Topological Evaluation of Realistic Mobility Models for Spontaneous Wireless Networks Using Graph Theory Metrics

In recent years, the exponential growth of mobile devices connected to access networks has led to the emergence of connection architectures characterized by a high density of end devices. This, in turn, has posed significant challenges in access management. As a result, the scientific community is increasingly recognizing the crucial need to develop equitable and unbiased access control mechanisms. A fundamental starting point is to conduct a comprehensive analysis of these massive end-device architectures, treating them as high-density graphs of interconnected nodes. In this work, we generated massive topologies/architectures using synthetic models of human mobility that accurately reflect real-world human behavior. Subsequently, we evaluated and compared these topologies using six key metrics derived from graph theory. Additionally, we established connections between nodes within each topology based on the concept of spontaneous Wireless Mesh Networks. The outcomes of our analysis shed light on mobility models that demonstrated superior performance in specific metrics, while also proposing a methodology to effectively characterize these mobility models.