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

Edge intelligence and, by extension, any distributed computing continuum system will bring
to our future society a plethora of new and useful applications, which will certainly …

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

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

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

Serverless computing has been establishing itself as a compelling paradigm for the
development and of modern cloud-native applications. Serverless represents the next step …

Application workload scheduling in hybrid Cloud-Edge-IoT infrastructures has been
extensively researched over the last years. The recent trend of containerizing application …

In the most popular serverless platform-Knative, dynamic resource allocation is implemented
using horizontal auto-scaling algorithms to create or delete service instances based on …

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

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 …