In edge computing, scheduling heterogeneous workloads with diverse resource
requirements is challenging. Besides limited resources, the servers may be overwhelmed …

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

Loosely coupled and highly cohesived microservices running in containers are becoming
the new paradigm for application development. Compared with monolithic applications …

KubeEdge is an open-source platform that orchestrates containerized Internet of Things
(IoT) application services in IoT edge computing environments. Based on Kubernetes, it …

The deployment and management of distributed latency-sensitive applications pose
significant challenges due to the volatile nature of modern Internet of Things (IoT) edge …

Abstract Internet of Vehicles (IoV) enables a wealth of modern vehicular applications, such
as pedestrian detection, real-time video analytics, etc., that can help to improve traffic …

Recently, edge computing is getting attention as a new computing paradigm that is expected
to achieve short-delay and high-throughput task offloading for large scale Internet-of-Things …

As the acceleration gaining for utilizing edge computing in various IoT applications, the
demands of effective task scheduling algorithms are rising alarmingly. Some of the real-time …

We have witnessed a surge in both the big data applications being hosted by an assortment
of cloud vendors, and in the astronomical amount of data they produce and consume on a …

Edge computing has recently emerged as an extension to cloud computing for quality of
service (QoS) provisioning particularly delay guarantee for delay-sensitive applications. By …