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Author Mancini, T.; Tronci, E.; Scialanca, A.; Lanciotti, F.; Finzi, A.; Guarneri, R.; Di Pompeo, S.
Title Optimal Fault-Tolerant Placement of Relay Nodes in a Mission Critical Wireless Network Type Conference Article
Year 2018 Publication (down) 25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018) Abbreviated Journal
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Call Number MCLab @ davi @ Serial 174
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Author Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E.; Gruber, J.; Hayes, B.; Prodanovic, M.; Elmegaard, L.
Title Parallel Statistical Model Checking for Safety Verification in Smart Grids Type Conference Article
Year 2018 Publication (down) 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) Abbreviated Journal
Volume Issue Pages 1-6
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Call Number MCLab @ davi @ mancini-etal:2018:smartgridcomm Serial 170
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Author Driouich, Y.; Parente, M.; Tronci, E.
Title Modeling cyber-physical systems for automatic verification Type Conference Article
Year 2017 Publication (down) 14th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD 2017) Abbreviated Journal
Volume Issue Pages 1-4
Keywords cyber-physical systems;formal verification;maximum power point trackers;power engineering computing;Modelica;automatic verification;complex power electronics systems;cyber-physical systems modeling;distributed maximum power point tracking system;open standard modeling language;Computational modeling;Control systems;Integrated circuit modeling;Mathematical model;Maximum power point trackers;Object oriented modeling;Radiation effects;Automatic Formal Verification;Cyber-Physical Systems;DMPPT;Modeling;Photovoltaic systems;Simulation;System Analysis and Design
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Call Number MCLab @ davi @ ref7981621 Serial 168
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Author Sinisi, S.; Alimguzhin, V.; Mancini, T.; Tronci, E.; Mari, F.; Leeners, B.
Title Optimal Personalised Treatment Computation through In Silico Clinical Trials on Patient Digital Twins Type Journal Article
Year 2020 Publication (down) Abbreviated Journal Fundamenta Informaticae
Volume 174 Issue Pages 283-310
Keywords Artificial Intelligence; Virtual Physiological Human; In Silico Clinical Trials; Simulation; Personalised Medicine; In Silico Treatment Optimisation
Abstract In Silico Clinical Trials (ISCT), i.e. clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine. In this paper we present methods and an algorithm that, by means of extensive computer simulation-based experimental campaigns (ISCT) guided by intelligent search, optimise a pharmacological treatment for an individual patient (precision medicine ). We show the effectiveness of our approach on a case study involving a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction in humans.
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Publisher IOS Press Place of Publication Editor
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ISSN 1875-8681 ISBN Medium
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Call Number MCLab @ davi @ Serial 187
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Author Chen, Q.M.; Finzi, A.; Mancini, T.; Melatti, I.; Tronci, E.
Title MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks Type Journal Article
Year 2020 Publication (down) Abbreviated Journal Fundamenta Informaticae
Volume 174 Issue Pages 229-258
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Abstract In critical infrastructures like airports, much care has to be devoted in protecting radio communication networks from external electromagnetic interference. Protection of such mission-critical radio communication networks is usually tackled by exploiting radiogoniometers: at least three suitably deployed radiogoniometers, and a gateway gathering information from them, permit to monitor and localise sources of electromagnetic emissions that are not supposed to be present in the monitored area. Typically, radiogoniometers are connected to the gateway through relay nodes . As a result, some degree of fault-tolerance for the network of relay nodes is essential in order to offer a reliable monitoring. On the other hand, deployment of relay nodes is typically quite expensive. As a result, we have two conflicting requirements: minimise costs while guaranteeing a given fault-tolerance. In this paper, we address the problem of computing a deployment for relay nodes that minimises the overall cost while at the same time guaranteeing proper working of the network even when some of the relay nodes (up to a given maximum number) become faulty (fault-tolerance ). We show that, by means of a computation-intensive pre-processing on a HPC infrastructure, the above optimisation problem can be encoded as a 0/1 Linear Program, becoming suitable to be approached with standard Artificial Intelligence reasoners like MILP, PB-SAT, and SMT/OMT solvers. Our problem formulation enables us to present experimental results comparing the performance of these three solving technologies on a real case study of a relay node network deployment in areas of the Leonardo da Vinci Airport in Rome, Italy.
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Call Number MCLab @ davi @ Serial 188
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Author Alimguzhin, Vadim; Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico
Title A Map-Reduce Parallel Approach to Automatic Synthesis of Control Software Type Report
Year 2012 Publication (down) Abbreviated Journal
Volume abs/1210.2276 Issue Pages
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Abstract Many Control Systems are indeed Software Based Control Systems, i.e. control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of control software.
Available algorithms and tools (e.g., QKS) may require weeks or even months of computation to synthesize control software for large-size systems. This motivates search for parallel algorithms for control software synthesis.
In this paper, we present a map-reduce style parallel algorithm for control software synthesis when the controlled system (plant) is modeled as discrete time linear hybrid system. Furthermore we present an MPI-based implementation PQKS of our algorithm. To the best of our knowledge, this is the first parallel approach for control software synthesis.
We experimentally show effectiveness of PQKS on two classical control synthesis problems: the inverted pendulum and the multi-input buck DC/DC converter. Experiments show that PQKS efficiency is above 65%. As an example, PQKS requires about 16 hours to complete the synthesis of control software for the pendulum on a cluster with 60 processors, instead of the 25 days needed by the sequential algorithm in QKS.
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Call Number Sapienza @ mari @ Serial 101
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