Now showing items 1-4 of 4
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
On Designing Smart Agents for Service Provisioning in Blockchain-powered Systems
( IEEE Computer Society , 2021 , Article)
Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users Quality of Experience (QoE) and the operation cost endured by providers. These ...
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)
The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an ...
Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
( Elsevier B.V. , 2022 , Article)
Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. It is a promising solution for telemonitoring ...