As technology for implementing quantum networks advances, the challenge of efficiently managing entanglement generation under resource constraints becomes critical. In this thesis, a systematic methodology for selecting scheduling strategies in a centralised quantum network is proposed, and applied to a specific case for a quantum hub network utilising an entanglement generation switch. Using the NetSquid simulator, the first in, first out, on-demand, MaxWeight, earliest deadline first, earliest feasible deadline first and round-robin scheduling algorithms are evaluated across a wide range of metrics compiled in this thesis.
These metrics include measures of throughput, fairness, responsiveness, demand completion, and resource utilisation, among others. Varying network load conditions are simulated and two application-level use cases, quantum key distribution and blind quantum computing, are considered. The results offer detailed insight into how each scheduler performs under different demand patterns and operational contexts.
Based on these results, the earliest deadline first performs better in most metrics than the other schedulers within the context of this thesis. Additionally, the results indicate that classical optimality of a scheduler does not always translate to superior performance in quantum network scenarios. The findings presented and the framework described here can provide practical guidance for network operators seeking to balance multiple performance goals in near-term quantum networks.