Results 11 to 20 of about 912,674 (282)
Predictive auto-scaling with OpenStack Monasca [PDF]
Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing, 2021 Accepted at 2021 IEEE/ACM 14th International Conference on Utility and Cloud Computing (UCC'21)
Lanciano G. +4 more
core +10 more sources
2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2018 Today, auto-scaling solutions are still largely reactive and are based on the load measured on existing nodes nearing a threshold or traffic forecast information provided in advance of a scheduled event. Despite these advancements, events which cause a flash flood of web traffic do not always benefit from this approach to auto-scaling because the ...
Peter Smith +2 more
openaire +3 more sources
Prediction-based auto-scaling of scientific workflows [PDF]
Proceedings of the 9th International Workshop on Middleware for Grids, Clouds and e-Science, 2011 In this paper we propose a novel method for auto-scaling data-centric workflow tasks. Scaling is achieved through a prediction mechanism where the input data load on each task within a workflow is used to compute the estimated task execution time. Through load prediction, the framework can take informed decisions on scaling multiple workflow tasks ...
Reginald Cushing +3 more
core +5 more sources
Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013 This paper presents an implementation -driven by Service Level Agreement (SLA)- of Cloud auto-scaling based on demand. Simulation experiments indicate that our model successfully keeps the best trade-off between SaaS provider profit and customer satisfaction without requiring manual calibration such as in Amazon Auto-Scaling.
Kouki, Yousri, Ledoux, Thomas
openaire +3 more sources
Pervasive Auto-Scaling Method for Improving the Quality of Resource Allocation in Cloud Platforms
Big Data and Cognitive ComputingCloud resource provider deployment at random locations increases operational costs regardless of the application demand intervals. To provide adaptable load balancing under varying application traffic intervals, the auto-scaling concept has been ...
Vimal Raja Rajasekar, G. Santhi
doaj +2 more sources
Enhanced Auto-scaling by using Dynamic scaling policy with Deep learning :LSTM [PDF]
, 2022 Cloud computing is becoming the main pillar of strength for most of the new technologies because of its ability to scale and change. Auto-scaling systems are being used to make this kind of flexibility on demand possible.
Ravikumaraiah, Mohith Srivathsa
core +3 more sources
Enabling modular design of an application-level auto-scaling and orchestration framework using tosca-based application description templates [PDF]
, 2019 This paper presents a novel approach to writing TOSCA templates for application reusability and portability in a modular auto-scaling and orchestration framework (MiCADO).
Kiss, T. +4 more
core +5 more sources
Reinforcement-learning-based, application-agnostic, and explainable auto-scaling in the cloud utilizing high-level SLOs [PDF]
, 2023 Cloud computing is a widely adopted paradigm in the software industry. The ability to adapt the provisioned resources for an application based on the actual demand is called auto-scaling. Auto-scaling is crucial to keep costs within limits while ensuring
Mayerhofer, Robin
core +1 more source
Archival bundle of the code used for "Predictive Auto-scaling with OpenStack Monasca" (UCC 2021)
, 2021 Companion repo of the UCC 2021 paper "Predictive Auto-scaling with OpenStack Monasca" (https://github.com/giacomolanciano/UCC2021-predictive-auto-scaling ...
Bacciu, Davide +4 more
core +1 more source
DEPAS: a decentralized probabilistic algorithm for auto-scaling [PDF]
Computing, 2012 The dynamic provisioning of virtualized resources offered by cloud computing infrastructures allows applications deployed in a cloud environment to automatically increase and decrease the amount of used resources. This capability is called auto-scaling and its main purpose is to automatically adjust the scale of the system that is running the ...
Nicolò Maria Calcavecchia +4 more
openaire +3 more sources