Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

Continuous integration enables the development of microservices-based applications using
container virtualization technology. Container orchestration systems such as Kubernetes …

The edge–cloud continuum combines heterogeneous resources, which are complex to
manage. Serverless edge computing is a suitable candidate to manage the continuum by …

This article presents our vision on the need of developing new managing technologies to
harness distributed “computing continuum” systems. These systems are concurrently …

The distributed computing continuum systems (DCCS) and representation learning (ReL)
are two diverse computer science technologies with their use cases, applications, and …

The development of cloud computing delivery models inspires the emergence of cloud-
native computing. Cloud-native computing, as the most influential development principle for …

The continuous expansion of Edge computing calls for efficient scheduling techniques for
the employed microservices. However, typical container schedulers often fall short when …

The growing amount of data generated at the edge of the network, eg, by Internet of Things
(IoT) devices, made it indispensable to relocate computational power close to the data …

Distributed computing continuum systems (DCCS) make use of a vast number of computing
devices to process data generated by edge devices such as the Internet of Things and …

The complexity inherent in managing cloud computing systems calls for novel solutions that
can effectively enforce high-level Service Level Objectives (SLOs) promptly. Unfortunately …