The precise estimation of resource usage is a complex and challenging issue due to the
high variability and dimensionality of heterogeneous service types and dynamic workloads …

Recently, containers have become the primary deployment form for cloud applications.
Predicting container workload accurately is critical to ensure the quality of service (QoS) and …

Current cloud data centers (CDCs) provide highly scalable, flexible, and cost-effective
services to meet the performance needs of emerging applications. It is critical for CDC …

Autoscaling systems provide means to automatically change the resources allocated to a
software system according to the incoming workload and its actual needs. Public cloud …

Artificial intelligence for IT Operations (AIOps) plays a critical role in operating and managing
cloud-native systems and microservice-based applications but is limited by the lack of high …

Accurately forecasting workloads can enable web service providers to achieve proactive
runtime management for applications and ensure service quality and cost efficiency. For …

Resource usage prediction in cloud data centers is critically important. It can improve
providers' service quality and avoid resource wastage and insufficiency. However, the time …

Abstract The combination of Artificial Intelligence and the Internet of Things (AIoT) is
enabling the next economic revolution in which data and immediacy are at the key players …

Load prediction is a critical component of effective resource management in cloud
computing. It ensures optimal performance and efficiency by anticipating overload …

Forecasting workloads and responding promptly with resource scaling and migration is
critical to optimizing operations and enhancing resource management in cloud …