Decision Tree with Whale Optimization Algorithm (DT-WOA) for QoS-Based IoT Service Composition

From smart homes to smart cities, the Internet of Things (IoT) has revolutionized our lives by connecting billions of devices into an interconnected network. Each smart device offers specific functions, such as remote door unlocking or sending alerts, which we call IoT services. To meet the complex needs of users, combining multiple atomic IoT services is required, as a single service is often insufficient. The increasing number of IoT services offering similar functionality makes service composition based on Quality of Service (QoS) attributes more challenging. To address this issue, we propose a DT-WOA approach combining a Decision Tree (DT) with the Whale Optimization Algorithm (WOA). We use DT-WOA to find a close-to-optimal solution that meets the QoS user requirements. Simulation results indicate that DT-WOA outperforms the original WOA in terms of fitness value by effectively reducing the search space.

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Published
2024-12-17
DOI
https://doi.org/10.1109/ecte-tech62477.2024.10851053
Primary Topic
IoT and Edge/Fog Computing
Type
article
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article

Decision Tree with Whale Optimization Algorithm (DT-WOA) for QoS-Based IoT Service Composition

Souhila Ait Hacène Ouhadda, Samia Chibani Sadouki, Abdelkamel Tari
IoT and Edge/Fog Computing
article

Decision Tree with Whale Optimization Algorithm (DT-WOA) for QoS-Based IoT Service Composition

Souhila Ait Hacène Ouhadda, Samia Chibani Sadouki, Abdelkamel Tari
article en

Abstract

From smart homes to smart cities, the Internet of Things (IoT) has revolutionized our lives by connecting billions of devices into an interconnected network. Each smart device offers specific functions, such as remote door unlocking or sending alerts, which we call IoT services. To meet the complex needs of users, combining multiple atomic IoT services is required, as a single service is often insufficient. The increasing number of IoT services offering similar functionality makes service composition based on Quality of Service (QoS) attributes more challenging. To address this issue, we propose a DT-WOA approach combining a Decision Tree (DT) with the Whale Optimization Algorithm (WOA). We use DT-WOA to find a close-to-optimal solution that meets the QoS user requirements. Simulation results indicate that DT-WOA outperforms the original WOA in terms of fitness value by effectively reducing the search space.

University of Béjaïa (DZ)
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Openalex Percentile: Top 69%
IoT and Edge/Fog Computing
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