Network Resiliency Against Earthquakes

Valentini, Alessandro; Vass, Balázs; Oostenbrink, Jorik; Csak, Levente; Kuipers, Fernando A.; Pace, Bruno; Hay, David; Tapolcai, János

doi:10.1109/rndm48015.2019.8949088

Cited by 16 publications

(11 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We demonstrate our methods on the undirected Italian subtopology of Interoute, a 25-node, 35-link network traced and made publicly available by the authors of [10]. All experiments were conducted on commodity hardware: a AMD Ryzen 7 3700X 3.6 GHz processor with 32 GB of available RAM.…”

Section: Experiments a Setupmentioning

confidence: 99%

Going the Extra Mile with Disaster-Aware Network Augmentation

Oostenbrink

Kuipers

2021

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications

Self Cite

View full text Add to dashboard Cite

Network outages have significant economic and societal costs. While network operators have become adept at managing smaller failures, this is not the case for larger, regional failures such as natural disasters. Although it is not possible, and certainly not economic, to prevent all potential disaster damage and impact, we can reduce their impact by adding cost-efficient, geographically redundant, cable connections to the network.In this paper, we provide algorithms for finding cost-efficient, disaster-aware cable routes based on empirical hazard data. In contrast to previous work, our approach finds disaster-aware routes by considering the impact of a large set of input disasters on the network as a whole, as well as on the individual cable. For this, we propose the Disaster-Aware Network Augmentation Problem of finding a new cable connection that minimizes a function of disaster impact and cable cost. We prove that this problem is NP-hard and give an exact algorithm, as well as a heuristic, for solving it. Our algorithms are applicable to both planar and geographical coordinates. Using actual seismic hazard data, we demonstrate that by applying our algorithms, network operators can cost-efficiently raise the resilience of their network and future cable connections.

show abstract

Section: Experiments a Setupmentioning

confidence: 99%

Going the Extra Mile with Disaster-Aware Network Augmentation

Oostenbrink

Kuipers

2021

IEEE INFOCOM 2021 - IEEE Conference on Computer Communications

Self Cite

View full text Add to dashboard Cite

show abstract

“…disaster (see Fig. 4b for an example) 2 . While this assumption holds in general for a variety of disasters, we only use it to achieve 'nicer' equations.…”

Section: A Stochastic Modeling Of Regional Failuresmentioning

confidence: 99%

“…In this section, we present numerical results that validate our model and demonstrate the use of the proposed algorithms on real backbone networks (taken from [42] and [2], resp.) accompanied with real seismic hazard inputs.…”

Section: Model Evaluation Based On Seismic Hazard Datamentioning

confidence: 99%

“…An earlier version of the paper appeared at IEEE INFOCOM 2018 [1]. The pre-processing of the seismic input follows the approach of our paper [2] explicitly defined in a contract between the communication service provider (CSP) and the customer, called a servicelevel agreement (SLA). A violation of the agreed-upon service availability may lead to a financial penalty for the CSP; hence, CSPs must carefully (under-) estimate the availability of their services and, if necessary, reserve protection resources and implement recovery schemes to meet the availability demands.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic Shared Risk Link Groups Modeling Correlated Resource Failures Caused by Disasters

Vass

Tapolcai

Heszberger

et al. 2021

IEEE J. Select. Areas Commun.

Self Cite

View full text Add to dashboard Cite

To evaluate the expected availability of a backbone network service, the 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 component failures is often insufficient. This paper builds a stochastic model of geographically correlated link failures caused by disasters to estimate the hazards an optical backbone network may be prone to and to understand the complex correlation between possible link failures. We first consider link failures only and later extend our model also to capture node failures. With such a model, one can quickly extract essential information such as the probability of an arbitrary set of network resources to fail simultaneously, the probability of two nodes to be disconnected, the probability of a path to survive a disaster. Furthermore, we introduce standard data structures and a unified terminology on Probabilistic Shared Risk Link Groups (PSRLGs), along with a pre-computation process, which represents the failure probability of a set of resources succinctly. In particular, we generate a quasilinear-sized data structure in polynomial time, which allows the efficient computation of the cumulative failure probability of any set of network elements. Our evaluation is based on carefully pre-processed seismic hazard data matched to real-world optical backbone network topologies.

show abstract

“…In fact, both models could be used for computing lists of FPs and CFPs. In [36], an approach for determining the list of CFPs and FPs based on the available historical Earthquake data is presented. This approach can be viewed as a special case of both models presented in Subsubsec.…”

Section: Cfps and Fps From Historical Earthquake Datamentioning

confidence: 99%

How to Model and Enumerate Geographically Correlated Failure Events in Communication Networks

Vass

Tapolcai

Hay

et al. 2020

Computer Communications and Networks

Self Cite

View full text Add to dashboard Cite

Several works shed light on the vulnerability of networks against regional failures, which are failures of multiple pieces of equipment in a geographical region as a result of a natural or human-made disaster. This chapter overviews how this information can be added to existing network protocols through defining Shared Risk Link Groups (SRLGs) and Probabilistic SRLGs (PSRLGs). The output of this chapter can be the inputs of later chapters to design and operate the networks to enhance the preparedness against disasters and regional failures in general. In particular, we are focusing on the state-of-the-art algorithmic approaches for generating lists of (P)SRLGs of the communication networks protecting different sets of disasters.

show abstract

Network Resiliency Against Earthquakes

Cited by 16 publications

References 29 publications

Going the Extra Mile with Disaster-Aware Network Augmentation

Going the Extra Mile with Disaster-Aware Network Augmentation

Probabilistic Shared Risk Link Groups Modeling Correlated Resource Failures Caused by Disasters

How to Model and Enumerate Geographically Correlated Failure Events in Communication Networks

Contact Info

Product

Resources

About