Abstract
The reliability and robustness of infrastructure networks are important problems
requiring network models with nodes at fixed locations and links that break and reform with time. These temporal spatial networks are however difficult to analyse and understand due to the coexistence of short and long range links and inherent temporal correlations. We provide a mathematically tractable framework to analytically study the isolation statistics responsible for disconnecting spatial networks. Small-world effects and temporal correlations are also incorporated
in our framework as we investigate the distribution of the time needed for information packets to be able to reach the whole network.
requiring network models with nodes at fixed locations and links that break and reform with time. These temporal spatial networks are however difficult to analyse and understand due to the coexistence of short and long range links and inherent temporal correlations. We provide a mathematically tractable framework to analytically study the isolation statistics responsible for disconnecting spatial networks. Small-world effects and temporal correlations are also incorporated
in our framework as we investigate the distribution of the time needed for information packets to be able to reach the whole network.
| Original language | English |
|---|---|
| Article number | 28002 |
| Number of pages | 7 |
| Journal | EPL |
| Volume | 119 |
| Issue number | 2 |
| Early online date | 5 Oct 2017 |
| DOIs | |
| Publication status | Published - 2017 |
Keywords
- Networks and genealogical trees
- Stochastic processes
- Lattice theory and statistics