Dynamic service placement in multi-access edge computing: A systematic literature review
The advent of new cloud-based applications such as mixed reality, online gaming,
autonomous driving, and healthcare has introduced infrastructure management challenges …
autonomous driving, and healthcare has introduced infrastructure management challenges …
A review of client selection methods in federated learning
Federated learning (FL) is a promising new technology that allows machine learning (ML)
models to be trained locally on edge devices while preserving the privacy of the devices' …
models to be trained locally on edge devices while preserving the privacy of the devices' …
Context-aware online client selection for hierarchical federated learning
Federated Learning (FL) has been considered as an appealing framework to tackle data
privacy issues of mobile devices compared to conventional Machine Learning (ML). Using …
privacy issues of mobile devices compared to conventional Machine Learning (ML). Using …
Edge computing technology enablers: A systematic lecture study
With the increasing stringent QoS constraints (eg, latency, bandwidth, jitter) imposed by
novel applications (eg, e-Health, autonomous vehicles, smart cities, etc.), as well as the …
novel applications (eg, e-Health, autonomous vehicles, smart cities, etc.), as well as the …
Budget-aware user satisfaction maximization on service provisioning in mobile edge computing
Mobile Edge Computing (MEC) promises to provide mobile users with delay-sensitive
services at the edge of network, and each user service request usually is associated with a …
services at the edge of network, and each user service request usually is associated with a …
Digital twin-empowered network planning for multi-tier computing
In this paper, we design a resource management scheme to support stateful applications,
which will be prevalent in sixth generation (6G) networks. Different from stateless …
which will be prevalent in sixth generation (6G) networks. Different from stateless …
Reward-oriented task offloading under limited edge server power for multiaccess edge computing
M Song, Y Lee, K Kim - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
In multiaccess edge computing (MEC), tasks are offloaded from mobile devices to servers at
the edge of the network. This speeds up task processing without incurring the latency …
the edge of the network. This speeds up task processing without incurring the latency …
On the convergence of multi-server federated learning with overlap** area
Multi-server Federated learning (FL) has been considered as a promising solution to
address the limited communication resource problem of single-server FL. We consider a …
address the limited communication resource problem of single-server FL. We consider a …
Task offloading for large-scale asynchronous mobile edge computing: An index policy approach
Mobile-edge computing (MEC) offloads computational tasks from wireless devices to
network edge, and enables real-time information transmission and computing. Most existing …
network edge, and enables real-time information transmission and computing. Most existing …
A computation offloading game for jointly managing local pre-processing time-length and priority selection in edge computing
Edge computing has been regarded as an enabling technology for supporting future smart
applications, such as industrial Internet of Things. In this paper, a novel computation …
applications, such as industrial Internet of Things. In this paper, a novel computation …