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Content Provider | IEEE Xplore Digital Library |
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Author | Yilin Shen Thai, M.T. |
Copyright Year | 2013 |
Description | Author affiliation: Dept. of CISE, Univ. of Florida, Gainesville, FL, USA (Yilin Shen; Thai, M.T.) |
Abstract | The assessment of network vulnerability is of great importance in the presence of unexpected disruptive events or adversarial attacks, which will lead to a much more devastating consequence especially when failures can be cascaded. In this context, we study the Cascading Vulnerability Node Detection (CVND) optimization problem to identify the most vulnerable nodes in a network whose removals maximally destroy the network's functions after cascading failures, based on the recently proposed effective metric, total pairwise connectivity. Besides its NP-hardness on various graphs, we further show that the CVND problem is NP-hard to be approximated within Ω $((1+(d/n1-∈_{-1})^{2}(n-k)/n^{∈}))$ equation with n vertices and k vulnerable nodes after d-hop failure cascades. Despite the intractability of this problem, we propose TRGA, a novel iterative two-phase algorithm, for efficiently solving the CVND problem in a timely manner. We also formulate the integer linear programming for obtaining the optimal solution. The effectiveness of our solutions is validated on various synthetic and real-world networks. |
Sponsorship | IEEE Commun. Soc. |
Starting Page | 1526 |
Ending Page | 1531 |
File Size | 608415 |
Page Count | 6 |
File Format | |
ISBN | 9781479913534 |
DOI | 10.1109/GLOCOM.2013.6831290 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2013-12-09 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Power system faults Power system protection Measurement Transmitters Quality of service Reliability Network topology Algorithm Complex Networks Cascading Failure Network Structure Analysis Inapproximability |
Content Type | Text |
Resource Type | Article |
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