The Routing and Wavelength Assignment (RWA) problem has attracted lots of attention in the research field for the past decade. Most of the existing works are the classic static RWA problem, which assumes every time for the reconfiguration, all the existing connections will be reconfigured. In a real operating network, the reconfiguration has to take the existing connections into consideration and any reconfiguration of the existing connection results in the disruption of the upper level traffic. The algorithms that are slow or do not consider the existing connections in the network cannot be used in the real-time reconfigurable network. In this paper, we propose the semi-dynamic/static network optimization problem that takes into consideration existing connections from the previous reconfiguration session. The objective function in the formulation is penalty-based, i.e., there are penalties for the reconfiguration of a connection, for the rejection of a connection demand and for the most congested link. Rules on the existing capacity and new demand in the new session are proposed. We have successfully used the Lagrange Relaxation (LR) and Subgradient Method to successfully solve this network optimization problem. This state-of-art frame work allows us to evaluate systematically some sample networks in terms of various network performances and behaviors. At the same time, excellent algorithm performance and efficient computation complexity are demonstrated.
The Agile All-photonic Backbone Network (AAPN) architecture has been proposed by the telecommunication industry as a potential candidate for the ultra high speed Next Generation Optical Network (NGON) architecture. AAPN network structure is composed of adaptive optical core switches and edge routers in an overlaid star physical topology. The AAPN employs fast packet switching architecture for the network traffic, and the packet scheduling is the main part of the AAPN. The objective is to forward the packets to their destination with the lowest drop rate and delay, the bandwidth allocation can be either located at the core node or the edge switch. Two types of scheduling are considered in the AAPN architecture, namely the centralized and the distributed schemes. In the centralized scheme all decisions are made at the core node while in the distributed scheme, they are made at the edge nodes. In this paper, we want to compare both scheduling schemes. We would also like to propose a promising integrated TDM architecture that combines the good attributes of both centralized and distributed scheduling schemes. We shall characterize such architecture by various measures such as delay and loss probabilities.
The Agile All-photonic Backbone Network (AAPN) architecture has been proposed by the telecommunication industry as a potential candidate for the ultra high speed Next Generation Optical Network (NGON) architecture. AAPN network structure is composed of adaptive optical core switches and edge routers in an overlaid star physical topology. In this paper, we examine various optimization issues for AAPN architectures. The optimization procedure is based on a Lagrangean relaxation and subgradient method. Based on the optimization methodology provided in the previous research, we propose a modified algorithm to optimize AAPN networks, with respect to the assumptions used in AAPN. The results for different network configurations are studied and the influence of network resources is also studied. Our algorithm is shown to be very computational effective on the AAPN networks, and the bounds generated are mostly within 1% of the final objective value.