Study on proactive auto scaling for instance through the prediction of ...

Abstract. In this paper, we propose container traffic analyzer (COTA) structure to improve accommodating more network traffic to VMs and to reduce the scale-out ...

Least Traffic Load Balancing (LTLB) algorithm is proposed to solve network traffic imbalance problem and is applied to the Docker based Container ...

Study on proactive auto scaling for instance through the prediction of ...

Study on proactive auto scaling for instance through the prediction of network traffic on the container environment ... To read the full-text of this research, ...

Study on proactive auto scaling for instance through the prediction of ...

Study on proactive auto scaling for instance through the prediction of network traffic on the container environment. / Kim, Won Yong; Lee, Jin ...

Study on proactive auto scaling for instance through the prediction of ...

Dive into the research topics of 'Study on proactive auto scaling for instance through the prediction of network traffic on the container environment'.

Study on proactive auto scaling for instance through ... - BibSonomy

Study on proactive auto scaling for instance through the prediction of network traffic on the container environment. W. Kim, J. Lee, and E. Huh.

A review on prediction based autoscaling techniques for ...

The other issues arising with respect to auto scaling in cloud is handling dynamic number of requests from time to time with efficient usage of existing ...

Effective priority-based resource allocation for proactive auto-scaling ...

To optimize resource allocation, this paper proposes a priority-based auto-scaling framework using machine learning (ML) for workload prediction ...

Proactive Auto-Scaling for Delay-Sensitive IoT Applications Over ...

Proactive Auto-Scaling for Delay-Sensitive IoT Applications Over Edge Clouds ... Abstract: As a new design mechanism for improving service quality ...

A case study of proactive auto-scaling for an ecommerce workload

We need to predict with such an advance that by the time the applica- tion needs to add or remove instances, our algorithm has already decided ...

Proactive auto-scaling for edge computing systems with Kubernetes

The proposed PPA is able to forecast workloads in advance with multiple user-defined/customized metrics and to scale edge computing applications up and down ...

Proactive Auto-scaling For Delay-sensitive Service Providers Over ...

We formulate the Proactive Cloud Resource Scaling Cost Minimization (PCRSCM) problem, in which we take the prediction, purchasing and deployment cost into ...

Online machine learning for auto-scaling in the edge computing

For example, in a video analytics scenario, instead of sending the images to the network core to be processed in the Cloud, auto-scaling enables the processing ...

(PDF) Effective priority-based resource allocation for proactive auto ...

To optimize resource allocation, this paper proposes a priority-based auto-scaling framework using machine learning (ML) for workload prediction ...

Proactive autoscaling for edge computing systems with kubernetes

In this work, we propose a Proactive Pod Autoscaler (PPA) for edge computing applications on Kubernetes. The proposed PPA is able to forecast workloads in ...

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

A proactive auto-scaling mechanism [31], can use past data on workload patterns. Hence, by using a predictive technique on these data, they can estimate the ...

AWS Scaling (Reactive VS Proactive VS Predictive) - Medium

It uses machine learning to predict usage of application in future and thus changes done accordingly. It collects data from your actual EC2 ...

thesis - Mountain Scholar

Amazon introduced predictive scaling to EC2 instances using ... the proactive techniques of auto-scaling and their feasibility of application in Apache STORM.

Proactive Auto-Scaling Technique for Web Applications in Container ...

Proactive auto-scaling techniques in Kubernetes improve utilization by allocating resources based on future workload prediction. However, ...

comparative analysis of predictive models for workload scaling in ...

[14] A SURVEY ON WORKLOAD PREDICTION. MODELS IN CLOUD BASED ON SPOT. INSTANCES FOR PROACTIVE AUTO. SCALING STRATEGY.. Journal of Critical.