Assessing the Vulnerability of the Fiber Infrastructure to Disasters

Neumayer, Sebastian; Zussman, Gil; Cohen, Reuven; Modiano, Eytan

doi:10.1109/infcom.2009.5062074

Cited by 95 publications

(79 citation statements)

References 17 publications

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“…Neumayer et al, study the impact of geographical disasters on network robustness and survivability in [13,17]. They focus on the problem of geographical network inhibition (i.e., finding the most vulnerable cut of geographic line segment or circle) in optical layer backbone networks.…”

Section: Related Workmentioning

confidence: 99%

“…One of the main themes of the current literature, is finding the geographic locations of disasters or attacks that will have the largest impact on the survivability of a network. Specifically the focus is on determining which geographic location for a specific failure scenario (e.g., node failure [20,2], geographic location of link cuts [13], geographic circular shaped failure area [18], etc.) has the greatest impact on the network.…”

Section: Introductionmentioning

confidence: 99%

“…Here, we propose using the variation of the WS in the presence of a geographic correlated failure as a performance measure (WS is formally defined in Section 3) to assess the network survivability. Given a network topology with geographic coordinates of the nodes, we use the algorithm proposed in [13] to obtain a set of potential vulnerable geographic linear cuts. We designate as the worst-case cut, according to a given performance measure X, the one which causes the greatest variation in X.…”

Section: Introductionmentioning

confidence: 99%

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Measuring the survivability of networks to geographic correlated failures

Long

Tipper

Gomes

2014

Optical Switching and Networking

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Wide area backbone communication networks are subject to a variety of hazards that can result in network component failures. Hazards such as power failures and storms can lead to geographical correlated failures. Recently there has been increasing interest in determining the ability of networks to survive geographic correlated failures and a number of measures to quantify the effects of failures have appeared in the literature. This paper proposes a the use of weighted spectrum to evaluate network survivability regarding geographic correlated failures. Further we conduct a comparative analysis by finding the most vulnerable geographic cuts or nodes in the network though solving an optimization problem to determine the cut with the largest impact for a number of measures in the literature as well as weighted spectrum. Numerical results on several sample network topologies show that the worst-case geographic cuts depend on the measure used in an unweighted or weighted graph. The proposed weighted spectrum measure is shown to be more versatile than other measures in both unweighted and weighted graphs.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measuring the survivability of networks to geographic correlated failures

Long

Tipper

Gomes

2014

Optical Switching and Networking

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“…Now we discuss protection of optical clouds specifically against large-scale disaster failures. Whereas traditional studies were more focused on small-scale (e.g., single link/node) failures, protection against disaster failures has become a major concern, given their risk of affecting communication networks (Neumayer, Zussman, Cohen, & Modiano, 2009;Reuters, 2005). Disasters can have natural (earthquakes, tornados, tsunamis, hurricanes, etc.)…”

Section: Disaster-resilient Optical Cloudsmentioning

confidence: 99%

“…Disasters can have natural (earthquakes, tornados, tsunamis, hurricanes, etc.) or human causes (e.g., weapons of mass destruction (WMD) and electro-magnetic pulse (EMP)) (Neumayer et al, 2009). In this chapter, the main focus of our analysis is optical backbone networks.…”

Section: Disaster-resilient Optical Cloudsmentioning

confidence: 99%

Dimensioning Resilient Optical Grid/Cloud Networks

Jaumard

Develder

Advances in Systems Analysis, Software Engineering, and High Performance Computing

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Optical networks play a crucial role in the provisioning of grid and cloud computing services. Their high bandwidth and low latency characteristics effectively enable universal users' access to computational and storage resources that thus can be fully exploited without limiting performance penalties. Given the rising importance of such cloud/grid services hosted in (remote) data centers, the various users (ranging from academics, over enterprises, to non-professional consumers) are increasingly dependent on the network connecting these data centers, that must be designed to ensure maximal service availability, i.e., minimizing interruptions. In this chapter we will outline the challenges encompassing the design, i.e., dimensioning, of large-scale backbone (optical) networks interconnecting data centers. This amounts to extensions of the classical routing and wavelength assignment algorithms (RWA) to so-called anycast RWA, but also pertains to jointly dimensioning not just the network but also the data center resources (i.e., servers). We specifically focus on resiliency, given the criticality of the grid/cloud infrastructure in today's businesses, and, for highly critical services, we also include specific design approaches to achieve disaster resiliency. INTRODUCTIONBack in the 1960s, John McCarthy envisioned the concept of "computation as a public utility", making computing power equally easily accessible as the classical utilities that provide users with water, gas, and electricity. That seminal idea reappeared in the 1990s under the form of grid computing, borrowing its name from the power grid, where "the grid" was aimed to be a highly powerful computing resource that scientists could easily tap into for performing challenging tasks. Similarly, today's cloud computing paradigm is built on the idea of relieving the user from worrying about the resources required to run applications and to store data, as well as on the idea of enabling access to such applications and data from basically any device. Clearly, such concept can be made possible only through a high capacity and low latency network that connects the user to "the cloud", i.e., the distributed computing/storage resources. Undeniably, development of optical network technology has been a major driver that enabled the realization of such grids/clouds. The rise of broadband access networks, and high speed optical networking in wide area networks (WAN) has increased the geographical scale of distributed computing paradigms, extending their range from on-site computing facilities to the cost-efficient aggregation of IT resources for both processing and storage in large scale data centers. These now can supply a broad spectrum of applications, serving a wide audience ranging from end consumers, over business users, to scientists requiring high performance computing (HPC) facilities. Basic concepts underlying so-called grid technology, originating in the e-Science domain (e.g., to process massive data flows from the large hadron collider (LHC) at CE...

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Exact algorithms for solving a Euclidean maximum flow network interdiction problem

Sullivan

Smith

2014

Networks

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We consider an interdiction problem that involves an operator (or defender) whose goal is to maximize flow from a source node to a sink node in some network that resides in Euclidean space. The problem we examine takes the perspective of an interdictor, who seeks to minimize the defender's maximum flow by locating a set of attacks that diminish arc capacities in accordance with the distance from the arc to the attack. Attacks are not restricted to node or arc locations, and can occur anywhere on the region in which the network is located. We refer to this problem as the Euclidean maximum flow network interdiction problem (E‐MFNIP). We show that E‐MFNIP is NP‐hard, as it generalizes the maximum flow interdiction problem studied by Wood . This article contributes two approaches to solving E‐MFNIP based on solving a sequence of lower‐bounding integer programs from which upper bounds can be readily obtained, and shows that these bounds are convergent. Computations on a set of test instances indicate that an approach based on space‐discretization tends to converge much faster than one based on linearizing the nonlinear capacity functions. We demonstrate the application of our space‐discretization approach on a real geographical network. © 2014 Wiley Periodicals, Inc. NETWORKS, Vol. 64(2), 109–124 2014

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Assessing the Vulnerability of the Fiber Infrastructure to Disasters

Cited by 95 publications

References 17 publications

Measuring the survivability of networks to geographic correlated failures

Measuring the survivability of networks to geographic correlated failures

Dimensioning Resilient Optical Grid/Cloud Networks

Exact algorithms for solving a Euclidean maximum flow network interdiction problem

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