On the local resilience of random geometric graphs with respect to connectivity and long cycles
Alberto Espuny D\'iaz, Lyuben Lichev, Alexandra Wesolek

TL;DR
This paper investigates the local resilience of random geometric graphs in maintaining connectivity, long cycles, and Hamiltonicity when a fraction of neighbors are removed, revealing thresholds and limitations in these properties.
Contribution
It introduces the concept of local resilience in random geometric graphs for connectivity and cycle properties, providing thresholds and resilience bounds that differ from binomial random graphs.
Findings
Random geometric graphs are $(1/2- ext{small } ext{epsilon})$-resilient for $k$-connectivity above the connectivity threshold.
Connectivity is not $(1/2- ext{small } ext{epsilon})$-resilient in 2D for small epsilon.
Graphs are $(1/2- ext{epsilon})$-resilient for containing long cycles above the threshold.
Abstract
Given an increasing graph property , a graph is -resilient with respect to if, for every spanning subgraph where each vertex keeps more than a -proportion of its neighbours, has property . We study the above notion of local resilience with being a random geometric graph obtained by embedding vertices independently and uniformly at random in , and connecting two vertices by an edge if the distance between them is at most . First, we focus on connectivity. We show that, for every , for a constant factor above the sharp threshold for connectivity of , the random geometric graph is -resilient for the property of being -connected, with of the same order as the expected degree. However, contrary to binomial random…
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Taxonomy
TopicsInterconnection Networks and Systems · Mobile Ad Hoc Networks · Advanced Graph Theory Research
