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Pretreatment Methods for Enhancing Machine Learning Performance on Metabolomics Data
IEEE AccessPretreatment methods are critical for metabolomics data analysis, yet their impact on machine learning performance remains insufficiently explored.
Rustam
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A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud
, 2022 Predictive autoscaling (autoscaling with workload forecasting) is an important mechanism that supports autonomous adjustment of computing resources in accordance with fluctuating workload demands in the Cloud. In recent works, Reinforcement Learning (RL)
Wang, Shijun +13 more
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, 2023 In the rapidly evolving cloud ecosystem, maintaining service levels while optimizing resource utilization is paramount. Autoscaling is a technique that can be used to dynamically adjust the resources allocated to an application to meet demand.
Shettihalli Anandreddy, Sri Madhan
core
On Optimized Scheduling Scheme for Rapid Pod Autoscaling in Kubernetes
Applied SciencesKubernetes, an open-source project initiated by Google for managing and organizing containers in cloud platforms, has become the preferred choice for deploying large-scale containerized microservice architectures.
Bowen Zhou +3 more
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Self-aware and self-adaptive autoscaling for cloud based services
, 2016 Modern Internet services are increasingly leveraging on cloud computing for flexible, elastic and on-demand provision. Typically, Quality of Service (QoS) of cloud-based services can be tuned using different underlying cloud configurations and resources,
Chen, Tao
core
Practical Efficient Microservice Autoscaling with QoS Assurance
, 2022 Cloud applications are increasingly moving away from monolithic services to agile microservices-based deployments. However, efficient resource management for microservices poses a significant hurdle due to the sheer number of loosely coupled and ...
Islam, Mohammad A. +2 more
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Citation: 'autoscaling' in the IUPAC Compendium of Chemical Terminology, 5th ed.; International Union of Pure and Applied Chemistry; 2025. Online version 5.0.0, 2025. 10.1351/goldbook.10044 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms.
openaire +1 more source
Application of Proximal Policy Optimization for Resource Orchestration in Serverless Edge Computing
ComputersServerless computing is a new cloud computing model suitable for providing services in both large cloud and edge clusters. In edge clusters, the autoscaling functions play a key role on serverless platforms as the dynamic scaling of function instances ...
Mauro Femminella, Gianluca Reali
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Evaluation of cloud autoscaling strategies under different incoming workload patterns
, 2020 Cloud computing provides cost-effective solutions for deploying services and applications. Although resources can be provisioned on demand, they need to adapt quickly and in a seamless way to the workload intensity and characteristics and satisfy at the ...
Maria Carla Calzarossa +7 more
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Fast autoscaling algorithm for cost optimization of container clusters
Journal of Cloud Computing: Advances, Systems and ApplicationsContainer clusters are widely used to execute containerized applications in cloud environments. An essential characteristic implemented by these clusters is autoscaling, which is the ability to automatically adapt the computing resources of a cluster to ...
José María López +5 more
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