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

Resilient network design: Challenges and future directions

This paper highlights the complexity and challenges of providing reliable services in the evolving communications infrastructure. The hurdles in providing end-to-end availability guarantees are discussed and research problems identified. Avenues for overcoming some of the challenges examined are presented. This includes the use of a highly available network spine embedded in a physical network together with efficient crosslayer mapping to offer survivability and differentiation of traffic into classes of resilience. © 2013 Springer Science+Business Media New York

Preliminary Interdependency Analysis: An Approach to Support Critical Infrastructure Risk Assessment

We present a methodology, Preliminary Interdependency Analysis (PIA), for analysing interdependencies between critical infrastructure (CI). Consisting of two phases – qualitative analysis followed by quantitative analysis – an application of PIA progresses from a relatively quick elicitation of CI-interdependencies to the building of representative CI models, and the subsequent estimation of any resilience, risk or criticality measures an assessor might be interested in. By design, stages in the methodology are both flexible and iterative, resulting in interacting CI models that are scalable and may vary significantly in complexity and fidelity, depending on the needs and requirements of an assessor. For model parameterisation, one relies on a combination of field data, sensitivity analysis and expert judgement. Facilitated by dedicated software tool support, we illustrate PIA by applying it to a complex case-study of interacting Power (distribution and transmission) and Telecommunications networks in the Rome area. A number of studies are carried out, including: 1) an investigation of how “strength of dependence” between the CIs’ components affects various measures of risk and uncertainty, 2) for resource allocation, an exploration of different, but related, notions of CI component importance, and 3) highlighting the impact of model fidelity on the estimated risk of cascades

Why Information Matters: A Foundation for Resilience

Embracing Change: The Critical Role of Information, a research project by the Internews' Center for Innovation & Learning, supported by the Rockefeller Foundation, combines Internews' longstanding effort to highlight the important role ofinformation with Rockefeller's groundbreaking work on resilience. The project focuses on three major aspects:- Building knowledge around the role of information in empowering communities to understand and adapt to different types of change: slow onset, long-term, and rapid onset / disruptive;- Identifying strategies and techniques for strengthening information ecosystems to support behavioral adaptation to disruptive change; and- Disseminating knowledge and principles to individuals, communities, the private sector, policymakers, and other partners so that they can incorporate healthy information ecosystems as a core element of their social resilience strategies