Jun 2026· IEEE Conference on Network Softwarization· pp. 469-475· 0 citations· 20 references
Computer Science
Abstract
The Cloud Continuum (CC) concept is to integrate private and public Far-Edge, Edge, and Central Cloud resources and provide uniform access to them for resource customers. The CC idea, by integrating all computing resources into a single domain, improves resource utilisation efficiency and simplifies the placement or migration of Virtual Functions (VFs). The paper focuses on the use of VFs' migration to optimise energy consumption in networks built atop CC. For this purpose, we adopt the CC-based 6G-Cloud project reference architecture, implemented using Kubernetes and cloud-native open-source tools (such as Karmada), as a platform for evaluating different algorithms aimed at optimising energy consumption. The work demonstrates key mechanisms for implementing the Energy Efficiency (EE) use case, showing benefits even with simple optimisation algorithms. Moreover, it highlights both the simplicity of the operational workflows and the resulting energy savings, while revealing important aspects of the EE problem in virtualised environments.
This research proposes a cost-aware, genetic-based task scheduling algorithm tailored for fog-cloud environments, which seeks to improve cost efficiency for real-time applications with strict deadlines, and demonstrates that the proposed algorithm surpasses existing techniques like Round-Robin and Trade-off algorithms.
Youssef Oukissou, Hamza Elhaou, Driss Ait Omar et al.· 1 citation
This work proposes an adaptive resource allocation framework that leverages Digital Twins for real-time system monitoring and integrates Large Language Models to support context-aware decision-making under multi-objective constraints, enabling intelligent workload orchestration across heterogeneous data center environm...
Pedro Henrique Sachete Garcia, A. F. Lorenzon, M. Luizelli et al.· SN Computer Science· 0 citations
The current invention outlines a Java-driven framework for efficient resource management in cloud data centres using the CloudSim simulation environment. The framework presents a predictive auto-scaling mechanism that examines historical traffic patterns to forecast future workload requirements, allowing for predictive...
S. Divya, P. Venkadesh, G. Vasunthraa et al.· International Conference on...· 0 citations
Experiments show that the proposed Hybrid Framework for Joint Optimization of Resource Allocation and Load Balancing that spans two layers in heterogeneous cloud computing systems obtains 25-30% energy savings compared with ordinary methods, significantly reduces p95 latency and also achieves a relatively better Qualit...
Eram Fatma, Nidhi Mishra, Mohammed Abdul Bari· Journal of Intelligent Decis...· 0 citations
The rapid growth of Internet-of-Things (IoT) devices has increased the need for computing support close to end users, particularly for applications that cannot tolerate long processing delays or excessive energy consumption. Fog computing has emerged as a practical extension of the cloud to address these requirements,...
Ashish Bagla, Deepak Dagar, Pratik Srivastava· International Journal For Mu...· 0 citations
This work introduces an emulation framework that allows developers and operators to decide how to deploy networks, computing devices, and applications in a Computing Continuum environment, ensuring compliance with established Quality of Service standards.
José Gómez-delaHiz, J. Herrera, S. Laso et al.· Infocommunications journal· 0 citations
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