Juan Segovia

Endurance: A new robustness measure for complex networks under multiple failure scenarios

Society is now, more than ever, highly dependent on the large-scale networks that underpin its functions. In relatively recent times, significant failures have occurred on large-scale networks that have a considerable impact upon sizable proportions of the world’s inhabitants. The failure of infrastructure has, in turn, begot a subsequent loss of services supported by that network. Consequently, it is now vitally important to evaluate the robustness of such networks in terms of the services supported by the network in question. Evaluating network robustness is integral to service provisioning and thus any network should include explicit indication of the impact upon service performance. Traditionally, network robustness metrics focused solely on topological characteristics, although some new approaches have considered, to a degree, the services supported by such networks. Several shortcomings of these new metrics have been identified. With the purpose of solving the drawbacks of these metrics, this paper presents a new measure called endurance, which quantifies the level of robustness supported by a specific topology under different types of multiple failure scenarios, giving higher importance to perturbations affecting low percentages of elements of a network. In this paper, endurance of six synthetic complex networks is computed for a range of defined multiple failure scenarios, taking into account the connection requests that cannot be satisfied. It is demonstrated that our proposal is able to quantify the robustness of a network under given multiple failure scenarios. Finally, results show that different types of networks react differently depending on the type of multiple failure.

A multiple failure propagation model in GMPLS-based networks

In this article, a new model to simulate different failure propagation scenarios in GMPLS-based networks is proposed. Several types of failures and malfunctions may spread along the network following different patterns (hardware failures, natural disasters, accidents, configuration errors, viruses, software bugs, etc.). The current literature presents several models for the spreading of failures in general networks. In communication networks, a failure affects not only nodes but also the connections passing through those nodes. The model in this article takes into account GMPLS node failures, affecting both data and control planes. The model is tested by simulation using different types of network topologies. In addition, a new method for the classification of network robustness is also introduced.

Availability analysis of GMPLS connections based on physical network topology

This paper presents a study of connection availability in GMPLS over optical transport networks (OTN) taking into account different network topologies. Two basic path protection schemes are considered and compared with the no protection case. The selected topologies are heterogeneous in geographic coverage, network diameter, link lengths, and average node degree. Connection availability is also computed considering the reliability data of physical components and a well-known network availability model. Results show several correspondences between suitable path protection algorithms and several network topology characteristics.

Topology-focused availability analysis of basic protection schemes in optical transport networks

We present a novel study of the availability in optical networks based on network topology. Connection availability is studied under two basic path protection schemes. Different topologies are selected in order to have heterogeneity in geographic coverage, network diameter, link lengths, and average node degree. Connection availability is also computed considering the reliability data of physical components and a well-known network availability model. Results report some useful information to select the suitable protection algorithms according to the network topology features and the required levels of availability.

Improving the Resilience of Transport Networks to Large-scale Failures

Telecommunication networks have to deal with fiber cuts, hardware malfunctioning and other failures on a daily basis, events which are usually treated as isolated and unrelated. Efficient methods have been developed for coping with such common failures and hence users rarely notice them. Although less frequently, there also arise cases of multiple failures with catastrophic consequences. Multiple failures can occur for many reasons, for example, natural disasters, epidemic outbreaks affecting software components, or intentional attacks. This article investigates new methods for lessening the impact of such failures in terms of the number of connections affected. Two heuristic-based link prioritization strategies for improving network resilience are proposed. One strategy is built upon the concept of betweenness centrality, while the second is based on what we call the observed link criticality. Both strategies are evaluated through simulation on a large synthetic topology that represents a GMPLS-based transport network. The provisioning of connections in a dynamic traffic scenario as well as the occurrence of large-scale failures are simulated for the evaluation.

Failure propagation in GMPLS optical rings: CTMC model and performance analysis

Abstract Network reliability and resilience has become a key design parameter for network operators and Internet service providers. These often seek ways to have their networks fully operational for at least 99.999% of the time, regardless of the number and type of failures that may occur in their networks. This article presents a continuous-time Markov chain model to characterise the propagation of failures in optical GMPLS rings. Two types of failures are considered depending on whether they affect only the control plane, or both the control and data planes of the node. Additionally, it is assumed that control failures propagate along the ring infecting neighbouring nodes, as stated by the Susceptible-Infected-Disabled (SID) propagation model taken from epidemic-based propagation models. A few numerical examples are performed to demonstrate that the CTMC model provides a set of guidelines for selecting the appropriate repair rates in order to attain specific availability requirements, both in the control plane and the data plane.

An improved method for discovering link criticality in transport networks

Quantitatively assessing the importance or criticality of each link in a network is of practical value to operators, as that can help them to increase the networks resilience, provide more efficient services, or improve some other aspect of the service. Betweenness is a graph-theoretical measure of centrality that can be applied to communication networks to evaluate link importance. However, as we illustrate in this paper, the basic definition of betweenness centrality produces inaccurate estimations as it does not take into account some aspects relevant to networking, such as the heterogeneity in link capacity or the difference between node-pairs in their contribution to the total traffic. A new algorithm for discovering link centrality in transport networks is proposed in this paper. It requires only static or semi-static network and topology attributes, and yet produces estimations of good accuracy, as verified through extensive simulations. Its potential value is demonstrated by an example application. In the example, the simple shortest-path routing algorithm is improved in such a way that it outperforms other more advanced algorithms in terms of blocking ratio.

Network Survivability: End-to-End Recovery Using Local Failure Information

This chapter presents an advanced shared protection approach called Failure Dependent Path Protection (FDPP). Under this approach, several protection paths can be assigned to connections in the context of a shared protection framework. After formalizing the survivable online routing problem, two possible implementations are compared, one based on heuristics and the other on ILP. Building upon the concepts of routing already exposed, the chapter then presents two case studies. The first one employs Shortcut Span Protection to examine how different protection strategies affect resource provisioning, while the second is a thorough analysis of the performance of path protection in terms of connection availability, both for dedicated and shared path protection in heterogeneous network topologies.

Robustness analysis to multiple failures in GMPLS networks

Natural disasters such as earthquakes and flooding, as well as massive blackouts and other large-scale accidents can all seriously disrupt the normal operation of communication networks. Such events potentially affect several network elements simultaneously, thus creating so-called multiple-failure events. This paper studies the robustness of GMPLS-based networks subjected to such multiple-failure events from the perspective of the survival of end-to-end connections when subsets of links are made invulnerable against the specific failure, i.e., when immunization is applied. Two immunization strategies for improving robustness are compared. The first one uses purely static topological data to prioritize links based on their estimation of centrality, while the second one relies on link usage information to derive a criticality measure. These strategies are evaluated through simulation on two synthetic topologies representing continental-size transport networks, on which the normal operation and the occurrence of large-scale failures are simulated. The results also show that the two immunization strategies are effective in minimizing the number of affected connections and at the same time highlight the limitation of purely topological-based measures of network robustness.