Trust your local scaler: a continuous, decentralized approach to autoscaling
Autoscaling is a critical component of modern cloud computing environments, improving flexibility, efficiency, and cost-effectiveness. Current approaches use centralized autoscalers that make decisions based on averaged monitoring data of managed service
Lange, Stanislav +5 more
core +1 more source
A scalable scheduling and resource management framework for cloud-native B2B applications. [PDF]
Komarasamy D +3 more
europepmc +1 more source
ScalableDigitalHealth (SDH): An IoT-Based Scalable Framework for Remote Patient Monitoring. [PDF]
Alasmary H.
europepmc +1 more source
Integrating Artificial Intelligence, Electronic Health Records, and Wearables for Predictive, Patient-Centered Decision Support in Healthcare. [PDF]
Fernandes Prabhu D +3 more
europepmc +1 more source
Dynamic machine learning approach for workload prediction in cloud environments. [PDF]
Nashaat M, Moussa W, Rizk R, Saber W.
europepmc +1 more source
Hybrid MLOps framework for automated lifecycle management of adaptive phishing detection models. [PDF]
Reda A, Taie SA, Shaheen ME.
europepmc +1 more source
A scalable machine learning strategy for resource allocation in database. [PDF]
Manhary FN, Mohamed MH, Farouk M.
europepmc +1 more source
A hybrid RL-GA-LSTM-AE framework for energy-aware and SLA-driven task scheduling in cloud computing environments. [PDF]
Narsimhulu B, Kumar TS.
europepmc +1 more source
Practices and Trends of Machine Learning Application in Nanotoxicology. [PDF]
Furxhi I +4 more
europepmc +1 more source
SLA aware deep reinforcement learning for adaptive EdgeCloud task scheduling. [PDF]
Yamsani N, P CR.
europepmc +1 more source

