Resource allocation of industry 4.0 micro-service applications across serverless fog federation
RF Hussain, MA Salehi - Future Generation Computer Systems, 2024 - Elsevier
The Industry 4.0 revolution has been made possible via AI-based applications (eg, for
automation and maintenance) deployed on the serverless edge (aka fog) computing …
automation and maintenance) deployed on the serverless edge (aka fog) computing …
Is Machine Learning Necessary for Cloud Resource Usage Forecasting?
Robust forecasts of future resource usage in cloud computing environments enable high
efficiency in resource management solutions, such as autoscaling and overcommitment …
efficiency in resource management solutions, such as autoscaling and overcommitment …
[HTML][HTML] Challenges and opportunities of using transformer-based multi-task learning in NLP through ML lifecycle: A position paper
L Torbarina, T Ferkovic, L Roguski, V Mihelcic… - Natural Language …, 2024 - Elsevier
The increasing adoption of natural language processing (NLP) models across industries has
led to practitioners' need for machine learning (ML) systems to handle these models …
led to practitioners' need for machine learning (ML) systems to handle these models …
IPA: Inference Pipeline Adaptation to Achieve High Accuracy and Cost-Efficiency
Efficiently optimizing multi-model inference pipelines for fast, accurate, and cost-effective
inference is a crucial challenge in ML production systems, given their tight end-to-end …
inference is a crucial challenge in ML production systems, given their tight end-to-end …
CAMEO: A Causal Transfer Learning Approach for Performance Optimization of Configurable Computer Systems
Modern computer systems are highly configurable, with hundreds of configuration options
that interact, resulting in an enormous configuration space. As a result, optimizing …
that interact, resulting in an enormous configuration space. As a result, optimizing …
Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling
Mobile and IoT applications increasingly adopt deep learning inference to provide
intelligence. Inference requests are typically sent to a cloud infrastructure over a wireless …
intelligence. Inference requests are typically sent to a cloud infrastructure over a wireless …
A Tale of Two Scales: Reconciling Horizontal and Vertical Scaling for Inference Serving Systems
Inference serving is of great importance in deploying machine learning models in real-world
applications, ensuring efficient processing and quick responses to inference requests …
applications, ensuring efficient processing and quick responses to inference requests …
Smart-Kube: Energy-Aware and Fair Kubernetes Job Scheduler Using Deep Reinforcement Learning
One of the most challenging problems in the popular orchestration framework Kubernetes is
assigning sufficient resources to containers to operate at a required level while also …
assigning sufficient resources to containers to operate at a required level while also …
Machine Learning in Container Orchestration Systems: Applications and Deployment
S Ghafouri - 2024 - qmro.qmul.ac.uk
In recent years, machine learning methods, particularly Reinforcement Learning, have
become increasingly popular for addressing resource management challenges, notably in …
become increasingly popular for addressing resource management challenges, notably in …
[PDF][PDF] Resource Allocation of Industry 4.0 Micro-Service Applications across Serverless Fog Federation
RF Hussaina, MA Salehib - hpcclab.org
The Industry 4.0 revolution has been made possible via AI-based applications (eg, for
automation and maintenance) deployed on the serverless edge (aka fog) computing …
automation and maintenance) deployed on the serverless edge (aka fog) computing …