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Engineering Micro-intelligence at the Edge of CPCS: Design Guidelines

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Internet and Distributed Computing Systems (IDCS 2019)

Abstract

The Intelligent Edge computing paradigm is playing a major role in the design and development of Cyber-Physical and Cloud Systems (CPCS), extending the Cloud and overcoming its limitations so as to better address the issues related with the physical dimension of data—and therefore of the data-aware intelligence (such as context-awareness and real-time responses). Despite the proliferation of research works in this area, a well-founded software engineering approach specifically addressing the distribution of intelligence sources between the Edge and the Cloud is still missing. In this paper we propose some general criteria along with a coherent set of guidelines to follow in the design of distributed intelligence within CPCS, suitably exploiting Edge and Cloud paradigms to effectively enable data intelligence and accounting for both symbolic and sub-symbolic approaches to reasoning. Then, we exploit the notion of micro-intelligence as situated intelligence for Edge computing, promoting the idea of intelligent environment embodying rational processes meant to complement the cognitive process of individuals in order to reduce their cognitive workload and augment their cognitive capabilities. In order to demonstrate the general applicability of our guidelines, we propose Situated Logic Programming (SLP) as the conceptual framework for delivering micro-intelligence in CPCS, and Logic Programming as a Service (LPaaS) as its reference architecture and technological embodiment.

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Notes

  1. 1.

    See http://cyberphysicalsystems.org for a quick and nice overview.

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Correspondence to Roberta Calegari .

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Calegari, R., Ciatto, G., Denti, E., Omicini, A. (2019). Engineering Micro-intelligence at the Edge of CPCS: Design Guidelines. In: Montella, R., Ciaramella, A., Fortino, G., Guerrieri, A., Liotta, A. (eds) Internet and Distributed Computing Systems . IDCS 2019. Lecture Notes in Computer Science(), vol 11874. Springer, Cham. https://doi.org/10.1007/978-3-030-34914-1_25

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  • DOI: https://doi.org/10.1007/978-3-030-34914-1_25

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