Driven by the vision of cloud and edge computing as the 5th utility, a major challenge is the
efficient resource management and pricing taking into account incentives and preferences of …

Nowadays, there is an ever-increasing interests in federated learning, which allows end
devices to collaboratively train a global machine learning model in a decentralized …

Cloudlets are resource-rich computing infrastructures of edge computing that are located at
physical proximity of users to provide one-hop, high-bandwidth wireless access to additional …

Emerging applications with low-latency requirements such as real-time analytics, immersive
media applications, and intelligent virtual assistants have rendered Edge Computing as a …

Cloud computing and mobile edge computing techniques supply efficient ways to solve the
contradiction between the increasing computing and storage demands of portable terminals …

Today's distributed computing infrastructures en-compass complex workflows for real-time
data gathering, transferring, storage, and processing, quickly overwhelming centralized …

Many mobile device applications require low end-to-end latency to edge computing
infrastructure when offloading their computation tasks in order to achieve real-time …

Mobile edge computing (MEC) is a technology deployed at the edge of mobile networks to
enhance computation capabilities and reduce transmission distances. It has been …

C loud-a ided m obile e dge n etworks (CAMENs) allow edge servers (ESs) to purchase
resources from remote cloud servers (CSs), while overcoming resource shortage when …

The demand for distributed applications has significantly increased over the past decade,
with improvements in machine learning techniques fueling this growth. These applications …