Tuesday 08 April 2025
The quest for energy efficiency in edge-cloud computing has led researchers to develop a novel framework that optimizes energy consumption across the entire continuum, from edge devices to cloud data centers. The GMB- ECC framework, as it’s called, employs a precision parameter to adjust measurement granularity, ensuring accurate assessments of energy efficiency.
In today’s data-hungry world, edge-cloud computing has emerged as a crucial enabler of real-time processing and analysis. However, the proliferation of devices and applications has resulted in significant energy consumption, leading to concerns about sustainability and cost-effectiveness. To address this challenge, researchers have been exploring various strategies for optimizing energy efficiency.
GMB-ECC takes a holistic approach by integrating hardware and software practices across the edge-cloud continuum. By leveraging a precision parameter, the framework adjusts measurement complexity to accommodate system heterogeneity, ensuring that local changes translate into significant global improvements in energy efficiency.
The framework’s effectiveness was demonstrated through an autonomous intra-logistic use case, where GMB-ECC guided optimization efforts to achieve a 12% reduction in energy consumption without compromising performance. This achievement highlights the framework’s ability to identify inefficiencies and prioritize targeted optimizations.
One of the key advantages of GMB-ECC is its adaptability across diverse applications and industrial scenarios. By incorporating real-world data, researchers can refine their models for greater granularity and accuracy, ensuring that energy efficiency assessments remain relevant and actionable.
The framework’s scalability was also tested in larger systems, with promising results. As edge-cloud computing continues to evolve, GMB-ECC provides a valuable tool for optimizing energy efficiency without sacrificing performance.
While the GMB-ECC framework holds significant potential, its limitations are acknowledged. Future work will focus on extending the framework’s evaluation to diverse industrial scenarios and refining its precision parameter for greater accuracy.
In summary, the development of GMB-ECC marks an important step towards achieving sustainable and cost-effective energy efficiency in edge-cloud computing. By integrating hardware and software practices across the continuum, this framework offers a powerful tool for optimizing energy consumption without compromising performance. As researchers continue to refine and expand its capabilities, GMB-ECC is poised to play a crucial role in shaping the future of edge-cloud computing.
Cite this article: “Unlocking Energy Efficiency in Edge-Cloud Continuum: A Holistic Framework for Guided Measuring and Benchmarking”, The Science Archive, 2025.
Edge-Cloud Computing, Energy Efficiency, Gmb-Ecc Framework, Precision Parameter, Measurement Granularity, Edge Devices, Cloud Data Centers, Autonomous Intra-Logistic, Optimization Efforts, Scalability, Industrial Scenarios.
