DocumentCode :
1355712
Title :
Resilience to Degree-Dependent and Cascading Node Failures in Random Geometric Networks
Author :
Kong, Zhenning ; Yeh, Edmund M.
Author_Institution :
Dept. of Electr. Eng., Yale Univ., New Haven, CT, USA
Volume :
56
Issue :
11
fYear :
2010
Firstpage :
5533
Lastpage :
5546
Abstract :
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.
Keywords :
graph theory; random processes; cascading failure problem; cascading node failures; computing networks; degree-dependent node failures; degree-dependent percolation process; electrical power networks; global communication; large-scale networks; operational network nodes; percolation-based viewpoint; power blackouts; random geometric graphs; random geometric networks; virus epidemics; wireless communication networks; Biology; Power system faults; Power system protection; Resilience; Wireless networks; Wireless sensor networks; Cascading failure; electric power network; epidemic; network resilience; percolation; power blackout; random geometric graph; wireless network;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2010.2068910
Filename :
5605369
Link To Document :
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