Democratizing the Edge: A Pervasive Edge Computing Framework

no code implementations • 1 Jul 2020 • Reza Tourani, Srikathyayani Srikanteswara, Satyajayant Misra, Richard Chow, Lily Yang, Xiruo Liu, Yi Zhang

The needs of emerging applications, such as augmented and virtual reality, federated machine learning, and autonomous driving, have motivated edge computing--the push of computation capabilities to the edge.

Networking and Internet Architecture

Energy Demand Prediction with Federated Learning for Electric Vehicle Networks

no code implementations • 3 Sep 2019 • Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen, Eryk Dutkiewicz, Markus Dominik Mueck, Srikathyayani Srikanteswara

Through experimental results, we show that our proposed approaches can improve the accuracy of energy demand prediction up to 24. 63% and decrease communication overhead by 83. 4% compared with other baseline machine learning algorithms.

BIG-bench Machine Learning Clustering +1