6GSoft: Software for Edge-to-Cloud Continuum
In the era of 6G, developing and managing software requires cutting-edge software engineering (SE) theories and practices tailored for such complexity across a vast number of connected edge devices. Our project aims to lead the development of sustainable methods and energy-efficient orchestration models specifically for edge environments, enhancing architectural support driven by AI for contemporary edge-to-cloud continuum computing. This initiative seeks to position Finland at the forefront of the 6G landscape, focusing on sophisticated edge orchestration and robust software architectures to optimize the performance and scalability of edge networks. Collaborating with leading Finnish universities and companies, the project emphasizes deep industry-academia collaboration and international expertise to address critical challenges in edge orchestration and software architecture, aiming to drive significant advancements in software productivity and market impact.
Code (0)
등록된 구현이 없습니다.
Tasks
PositionSimilar Papers 제목 키워드 기반
Reproducible Performance Optimization of Complex Applications on the Edge-to-Cloud Continuum
In more and more application areas, we are witnessing the emergence of complex workflows that combine computing, analytics and learning. They often require a hybrid execution infrastructure with IoT devices interconnecte…
Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration
Future AI applications require performance, reliability and privacy that the existing, cloud-dependant system architectures cannot provide. In this article, we study orchestration in the device-edge-cloud continuum, and …
Cloud ComputingSigsoftmax: Reanalysis of the Softmax Bottleneck
Softmax is an output activation function for modeling categorical probability distributions in many applications of deep learning. However, a recent study revealed that softmax can be a bottleneck of representational cap…
Language ModelingLanguage ModellingDistributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review
The explosion of data volumes generated by an increasing number of applications is strongly impacting the evolution of distributed digital infrastructures for data analytics and machine learning (ML). While data analytic…
Systematic Literature ReviewDownsides of Smartness Across Edge-Cloud Continuum in Modern Industry
The fast pace of modern AI is rapidly transforming traditional industrial systems into vast, intelligent and potentially unmanned autonomous operational environments driven by AI-based solutions. These solutions leverage…
Reinforcement Learning