4.5 Article

Resilience to Degree-Dependent and Cascading Node Failures in Random Geometric Networks

Journal

IEEE TRANSACTIONS ON INFORMATION THEORY
Volume 56, Issue 11, Pages 5533-5546

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIT.2010.2068910

Keywords

Cascading failure; electric power network; epidemic; network resilience; percolation; power blackout; random geometric graph; wireless network

Funding

  1. National Science Foundation (NSF) Cyber Trust [CNS-0716335]
  2. Army Research Office (ARO) [W911NF-07-1-0524]
  3. Air Force Office of Scientific Research (AFOSR) [FA9550-09-1-0187]
  4. Direct For Computer & Info Scie & Enginr
  5. Division Of Computer and Network Systems [1205560] Funding Source: National Science Foundation
  6. Direct For Computer & Info Scie & Enginr
  7. Division Of Computer and Network Systems [0916877] Funding Source: National Science Foundation

Ask authors/readers for more resources

This paper studies the problem of resilience to node failures in large-scale networks modelled by random geometric graphs. Adopting a percolation-based viewpoint, the paper investigates the ability of the network to maintain global communication in the face of dependent node failures. Degree-dependent site percolation processes on random geometric graphs are examined, and the first known analytical conditions are obtained for the existence and non-existence, respectively, of a large connected component of operational network nodes after degree-dependent node failures. In electrical power networks or wireless communication and computing networks, cascading failure from power blackouts or virus epidemics may result from a small number of initial node failures triggering global failure events affecting the whole network. With the use of a simple but descriptive model, it is shown that the cascading failure problem is equivalent to a degree-dependent percolation process. The first analytical conditions are obtained for the occurrence and non-occurrence of cascading failures, respectively, in large-scale networks with geometric constraints.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available