Title: Combining planning and learning for context aware service composition

Authors: Tarik Fissaa; Mahmoud El Hamlaoui; Hatim Guermah; Hatim Hafiddi; Mahmoud Nassar

Addresses: EVEREST Team, STRS Lab, INPT Rabat, Morocco ' IMS Team, ADMIR Lab, ENSIAS, Mohammed V University in Rabat, Morocco ' IMS Team, ADMIR Lab, ENSIAS, Mohammed V University in Rabat, Morocco ' EVEREST Team, STRS Lab, INPT Rabat, Morocco ' IMS Team, ADMIR Lab, ENSIAS, Mohammed V University in Rabat, Morocco

Abstract: Computing vision introduced by Mark Weiser in the early '90s has defined the basis of what is called now ubiquitous computing. This new discipline results from the convergence of powerful, small and affordable computing devices with networking technologies that connect them all together. Thus, ubiquitous computing has brought a new generation of service-oriented architectures (SOA) based on context-aware services. These architectures provide users with personalised and adapted behaviours by composing multiple services according to their contexts. In this context, the objective of this paper is to propose an approach for context-aware semantic-based services composition. Our contributions are built around following axes: 1) a semantic-based context modelling and context-aware semantic composite service specification; 2) an architecture for context-aware semantic-based services composition using artificial intelligence planning; 3) an intelligent mechanism based on reinforcement learning for context-aware selection in order to deal with dynamicity and uncertain character of modern ubiquitous environment.

Keywords: context awareness; ontology; service composition; semantic web; AI planning; reinforcement learning.

DOI: 10.1504/IJDATS.2021.114673

International Journal of Data Analysis Techniques and Strategies, 2021 Vol.13 No.1/2, pp.151 - 169

Received: 15 Dec 2018
Accepted: 03 May 2019
Published online: 30 Apr 2021 *

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