4,931 research outputs found
Cascades tolerance of scale-free networks with attack cost
Network robustness against cascades is a major topic in the fields of complex networks. In this paper, we propose an attack-cost-based cascading failure model, where the attack cost of nodes is positively related to its degree. We compare four attacking strategies: the random removal strategy (RRS), the low-degree removal strategy (LDRS), the high-degree removal strategy (HDRS) and the genetic algorithm removal
strategy (GARS). It is shown that the network robustness against cascades is heavily affected by attack costs and the network exhibits the weakest robustness under GARS. We also explore the relationship
between the network robustness and tolerance parameter under these attacking strategies. The simulation results indicate that the critical value of tolerance parameter under GARS is greatly larger than that of other attacking strategies. Our work can supply insight into the robustness and vulnerability of complex networks corresponding to cascading failures.Peer ReviewedPostprint (published version
Cascade-based attacks on complex networks
We live in a modern world supported by large, complex networks. Examples
range from financial markets to communication and transportation systems. In
many realistic situations the flow of physical quantities in the network, as
characterized by the loads on nodes, is important. We show that for such
networks where loads can redistribute among the nodes, intentional attacks can
lead to a cascade of overload failures, which can in turn cause the entire or a
substantial part of the network to collapse. This is relevant for real-world
networks that possess a highly heterogeneous distribution of loads, such as the
Internet and power grids. We demonstrate that the heterogeneity of these
networks makes them particularly vulnerable to attacks in that a large-scale
cascade may be triggered by disabling a single key node. This brings obvious
concerns on the security of such systems.Comment: 4 pages, 4 figures, Revte
Analyzing Cascading Failures in Smart Grids under Random and Targeted Attacks
We model smart grids as complex interdependent networks, and study targeted
attacks on smart grids for the first time. A smart grid consists of two
networks: the power network and the communication network, interconnected by
edges. Occurrence of failures (attacks) in one network triggers failures in the
other network, and propagates in cascades across the networks. Such cascading
failures can result in disintegration of either (or both) of the networks.
Earlier works considered only random failures. In practical situations, an
attacker is more likely to compromise nodes selectively.
We study cascading failures in smart grids, where an attacker selectively
compromises the nodes with probabilities proportional to their degrees; high
degree nodes are compromised with higher probability. We mathematically analyze
the sizes of the giant components of the networks under targeted attacks, and
compare the results with the corresponding sizes under random attacks. We show
that networks disintegrate faster for targeted attacks compared to random
attacks. A targeted attack on a small fraction of high degree nodes
disintegrates one or both of the networks, whereas both the networks contain
giant components for random attack on the same fraction of nodes.Comment: Accepted for publication in 28th IEEE International Conference on
Advanced Information Networking and Applications (AINA) 201
MATCASC: A tool to analyse cascading line outages in power grids
Blackouts in power grids typically result from cascading failures. The key
importance of the electric power grid to society encourages further research
into sustaining power system reliability and developing new methods to manage
the risks of cascading blackouts. Adequate software tools are required to
better analyze, understand, and assess the consequences of the cascading
failures. This paper presents MATCASC, an open source MATLAB based tool to
analyse cascading failures in power grids. Cascading effects due to line
overload outages are considered. The applicability of the MATCASC tool is
demonstrated by assessing the robustness of IEEE test systems and real-world
power grids with respect to cascading failures
Integrating fluctuations into distribution of resources in transportation networks
We propose a resource distribution strategy to reduce the average travel time
in a transportation network given a fixed generation rate. Suppose that there
are essential resources to avoid congestion in the network as well as some
extra resources. The strategy distributes the essential resources by the
average loads on the vertices and integrates the fluctuations of the
instantaneous loads into the distribution of the extra resources. The
fluctuations are calculated with the assumption of unlimited resources, where
the calculation is incorporated into the calculation of the average loads
without adding to the time complexity. Simulation results show that the
fluctuation-integrated strategy provides shorter average travel time than a
previous distribution strategy while keeping similar robustness. The strategy
is especially beneficial when the extra resources are scarce and the network is
heterogeneous and lowly loaded.Comment: 14 pages, 4 figure
A Topological Investigation of Phase Transitions of Cascading Failures in Power Grids
Cascading failures are one of the main reasons for blackouts in electric
power transmission grids. The economic cost of such failures is in the order of
tens of billion dollars annually. The loading level of power system is a key
aspect to determine the amount of the damage caused by cascading failures.
Existing studies show that the blackout size exhibits phase transitions as the
loading level increases. This paper investigates the impact of the topology of
a power grid on phase transitions in its robustness. Three spectral graph
metrics are considered: spectral radius, effective graph resistance and
algebraic connectivity. Experimental results from a model of cascading failures
in power grids on the IEEE power systems demonstrate the applicability of these
metrics to design/optimize a power grid topology for an enhanced phase
transition behavior of the system
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