Results 101 to 110 of about 3,474 (205)

SBPAM: Secure Based Predictive Autoscaling Model For containerized application [PDF]

IJCI International Journal of Computers and Information, 2021
M. Shenawy, Khalid Amin, Hayam Mousa
doaj   +1 more source

Auto-Scaling Techniques in Cloud Computing: Issues and Research Directions

Sensors
In the dynamic world of cloud computing, auto-scaling stands as a beacon of efficiency, dynamically aligning resources with fluctuating demands. This paper presents a comprehensive review of auto-scaling techniques, highlighting significant advancements ...
Saleha Alharthi, Afra Alshamsi, Anoud Alseiari, Abdulmalik Alwarafy   +3 more
doaj   +1 more source

Optimizing Simultaneous Autoscaling for Serverless Cloud Computing

2024 IEEE 17th International Conference on Cloud Computing (CLOUD)
This paper explores resource allocation in serverless cloud computing platforms and proposes an optimization approach for autoscaling systems. Serverless computing relieves users from resource management tasks, enabling focus on application functions. However, dynamic resource allocation and function replication based on changing loads remain crucial ...
Harold J. Ship, Evgeny Shindin, Chen Wang 0039, Diana Arroyo, Asser N. Tantawi   +4 more
openaire   +2 more sources

A Deep Recurrent-Reinforcement Learning Method for Intelligent AutoScaling of Serverless Functions

FaaS introduces a lightweight, function-based cloud execution model that finds its relevance in a range of applications like IoT-edge data processing and anomaly detection.
Agarwal, Siddharth, Rodriguez, Maria A., Buyya, Rajkumar   +2 more
core   +1 more source

Multi-Level ML Based Burst-Aware Autoscaling for SLO Assurance and Cost Efficiency [PDF]

Autoscaling is a technology to automatically scale the resources provided to their applications without human intervention to guarantee runtime Quality of Service (QoS) while saving costs.
Yu, Yang, Tong, Haogang, Meng, Chunyang, Pan, Maolin, Wu, Tianyang   +4 more
core   +1 more source

Enhancing Machine Learning-Based Autoscaling for Cloud Resource Orchestration

Performance and cost-effectiveness are sustained by efficient management of resources in cloud computing. Current autoscaling approaches, when trying to balance between the consumption of resources and QoS requirements, usually fall short and end up ...
Pintye, I., Lovas, R., Kovacs, J.
core   +1 more source

Considerations for transoral robotic surgery with fluorescence imaging: a narrative review. [PDF]

J Robot Surg
Wodeyar AM, Kasten BB, James S, Jeyarajan H, Kane AC, Rosenthal EL, Warram JM.   +6 more
europepmc   +1 more source

Impact of regularization methods and outlier removal on unsupervised sample classification. [PDF]

BMC Bioinformatics
Heckman C.
europepmc   +1 more source

Daedalus: Self-adaptive horizontal autoscaling for resource efficiency of distributed stream processing systems

To maintain a stable Quality of Service (QoS), these systems require a sufficient allocation of resources. At the same time, over-provisioning can result in wasted energy and high operating costs.
Scheinert, Dominik, Kao, Odej, Pfister, Benjamin J. J., Geldenhuys, Morgan K.   +3 more
core   +1 more source

Broad-coverage targeted lipidomics reveals stage-specific lipid metabolic profiles and diagnostic and prognostic marker panels in ischemic stroke. [PDF]

Metabolomics
Huang H, Liu L, Zhao C, Cheng S, Li W, Xu A, Yin X, Xu X.   +7 more
europepmc   +1 more source