HierTrain: Fast hierarchical edge AI learning with hybrid parallelism in mobile-edge-cloud computing
Nowadays, deep neural networks (DNNs) are the core enablers for many emerging edge AI
applications. Conventional approaches for training DNNs are generally implemented at …
applications. Conventional approaches for training DNNs are generally implemented at …
A Survey on Collaborative Learning for Intelligent Autonomous Systems
JCSD Anjos, KJ Matteussi, FC Orlandi… - ACM Computing …, 2023 - dl.acm.org
This survey examines approaches to promote Collaborative Learning in distributed systems
for emergent Intelligent Autonomous Systems (IAS). The study involves a literature review of …
for emergent Intelligent Autonomous Systems (IAS). The study involves a literature review of …
Artificial intelligence internet of things for the elderly: From assisted living to health-care monitoring
An aging population is increasingly prevalent in both developed and developing countries,
raising a series of social challenges and economic burdens. In particular, more elderly …
raising a series of social challenges and economic burdens. In particular, more elderly …
Survey on Federated Learning enabling indoor navigation for industry 4.0 in B5G
SH Alsamhi, AV Shvetsov, A Hawbani… - Future Generation …, 2023 - Elsevier
With the expansion of intelligent services and applications powered by Artificial Intelligence
(AI), the Internet of Things (IoT) permeates many aspects of our everyday lives. In order to …
(AI), the Internet of Things (IoT) permeates many aspects of our everyday lives. In order to …
Federated learning for internet of things: Recent advances, taxonomy, and open challenges
The Internet of Things (IoT) will be ripe for the deployment of novel machine learning
algorithm for both network and application management. However, given the presence of …
algorithm for both network and application management. However, given the presence of …
Over-the-air computing for wireless data aggregation in massive IoT
Wireless data aggregation (WDA), referring to aggregating data distributed at devices (eg,
sensors and smartphones), is a common operation in 5G-and-beyond machine-type …
sensors and smartphones), is a common operation in 5G-and-beyond machine-type …
A triple-step asynchronous federated learning mechanism for client activation, interaction optimization, and aggregation enhancement
Federated Learning in asynchronous mode (AFL) is attracting much attention from both
industry and academia to build intelligent cores for various Internet of Things (IoT) systems …
industry and academia to build intelligent cores for various Internet of Things (IoT) systems …
Starfl: Hybrid federated learning architecture for smart urban computing
From facial recognition to autonomous driving, Artificial Intelligence (AI) will transform the
way we live and work over the next couple of decades. Existing AI approaches for urban …
way we live and work over the next couple of decades. Existing AI approaches for urban …
Enterprise IoT modeling: supervised, unsupervised, and reinforcement learning
RK Dhanaraj, K Rajkumar, U Hariharan - Business Intelligence for …, 2020 - Springer
Abstract The Internet of Things (IoT)—the internetworking of physical devices—has been a
significant advancement in recent decades and has been the catalyst for several other …
significant advancement in recent decades and has been the catalyst for several other …
Key advances in pervasive edge computing for industrial Internet of Things in 5G and beyond
This article surveys emerging technologies related to pervasive edge computing (PEC) for
industrial internet-of-things (IIoT) enabled by fifth-generation (5G) and beyond …
industrial internet-of-things (IIoT) enabled by fifth-generation (5G) and beyond …