| Records |
| 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 |
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Abbreviated Journal |
Fundamenta Informaticae |
| Volume |
174 |
Issue |
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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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IOS Press |
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1875-8681 |
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no |
| Call Number |
MCLab @ davi @ |
Serial |
188 |
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| Author |
Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Tronci, E. |
| Title |
SyLVaaS: System Level Formal Verification as a Service |
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Journal Article |
| Year |
2016 |
Publication |
Fundamenta Informaticae |
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| Volume |
149 |
Issue |
1-2 |
Pages |
101-132 |
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no |
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MCLab @ davi @ DBLP:journals/fuin/ManciniMMMT16 |
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160 |
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Mancini, T.; Mari, F.; Massini, A.; Melatti, I.; Salvo, I.; Sinisi, S.; Tronci, E.; Ehrig, R.; Röblitz, S.; Leeners, B. |
| Title |
Computing Personalised Treatments through In Silico Clinical Trials. A Case Study on Downregulation in Assisted Reproduction |
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Conference Article |
| Year |
2018 |
Publication |
25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018) |
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no |
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MCLab @ davi @ |
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175 |
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| Author |
Verzino Giovanni ; Cavaliere, Federico; Mari, Federico; Melatti, Igor; Minei, Giovanni; Salvo, Ivano; Yushtein, Yuri; Tronci, Enrico |
| Title |
Model checking driven simulation of sat procedures |
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Conference Article |
| Year |
2012 |
Publication |
Proceedings of 12th International Conference on Space Operations (SpaceOps 2012) |
Abbreviated Journal |
International Conference on Space Operations |
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no |
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Sapienza @ melatti @ |
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117 |
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| Author |
Alimguzhin, Vadim; Mari, Federico; Melatti, Igor; Salvo, Ivano; Tronci, Enrico |
| Title |
On Model Based Synthesis of Embedded Control Software |
Type |
Conference Article |
| Year |
2012 |
Publication |
Proceedings of the 12th International Conference on Embedded Software, EMSOFT 2012, part of the Eighth Embedded Systems Week, ESWeek 2012, Tampere, Finland, October 7-12, 2012 |
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Pages |
227-236 |
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ACM |
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Ahmed Jerraya and Luca P. Carloni and Florence Maraninchi and John Regehr |
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978-1-4503-1425-1 |
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Techreport version can be found at arxiv.org |
Approved |
yes |
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Sapienza @ mari @ emsoft12 |
Serial |
97 |
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| Author |
Mancini, T.; Melatti, I.; Tronci, E. |
| Title |
Any-horizon uniform random sampling and enumeration of constrained scenarios for simulation-based formal verification |
Type |
Journal Article |
| Year |
2021 |
Publication |
IEEE Transactions on Software Engineering |
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Issue |
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Pages |
1-1 |
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| Abstract |
Model-based approaches to the verification of non-terminating Cyber-Physical Systems (CPSs) usually rely on numerical simulation of the System Under Verification (SUV) model under input scenarios of possibly varying duration, chosen among those satisfying given constraints. Such constraints typically stem from requirements (or assumptions) on the SUV inputs and its operational environment as well as from the enforcement of additional conditions aiming at, e.g., prioritising the (often extremely long) verification activity, by, e.g., focusing on scenarios explicitly exercising selected requirements, or avoiding </i>vacuity</i> in their satisfaction. In this setting, the possibility to efficiently sample at random (with a known distribution, e.g., uniformly) within, or to efficiently enumerate (possibly in a uniformly random order) scenarios among those satisfying all the given constraints is a key enabler for the practical viability of the verification process, e.g., via simulation-based statistical model checking. Unfortunately, in case of non-trivial combinations of constraints, iterative approaches like Markovian random walks in the space of sequences of inputs in general fail in extracting scenarios according to a given distribution (e.g., uniformly), and can be very inefficient to produce at all scenarios that are both legal (with respect to SUV assumptions) and of interest (with respect to the additional constraints). For example, in our case studies, up to 91% of the scenarios generated using such iterative approaches would need to be neglected. In this article, we show how, given a set of constraints on the input scenarios succinctly defined by multiple finite memory monitors, a data structure (scenario generator) can be synthesised, from which any-horizon scenarios satisfying the input constraints can be efficiently extracted by (possibly uniform) random sampling or (randomised) enumeration. Our approach enables seamless support to virtually all simulation-based approaches to CPS verification, ranging from simple random testing to statistical model checking and formal (i.e., exhaustive) verification, when a suitable bound on the horizon or an iterative horizon enlargement strategy is defined, as in the spirit of bounded model checking. |
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1939-3520 |
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To appear |
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no |
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MCLab @ davi @ ref9527998 |
Serial |
191 |
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| Author |
Melatti, I.; Mari, F.; Mancini, T.; Prodanovic, M.; Tronci, E. |
| Title |
A Two-Layer Near-Optimal Strategy for Substation Constraint Management via Home Batteries |
Type |
Journal Article |
| Year |
2021 |
Publication |
IEEE Transactions on Industrial Electronics |
Abbreviated Journal |
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Pages |
1-1 |
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Within electrical distribution networks, substation constraints management requires that aggregated power demand from residential users is kept within suitable bounds. Efficiency of substation constraints management can be measured as the reduction of constraints violations w.r.t. unmanaged demand. Home batteries hold the promise of enabling efficient and user-oblivious substation constraints management. Centralized control of home batteries would achieve optimal efficiency. However, it is hardly acceptable by users, since service providers (e.g., utilities or aggregators) would directly control batteries at user premises. Unfortunately, devising efficient hierarchical control strategies, thus overcoming the above problem, is far from easy. We present a novel two-layer control strategy for home batteries that avoids direct control of home devices by the service provider and at the same time yields near-optimal substation constraints management efficiency. Our simulation results on field data from 62 households in Denmark show that the substation constraints management efficiency achieved with our approach is at least 82% of the one obtained with a theoretical optimal centralized strategy. |
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To appear |
Approved |
no |
| Call Number |
MCLab @ davi @ ref9513535 |
Serial |
190 |
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| Author |
Alimguzhin, V.; Mari, F.; Melatti, I.; Salvo, I.; Tronci, E. |
| Title |
Linearising Discrete Time Hybrid Systems |
Type |
Journal Article |
| Year |
2017 |
Publication |
IEEE Transactions on Automatic Control |
Abbreviated Journal |
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| Volume |
62 |
Issue |
10 |
Pages |
5357-5364 |
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Model Based Design approaches for embedded systems aim at generating correct-by-construction control software, guaranteeing that the closed loop system (controller and plant) meets given system level formal specifications. This technical note addresses control synthesis for safety and reachability properties of possibly non-linear discrete time hybrid systems. By means of syntactical transformations that require non-linear terms to be Lipschitz continuous functions, we over-approximate non-linear dynamics with a linear system whose controllers are guaranteed to be controllers of the original system. We evaluate performance of our approach on meaningful control synthesis benchmarks, also comparing it to a state-of-the-art tool. |
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0018-9286 |
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no |
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Sapienza @ mari @ ref7902199 |
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164 |
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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 |
2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) |
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1-6 |
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no |
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MCLab @ davi @ mancini-etal:2018:smartgridcomm |
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170 |
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Tronci, E.; Mancini, T.; Mari, F.; Melatti, I.; Salvo, I.; Prodanovic, M.; Gruber, J. K.; Hayes, B.; Elmegaard, L. |
| Title |
Demand-Aware Price Policy Synthesis and Verification Services for Smart Grids |
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Conference Article |
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2014 |
Publication |
Proceedings of Smart Grid Communications (SmartGridComm), 2014 IEEE International Conference On |
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no |
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Sapienza @ melatti @ |
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121 |
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