[HTML][HTML] Edge AI: a survey
Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …
refers to the practice of doing AI computations near the users at the network's edge, instead …
Serverless computing: state-of-the-art, challenges and opportunities
Serverless computing is growing in popularity by virtue of its lightweight and simplicity of
management. It achieves these merits by reducing the granularity of the computing unit to …
management. It achieves these merits by reducing the granularity of the computing unit to …
[HTML][HTML] {SONIC}: Application-aware data passing for chained serverless applications
The conference papers and full proceedings are available to registered attendees now and
will be available to everyone beginning Wednesday, July 14, 2021. Paper abstracts and …
will be available to everyone beginning Wednesday, July 14, 2021. Paper abstracts and …
[HTML][HTML] Optimized container scheduling for data-intensive serverless edge computing
Operating data-intensive applications on edge systems is challenging, due to the extreme
workload and device heterogeneity, as well as the geographic dispersion of compute and …
workload and device heterogeneity, as well as the geographic dispersion of compute and …
Edge AI for Internet of Energy: Challenges and perspectives
The digital landscape of the Internet of Energy (IoE) is on the brink of a revolutionary
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …
Towards demystifying serverless machine learning training
The appeal of serverless (FaaS) has triggered a growing interest on how to use it in data-
intensive applications such as ETL, query processing, or machine learning (ML). Several …
intensive applications such as ETL, query processing, or machine learning (ML). Several …
Federated learning for medical applications: A taxonomy, current trends, challenges, and future research directions
With the advent of the Internet of Things (IoT), artificial intelligence (AI), machine learning
(ML), and deep learning (DL) algorithms, the landscape of data-driven medical applications …
(ML), and deep learning (DL) algorithms, the landscape of data-driven medical applications …
[HTML][HTML] The pipeline for the continuous development of artificial intelligence models—Current state of research and practice
Companies struggle to continuously develop and deploy Artificial Intelligence (AI) models to
complex production systems due to AI characteristics while assuring quality. To ease the …
complex production systems due to AI characteristics while assuring quality. To ease the …
A decentralized framework for serverless edge computing in the internet of things
C Cicconetti, M Conti… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Serverless computing is becoming widely adopted among cloud providers, thus making
increasingly popular the Function-as-a-Service (FaaS) programming model, where the …
increasingly popular the Function-as-a-Service (FaaS) programming model, where the …
tinyfaas: A lightweight faas platform for edge environments
T Pfandzelter, D Bermbach - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
The Function-as-a-Service (FaaS) model is a great fit for data and event processing in the
Internet of Things (IoT). Sending all data to a cloud-based FaaS platform, however, may …
Internet of Things (IoT). Sending all data to a cloud-based FaaS platform, however, may …