Results 1 to 10 of about 2,745 (218)

Addressing QoS in Kubernetes Pods Autoscaling. [PDF]

Jiregna Abdissa Olana, Maurizio Giacobbe, Sarah Zanafi, Antonio Puliafito   +3 more
openaire   +1 more source

Autoscaling in heterogeneous Cloud infrastructures

2014
Fernandez, H.J., Guillaume, Pierre, Kielmann, Thilo   +2 more
openaire   +1 more source

Burst-Aware Predictive Autoscaling for Containerized Microservices [PDF]

IEEE Transactions on Services Computing, 2022
This work was partially supported by the European Research Council (ERC) under the EU Horizon 2020 programme (GA 639595), the Spanish Ministry of Economy, Industry and Competitiveness (TIN2015-65316-P and IJCI2016-27485) and the Generalitat de Catalunya (2014-SGR-1051).
Jordá Polo, Muhammad Abdullah, Waheed Iqbal   +2 more
exaly   +6 more sources

Intelligent Autoscaling of Microservices in the Cloud for Real-Time Applications

IEEE Access, 2021
Cloud applications are becoming more containerized in nature. Developing a cloud application based on a microservice architecture imposes different challenges including scalability at the container level.
Ilkyeun Ra
exaly   +3 more sources

An Autoscaling System Based on Predicting the Demand for Resources and Responding to Failure in Forecasting [PDF]

Sensors, 2023
In recent years, the convergence of edge computing and sensor technologies has become a pivotal frontier revolutionizing real-time data processing. In particular, the practice of data acquisition—which encompasses the collection of sensory information in
Jieun Park, Junho Jeong
doaj   +2 more sources

Wide Area Network Autoscaling for Cloud Applications [PDF]

Proceedings of the ACM SIGCOMM 2021 Workshop on Network-Application Integration, 2021
Modern cloud orchestrators like Kubernetes provide a versatile and robust way to host applications at scale. One of their key features is autoscaling, which automatically adjusts cloud resources (compute, memory, storage) in order to adapt to the demands of applications.
Serracanta Pujol, Berta, Paillissé Vilanova, Jordi, Cabellos Aparicio, Alberto, Claiborne, Anna, Rodríguez Natal, Alberto, Ward, Dave, Maino, Fabio   +6 more
core   +10 more sources

MagicScaler: Uncertainty-Aware, Predictive Autoscaling [PDF]

Proceedings of the VLDB Endowment, 2023
Predictive autoscaling is a key enabler for optimizing cloud resource allocation in Alibaba Cloud's computing platforms, which dynamically adjust the Elastic Compute Service (ECS) instances based on predicted user demands to ensure Quality of Service (QoS). However, user demands in the cloud are often highly complex,
Pan, Zhicheng, Wang, Yihang, Zhang, Yingying, Yang, Sean Bin; id_orcid 0000-0001-7819-2290, Cheng, Yunyao; id_orcid 0000-0002-1819-4056, Chen, Peng, Guo, Chenjuan, Wen, Qingsong, Tian, Xiduo, Dou, Yunliang, Zhou, Zhiqiang, Yang, Chengcheng, Zhou, Aoying, Yang, Bin; id_orcid 0000-0002-1658-1079   +13 more
openaire   +4 more sources

ScalableDigitalHealth (SDH): An IoT-Based Scalable Framework for Remote Patient Monitoring [PDF]

Sensors
Addressing the increasing demand for remote patient monitoring, especially among the elderly and mobility-impaired, this study proposes the “ScalableDigitalHealth” (SDH) framework.
Hisham Alasmary
doaj   +2 more sources

Predictive Hybrid Autoscaling for Containerized Applications

IEEE Access, 2022
One of the main challenges in deploying container service is providing the scalability to satisfy the service performance and avoid resource wastage.
Dinh-Dai Vu, Minh-Ngoc Tran, Younghan Kim   +2 more
doaj   +2 more sources

Multilayered Autoscaling Performance Evaluation: Can Virtual Machines and Containers Co–Scale? [PDF]

International Journal of Applied Mathematics and Computer Science, 2019
The wide adoption of cloud computing by businesses is due to several reasons, among which the elasticity of the cloud virtual infrastructure is the definite leader.
Podolskiy Vladimir, Jindal Anshul, Gerndt Michael   +2 more
doaj   +2 more sources