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1
Content available New approaches for the identification of influential and critical nodes in an electric grid
Adebayo Isaiah, Sun Yanxia
Archives of Electrical Engineering
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2022
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Vol. 71, nr 3
671--686
EN
The aftermath of including new technologies in a modern electric system in conjunction with the incessant rise in power demand could pose a risk to the optimal operation of the system. Therefore, it becomes imperative to identify the most influential and critical nodes of such a system to avert future problems in network operation. In this paper, to identify most significant nodes of the system, the authors propose two measures of centrality in accordance with the network structural properties of a power system, namely, degree centrality (DC) and eigenvector centrality (EC). These are expressed considering the admittance matrix that exists among the interconnection of load to load nodes in an electrical power network. A critical node closeness centrality (CNCC) method is also proposed to identify critical nodes of the system. This is done by modifying the conventional closeness centrality (CC) to include the influence of interconnection that exists between network load to load nodes as captured by the admittance matrix between them. A comparative analysis of the proposed techniques with other conventional methods is also carried out. The result of the simulation shows that the proposed methods could serve as alternative tools in the identification of influential and weak nodes in a power system.
2
Content available A comparative performance analysis of the exponential-based and resolvent-based centrality measures
Wilczek Piotr
Silesian Journal of Pure and Applied Mathematics
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2020
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vol. 10, iss. 1
45--102
EN
The present study aims to quantitatively assess the effect of the attenuation factor on the resolution, performance, rank correlations, robustness and assortativity of the Katz centrality measure. We found that the granularity of the exponential-based and resolvent-based ranking algorithms is strongly correlated with the number of automorphically equivalent nodes within the network. Thus, this result can be viewed as a bridge between algebraic and quantitative graph theory. Moreover, we substituted the dichotomous adjacency matrix in the definitions of the exponential-based and resolvent-based centrality indices by its weighted (normalized) version and, therefore, we obtained two novel ranking algorithms. The deliberate attack simulation experiments carried out on four empirical and on two model networks showcased that the newly suggested ranking methods considerably outperform their unweighted counterparts as well as the classical degree centrality measure. In the last part of the paper, we introduced the concept of the centrality assortativity profile of a complex network. The extensive numerical results demonstrated that this novel theoretical notion is useful in complex network mining.
3
Content available Identifying influential nodes in the genome-scale metabolic networks
Wilczek Piotr
Silesian Journal of Pure and Applied Mathematics
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2019
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vol. 9, iss. 1
9--47
EN
The present article introduces two novel centrality indices which can be used in order to characterize the genome-scale metabolic networks. The deliberate attack simulation experiments conducted on two Barab´asi-Albert models and four genome-scale metabolic networks demonstrate that the proposed ranking methods are effective in identifying essential nodes in complex networks. Also, the Principal Component Analysis reveals that the Kendall centrality correlation profile can be used to describe the metabolic networks and distinguish them from their random counter-parts with the preserved degree distribution.
4
Content available Novel centrality measures and distance-related topological indices in network data mining
Wilczek P.
Silesian Journal of Pure and Applied Mathematics
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2017
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Vol. 7, iss. 1
21--63
EN
The present work proposes two new Euclidean distance functions, six new centrality measures as well as several new entropies definable on any complex network. It is demonstrated on four spatial and two social real-world datasets that these concepts are applicable in network data mining. Also, several new topological indices are introduced and their basic computational properties are established.
5
Content available Grafowa metoda priorytetyzacji zdolności sił zbrojnych
Kasprzyk R., Tarapata Z., Szkółka K., Cieślewicz M.
Symulacja w Badaniach i Rozwoju
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2015
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Vol. 6, nr 4
241--253
PL
W referacie przedstawiona została opracowana metoda priorytetyzacji zdolności Sił Zbrojnych RP, wykorzystywana w ramach jednej z kluczowych czynności procesu planowania tj. Oceny Wymaganych Zdolności i ich Priorytetyzacji. Przedstawiono grafowy model zależności pomiędzy zdolnościami i szczegółowo opisano miary centralności wierzchołów będące podstawą metody priorytetyzacji.
EN
The paper presents a novel method to prioritize capabilities of Polish Armed Forces, used in one of the most important stages of planning process i.e. “Required Capabilities Assessment and Prioritetization”. Capability dependency graph model was presented and centrality measures were described in details which are the basis for prioritetization method.
6
Content available CART : Creative Application to Remedy Traffic
Kasprzyk R., Szkółka K., Poławski T., Pyżarnowski M., Giętkowski P.
Biuletyn Instytutu Systemów Informatycznych
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2014
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nr 14
5-12
EN
CART is a simulation software assisting decision-making process, aiming at enhancing the throughput of transport infrastructure and “fluidity” of vehicle traffic in urban agglomerations. Thanks to innovative solutions combining state-of-the-art software technologies with achievements in graph and network theories, the system is capable of improving present traffic conditions. The system is designated both for organisations responsible for management of urban traffic and for road users. The first group is able, in a conscious and effective way assess usability of the solution (layout of traffic lights, construction of gas stations/parking lots, modifying/extending the network of roads) to the town, by analysing results of simulations of modified road infrastructure. The second group, thanks to using the intelligent traffic management assistance system, will be able to drive throughout the town in a more fluid way.
PL
CART to symulacyjny system wspomagania podejmowania decyzji, którego celem jest poprawa przepustowości infrastruktury transportowej i ,,płynności” ruchu pojazdów w aglomeracjach miejskich. Dzięki innowacyjnym rozwiązaniom łączącym nowoczesne technologie informatyczne oraz osiągnięcia z dziedziny teorii grafów i sieci, system jest w stanie przyczynić się do poprawy obecnych warunków na drogach. System przeznaczony jest zarówno dla organizacji odpowiadających za zarządzanie ruchem w mieście, jak i dla użytkowników dróg. Pierwsza grupa poprzez analizę wyników symulacji zmodyfikowanej infrastruktury dróg może w sposób świadomy i efektywny ocenić przydatność rozwiązania dla miasta (rozmieszczenie sygnalizacji świetlnej, budowa stacji benzynowych/parkingów, modyfikacja/rozbudowa samej sieci połączeń drogowych). Druga grupa dzięki wykorzystaniu inteligentnego systemu wspomagania organizacji ruchu będzie mogła płynniej przemieszczać się po mieście.
7
Content available Application of Social Network Analysis to the Investigation of Interpersonal Connections
Mincer M., Niewiadomska-Szynkiewicz E.
Journal of Telecommunications and Information Technology
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2012
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nr 2
83-91
EN
Social network analysis (SNA) is an important and valuable tool for knowledge extraction from massive and unstructured data. Social network provides a powerful abstraction of the structure and dynamics of diverse kinds of interpersonal connection and interaction. In this paper, we address issues associated with the application of SNA to the investigation and analysis of social relationships of people. We provide a brief introduction to representation and analysis of social networks, SNA models and methods. The main objective is to investigate the application of SNA techniques to data mining in case of two social networks Facebook and Twitter. The presented simulations illustrate how social analysis can be used to determine the interpersonal connections, importance of actors in a given social network and detect communities of people. We then discuss strength and weakness of SNA techniques.
8
Content available Symulator rozprzestrzeniania się złośliwego oprogramowania w sieciach komputerowych
Najgebauer A., Kasprzyk R.
Biuletyn Instytutu Systemów Informatycznych
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2009
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nr 4
41-47
PL
Wyraźny wzrost zainteresowania systemami dających się modelować z wykorzystaniem teorii grafów i sieci jest spowodowany rosnącym znaczeniem rzeczywistych sieci wielkiej skali. Badania niezawodności odporności tych systemów na przypadkowe, jak i celowe ataki oraz trudne do przewidzenia awarie mają oczywiste znaczenie praktyczne. W artykule przedstawiono koncepcję modelowania i symulacji zagrożeń dla sieci teleinformatycznych. Zaprezentowano aplikację umożliwiającą symulację rozprzestrzeniania się złośliwego oprogramowania, badanie struktury i prognozowanie mozliwych kierunków ewolucji sieci teleinformatycznych, optymalizacji sposobów wykorzystania zasobów czy w końcu formułowanie możliwych procedur postępowania w sytuacjach kryzysowych np. przypadkowe awarie pewnych węzłów lub celowe ataki terrorystyczne.
EN
The paper focuses special attention on research of Complex Networks (CN). CN have Scale Free and Small Word features, what make them accurate model of many networks such as telecommunication. These features, which appear to be very efficient for communication, favor at the same time the spreading of computer viruses. Based on defined centrality measures, we show how to discover the critical elements of any networks. The identification of the critical elements of a given network should be the first concern in order to reduce the consequence of viruses spreading. We define dynamic model for the spreading of viruses on networks and build application to simulate and analyze many epidemic scenarios. Based on available data of some networks, we show how and why epidemics are spreading in real telecommunication networks like Internet and how could be halted.
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