### Abstract

In order to evaluate the expected availability of a service, a network administrator should consider all possible failure scenarios under the specific service availability model stipulated in the corresponding service-level agreement. Given the increase in natural disasters and malicious attacks with geographically extensive impact, considering only independent single link failures is often insufficient. In this paper, we build a stochastic model of geographically correlated link failures caused by disasters, in order to estimate the hazards a network may be prone to, and to understand the complex correlation between possible link failures. With such a model, one can quickly extract information, such as the probability of an arbitrary set of links to fail simultaneously, the probability of two nodes to be disconnected, the probability of a path to survive a failure, etc. Furthermore, we introduce a pre-computation process, which enables us to succinctly represent the joint probability distribution of link failures. In particular, we generate, in polynomial time, a quasilinear-sized data structure, with which the joint failure probability of any set of links can be computed efficiently.

Original language | English |
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Title of host publication | INFOCOM 2018 - IEEE Conference on Computer Communications |

Publisher | Institute of Electrical and Electronics Engineers Inc. |

Pages | 2105-2113 |

Number of pages | 9 |

Volume | 2018-April |

ISBN (Electronic) | 9781538641286 |

DOIs | |

Publication status | Published - Oct 8 2018 |

Event | 2018 IEEE Conference on Computer Communications, INFOCOM 2018 - Honolulu, United States Duration: Apr 15 2018 → Apr 19 2018 |

### Other

Other | 2018 IEEE Conference on Computer Communications, INFOCOM 2018 |
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Country | United States |

City | Honolulu |

Period | 4/15/18 → 4/19/18 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Science(all)
- Electrical and Electronic Engineering

### Cite this

*INFOCOM 2018 - IEEE Conference on Computer Communications*(Vol. 2018-April, pp. 2105-2113). [8486218] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFOCOM.2018.8486218

**A Tractable Stochastic Model of Correlated Link Failures Caused by Disasters.** / Tapolcai, J.; Vass, Balazs; Heszberger, Zalan; Biro, Jozsef; Hay, David; Kuipers, Fernando A.; Rónyai, L.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*INFOCOM 2018 - IEEE Conference on Computer Communications.*vol. 2018-April, 8486218, Institute of Electrical and Electronics Engineers Inc., pp. 2105-2113, 2018 IEEE Conference on Computer Communications, INFOCOM 2018, Honolulu, United States, 4/15/18. https://doi.org/10.1109/INFOCOM.2018.8486218

}

TY - GEN

T1 - A Tractable Stochastic Model of Correlated Link Failures Caused by Disasters

AU - Tapolcai, J.

AU - Vass, Balazs

AU - Heszberger, Zalan

AU - Biro, Jozsef

AU - Hay, David

AU - Kuipers, Fernando A.

AU - Rónyai, L.

PY - 2018/10/8

Y1 - 2018/10/8

N2 - In order to evaluate the expected availability of a service, a network administrator should consider all possible failure scenarios under the specific service availability model stipulated in the corresponding service-level agreement. Given the increase in natural disasters and malicious attacks with geographically extensive impact, considering only independent single link failures is often insufficient. In this paper, we build a stochastic model of geographically correlated link failures caused by disasters, in order to estimate the hazards a network may be prone to, and to understand the complex correlation between possible link failures. With such a model, one can quickly extract information, such as the probability of an arbitrary set of links to fail simultaneously, the probability of two nodes to be disconnected, the probability of a path to survive a failure, etc. Furthermore, we introduce a pre-computation process, which enables us to succinctly represent the joint probability distribution of link failures. In particular, we generate, in polynomial time, a quasilinear-sized data structure, with which the joint failure probability of any set of links can be computed efficiently.

AB - In order to evaluate the expected availability of a service, a network administrator should consider all possible failure scenarios under the specific service availability model stipulated in the corresponding service-level agreement. Given the increase in natural disasters and malicious attacks with geographically extensive impact, considering only independent single link failures is often insufficient. In this paper, we build a stochastic model of geographically correlated link failures caused by disasters, in order to estimate the hazards a network may be prone to, and to understand the complex correlation between possible link failures. With such a model, one can quickly extract information, such as the probability of an arbitrary set of links to fail simultaneously, the probability of two nodes to be disconnected, the probability of a path to survive a failure, etc. Furthermore, we introduce a pre-computation process, which enables us to succinctly represent the joint probability distribution of link failures. In particular, we generate, in polynomial time, a quasilinear-sized data structure, with which the joint failure probability of any set of links can be computed efficiently.

UR - http://www.scopus.com/inward/record.url?scp=85056161168&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85056161168&partnerID=8YFLogxK

U2 - 10.1109/INFOCOM.2018.8486218

DO - 10.1109/INFOCOM.2018.8486218

M3 - Conference contribution

AN - SCOPUS:85056161168

VL - 2018-April

SP - 2105

EP - 2113

BT - INFOCOM 2018 - IEEE Conference on Computer Communications

PB - Institute of Electrical and Electronics Engineers Inc.

ER -