Segment Routing with Digital Annealing
Sebastian Engel, Christian Munch, Fritz Schinkel, Oliver Holschke, Marc Geitz, Timmy Schüller · NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium · 2022
The growing demand in broadband and data networks is a tremendous driver for innovation and investment. Efficient usage of resources and reliable operations are key objectives for network management. Optimization plays a pivotal role to make the best decisions in limited time. To tackle such difficult and elaborate (typically NP-hard) computational problems the latest developments in Quantum Computing are coming into focus. Successes with models for road traffic, logistics or financial industry have already demonstrated the applicability of these new methods to real-world problems. In this paper we formulate a model for resource assignment for transporting data over networks. For applicability in existing network management environments the model was designed on top of Segment Routing (SR) concepts. The validity of the model is proven for different cost and reliability targets. Based on a Digital Annealer (DA) as quantum-inspired hardware and an appropriate decomposition approach realistic data sets of a tier-1 provider can be processed. The quality of the results is comparable to classical optimization methods while the new approaches outperform those in computation time and have potential for a higher number of demands. An end-to-end comparison of quadratic model creation and solving on large data sets versus a processing as linear integer problem is presented. This shows that quantum approaches and algorithms are not only a preparation for a more distant future of fully functional quantum computers but can generate business advantages even today.