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Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
The rapid production of mobile devices along with the wireless applications boom is continuing to evolve daily. This motivates the exploitation of wireless spectrum using multiple Radio Access Technologies (multi-RAT) and ...
On Designing Smart Agents for Service Provisioning in Blockchain-Powered Systems
(
IEEE Computer Society
, 2022 , 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 ...
Energy-Efficient Device Assignment and Task Allocation in Multi-Orchestrator Mobile Edge Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Mobile Edge Learning (MEL) is a decentralized learning paradigm that enables resource-constrained IoT devices to either learn a shared model without sharing the data, or to distribute the learning task with the data to ...
Patient-Driven Network Selection in multi-RAT Health Systems Using Deep Reinforcement Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
The recent pandemic along with the rapid increase in the number of patients that require continuous remote monitoring imposes several challenges to support the high quality of services (QoS) in remote health applications. ...
Zero Touch Realization of Pervasive Artificial Intelligence as a Service in 6G Networks
(
IEEE
, 2023 , Article)
The vision of the upcoming 6G technologies, characterized by ultra-dense networks, low latency, and fast data rate, is to support pervasive artificial intelligence (PAI) using zero touch solutions enabling self-X (e.g., ...
RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning
(2022 , Conference Paper)
The extremely heavy global reliance on IoT devices is causing enormous amounts of data to be gathered and shared in IoT networks. Such data need to efficiently be used in training and deploying of powerful artificially ...
On the Modeling of Reliability in Extreme Edge Computing Systems
(
IEEE
, 2022 , Conference Paper)
Extreme edge computing (EEC) refers to the end-most part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer ...