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Hussein, N.H., Koh, S.P., Yaw, C.T., Tiong, S.K., Benedict, F., Yusaf, T., et al. (2024) SDN-Based VANET Routing: A Comprehensive Survey on Architectures, Protocols, Analysis, and Future Challenges. IEEE Access, 12, 1432-1468.
https://doi.org/10.1109/access.2024.3355313

has been cited by the following article:

• TITLE: Implementation of a New SDN-Expert Architecture for Reducing Energy Consumption in SDNs

  AUTHORS: Lagasane Ouattara Kra, Ahoua Cyrille Aka, Nabongo Diabaté, Olivier Asseu

  KEYWORDS: SDN, SDN-Expert Architecture, Reducing Energy, Energy Consumption

  JOURNAL NAME: Journal of Sensor Technology, Vol.15 No.2, June 20, 2025

  ABSTRACT: Reducing energy consumption in smart networks such as the Internet of Things (IoT), 5G and software-defined networks (SDN) is a major challenge. With the exponential increase in connected devices, network and energy resources are under severe strain. This paper proposes an innovative architecture, named SDN-Expert, integrating an expert system based on artificial intelligence (AI) with a hybrid inference engine combining decision trees and neural networks. This approach dynamically optimizes energy consumption by turning off unused router ports while maintaining optimal Quality of Service (QoS). Extended simulations performed on realistic large-scale network topologies using real-world traffic data (CAIDA datasets) demonstrate substantial energy savings (up to 32% improvement) and clearly illustrate the practicality and competitiveness of our solution compared to existing energy-efficient techniques in SDNs. Finally, we discuss potential applications of the proposed architecture to wireless sensor networks, highlighting its broader applicability and environmental impact.