Predictive cloud resource management has been widely adopted to overcome the
limitations of reactive cloud autoscaling. The predictive resource management is highly …

Many predictive approaches have been proposed to overcome the limitations of reactive
autoscaling on clouds. These approaches leverage workload predictors that are usually …

As companies shift from desktop applications to cloud-based software as a service (SaaS)
applications deployed on public clouds, the competition for end-users by cloud providers …

Many predictive resource scaling approaches have been proposed to overcome the
limitations of the conventional reactive approaches most often used in clouds today. In …

Robust forecasts of future resource usage in cloud computing environments enable high
efficiency in resource management solutions, such as autoscaling and overcommitment …

One of the challenges of cloud computing is effective resource management due to its auto-
scaling feature. Prediction techniques have been proposed for cloud computing to improve …

Workload estimation and prediction has become a very relevant research area in the field of
cloud computing. The reason lies in its many benefits, which include QoS (Quality of …

Predicting computing resource usage in any system allows optimized management of
resources. As cloud computing is gaining popularity, the urgency of accurate prediction is …

Cloud computing enables clients to acquire cloud resources dynamically and on demand for
their cloud applications and services. For cloud providers, especially, Software as a Service …

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) …