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

Nowadays, extremely large amounts of structured and unstructured types of data are stored
in public, private, and hybrid cloud storage using object storage systems. Among these …

Cloud service providers use the concept of" burstable performance instance" that can
temporally ramp up its performance to handle bursty workloads by utilizing spare resources …

Cloud computing conveys the image of a pool of unlimited virtual resources that can be
quickly and easily provisioned to accommodate the user requirements. However, this …

The widespread adoption of public and hybrid clouds, along with elastic resources and
various automation tools for dynamic deployment, has accelerated the rapid provisioning of …

In modern data centers, enterprise cloud instances run not only foreground applications like
web and databases, but also different background services (eg, backup, virus/compliance …

Machine learning based classifiers used quite often for predicting forest cover types, are the
Naïve Bayes classifier, the k-Nearest Neighbors classifier, and the Random forest classifier …

A large number of companies and organizations nowadays are making the decision to
migrate their applications to the cloud. The resources needed to host their applications are …

Large cloud architectures consist of numerous high-performance servers, each hosting a
multitude of Virtual Machines (VMs). Naturally, the server resources for processing and …

Due to unreasonable virtual machine (VM) resource planning and complex load variation,
the waste of VM resource has become a significant issue for many enterprises. Although …