The compute capability of edge devices is expanding owing to the wide adoption of edge
computing for various application scenarios and specialized hardware explicitly developed …

Collaborative edge computing (CEC) is an emerging paradigm enabling sharing of the
coupled data, computation, and networking resources among heterogeneous geo …

Containers simplify the packaging, deployment and orchestration of diverse workloads on
distributed infrastructure. Containers are primarily used for web applications, databases …

With the fast growing trend in deep learning driven AI services over the past decade, deep
learning, especially the resource-intensive and time-consuming training jobs, have become …

Since emerging edge applications such as Internet of Things (IoT) analytics and augmented
reality have tight latency constraints, hardware AI accelerators have been recently proposed …

Container technology has revolutionized the way software is being packaged and run. The
telecommunications industry, now challenged with the 5G transformation, views containers …

Operating data-intensive applications on edge systems is challenging, due to the extreme
workload and device heterogeneity, as well as the geographic dispersion of compute and …

Motivated by the popularity of edge intelligence, DNN services have been widely deployed
at the edge, posing significant performance pressure on edge servers. How to improve the …

Kubernetes (k8s) has the potential to merge the distributed edge and the cloud but lacks a
scheduling framework specifically for edge-cloud systems. Besides, the hierarchical …

New applications such as intelligent manufacturing, autonomous vehicles and smart cities
drive large-scale deep learning models deployed in the Internet of Things (IoT) edge …