Towards an Internet of Agents model based on Linked Open Data approach

Pablo Pico-Valencia, Juan A. Holgado-Terriza, J. A. Senso

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

11 Citas (Scopus)

Resumen

The Internet of Agents (IoA) is a current approach to the Future Internet that has arisen as an alternative to mitigate the limitations of the Internet of Things (IoT) concerning autonomy, reasoning and social capabilities. The aim of this paper is to present a novel architectural model governed by semantic contracts, published as linked data which describe the main aspects regarding the IoA domain, such as context, social circles, services ecosystems, IoT resources, and real-time restrictions. This proposal introduces some mechanisms such as (i) Linked Open Agents (LOAs) as the main unit of process for coordinating and managing IoT-objects, (ii) Linked Agent Contracts (LACs) as contractual semantic descriptions of entities of IoA ecosystems, (iii) an ontology named IoA-OWL that covers the current main aspects related to the IoA, (iv) a Reference Architecture for the IoA approach driven by LOAs and LACs, and (v) a mechanism for agent-discovery based on semantic descriptors. Both the model and its mechanisms are integrated, in order to improve the semantic interoperability and intelligence in heterogeneous IoT networks controlled by Multi-Agent Systems. Finally, a case study is proposed for a scenario of Ambient Intelligence as a working example of the novel architectural model. In addition, a qualitative and quantitative evaluation is then performed to analyze the applicability, performance, functionality of our proposal. A better performance was obtained for the agent discovery process with our architecture in contrast to JADE Yellow Pages and the Java implementation of the Universal Description, Discovery, and Integration.

Idioma originalInglés
Páginas (desde-hasta)84-131
Número de páginas48
PublicaciónAutonomous Agents and Multi-Agent Systems
Volumen33
N.º1-2
DOI
EstadoPublicada - 14 mar. 2019

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© 2018, Springer Science+Business Media, LLC, part of Springer Nature.

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