time division multiplexing in optical communication networks has been working smoothly for a long time. In the proposed research, the problem of multicast groups aggregation and multicast routing and wavelength assignment in wavelength-routed WDM network is studied. The optical cross connect switches in the problem are assumed to have limited optical multicast/splitting and TDM functionalities. Given the physical network topology and capacity, the objective is to maximize the total revenue by means of utmost merging multicast groups into larger macro-groups. The groups in the same macro-group will share a multicast tree to conduct data transmission. The problem is formulated as an optimization problem, where the objective function is to maximize the total revenue subject to capacity constraints of components in the optical network, wavelength continuity constraints, and tree topology constraints. The decision variables in the formulations include the merging results between groups, multicast tree routing assignment and wavelength assignment. The basic approach to the algorithm development for this model is Lagrangean relaxation in conjunction with a number of optimization techniques. In computational experiments, the proposed algorithms are evaluated on different network topologies and perform efficiently and effectively according to the experiment results.

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