In the last few years, we have been witnessing the spread of computing devices getting smaller and smaller (e.g., Smartphones, Smart Devices, Raspberry, etc.), and the production and availability of data get- ting bigger and bigger. In this work we introduce DLV Large Scale (DLV- LS), a framework based on Answer Set Programming (ASP) for perform- ing declarative-based reasoning tasks over data-intensive applications, possibly on Smart Devices. The framework encompasses DLV Mobile Edition (DLV-ME), an ASP based solver for Android systems and Rasp- berry devices, and DLV Enterprise Edition (DLV-EE), an ASP-based platform, accessible by REST interfaces, for large-scale reasoning over Big Data, classical relational database systems, and NoSQL databases. DLV-LS enables Smart Devices to both locally perform reasoning over data generated by their own sensors and properly interact with DLV- EE when more computational power is needed for harder tasks, possibly over bigger centralized data. We present also a real-world application of DLV-LS; the use case consists of a tourist navigator that calculates the best routes and optimizes a tour of a tourist under custom-defined time constraints.

Smart Devices and Large Scale Reasoning via ASP: Tools and Applications

Kristian Reale
;
Francesco Calimeri;Nicola Leone;Francesco Ricca
2022-01-01

Abstract

In the last few years, we have been witnessing the spread of computing devices getting smaller and smaller (e.g., Smartphones, Smart Devices, Raspberry, etc.), and the production and availability of data get- ting bigger and bigger. In this work we introduce DLV Large Scale (DLV- LS), a framework based on Answer Set Programming (ASP) for perform- ing declarative-based reasoning tasks over data-intensive applications, possibly on Smart Devices. The framework encompasses DLV Mobile Edition (DLV-ME), an ASP based solver for Android systems and Rasp- berry devices, and DLV Enterprise Edition (DLV-EE), an ASP-based platform, accessible by REST interfaces, for large-scale reasoning over Big Data, classical relational database systems, and NoSQL databases. DLV-LS enables Smart Devices to both locally perform reasoning over data generated by their own sensors and properly interact with DLV- EE when more computational power is needed for harder tasks, possibly over bigger centralized data. We present also a real-world application of DLV-LS; the use case consists of a tourist navigator that calculates the best routes and optimizes a tour of a tourist under custom-defined time constraints.
2022
978-3-030-94478-0
Large scale reasoning
Smart devices
Answer set programming
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/327910
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