Quantitative Assessment of Distributed Networks through Hybrid Stochastic Modeling

Cavalieri, Salvatore; Chiacchio, Francesco; Manno, Gabriele; Popov, Peter

doi:10.1002/9781119131151.ch9

Cited by 4 publications

(4 citation statements)

References 31 publications

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“…The PIA approach -building hybrid models with level of abstraction tailored to the needs of the particular study -fits the modeling task well. In a recent study [12] we recorded evidence that the PIA style of modeling scales well to such detailed models.…”

Section: Discussionmentioning

confidence: 99%

Quantification of the Impact of Cyber Attack in Critical Infrastructures

Netkachov

Popov

Salako

2014

Lecture Notes in Computer Science

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract. In this paper we report on a recent study of the impact of cyberattacks on the resilience of complex industrial systems. We describe our approach to building a hybrid model consisting of both the system under study and an Adversary, and we demonstrate its use on a complex case study -a reference power transmission network (NORDIC 32), enhanced with a detailed model of the computer and communication system used for monitoring, protection and control. We studied the resilience of the modelled system under different scenarios: i) a base-line scenario in which the modelled system operates in the presence of accidental failures without cyber-attacks; ii) scenarios in which cyber-attacks can occur. We discuss the usefulness of our findings and outline directions for further work. Permanent repository link

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Section: Discussionmentioning

confidence: 99%

Quantification of the Impact of Cyber Attack in Critical Infrastructures

Netkachov

Popov

Salako

2014

Lecture Notes in Computer Science

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“…Static or Boolean models are the simplest models as they are based on combinatorial logic. These models are not computationally demanding because the system structure function can be obtained applying direct Boolean algebra that is not time-dependent [31]. Most of the reliability and risk assessment reports, including many examples of renewable power plants [16], [27][28][29], [32][33][34][35], are still based on static models.…”

Section: Related Workmentioning

confidence: 99%

On the use of dynamic reliability for an accurate modelling of renewable power plants

Chiacchio

D’Urso

Famoso

et al. 2018

Energy

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Renewable energies are a key element of the modern sustainable development. They play a key role in contributing to the reduction of the impact of fossil sources and to the energy supply in remote areas where the electrical grid cannot be reached. Due to the intermittent nature of the primary renewable resource, the feasibility assessment, the performance evaluation and the lifecycle management of a renewable power plant are very complex activities. In order to achieve a more accurate system modelling, improve the productivity prediction and better plan the lifecycle management activities, the modelling of a renewable plant may consider not only the physical process of energy transformation, but also the stochastic variability of the primary resource and the degradation mechanisms that affect the aging of the plant components resulting, eventually, in the failure of the system. This paper presents a modelling approach which integrates both the deterministic and the stochastic nature of renewable power plants using a novel methodology inspired from reliability engineering: the Stochastic Hybrid Fault Tree Automaton. The main steps for the design of a renewable power plant are discussed and implemented to estimate the energy production of a real photovoltaic power plant by means of a Monte Carlo simulation process. The proposed approach, modelling the failure behavior of the system, helps also with the evaluation of other key performance indicators like the power plant and the service availability.

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“…The instantaneous steady state and the interval availability metrics can be calculated using this state reward function. A stochastic activity networks (SAN) [61,62], i.e., a variant of SPN, are specifically being developed for performance, dependability, and performability evaluation of a wide range of real-world systems. For instance, an integrated modeling approach for fault tolerant systems based on SAN has been used for the evaluation of systems performance parameters, such as re-liability, availability and maintenance costs [63].…”

Section: Petri Netsmentioning

confidence: 99%

Reliability modeling and analysis of communication networks

Ahmed

Hasan

Pervez

et al. 2017

Journal of Network and Computer Applications

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In recent times, the functioning of various aspects of modern society-ranging from the various infrastructural utilities such as electrical power, water to socio-economical aspects such as telecommunications, business, commerce, education-has become critically reliant on communication networks, and particularly on the Internet. With the migration of critical facilities to the Internet, it has become vitally important to ensure the reliability and availability of networks. In this paper, we study various modeling and analysis techniques that can aid in the study of reliability of communication networks. In this regard, we provide background on the modeling techniques (such as reliability block diagrams, fault trees, Markov chains, etc.) and analysis techniques (such as mathematical analytical methods, simulation methods, and formal methods). Apart from providing the necessary background, we also critically evaluate the pros and cons of different approaches, and provide a detailed survey of their applications in communication networks. To the best of our knowledge, this is the first in-depth review of the application of reliability modeling and analysis techniques in communication networks. work, the ability of a network to maintain an acceptable reliability level under extreme environmental conditions and assess the impact of design changes on the reliability of the overall network [17]. Similarly, the availability prediction allows us to evaluate various maintenance design options to achieve the desired availability of the network [18].The qualitative and quantitative reliability analysis requires the selection of an appropriate mathematical modeling and analysis technique. The modeling technique must be able to effectively capture the important parameters of the real system and the analysis technique should be capable of providing insights into the system behavior without running (or executing) the real system. There are numerous techniques that can provide analysis in the early phase, when only initial details are available of the design, and there are other techniques that cater the analysis of the later design phases, when more precise implementation details are available [16]. Some of the most widely used formalisms/techniques for modeling reliability and availability of communication networks are: Reliability Block Diagram (RBD) [19], Fault Tree (FT) [20], and Markov Chain (MC) [21]. Traditionally, the models developed using these techniques are analyzed using analytical methods or simulation tools.Recently, the computer networks community has shown great interest in the utilization of formal methods [22] as a reliability analysis technique for communication networks. Formal methods use mathematical logic to precisely model the system's intended behavior and deploy mathematical reasoning to construct an irrefutable proof that the given system satisfies its requirements. This kind of mathematical modeling and analysis makes formal methods an accurate and rigorous analysis method compared to the traditional a...

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Quantitative Assessment of Distributed Networks through Hybrid Stochastic Modeling

Cited by 4 publications

References 31 publications

Quantification of the Impact of Cyber Attack in Critical Infrastructures

Quantification of the Impact of Cyber Attack in Critical Infrastructures

On the use of dynamic reliability for an accurate modelling of renewable power plants

Reliability modeling and analysis of communication networks

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