Article: Self-organised map and trust-aware-based quality of service prediction for reliable services selection in distributed computing environment Journal: International Journal of Advanced Intelligence Paradigms (IJAIP) 2024 Vol.28 No.1/2 pp.169 - 192 Abstract: The distributed computing environment allows to provide the outsourced computing services in addition to web-services for IoT and mobile technologies. An emerging research topic is the QoS and security indicator prediction to achieve a reliable service selection that meets user requirements. Collaborative filtering technique is one of the most widely used model in service selection. It is based on similarity computation between users or services. But the main drawback of this method is the lack of data to compute an effective similarity value. Furthermore, malicious users give false feedback which influences the accuracy of prediction. In this work, we propose a novel similarity evaluation model based on self-organisation map to address the problem of data lack and the robust index computation to detect the untrustworthy users. The proposed approach uses a K-means-based average evaluation to determine the tenderness of the data and an offline build-up model to increase computational efficiency. Inderscience Publishers - linking academia, business and industry through research

Title: Self-organised map and trust-aware-based quality of service prediction for reliable services selection in distributed computing environment

Authors: Youcef Ould-Yahia; Meziane Yacoub; Samia Bouzefrane; Hanifa Boucheneb

Addresses: CEDRIC Lab, Conservatoire National des Arts et Métiers, 292 rue Saint Martin 75141, Paris Cédex 03, France ' CEDRIC Lab, Conservatoire National des Arts et Métiers, 292 rue Saint Martin 75141, Paris Cédex 03, France ' CEDRIC Lab, Conservatoire National des Arts et Métiers, 292 rue Saint Martin 75141, Paris Cédex 03, France ' VeriForm Lab, Ecole Polytechnique de Montréal, P.O. Box 6079, Station Centre-ville, Montréal, Qu´ebec, H3C 3A7, Canada

Abstract: The distributed computing environment allows to provide the outsourced computing services in addition to web-services for IoT and mobile technologies. An emerging research topic is the QoS and security indicator prediction to achieve a reliable service selection that meets user requirements. Collaborative filtering technique is one of the most widely used model in service selection. It is based on similarity computation between users or services. But the main drawback of this method is the lack of data to compute an effective similarity value. Furthermore, malicious users give false feedback which influences the accuracy of prediction. In this work, we propose a novel similarity evaluation model based on self-organisation map to address the problem of data lack and the robust index computation to detect the untrustworthy users. The proposed approach uses a K-means-based average evaluation to determine the tenderness of the data and an offline build-up model to increase computational efficiency.

Keywords: distributed computing; web-services; QoS prediction; trust-aware; internet of things; mobile-edge computing; self-organising map; SOM.

DOI: 10.1504/IJAIP.2024.139957

International Journal of Advanced Intelligence Paradigms, 2024 Vol.28 No.1/2, pp.169 - 192

Received: 05 Mar 2019
Accepted: 29 Apr 2019
Published online: 15 Jul 2024 *

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Title: Self-organised map and trust-aware-based quality of service prediction for reliable services selection in distributed computing environment

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