Recently, we have been witnessing a rapid increase in the use of machine learning
techniques in self-adaptive systems. Machine learning has been used for a variety of …

In recent years, cloud computing has evolved as an effective, proactive and widely accepted
technology. Scalability is an important characteristic to the success of enterprises involved in …

A goal of cloud service management is to design self-adaptable auto-scaler to react to
workload fluctuations and changing the resources assigned. The key problem is how and …

A cloud is a distributed Internet-based software system providing resources as tiered
services. Through service-orientation and virtualization for resource provisioning, cloud …

Modern software systems are built to be used in dynamic environments using configuration
capabilities to adapt to changes and external uncertainties. In a self-adaptation context, we …

Reinforcement Learning (RL) has demonstrated a great potential for automatically solving
decision-making problems in complex, uncertain environments. RL proposes a …

Predictive autoscaling (autoscaling with workload forecasting) is an important mechanism
that supports autonomous adjustment of computing resources in accordance with fluctuating …

Cloud computing has been one of the most popular distributed computing paradigms.
Elasticity is a crucial feature that distinguishes cloud computing from other distributed …

The pervasiveness and growing complexity of software systems are challenging software
engineering to design systems that can adapt their behavior to withstand unpredictable …

Container-based microservice architectures are emerging as a new approach for building
distributed applications as a collection of independent services that works together. As a …