A New Method for Assessing the Resiliency of Large, Complex Networks

Designing resilient and reliable networks is a principle concern of planners and private firms. Traffic congestion whether recurring or as the result of some aperiodic event is extremely costly. This paper describes an alternative process and a model for analyzing the resiliency of networks that address some of the shortcomings of more traditional approaches – e.g., the four-step modeling process used in transportation planning. It should be noted that the authors do not view this as a replacement to current approaches but rather as a complementary tool designed to augment analysis capabilities. The process that is described in this paper for analyzing the resiliency of a network involves at least three steps: 1. assessment or identification of important nodes and links according to different criteria 2. verification of critical nodes and links based on failure simulations and 3. consequence. Raster analysis, graph-theory principles and GIS are used to develop a model for carrying out each of these steps. The methods are demonstrated using two, large interdependent networks for a metropolitan area in the United States.

Understanding Internet topology: principles, models, and validation

Building on a recent effort that combines a first-principles approach to modeling router-level connectivity with a more pragmatic use of statistics and graph theory, we show in this paper that for the Internet, an improved understanding of its physical infrastructure is possible by viewing the physical connectivity as an annotated graph that delivers raw connectivity and bandwidth to the upper layers in the TCP/IP protocol stack, subject to practical constraints (e.g., router technology) and economic considerations (e.g., link costs). More importantly, by relying on data from Abilene, a Tier-1 ISP, and the Rocketfuel project, we provide empirical evidence in support of the proposed approach and its consistency with networking reality. To illustrate its utility, we: 1) show that our approach provides insight into the origin of high variability in measured or inferred router-level maps; 2) demonstrate that it easily accommodates the incorporation of additional objectives of network design (e.g., robustness to router failure); and 3) discuss how it complements ongoing community efforts to reverse-engineer the Internet

Mathematics and the Internet: A Source of Enormous Confusion and Great Potential

Graph theory models the Internet mathematically, and a number of plausible mathematically intersecting network models for the Internet have been developed and studied. Simultaneously, Internet researchers have developed methodology to use real data to validate, or invalidate, proposed Internet models. The authors look at these parallel developments, particularly as they apply to scale-free network models of the preferential attachment type

Assessing the Physical Vulnerability of Backbone Networks

Communication networks are vulnerable to natural as well as man-made disasters. The geographical layout of the network influences the impact of these disasters. It is therefore, necessary to identify areas that could be most affected by a disaster and redesign those parts of the network so that the impact of a disaster has least effect on them. In this work, we assume that disasters which have a circular impact on the network. The work presents two new algorithms, namely the WHF-PG algorithm and the WHF-NPG algorithm, designed to solve the problem of finding the locations of disasters that would have the maximum disruptive effect on the communication infrastructure in terms of capacity

Survivable Cloud Network Mapping for Disaster Recovery Support

Network virtualization is a key provision for improving the scalability and reliability of cloud computing services. In recent years, various mapping schemes have been developed to reserve VN resources over substrate networks. However, many cloud providers are very concerned about improving service reliability under catastrophic disaster conditions yielding multiple system failures. To address this challenge, this work presents a novel failure region-disjoint VN mapping scheme to improve VN mapping survivability. The problem is first formulated as a mixed integer linear programming problem and then two heuristic solutions are proposed to compute a pair of failure region-disjoint VN mappings. The solution also takes into account mapping costs and load balancing concerns to help improve resource efficiencies. The schemes are then analyzed in detail for a variety of networks and their overall performances compared to some existing survivable VN mapping scheme

Improving the connectivity resilience of a telecommunications network to multiple link failures through a third-party network

Currently, telecommunication networks are fully resilient, in terms of connectivity, to single link failures. On the other hand, multiple simultaneous link failures are becoming a concern to network operators, mainly due to malicious human activities. Full connectivity resilience to multiple link failures is too costly and other solutions must be envisaged. For a given maximum number of simultaneous link failures, the connectivity resilience metric adopted here is the minimum number of network node pairs that can still communicate for any set of failing links. In this work, the connectivity resilience to multiple link failures is improved by resorting to a third-party network for temporary additional connectivity (i.e., while the failing links are not reestablished). In such a solution, some nodes must be selected to act as gateway nodes between the two networks. For a given network topology and a given number of gateway nodes, the aim is to select the most appropriate gateway nodes so that the connectivity resilience is improved as much as possible. To address this problem, a Gateway Node Selection (GNS) algorithm is proposed where the most damaging sets of failing links are identified and, then, a set cover problem type is defined and solved to select the gateway nodes. The computational results demonstrate the effectiveness of the proposed GNS algorithm over two well-known network topologies.publishe

Nuevas técnicas para modelizar y analizar la vulnerabilidad de infraestructuras críticas de energía interdependientes

La interdependencia entre las redes de gas y electricidad es motivo de preocupación debido a la creciente utilización del gas para la generación de electricidad en centrales de ciclo combinado y al uso de energía eléctrica de los compresores en la red de gas. Estas redes están sujetas a riesgos de interrupción del suministro derivados de posibles problemas técnicos o amenazas intencionadas. Por lo tanto, resulta conveniente modelizar y analizar la vulnerabilidad de estas infraestructuras críticas de energía interdependientes.En esta tesis doctoral se presenta, en primer lugar, una metodología para analizar conjuntamente los flujos de electricidad y gas. El conjunto de ecuaciones no lineales que representan la operación del sistema de potencia se resuelve utilizando el método de Newton-Raphson, mientras que las ecuaciones en la red de gas se resuelven utilizando el enfoque de transformada análoga-lineal. Se presentan dos casos de estudio para demostrar la simplicidad de la metodología propuesta. Los resultados obtenidos se verifican contra el método Newton-Raphson tradicional con el fin de comprobar la solución alcanzada, encontrando un buen desempeño de la metodología conjunta aplicada. La aplicación del enfoque propuesto permite el análisis de la vulnerabilidad de las infraestructuras energéticas interdependientes. También, se desarrolla una metodología para evaluar la vulnerabilidad estructural de las redes de energía eléctrica y gas acopladas, considerando interdependencias en el proceso de fallos en cascada. La vulnerabilidad se evalúa empleando el índice de desconexión de carga y las medidas de centralidad de vulnerabilidad geodésica e impacto en la conectividad. El estudio muestra una elevada correlación entre el índice de desconexión de carga y el índice de vulnerabilidad geodésica. De esta manera, la teoría de grafos puede usarse como sustituto de los enfoques de flujos de carga que demandan un conocimiento detallado de los parámetros eléctricos e hidráulicos de los sistemas bajo estudio y son computacionalmente más intensivos que los métodos estadísticos de grafos. Como resultado, se propone un nuevo método para estimar la vulnerabilidad de las redes de energía eléctrica y gas conjuntas utilizando el índice de vulnerabilidad geodésica. Asimismo, se estudia el comportamiento de las redes de electricidad y gas natural de España, tanto de manera separada como conjunta. Los resultados muestran que la red de gas natural es menos robusta que la red eléctrica y que la red acoplada es más vulnerable que la red eléctrica ante fallos aleatorios y deliberados. Además, eliminar los nodos más fuertemente conectados de los dos sistemas independientes resultaría una estrategia de ataque eficaz para el rápido colapso de las infraestructuras acopladas interdependientes. Por último, se evalúa la robustez estructural de los planes de expansión de las infraestructuras de electricidad y gas natural en España. Los casos de estudio corresponden a las principales inversiones propuestas por los operadores de los sistemas en 2015-2020. Los resultados demuestran que la construcción de algunas instalaciones para la expansión de ambas redes no mejora la robustez estructural de la red acoplada; sin embargo, cuando se tiene en cuenta todo el programa de inversión se produce una mejora relativa de hasta un 6% con respecto al caso base. La metodología propuesta en esta tesis corrobora que la aplicación de la teoría de grafos es adecuada para analizar la planificación de activos de una infraestructura energética crítica, requiriendo únicamente la topología y el programa de inversiones para evaluar el desempeño de la red acoplada en caso de fallos en cascada. En suma, esta tesis doctoral pone de relieve la importancia de que los sistemas energéticos se aborden como redes acopladas debido a sus fuertes interacciones. Una perturbación en un sistema puede no ser crítica si las infraestructuras están separadas, pero dado que ambas redes son interdependientes, el impacto resultante podría causar fallos en el otro sistema. En otras palabras, las interdependencias aumentan el impacto de las perturbaciones.<br /

Using a random road graph model to understand road networks robustness to link failures

Disruptions to the transport system have a greater impact on society and the economy now than ever before due to the increased interconnectivity and interdependency of the economic sectors. The ability of transport systems to maintain functionality despite various disturbances (i.e. robustness) is hence of tremendous importance and has been the focus of research seeking to support transport planning, design and management. These approaches and findings may nevertheless be only valid for the specific networks studied. The present study attempts to find universal insights into road networks robustness by exploring the correlation between different network attributes and network robustness to single, multiple, random and targeted link failures. For this purpose, the common properties of road graphs were identified through a literature review. On this basis, the GREREC model was developed to randomly generate a variety of abstract networks presenting the topological and operational characteristics of real-road networks, on which a robustness analysis was performed. This analysis quantifies the difference between the link criticality rankings when only single-link failures are considered as opposed to when multiple-link failures are considered and the difference between the impact of targeted and random attacks. The influence of the network attributes on the network robustness and on these two differences is shown and discussed. Finally, this analysis is also performed on a set of real road networks to validate the results obtained with the artificial networks