Graph-based methods have become essential for analyzing many different types of networks, including wireless, optical, and social networks. In the last decade, these mathematical methods have been expanded and developed considerably. In the wireless realm, for example, stochastic geometry and the theory of random geometric graphs have emerged as essential tools in the analysis and design of cellular, ad hoc, and sensor networks. These techniques have led to important results and insights such as the connectivity, capacity, and vulnerability of wireless networks, and the coverage of sensor networks. Specifically, point process theory, percolation theory, and probabilistic combinatorics were instrumental in recent breakthroughs. Other types of networks have similarly benefited from graphical modeling and probabilistic analysis.
The aim of this workshop is to bring together researchers with interest in tackling fundamental problems in large-scale networks using percolation theory, geometric probability, and the theory of random graphs - in conjunction with established techniques such as information theory and queuing theory. In particular, the workshop will focus on network connectivity, resilience, trust, epidemics, and geometric approaches to security.
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