Connectivity of random k-nearest-neighbour graphs

By Paul N. Balister, Béla Bollobás, Amites Sarkar, Mark Walters. Advances in Applied Probability, 2005

122 citations recorded by the source corpus.

Subfields: Computer Graphics and Computer-Aided Design, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/7dc969544f6e5c874266f76a596676764365491b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Graphics and Computer-Aided Design

1. Sertac Karaman
2. Jeffrey G. Andrews
3. Emilio Frazzoli

In Computer Networks and Communications

1. Jeffrey G. Andrews
2. Martin Haenggi
3. François Baccelli
4. Massimo Franceschetti
5. Olivier Dousse
6. Emilio Frazzoli
7. Sertac Karaman
8. Tony Q. S. Quek

In Electrical and Electronic Engineering

1. Jeffrey G. Andrews
2. Martin Haenggi
3. François Baccelli
4. Tony Q. S. Quek
5. Ekram Hossain
6. Hesham Elsawy
7. Sertac Karaman
8. Yuval Kluger

Citations in the corpus

• Sampling-based algorithms for optimal motion planning (2011, background): “The value of kc2 is not known; the current best estimate is 0.3043 ≤ kc2 ≤ 0.5139 (Balister et al. 2005).”
• Randomized Near Neighbor Graphs, Giant Components, and Applications in Data Science (2017, background): “Arguments for both directions are sketched in the first section of a paper by Balister, Bollob´as, Sarkar & Walters [3].”
• Stochastic geometry and random graphs for the analysis and design of wireless networks (2009, background): “The rate at which the number of neighbors k must increase with n is [73]: In summary, tools from percolation theory and random geometric graphs have enabled analytical studies of the connectivity properties of large ad hoc networks.”