Article Dans Une Revue Future Generation Computer Systems Année : 2026

A coclustering and computational intelligence-based approach for internet-of-things services composition

Résumé

The Internet of Things (IoT) paradigm aims at interconnecting heterogeneous devices, called smart objects and seamlessly offering a multitude of services tailored to the user requirements. With the extremely rapid growth of the number of connected objects, the IoT services composition process becomes an NP-hard challenge due to the very high increase of the number of services offering similar functionalities but that may differ in their Quality of Service (QoS) parameter values. Various approaches have been proposed in the literature to obtain compositions with suboptimal QoS in a reasonable computation time. However, when the number of services and QoS parameters increases, the performance of these approaches is limited in terms of the composition time and/or the QoS utility of the composition. To address these limitations, a coclustering-based approach for QoS-constrained services composition (CoQSC) is proposed to reduce the composition space and improve the composition time as well as the composition utility. Unlike existing services composition algorithms where the composition space is reduced only in terms of the number of candidate services, the CoQSC approach exploits a coclustering method to reduce both the number of candidate services and the number of QoS parameters to be considered in the composition process. This reduction allows the composition process to find suboptimal compositions in a reduced computation time using eight among the most representative and recent computational intelligence (CI) techniques in the literature separately. The formulation of the CoQSC approach is complemented by a complexity analysis. Simulation scenarios show that the CoQSC approach significantly improves the QoS utility of composition and substantially decreases the composition time compared to recent and representative state-of-the-art composition approaches, making it suitable for large-scale IoT service environments.

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Dates et versions

hal-05544995 , version 1 (10-03-2026)

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Citer

Nawel Atmani, Mohamed Essaid Khanouche, Ahror Belaid, Abdelghani Chibani. A coclustering and computational intelligence-based approach for internet-of-things services composition. Future Generation Computer Systems, 2026, 180, pp.108381. ⟨10.1016/j.future.2026.108381⟩. ⟨hal-05544995⟩
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