The rapid advancement of Quantum Network architectures necessitates a comprehensive and quantitative comparison to assess their effectiveness and performance. Unfortunately, there does not exist an implemented quantum network benchmark suite capable of determining the superior architecture. Hence, our study aims to establish the foundation for developing a benchmark suite by leveraging existing quantum network applications. However, the specific inclusion of quantum network applications in the suite remains to be determined. Therefore, to address this gap, our study will explore the potential inclusion of the Clauser-Horne-Shimony-Holt (CHSH) game based on its effectiveness in identifying errors within various properties of the quantum networking system. We use an exploratory research methodology involving experiments performed on simulated quantum networks utilizing SquidASM. Each experiment simulates multiple quantum networks, with a single property as the independent variable. For each value of the independent variable, we calculate both the success probability of the game and the number of successes per second. Subsequently, we employ the one-way ANOVA test to examine if there are significant variations in these performance metrics. Our results demonstrate that the CHSH game exhibits sensitivity to all properties affecting the quality of entanglement between nodes, execution time, and the error probability of both single-qubit gates and measure operations. Additionally, we compare the success probabilities based on different input combinations using the Root Mean Squared metric to uncover any underlying patterns within the data. As a result, we discovered a procedure for quantifying the difference between the error probabilities of measurements of zero and one. Based on the outcomes of our study, we consider the CHSH game to be a suitable addition to the benchmark suite if the testing requirements of the suite align with the qualities offered by the application. We anticipate that these results will aid the development of the benchmark suite and advance the understanding of quantum network architectures and their evaluation

In the development of any new technology, it is essential to have methods to assess the quality of a system, to compare different systems to one another, and to compare different versions of the same system, to see if changes to the system can actually be classified as improvements. For quantum networks, this is no different. To further develop quantum networks, we need a benchmarking suite to judge the quality of such systems.

The aim of this research is to determine the effectiveness of blind quantum computation - a quantum network algorithm - as a benchmark. We determine what changes to the system affect the results of executing this application, and we use this to determine whether it would be effective to use this application as part of a larger benchmarking suite. We do this by simulating a quantum network, and manually varying system parameters one by one, to see if they have an effect on the results.

What we observed from these experiments is that blind quantum computation is sensitive to almost all system parameters. This means that introducing an imperfection into almost any system parameter will negatively affect the results of the application. This means the application is useful as a full-system benchmark, because it is affected by almost the entire system. However, it also means that the application is less useful as a benchmark for individual parameters.

This means that to make the most useful benchmarking suite, blind quantum computation would have to be combined with other quantum network applications that are more suitable for benchmarking individual system parameters.