title: Software-definierte IP-Optische Netze: Planung, Rekonfiguration und techno-ökonomische Optimierung
Creators: name: Romero Reyes, Ronald
Publisher: name: Chemnitz University of Technology
publisherIdentifier: https://ror.org/00a208s56
publisherIdentifierScheme: ROR
Year: 2025

description: Software defined networking (SDN) enables the design of multilayer and multi-domain control functions for optimum service and network resource management. These functions require the design of algorithms that exploit the automation capabilities offered by cross-layer and cross-domain SDN control. This thesis investigates the design of these algorithms for networks that integrate packet-switched electrical systems with circuit-switched optical systems. In particular, algorithms are investigated for the planning and online reoptimization of IP-Optical networks. These algorithms consider the resource dependencies between the IP and optical layers in order to perform optimum routing, traffic restoration, network reconfiguration and capacity planning. The algorithms aim at designing networks that supply low-cost services while meeting their quality of service (QoS) requirements. Algorithms are investigated for use cases that include Metro/Core transport, intra-data centre networks and fixed broadband access. Concerning Metro/Core transport, the problem of resilient network design is investigated by applying adjustable robust optimization for the planning of networks that integrate Fast-Reroute with IP-Optical restoration. By this strategy, IP traffic is efficiently restored from optical failures. This is achieved by a linear program that optimizes the network capacity along with the routing and capacity of IP tunnels in failure-free mode and in a selected set of optical failures. Compared to existing traffic restoration approaches, the proposed method significantly reduces the network capacity while providing robustness against unforeseen failures. This problem is also studied from a meta-learning inspired perspective, where an algorithm selection (AS) function learns the relationship between the characteristics of the problem instance (i.e. the size and distribution of the traffic load and an observed optical failure) and the performance of candidate algorithms for traffic restoration. The function provides a hyperheuristic method that predicts the algorithm that requires less capacity to restore traffic for an observed instance. Heuristic methods that integrate IP-Optical restoration are formulated to test the performance of the approach. The results show that the AS function predicts with high accuracy the algorithm that performs best for an observed instance, thereby outperforming existing pure IP-based traffic restoration schemes. The problem of network reoptimization is investigated for transport networks that suffer from spectrum fragmentation in the optical layer. Linear programming is used to formulate algorithms that optimize two objectives, i.e. the spectrum defragmentation state and the strategy whereby optical connections migrate towards their optimized spectrum. The migration strategy minimizes service disruption periods experienced in the IP layer. The proposed algorithms significantly outperform existing defragmentation strategies in both optimization objectives. Regarding intra-data centre networks, a planning approach is proposed for the dimensioning of the network infrastructure and the calculation of the cost of ownership. Compared to networks based on packet-switching, the approach shows that hybrid networks that integrate IP-Optical switching perform well for large data centres. Hybrid networks require less infrastructure and save costs due to reduced energy consumption and repair effort in case of failures. A method for service-oriented optimization is also formulated for the minimization of the direct, shared and common costs incurred for the provisioning of services. Use cases for Metro/Core transport and fixed broadband access show that the method optimizes the economies of scale and scope that arises from the operation of multi-service networks.