Structural Vulnerability Analysis of Electric Power Distribution Grids

Power grid outages cause huge economical and societal costs. Disruptions in the power distribution grid are responsible for a significant fraction of electric power unavailability to customers. The impact of extreme weather conditions, continuously increasing demand, and the over-ageing of assets in the grid, deteriorates the safety of electric power delivery in the near future. It is this dependence on electric power that necessitates further research in the power distribution grid security assessment. Thus measures to analyze the robustness characteristics and to identify vulnerabilities as they exist in the grid are of utmost importance. This research investigates exactly those concepts- the vulnerability and robustness of power distribution grids from a topological point of view, and proposes a metric to quantify them with respect to assets in a distribution grid. Real-world data is used to demonstrate the applicability of the proposed metric as a tool to assess the criticality of assets in a distribution grid

Network Resilience Improvement and Evaluation Using Link Additions

Computer networks are getting more involved in providing services for most of our daily life activities related to education, business, health care, social life, and government. Publicly available computer networks are prone to targeted attacks and natural disasters that could disrupt normal operation and services. Building highly resilient networks is an important aspect of their design and implementation. For existing networks, resilience against such challenges can be improved by adding more links. In fact, adding links to form a full mesh yields the most resilient network but it incurs an unfeasibly high cost. In this research, we investigate the resilience improvement of real-world networks via adding a cost-efficient set of links. Adding a set of links to an obtain optimal solution using an exhaustive search is impracticable for large networks. Using a greedy algorithm, a feasible solution is obtained by adding a set of links to improve network connectivity by increasing a graph robustness metric such as algebraic connectivity or total graph diversity. We use a graph metric called flow robustness as a measure for network resilience. To evaluate the improved networks, we apply three centrality-based attacks and study their resilience. The flow robustness results of the attacks show that the improved networks are more resilient than the non-improved networks

A Dynamic Game on Network Topology for Counterinsurgency Applications

Successful military operations are increasingly reliant upon an advanced understanding of relevant networks and their topologies. The methodologies of network science are uniquely suited to inform senior military commanders; however, there is a lack of research in the application of these methods in a realistic military scenario. This study creates a dynamic game on network topology to provide insight into the effectiveness of offensive targeting strategies determined by various centrality measures given limited states of information and varying network topologies. Improved modeling of complex social behaviors is accomplished through incorporation of a distance-based utility function. Moreover, insights into effective defensive strategies are gained through incorporation of a hybrid model of network regeneration. Model functions and parameters are thoroughly presented, followed by a detailed sensitivity analysis of factors. Two designed experiments fully investigate the significance of factor main effects and two-factor interactions. Results show select targeting criteria utilizing uncorrelated network measures are found to outperform others given varying network topologies and defensive regeneration methods. Furthermore, the attacker state of information is only significant given certain defending network topologies. The costs of direct relationships significantly impact optimal methods of regeneration, whereas restructuring methods are insignificant. Model applications are presented and discussed

A Survey on Centrality Metrics and Their Implications in Network Resilience

Centrality metrics have been used in various networks, such as communication, social, biological, geographic, or contact networks. In particular, they have been used in order to study and analyze targeted attack behaviors and investigated their effect on network resilience. Although a rich volume of centrality metrics has been developed for decades, a limited set of centrality metrics have been commonly in use. This paper aims to introduce various existing centrality metrics and discuss their applicabilities and performance based on the results obtained from extensive simulation experiments to encourage their use in solving various computing and engineering problems in networks.Comment: Main paper: 36 pages, 2 figures. Appendix 23 pages,45 figure

Modelling and Design of Resilient Networks under Challenges

Communication networks, in particular the Internet, face a variety of challenges that can disrupt our daily lives resulting in the loss of human lives and significant financial costs in the worst cases. We define challenges as external events that trigger faults that eventually result in service failures. Understanding these challenges accordingly is essential for improvement of the current networks and for designing Future Internet architectures. This dissertation presents a taxonomy of challenges that can help evaluate design choices for the current and Future Internet. Graph models to analyse critical infrastructures are examined and a multilevel graph model is developed to study interdependencies between different networks. Furthermore, graph-theoretic heuristic optimisation algorithms are developed. These heuristic algorithms add links to increase the resilience of networks in the least costly manner and they are computationally less expensive than an exhaustive search algorithm. The performance of networks under random failures, targeted attacks, and correlated area-based challenges are evaluated by the challenge simulation module that we developed. The GpENI Future Internet testbed is used to conduct experiments to evaluate the performance of the heuristic algorithms developed