|
Q. M. Chen, A. Finzi, T. Mancini, I. Melatti, and E. Tronci. "MILP, Pseudo-Boolean, and OMT Solvers for Optimal Fault-Tolerant Placements of Relay Nodes in Mission Critical Wireless Networks." Fundamenta Informaticae 174 (2020): 229–258. IOS Press. ISSN: 1875-8681. DOI: 10.3233/FI-2020-1941.
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.
|
|
|
Antonio Bucciarelli, and Ivano Salvo. "Totality, Definability and Boolean Circuits." 1443 (1998): 808–819. Springer. DOI: 10.1007/BFb0055104.
Abstract: In the type frame originating from the flat domain of boolean values, we single out elements which are hereditarily total. We show that these elements can be defined, up to total equivalence, by sequential programs. The elements of an equivalence class of the totality equivalence relation (totality class) can be seen as different algorithms for computing a given set-theoretic boolean function. We show that the bottom element of a totality class, which is sequential, corresponds to the most eager algorithm, and the top to the laziest one. Finally we suggest a link between size of totality classes and a well known measure of complexity of boolean functions, namely their sensitivity.
|
|
|
Antonio Bucciarelli, Silvia de Lorenzis, Adolfo Piperno, and Ivano Salvo. "Some Computational Properties of Intersection Types (Extended Abstract)." (1999): 109–118. IEEE Computer Society. DOI: 10.1109/LICS.1999.782598.
Abstract: This paper presents a new method for comparing computation-properties of λ-terms typeable with intersection types with respect to terms typeable with Curry types. In particular, strong normalization and λ-definability are investigated. A translation is introduced from intersection typing derivations to Curry typeable terms; the main feature of the proposed technique is that the translation is preserved by β-reduction. This allows to simulate a computation starting from a term typeable in the intersection discipline by means of a computation starting from a simply typeable term. Our approach naturally leads to prove strong normalization in the intersection system by means of purely syntactical techniques. In addition, the presented method enables us to give a proof of a conjecture proposed by Leivant in 1990, namely that all functions uniformly definable using intersection types are already definable using Curry types.
Keywords: lambda calculusCurry types, intersection types, lambda-definability, lambda-terms, strong normalization
|
|