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

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

In this respect, this research proposes a priority-based resource allocation framework for proactive auto-scaling, with hybrid approaches that ...

(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 ...

Optimizing resource allocation using proactive scaling with ...

However, existing research suggests that Kubernetes' reactive scaling methods initiate scaling actions based on predefined thresholds, which potentially causes ...

Adaptive workload prediction for proactive auto scaling in PaaS ...

Abstract: Elasticity is a key feature of cloud computing where resources are allocated and released according to user demands. Reactive auto scaling, in ...

Optimizing resource allocation using proactive scaling with ... - CoLab

A Time Series-Based Approach to Elastic Kubernetes Scaling. Yuan H., Liao S. · citations by CoLab: 3 ,. Open Access. Open access. , PDF | ...

(PDF) Proactive Auto-scaling Approach Of Production Applications ...

Another option would be automating the resource provisioning processing using automated rules. Once such rules are met, the hosting environment will scale the ...

Proactive Scaling Strategies for Cost-Efficient Hyperparameter ...

Autoscaling is an essential strategy for allocating only the required resources based on a workload in cloud computing to minimize costs. Based on the ...

Using AI for Dynamic Resource Allocation and Scaling in Managed ...

These models can anticipate traffic spikes based on historical data and current trends, allowing the system to scale resources up or down ...

Instance Type Selection in Proactive Horizontal Auto-Scaling

In this paper, we study the impact that an efficient instance type selection based ... resources has on the performance of proactive auto-scaling. This ...

Workload and Resource Aware Proactive Auto-Scaler for PaaS Cloud

Second, auto-scaler should allocate the right amount of resources to the system in a cost-effective manner while maintaining its QoS. Auto- scalers use two main ...

Proactive Resource Allocation Policy for Microsoft Azure Cognitive ...

In addition to the current resource demand, the proactive policy takes the typical resource usage patterns into account. We gained the following ...

Proactive Scaling Strategies for Cost-Efficient Hyperparameter ...

By employing machine learning algorithms to analyze workload patterns and predict future requirements, cloud infrastructure can automatically allocate resources ...

Heterogeneity-Aware Proactive Elastic Resource Allocation for ...

Furthermore, we present a proactive server elastic scaling method that senses workload features, including workload level, trend, and magnitude changes, and ...

Leveraging Interpretability in the Transformer to Automate the ... - arXiv

Figure 1 presents our approach to proactive autoscaling of cloud resources. The approach starts with using the TFT to predict an end-to-end ...

Adaptive Workload Prediction for Proactive Auto Scaling in PaaS ...

Abstract—Elasticity is a key feature of cloud computing where resources are allocated and released according to user demands. ... Nevertheless, the effectiveness ...

Proactive Resource Allocation Policy for Microsoft Azure Cognitive ...

Given that scaling mechanisms are not in- stantaneous, the reactive policy may introduce delays to latency-sensitive customer workloads and waste op- erational ...

Proactive AI Strategies for Startups Scaling | Restackio

... resource allocation dynamically. Techniques such as reactive and predictive auto-scaling can help ensure that resources are allocated based on real-time demand.

Proactive Resource Autoscaling Scheme Based on SCINet for High ...

The container resource autoscaling technique provides scalability to cloud services composed of microservice architecture in a cloud-native computing ...

GRAF: A Graph Neural Network based Proactive Resource ...

In addition, an efficient resource allocation framework should allocate resources to every microservices on the application proac- tively, according to the ...

RLPRAF: Reinforcement Learning-Based Proactive Resource ... - DOI

Hence automated resource provisioning becomes an effective method to deal with such workload fluctuations. The aforementioned problems can also be resolved by ...