All-optical wavelength-division-multiplexed (WDM) networks using wavelength routing are considered to be potential candidates for the next generation of wide-area backbone networks. The main problem in such networks is the Routing and Wavelength Assignment (RWA) problem, which has been proved NP-hard. Many algorithms are proposed in order to solve this problem efficiently. The main objective of the algorithms is to maximize the one-optical-hop traffic and balance the load on links as well as every intermediate nodes. However, most researchers assume that the traffic demand only contains unicast traffic....[ Read more ]

All-optical wavelength-division-multiplexed (WDM) networks using wavelength routing are considered to be potential candidates for the next generation of wide-area backbone networks. The main problem in such networks is the Routing and Wavelength Assignment (RWA) problem, which has been proved NP-hard. Many algorithms are proposed in order to solve this problem efficiently. The main objective of the algorithms is to maximize the one-optical-hop traffic and balance the load on links as well as every intermediate nodes. However, most researchers assume that the traffic demand only contains unicast traffic.

Currently, multicasting is becoming a more and more important requirement in high-speed networks. Therefore, the traffic demands in the wavelength-routing network must be considered as hybrid, consisting of both unicast and multicast traffic. Although with some simple modifications, the current algorithms can be extended to support such a hybrid traffic model, the performance is not so good. The main problem is that there are many duplicated data transmitted in the network. In this thesis, we propose several SMT based algorithms which can reduce the duplicated information using channel sharing technology. Finally, we compare the performance of these algorithms using simulation in a realistic network and some hybrid traffic models. The results illustrate that the SMT based algorithms can achieve remarkable performance under the hybrid traffic model.