A Sustainability-Aware Monitoring Framework Using Fuzzy Logic Routing for Green Digital Supply Chain Networks

Bandar Z Altubaishe; Zeana Abdijabar; Najlaa Flayyih; Ghassan Samara; Mahmoud Odeh; Ahmad Fadli; Mohammad Kanan

doi:10.31081/dmame8120251687

Authors

Bandar Z Altubaishe Supply Chain Management Department, University of Business and Technology, Jeddah, Saudi Arabia.
Zeana Abdijabar Department of Law, School of Law, Ajman University, Ajman, United Arab Emirates.
Najlaa Flayyih Department of Law, School of Law, Ajman University, Ajman, United Arab Emirates.
Ghassan Samara Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa, Jordan.
Mahmoud Odeh Department of Cybersecurity, Faculty of Information Technology, Zarqa University, Zarqa, Jordan.
Ahmad Fadli Department of Law, School of Law, Ajman University, Ajman, United Arab Emirates.
Mohammad Kanan Department of Industrial Engineering, College of Engineering, University of Business and Technology, Jeddah 21448, Saudi Arabia.

DOI:

https://doi.org/10.31081/dmame8120251687

Keywords:

Green Networking; Sustainable Computer Networks; Energy-Efficient Networking; Carbon-Aware Networking; Intelligent Network Control; Network Energy Optimization; Sustainability Aware Networking.

Abstract

The accelerated expansion of contemporary computer networks, coupled with the proliferation of data-intensive applications, has resulted in a marked escalation in energy demand and associated ecological consequences, thereby positioning sustainability as a central consideration in network architecture and management. Although current green networking approaches predominantly emphasise isolated energy optimisation techniques, they frequently lack coordinated strategic integration across protocol layers and seldom incorporate explicit carbon emission considerations. This study introduces a comprehensive strategic framework for sustainable computer networking that unifies energy optimisation, carbon-conscious operation, and performance retention within an integrated cross-layer design. The proposed framework incorporates sustainability-oriented monitoring, advanced decision-making mechanisms, and adaptive control strategies to facilitate harmonised network functionality in dynamic and heterogeneous operational environments. To support systematic evaluation, formalised energy and carbon quantification models are developed, enabling precise assessment of trade-offs between sustainability objectives and network performance metrics. A detailed simulation-driven analysis is performed under diverse traffic intensities, heterogeneous energy consumption profiles, and dynamically evolving network conditions. Empirical findings indicate that the proposed framework delivers substantial reductions in overall energy usage and carbon emissions when benchmarked against traditional performance-centric and energy-aware methodologies, while preserving comparable levels of throughput, latency, and packet delivery efficiency. These results substantiate that the deliberate incorporation of carbon-aware intelligence, alongside energy optimisation, supports environmentally sustainable networking practices without degrading quality of service. Furthermore, the framework maintains technological neutrality, allowing seamless adaptation and scalability across a broad spectrum of existing and next-generation network infrastructures.

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