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2020 Article Open Access OPEN

Computing performability measures in Markov chains by means of matrix functions
Masetti G., Robol L.
We discuss the efficient computation of performance, reliability, and availability measures for Markov chains; these metrics - and the ones obtained by combining them, are often called performability measures. We show that this computational problem can be recasted as the evaluation of a bilinear form induced by appropriate matrix functions, and thus solved by leveraging the fast methods available for this task.Source: Journal of computational and applied mathematics 368 (2020). doi:10.1016/j.cam.2019.112534
DOI: 10.1016/j.cam.2019.112534

See at: arXiv.org e-Print Archive Open Access | Journal of Computational and Applied Mathematics Open Access | Journal of Computational and Applied Mathematics Restricted | Journal of Computational and Applied Mathematics Restricted | Journal of Computational and Applied Mathematics Restricted | Journal of Computational and Applied Mathematics Restricted | CNR ExploRA Restricted | Journal of Computational and Applied Mathematics Restricted | www.sciencedirect.com Restricted | Journal of Computational and Applied Mathematics Restricted


2019 Report Open Access OPEN

Tensor methods for the computation of MTTF in large systems of loosely interconnected components
Masetti G., Robol L.
We are concerned with the computation of the mean-time-to-failure(MTTF) for a large system of loosely interconnected components, mod-eled as continuous time Markov chains. In particular, we show that split-ting the local and synchronization transitions of the smaller subsystemsallows to formulate an algorithm for the computation of the MTTF whichis proven to be linearly convergent. Then, we show how to modify themethod to make it quadratically convergent, thus overcoming the difficul-ties for problems with convergent rate close to1.In addition, it is shown that this decoupling of local and synchroniza-tion transitions allows to easily represent all the matrices and vectors in-volved in the method in the tensor-train (TT) format -- and we providenumerical evidence showing that this allows to treat large problems withup to billions of states -- which would otherwise be unfeasible.Source: ISTI Technical reports, 2019

See at: dcl.isti.cnr.it Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2019 Conference object Open Access OPEN

Distinguishing Violinists and Pianists Based on Their Brain Signals
Coro G., Masetti G., Bonhoeffer P., Betcher M.
Many studies in neuropsychology have highlighted that expert musicians, who started learning music in childhood, present structural differences in their brains with respect to non-musicians. This indicates that early music learning affects the development of the brain. Also, musicians' neuronal activity is different depending on the played instrument and on the expertise. This difference can be analysed by processing electroencephalographic (EEG) signals through Artificial Intelligence models. This paper explores the feasibility to build an automatic model that distinguishes violinists from pianists based only on their brain signals. To this aim, EEG signals of violinists and pianists are recorded while they play classical music pieces and an Artificial Neural Network is trained through a cloud computing platform to build a binary classifier of segments of these signals. Our model has the best classification performance on 20 seconds EEG segments, but this performance depends on the involved musicians' expertise. Also, the brain signals of a cellist are demonstrated to be more similar to violinists' signals than to pianists' signals. In summary, this paper demonstrates that distinctive information is present in the two types of musicians' brain signals, and that this information can be detected even by an automatic model working with a basic EEG equipment.Source: ICANN 2019: Theoretical Neural Computation 28th International Conference on Artificial Neural Networks, pp. 123–137, Monaco di Baviera, 17-19/10/2019
DOI: 10.1007/978-3-030-30487-4_11

See at: ISTI Repository Open Access | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | link.springer.com Restricted | Unknown Repository Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | Unknown Repository Restricted


2019 Article Open Access OPEN

On Extending and Comparing Newton-Raphson Variants for Solving Power-Flow Equations
Dutto S., Masetti G., Chiaradonna S., Di Giandomenico F.
This paper focuses on power-flow equations solutions, based on the Newton-Raphson method. Two major contributions are offered. First, the definition of novel solution variants, resorting to Wirtinger calculus, is attempted. The obtained developments, although original in their formulation, led to already known variants. Despite the impaired originality of the obtained solution, there are significant lessons learned from such an effort. The second major contribution consists of a deep comparison analysis of existing solution strategies, based on complex and real variables, and the Wirtinger based ones, all properly reformulated to allow direct comparison with each other. The goal is to investigate strengths and weaknesses of the addressed techniques in terms of computational effort and convergence rate, which are the most relevant aspects to consider while choosing the approach to employ to solve power-flow equations for a specific power system under study.Source: IEEE transactions on power systems 34 (2019): 2577–2587. doi:10.1109/TPWRS.2019.2897640
DOI: 10.1109/TPWRS.2019.2897640

See at: ieeexplore.ieee.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2019 Conference object Open Access OPEN

Stochastic modeling and evaluation of large interdependent composed models through Kronecker algebra and exponential sums
Masetti G., Robol L., Chiaradonna S., Di Giandomenico F.
The KAES methodology for efficient evaluation of dependability-related properties is proposed. KAES targets systems representable by Stochastic Petri Nets-based models, composed by a large number of submodels where interconnections are managed through synchronization at action level. The core of KAES is a new numerical solution of the underlying CTMC process, based on powerful mathematical techniques, including Kronecker algebra, Tensor Trains and Exponential Sums. Specifically, advancing on existing literature, KAES addresses efficient evaluation of the Mean-Time-To-Absorption in CTMC with absorbing states, exploiting the basic idea to further pursue the symbolic representation of the elements involved in the evaluation process, so to better cope with the problem of state explosion. As a result, computation efficiency is improved, especially when the submodels are loosely interconnected and have small number of states. An instrumental case study is adopted, to show the feasibility of KAES, in particular from memory consumption point of view.Source: The 40th International Conference on Application and Theory of Petri Nets and Concurrency, pp. 47–66, Berlin, 23-28/06/2019
DOI: 10.1007/978-3-030-21571-2_3

See at: link.springer.com Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2019 Part of book or chapter of book Open Access OPEN

A Refined Framework for Model-Based Assessment of Energy Consumption in the Railway Sector
Chiaradonna S., Di Giandomenico F., Masetti G., Basile D.
Awareness and efforts to moderate energy consumption, desirable from both economical and environmental perspectives, are nowadays increasingly pursued. However, when critical sectors are addressed, energy saving should be cautiously tackled, so to not impair stringent dependability properties such contexts typically require. This is the case of the railway transportation system, which is the critical infrastructure this paper focuses on. For this system category, the attitude has been typically to neglect efficient usage of energy sources, motivated by avoiding to put dependability in danger. The new directives, both at national and international level, are going to change this way of thinking. Our study intends to be a useful support to careful energy consumption. In particular, a refined stochastic modeling framework is offered, tailored to the railroad switch heating system, through which analyses can be performed to understand the sophisticated dynamics between the system (both the cyber and physical components) and the surrounding weather conditions.Source: From Software Engineering to Formal Methods and Tools, and Back. Essays Dedicated to Stefania Gnesi on the Occasion of Her 65th Birthday, edited by Maurice H. ter Beek, Alessandro Fantechi, Laura Semini, pp. 481–501, 2019
DOI: 10.1007/978-3-030-30985-5_28

See at: link.springer.com Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted


2019 Doctoral thesis Open Access OPEN

Enhanced power grid evaluation through efficient stochastic model-based analysis
Masetti G.
The electrical infrastructure can be considered nowadays as a meta-critical infrastructure: in fact it is the basis for almost all the critical infrastructures a modern nation can have, such as water, oil, gas and transportation. This implies that its correct operation is a fundamental requirement to the correct operation of the critical infrastructures that depend on it. To allow pervasive control and monitoring towards resilience and performance enhancements, the Smart Grid is emerging as a convergence of information and commu- nication technology with power system engineering. In particular, the ever increasing level of distributed energy resources penetration calls for more and more sophisticated monitoring and control facilities. So, studying the influence of distributed energy resources, of new control policies and ICT on the dependability of distribution grids offers valuable insights on how to improve the design of Smart Grids. In addition to standard dependability measures such as reliability and availability, among greatly relevant measures specifically defined for electrical distribution systems there are the voltage quality and the energy required, but not supplied, by the distribution system. A popular approach to assess electrical distribution specific measures, in presence of failures or attacks to the ICT system and/or to the electric in- frastructure, is the stochastic model-based analysis. Although several studies have been already proposed, the research in this context still faces a number of challenges, mainly due to the need: i) to consider both the ICT sub- system and the controlled electrical infrastructure, to properly account for (inter)dependencies through which operations (and failures/attacks) propa- gate; ii) to model and analyze the SG components at a sufficiently detailed level of abstraction, targeting realistic representation of their structure and behavior in view of promoting accuracy of the assessment itself. Both nomi- nal and a variety of faulty behaviors are to be investigated, since the interest is on assessing resilience and quality related attributes; iii) to tackle realistic segments of SG in terms of topology size, to make the evaluation study of real interest to stakeholders involved in the field. To cope with all these needs results in huge and complex models, to be typically defined in a modular fashion and requiring sophisticated composi- tional operators. Moreover, model solution through simulation-based eval- uation becomes unavoidable in presence of non-Markovian behavior of the involved components, thus preventing the use of analytical approaches. Given the above premises, the stochastic model-based analysis of realistic SG topologies is a research area where further investigations and enhance- ments are highly desirable. In this context, this thesis offers contributions in the direction of promoting efficient evaluation of SG in realistic scenarios from a resilience perspective.

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2018 Report Open Access OPEN

Analyzing a security and reliability model using Krylov methods and matrix functions
Masetti G., Robol L.
It has been recently shown how the computation of performability measures for Markov models can be recasted as the evaluation of a bilinear forminduced by appropriate matrix functions. In view of these results, we show how to analyze a security model, inspired by a real world scenario. The model describes a mobile cyber-physical system of communicating nodes which are subject to security attacks. We take advantage of the properties of matrix functions of block matrices, and provide efficient evaluation methods.Moreover, we show how this new formulation can be used to retrieve interesting theoretical results, which can also rephrased in probabilistic terms.Source: ISTI Technical reports, 2018

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2018 Conference object Open Access OPEN

The role of groundwater modelling for the sustainable management of water resources in a context of climatic change: an experience on a carbonate aquifer in Tuscany (Italy)
Scozzari A., Doveri M., Masetti G., Menichini M., Provenzale A., Raco B., Vivaldo G.
In a growing number of countries, safeguarding drinking water supplies is strictly linked with the sustainable usage of groundwater resources. In the European Union, about 70% of the water destined to the supply network is groundwater, and almost 75% of this source comes from carbonate aquifers. Although groundwater systems can be considered as more resilient to climate change than surface waters, climate change affects them both directly and indirectly. For carbonate aquifers the impact can be very significant, given the high sensitivity of these reservoirs.caused by their karst features. The analysis of hydro-meteorological data over a few decades highlights that also Italy is experiencing a change in the climate regime, with impacts on groundwater yield that are not yet well understood. In this work, we discuss the results of the analysis of data provided by the Tuscan Water Authority (AIT) and GAIA SpA (Integrated Water Service). Data refer to flowrate at springs of the karst aquifer system of the Apuan Alps (northwestern Tuscany). Flowrates trend indicates a slight decline of groundwater yields in this system over the last two decades. A tendency to consume more recharge water through sudden and short flow rate peaks seems also to occur, as a consequence of the increased occurrence of storm events. Data were elaborated in order to study possible empirical relationships between meteorological parameters and groundwater quantity indices, in the wider framework of a research for the development of support tools for the management of the resource under specific climate scenarios. In particular, this work describes the different data-driven approaches experimented with the collected time series, essentially based on multi-variate analysis techniques and on a simplified machine learning scheme based on neural networks. The collected time series were first analyzed by classical statistical and advanced spectral analysis techniques, in order to extract the embedded significant periodicities and trends. Forecasting was thus applied on clean signals only, to reduce the background noise propagation; both empirical models applied to the whole cleaned dataset, and single components projection methodologies were taken into account.Source: EGU General Assembly 2018, Vienna, Austria, 8-13 April 2018

See at: meetingorganizer.copernicus.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2018 Conference object Open Access OPEN

An efficient strategy for model composition in the Möbius modeling environment
Masetti G., Chiaradonna S., Di Giandomenico F., Feddersen B., Sanders W. H.
Möbius is well known as a modeling and evaluation environment for performance and dependability indicators. One of Möbius' key features is the modular and compositional approach to model definition and analysis. In particular, the modeler can define submodels using several formalisms and compose them to form the overall model of the system under analysis. The current algorithm for model composition in Möbius revealed performance issues when large systems are considered (such as in the modeling of realistic segments of energy or transportation infrastructures), due to the chosen data flow scheme. In this paper, a new algorithm for the same composition mechanism is proposed to improve efficiency. A case study is also developed to demonstrate the performance enhancements.Source: 14th European Dependable Computing Conference 2018, pp. 116–119, Iasi, Romania, 10-14 September, 2018
DOI: 10.1109/EDCC.2018.00029

See at: ieeexplore.ieee.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2018 Conference object Open Access OPEN

Supporting CPS modeling through a new method for solving complex non-holomorphic equations
Masetti G., Dutto S., Chiaradonna S., Di Giandomenico F.
Modeling cyber-physical systems (CPSs) for assessment or design support purposes is a complex activity. Capturing all relevant physical, structural or behavioral aspects of the system at hand is a crucial task, which often implies representation of peculiar features/constraints through non-linear equations. Values that fulfill the constraints, described with a domain specific language, are obtained solving the equations through a properly developed solution tool. Only for a limited set of CPSs it is possible to find a straightforward strategy to design the software that solves the constraints equations. In the general case, instead, the modeler has to develop an ad-hoc artifact for each different system. This is the case of non-holomorphic but real analytic complex equations, adopted to represent system components with wave behaviors. In this paper, we present a new approach to develop a software for solving such complex equations following a generative programming strategy, based on Wirtinger derivatives within the Newton-Raphson method.Source: 6th International Conference on Model-Driven Engineering and Software Development, MODELSWARD, pp. 680–688, Madeira, Portugal, 22-24 January, 2018
DOI: 10.5220/0006752306800688

See at: Unknown Repository Open Access | ISTI Repository Open Access | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | www.scitepress.org Restricted


2018 Conference object Restricted

Enhanced dependability evaluation through Krylov methods and matrix functions: the case of load-sharing systems
Masetti G.
Recently, the link between performance and dependability measures for Markovian models and the evaluation of bilinear forms induced by well-known matrix functions has been established. The connection can be exploited to obtain effective and efficient solution methods for allowing in particular the computation of reliability-related measures. In this paper, a reliability model for a load-sharing system is discussed and then solved through Krylov methods generated by the mentioned connection.Source: 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W 2018), pp. 92–95, Luxembourg City, Luxembourg, 25-28/06/2018
DOI: 10.1109/DSN-W.2018.00043
DOI: 10.1109/dsn-w.2018.00043

See at: Unknown Repository Restricted | Unknown Repository Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | Unknown Repository Restricted


2017 Conference object Open Access OPEN

How the availability of free satellite data can improve the observation of critical infrastructures: a proposed application to landfills for municipal solid wastes
Scozzari A., Masetti G., Raco B., Battaglini R.
Landfills for Municipal Solid Wastes (MSW) produce about 20% of the total anthropogenic methane released to the atmosphere. As a consequence, these infrastructures require a systematic and efficient monitoring. Various techniques have been proposed until now for the estimation of biogas production and its release, by using more or less direct measurements, mostly characterised by a low or completely absent invasivity. During the last 13 years, observational data about a MSW disposal site located in Tuscany (Italy) have been collected on a regular basis, consisting in direct measurements of gas flux with the accumulation chamber method, combined with infrared radiometry performed in situ with portable radiometers. The availability of free Landsat imagery and the more recent availability of ASTER data (freely available since April 2016) open new monitoring possibilities, in addition to the in situ measurements described above. In particular, we present the preliminary results of a study about the usability of low resolution thermal infrared scenes to build timeseries describing the overall status of a waste disposal site. This work discusses the possibility to complement in situ measurements with satellite observations, taking benefit from the high revisit time with respect to the timings of in situ campaigns.Source: EGU 2017 - General Assemblies of the European Geosciences Union, Vienna, Austria, 23-28 April 2017

See at: meetingorganizer.copernicus.org Open Access | CNR ExploRA Open Access


2017 Conference object Restricted

Enhanced power grid evaluation through efficient stochastic model-based analysis
Masetti G.
Electrical infrastructures provide services at the basis of a number of application sectors, several of which are critical from the perspective of human life, environment or financials. Following the increasing trend in electricity generation from renewable sources, pushed by the need to meet sustainable energy goals in many countries, more sophisticated control strategies are being adopted to regulate the operation of the electric power system, driving electrical infrastructures towards the so called Smart Grid scenario. It is therefore paramount to be assisted by technologies able to analyze the Smart Grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this context, stochastic model-based analysis are well suited to assess dependability and quality of service related indicators, and continuous improvements in modeling strategies and system models design are required. Thus, my PhD work addresses this topic by contributing to study new Smart Grid scenarios, concerning the advanced interplay between ICT and electrical infrastructures in presence of cyber faults/attacks, define a new modeling approach, based on modularity and composition, and start to study how to improve the electrical grid dynamics representation. In this article these studies are briefly presented and discussed.Source: European Dependable Computing Conference, Ginevra, 4-8/09/2017

See at: arxiv.org Restricted | CNR ExploRA Restricted


2017 Conference object Restricted

A stochastic modeling approach for an efficient dependability evaluation of large systems with non-anonymous interconnected components
Chiaradonna S., Di Giandomenico F., Masetti G.
This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, interconnected with each other according to a variety of topologies. A new efficient replication technique is presented and its implementation is discussed. The goal is to improve the performance of simulation solvers with respect to standard approaches, when employed in the modeling of the addressed class of systems, in particular for loosely interconnected system components (as typically encountered in the electrical or transportation sectors). Effectiveness of the new technique is demonstrated by comparison with a state of the art alternative solution on a representative case study.Source: Internationa Symposium on Software Reliability Engineering, pp. 46–55, Tolosa, Francia, 23-26/10/2017
DOI: 10.1109/ISSRE.2017.17
DOI: 10.1109/issre.2017.17

See at: Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | Unknown Repository Restricted


2017 Conference object Restricted

Model-based simulation in möbius: An efficient approach targeting loosely interconnected components
Masetti G., Chiaradonna S., Di Giandomenico F.
This paper addresses the generation of stochastic models for dependability and performability analysis of complex systems, through automatic replication of template models inside the Möbius modeling framework. The proposed solution is tailored to systems composed by large populations of similar non-anonymous components, loosely interconnected with each other (as typically encountered in the electrical or transportation sectors). The approach is based on models that define channels shared among replicas, used to exchange the values of each state variable of a replica with the other replicas that need to use them. The goal is to improve the performance of simulation based solvers with respect to the existing state-sharing approach, when employed in the modeling of the addressed class of systems. Simulation results for the time overheads induced by both channel-sharing and state-sharing approaches for different system scenarios are presented and discussed. They confirm the expected gain in efficiency of the proposed channel-sharing approach in the addressed system context.Source: European Workshop on Performance Engineering, pp. 184–198, Berlino, 7-8/09/2017
DOI: 10.1007/978-3-319-66583-2_12

See at: Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | www.scopus.com Restricted


2016 Conference object Restricted

A stochastic modelling framework to analyze smart grids control strategies
Chiaradonna S., Di Giandomenico F., Masetti G.
Smart grids provide services at the basis of a number of application sectors, several of which are critical from the perspective of human life, environment or financials. It is therefore paramount to be assisted by technologies able to analyze the smart grid behavior in critical scenarios, e.g. where cyber malfunctions or grid disruptions occur. In this paper, we present a stochastic modelling framework to quantitatively assess representative indicators of the resilience and quality of service of the distribution grid, in presence of accidental faults and malicious attacks. The results from the performed analysis can be exploited to understand the dynamics of failures and to identify potential system vulnerabilities, against which appropriate countermeasures should be developed. The features of the proposed analysis framework are discussed, pointing out the strong non-linearity of the involved physics, the developed solutions to deal with control actions and the definition of indicators under analysis. A case study based on a real-world network is also presented.Source: SEGE 2016 - 4th IEEE International Conference on Smart Energy Grid Engineering, pp. 123–130, Oshawa, Canada, 21-24 August 2016
DOI: 10.1109/SEGE.2016.7589512
DOI: 10.1109/sege.2016.7589512

See at: Unknown Repository Restricted | Unknown Repository Restricted | ieeexplore.ieee.org Restricted | Unknown Repository Restricted | CNR ExploRA Restricted | Unknown Repository Restricted


2016 Conference object Restricted

Exploring equations ordering influence on variants of the Newton-Raphson method
Masetti G., Chiaradonna S., Di Giandomenico F.
Jacobian-free Newton-Raphson methods are general purpose iterative non-linear system solvers. The need to solve non-linear systems is ubiquitous throughout computational physics [1] and Jacobian-free Newton-Raphson methods can offer scalability, super-linear convergence and applicability. In fact, applications span from discretized PDEs [2] to power-flow problems [3]. The focus of this article is on Inexact-Newton-Krylov [2] and Quasi-Inverse-Newton [4] methods. For both of them, we prove analytically that the initial ordering of the equations can have a great impact on the numerical solution, as well as on the number of iterations to reach the solution. We also present numerical results obtained from a simple but representative case study, to quantify the impact of initial equations ordering on a concrete scenario.Source: 2ND International Conference "Numerical Computations: Theory and Algorithms", pp. 090053–090055, Pizzo Calabro, Italy, 19-25 June 2016
DOI: 10.1063/1.4965417

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2016 Conference object Restricted

Analyzing the Impact of Failures in the Electric Power Distribution Grid
Chiaradonna S., Di Giandomenico F., Masetti G.
The electric power system is among the most critical infrastructures, being a support for many of them and for key resource sectors. In fact, the complex, digital world around us requires electric power for fundamental aspects of most business and consumer activities. Therefore, it is paramount to assure the correct power supply. Following the increasing trend in electricity generation from renewable sources, pushed by the need to meet sustainable energy goals in many countries, more sophisticated control strategies are being adopted to regulate the operation of the electric power system. Analyzing their effectiveness and ability to face operation in critical scenarios, such as in presence of failures, is certainly a relevant aspect to investigate. In this paper we focus on the medium voltage grid control and adopt a stochastic modeling framework appropriate to analyze voltage control strategies in presence of selected failure scenarios. The impact of the addressed failures on indicators of voltage stability, representative of the resilience shown by the analyzed system, is assessed in a real-world reference grid. Variability in both generation and loads is covered, to reflect realistic contexts where the addressed system is called to operate.Source: Seventh Latin-American Symposium on Dependable Computing, pp. 99–108, Calì, Colombia, 19-21 October 2016
DOI: 10.1109/LADC.2016.23
DOI: 10.1109/ladc.2016.23

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2016 Conference object Open Access OPEN

Efficient non-anonymous composition operator for modeling complex dependable systems
Chiaradonna S., Di Giandomenico F., Masetti G.
A new model composer is proposed to automatically generate non-anonymous model replicas in the context of performability and dependability evaluation. It is a state-sharing composer that extends the standard anonymous replication composer in order to share the state of a replica among a set of other specific replicas or among the replica and another external model. This new composition operator aims to improve expressiveness and performance with respect to the standard anonymous replicator, namely the one adopted by the Mobius modeling framework.Source: EDCC 2016 - 12nd European Dependable Computing Conference, Gothenburg, Sweden, 5-9 September 2016

See at: arxiv.org Open Access | CNR ExploRA Open Access