A Survey on Graph Neural Networks for Microservice-Based Cloud Applications. [PDF]
Sensors (Basel), 2022 Nguyen HX, Zhu S, Liu M.
europepmc +1 more source
Cloud autoscaling for HTTP/2 workloads
, 2017 loud computing provides cost effective solutions for deploying services and applications. Even though resources can be provisioned on demand, they need to adapt quickly and in a seamless way to the workload intensity and
Maria Carla Calzarossa +7 more
core +1 more source
Adaptive Autoscaling Using Workload Forecasting
, 2021 Cloud computing environments must continuously adapt to fluctuating workload demands while maintaining service reliability and operational efficiency. Traditional static and reactive resource allocation approaches often struggle to respond effectively to
Ramineni, Vishnu +1 more
core
At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives. [PDF]
Sensors (Basel), 2023 Bourechak A +5 more
europepmc +1 more source
Moving Microgrid Hierarchical Control to an SDN-Based Kubernetes Cluster: A Framework for Reliable and Flexible Energy Distribution. [PDF]
Sensors (Basel), 2023 Pérez R +4 more
europepmc +1 more source
Latency Reduction in Vehicular Sensing Applications by Dynamic 5G User Plane Function Allocation with Session Continuity. [PDF]
Sensors (Basel), 2021 Fondo-Ferreiro P +3 more
europepmc +1 more source
Predicting Failures of Autoscaling Distributed Applications
<div> <div>This replication package can be used to fully replicate the results of our paper <em><a href="https://2024.esec-fse.org/details/fse-2024-research-papers/55/Predicting-Failures-of-Autoscaling-Distributed-Applications ...
Lomio, Fracesco +5 more
core +1 more source
FogFrame: a framework for IoT application execution in the fog. [PDF]
PeerJ Comput Sci, 2021 Skarlat O, Schulte S.
europepmc +1 more source
Workload-Aware Autoscaling Support to LLM Inference in Cloud-Native Environments
The growing adoption of Large Language Models (LLM) in production environments and the emerging Model-as-a-Service paradigm pose new challenges for cloud infrastructures.
Sgreccia, Tommaso
core
Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges. [PDF]
Diagnostics (Basel), 2021 El-Rashidy N +4 more
europepmc +1 more source