2,435 research outputs found
Controlling complex policy problems: a multimethodological approach using system dynamics and network controllability
Notwithstanding the usefulness of system dynamics in analyzing complex policy
problems, policy design is far from straightforward and in many instances
trial-and-error driven. To address this challenge, we propose to combine system
dynamics with network controllability, an emerging field in network science, to
facilitate the detection of effective leverage points in system dynamics models
and thus to support the design of influential policies. We illustrate our
approach by analyzing a classic system dynamics model: the World Dynamics
model. We show that it is enough to control only 53% of the variables to steer
the entire system to an arbitrary final state. We further rank all variables
according to their importance in controlling the system and we validate our
approach by showing that high ranked variables have a significantly larger
impact on the system behavior compared to low ranked variables
The web of federal crimes in Brazil: topology, weaknesses, and control
Law enforcement and intelligence agencies worldwide struggle to find
effective ways to fight and control organized crime. However, illegal networks
operate outside the law and much of the data collected is classified.
Therefore, little is known about criminal networks structure, topological
weaknesses, and control. In this contribution we present a unique criminal
network of federal crimes in Brazil. We study its structure, its response to
different attack strategies, and its controllability. Surprisingly, the network
composed of multiple crimes of federal jurisdiction has a giant component,
enclosing more than a half of all its edges. This component shows some typical
social network characteristics, such as small-worldness and high clustering
coefficient, however it is much "darker" than common social networks, having
low levels of edge density and network efficiency. On the other side, it has a
very high modularity value, . Comparing multiple attack strategies, we
show that it is possible to disrupt the giant component of the network by
removing only of its edges or nodes, according to a module-based
prescription, precisely due to its high modularity. Finally, we show that the
component is controllable, in the sense of the exact network control theory, by
getting access to of the driver nodes.Comment: 9 pages, 5 figure
Hierarchy measure for complex networks
Nature, technology and society are full of complexity arising from the
intricate web of the interactions among the units of the related systems (e.g.,
proteins, computers, people). Consequently, one of the most successful recent
approaches to capturing the fundamental features of the structure and dynamics
of complex systems has been the investigation of the networks associated with
the above units (nodes) together with their relations (edges). Most complex
systems have an inherently hierarchical organization and, correspondingly, the
networks behind them also exhibit hierarchical features. Indeed, several papers
have been devoted to describing this essential aspect of networks, however,
without resulting in a widely accepted, converging concept concerning the
quantitative characterization of the level of their hierarchy. Here we develop
an approach and propose a quantity (measure) which is simple enough to be
widely applicable, reveals a number of universal features of the organization
of real-world networks and, as we demonstrate, is capable of capturing the
essential features of the structure and the degree of hierarchy in a complex
network. The measure we introduce is based on a generalization of the m-reach
centrality, which we first extend to directed/partially directed graphs. Then,
we define the global reaching centrality (GRC), which is the difference between
the maximum and the average value of the generalized reach centralities over
the network. We investigate the behavior of the GRC considering both a
synthetic model with an adjustable level of hierarchy and real networks.
Results for real networks show that our hierarchy measure is related to the
controllability of the given system. We also propose a visualization procedure
for large complex networks that can be used to obtain an overall qualitative
picture about the nature of their hierarchical structure.Comment: 29 pages, 9 figures, 4 table
Tracking advanced persistent threats in critical infrastructures through opinion dynamics
Advanced persistent threats pose a serious issue for modern industrial environments, due to their targeted and complex attack vectors that are difficult to detect. This is especially severe in critical infrastructures that are accelerating the integration of IT technologies. It is then essential to further develop effective monitoring and response systems that ensure the continuity of business to face the arising set of cyber-security threats. In this paper, we study the practical applicability of a novel technique based on opinion dynamics, that permits to trace the attack throughout all its stages along the network by correlating different anomalies measured over time, thereby taking the persistence of threats and the criticality of resources into consideration. The resulting information is of essential importance to monitor the overall health of the control system and cor- respondingly deploy accurate response procedures. Advanced Persistent Threat Detection Traceability Opinion Dynamics.Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech
Preventing Advanced Persistent Threats in Complex Control Networks
An Advanced Persistent Threat (APT) is an emerging attack against Industrial Control and Automation Systems, that is executed over a long period of time and is difficult to detect. In this context, graph theory can be applied to model the interaction among nodes and the complex attacks affecting them, as well as to design recovery techniques that ensure the survivability of the network. Accordingly, we leverage a decision model to study how a set of hierarchically selected nodes can collaborate to detect an APT within the network, concerning the presence of changes in its topology. Moreover, we implement a response service based on redundant links that dynamically uses a secret sharing scheme and applies a flexible routing protocol depending on the severity of the attack. The ultimate goal is twofold: ensuring the reachability between nodes despite the changes and preventing the path followed by messages from being discovered.Universidad de Málaga. Campus de Excelencia Internacional AndalucĂa Tech
Power network and smart grids analysis from a graph theoretic perspective
The growing size and complexity of power systems has given raise to the use of complex network theory in their modelling, analysis, and synthesis. Though most of the previous studies in this area have focused on distributed control through well established protocols like synchronization and consensus, recently, a few fundamental concepts from graph theory have also been applied, for example in symmetry-based cluster synchronization. Among the existing notions of graph theory, graph symmetry is the focus of this proposal. However, there are other development around some concepts from complex network theory such as graph clustering in the study.
In spite of the widespread applications of symmetry concepts in many real world complex networks, one can rarely find an article exploiting the symmetry in power systems. In addition, no study has been conducted in analysing controllability and robustness for a power network employing graph symmetry. It has been verified that graph symmetry promotes robustness but impedes controllability. A largely absent work, even in other fields outside power systems, is the simultaneous investigation of the symmetry effect on controllability and robustness.
The thesis can be divided into two section. The first section, including Chapters 2-3, establishes the major theoretical development around the applications of graph symmetry in power networks. A few important topics in power systems and smart grids such as controllability and robustness are addressed using the symmetry concept. These topics are directed toward solving specific problems in complex power networks. The controllability analysis will lead to new algorithms elaborating current controllability benchmarks such as the maximum matching and the minimum dominant set. The resulting algorithms will optimize the number of required driver nodes indicated as FACTS devices in power networks. The second topic, robustness, will be tackled by the symmetry analysis of the network to investigate three aspects of network robustness: robustness of controllability, disturbance decoupling, and fault tolerance against failure in a network element.
In the second section, including Chapters 4-8, in addition to theoretical development, a few novel applications are proposed for the theoretical development proposed in both sections one and two. In Chapter 4, an application for the proposed approaches is introduced and developed. The placement of flexible AC transmission systems (FACTS) is investigated where the cybersecurity of the associated data exchange under the wide area power networks is also considered. A new notion of security, i.e. moderated-k-symmetry, is introduced to leverage on the symmetry characteristics of the network to obscure the network data from the adversary perspective. In chapters 5-8, the use of graph theory, and in particular, graph symmetry and centrality, are adapted for the complex network of charging stations. In Chapter 5, the placement and sizing of charging stations (CSs) of the network of electric vehicles are addressed by proposing a novel complex network model of the charging stations. The problems of placement and sizing are then reformulated in a control framework and the impact of symmetry on the number and locations of charging stations is also investigated. These results are developed in Chapters 6-7 to robust placement and sizing of charging stations for the Tesla network of Sydney where the problem of extending the capacity having a set of pre-existing CSs are addressed. The role of centrality in placement of CSs is investigated in Chapter 8. Finally, concluding remarks and future works are presented in Chapter 9
Control of coupled oscillator networks with application to microgrid technologies
The control of complex systems and network-coupled dynamical systems is a
topic of vital theoretical importance in mathematics and physics with a wide
range of applications in engineering and various other sciences. Motivated by
recent research into smart grid technologies we study here control of
synchronization and consider the important case of networks of coupled phase
oscillators with nonlinear interactions--a paradigmatic example that has guided
our understanding of self-organization for decades. We develop a method for
control based on identifying and stabilizing problematic oscillators, resulting
in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized
state. Interestingly, the amount of control, i.e., number of oscillators,
required to stabilize the network is primarily dictated by the coupling
strength, dynamical heterogeneity, and mean degree of the network, and depends
little on the structural heterogeneity of the network itself
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