Edge Computing is emerging as a promising solution to meet the ultra-low latency
requirement of data processing at the edge of the Internet, and it is close to end users and …

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 …

In this paper, we introduce an infrastructure in edge computing environment, KubeEdge, to
extend cloud capabilities to the edge. In the new form of cloud architecture, Cloud consists of …

The inference workload redistribution is a technique for evacuating inference requests from
hot edges to idle edges in edge collaborative systems, thereby achieving inference …

Novel applications will require extending traditional cloud computing infrastructure with
compute resources deployed close to the end user. Edge and fog computing tightly …

In Mobile Edge Computing (MEC), each edge server can be configured with only a small
number of functions due to the limited capacity of various resources. Meanwhile, mobile …

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 …

With the proliferation of novel Internet of Things (IoT) mobile applications and advanced
communication technologies, nowadays we are surrounded by ubiquitous sensors and …

Rapid growth of Internet of Things (IoT), and other intelligent devices, introduced different
applications which offer real-time latency features; however, it is difficult to handle the large …

The recent trend in the Internet of Things (IoT) is to distribute and move the computation from
centralized cloud devices to edge devices which are closer to data sources. Researchers …