Even for experts, networks are complicated to troubleshoot, manage, and plan. Adopting human-centered design methods has the potential to facilitate the creation of more manageable networks. In this paper, we investigate a quantitative method that involves defining and measuring the complexity of operating different types of architectures from the perspective of the space of network parameters that need to be monitored and configured. We present OPLEX, a novel framework based on the analysis of YANG data models of network implementations that enables operators to compare architecture options based on the dimension of the parameter space. The benefits of the proposed framework are illustrated in the use case of Internet Exchange Point (IXP) network architectures, for which we take advantage of the rich set of publicly available data. We also exploit the survey results and direct consultations we conducted with operators and vendors of IXPs on their perception of complexity when operating different architectures. OPLEX is flexible, builds upon data models with widespread usage in the community, and provides a practical solution geared towards operators for characterizing the complexity of network architecture options.
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