In con- trast, representation learning extracts the features (meaningful information) and underlying explanatory factors from the given datasets. With these benefits, using ReL for DCCS to improve its performance by monitoring the devices will increase the utilization efficiency, zero downtime, etc.
This paper discusses the promising role of ReL for DCCS in terms of different aspects, including device condition monitoring, predictions, management of the ...
The DCCS helps increase flexibility with improved performance of hybrid IoT-Edge-Cloud infrastructures. In contrast, representation learning extracts the ...
Aug 17, 2022 · • Representation learning for Distributed computing continuum systems. • Challenges of DCCS's data. • Outcomes of representation learning.
The Promising Role of Representation Learning for Distributed Computing Continuum Systems. Praveen Kumar Donta 1. ,. Schahram Dustdar 1.
The promising role of representation learning for distributed computing continuum systems. In Proceedings of the 2022 IEEE International Conference on ...
The Promising Role of Representation Learning for Distributed Computing Continuum Systems · Praveen Kumar DontaS. Dustdar. Computer Science, Engineering.
Títol: The Promising Role of Representation Learning for Distributed Computing Continuum Systems ; Autors: Donta P.K.; Dustdar S. ; Investigadors/es (PRC): ...
Mar 19, 2023 · Donta, P.K., Dustdar, S.: The promising role of representation learning for distributed computing continuum systems.
The promising role of representation learning for distributed computing continuum systems. Proceedings of the 2022 IEEE International Conference on Service ...