Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …

In recent years, the landscape of computing paradigms has witnessed a gradual yet
remarkable shift from monolithic computing to distributed and decentralized paradigms such …

Integrating user ends (UEs), edge servers (ESs), and the cloud into end-edge-cloud
computing (EECC) can enhance the utilization of resources and improve quality of …

Intelligent task placement and management of tasks in large-scale fog platforms is
challenging due to the highly volatile nature of modern workload applications and sensitive …

The worldwide adoption of cloud data centers (CDCs) has given rise to the ubiquitous
demand for hosting application services on the cloud. Further, contemporary data-intensive …

The computing continuum extends the high-performance cloud data centers with energy-
efficient and low-latency devices close to the data sources located at the edge of the …

Automated deployment and run-time management of microservices-based applications in
cloud computing environments is relatively well studied with several mature solutions …

Fog Computing is emerging as the dominating paradigm bridging the compute and
connectivity gap between sensing devices and latency-sensitive services. However …

With the increasing number of Internet of Things (IoT) devices, massive amounts of raw data
is being generated. The latency, cost, and other challenges in cloud-based IoT data …

Building a fault-tolerant edge system that can quickly react to node overloads or failures is
challenging due to the unreliability of edge devices and the strict service deadlines of …