A survey on computation offloading modeling for edge computing

H Lin, S Zeadally, Z Chen, H Labiod, L Wang - Journal of Network and …, 2020 - Elsevier
As a promising technology, edge computing extends computation, communication, and
storage facilities toward the edge of a network. This new computing paradigm opens up new …

Toward edge intelligence: Multiaccess edge computing for 5G and Internet of Things

Y Liu, M Peng, G Shou, Y Chen… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
To satisfy the increasing demand of mobile data traffic and meet the stringent requirements
of the emerging Internet-of-Things (IoT) applications such as smart city, healthcare, and …

[HTML][HTML] Edge intelligence secure frameworks: Current state and future challenges

E Villar-Rodriguez, MA Pérez, AI Torre-Bastida… - Computers & …, 2023 - Elsevier
At the confluence of two great paradigms such as Edge Computing and Artificial Intelligence,
Edge Intelligence arises. This new concept is about the smart exploitation of Edge …

Mobility-aware joint task scheduling and resource allocation for cooperative mobile edge computing

U Saleem, Y Liu, S Jangsher, Y Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) has emerged as a new paradigm to assist low latency
services by enabling computation offloading at the network edge. Nevertheless, human …

Latency minimization for D2D-enabled partial computation offloading in mobile edge computing

U Saleem, Y Liu, S Jangsher, X Tao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
We consider Device-to-Device (D2D)-enabled mobile edge computing offloading scenario,
where a device can partially offload its computation task to the edge server or exploit the …

An efficient computation offloading management scheme in the densely deployed small cell networks with mobile edge computing

F Guo, H Zhang, H Ji, X Li… - IEEE/ACM Transactions …, 2018 - ieeexplore.ieee.org
To tackle the contradiction between the computation intensive applications and the resource-
hungry mobile user equipments (UEs), mobile edge computing (MEC) has been provisioned …

Optimization of lightweight task offloading strategy for mobile edge computing based on deep reinforcement learning

H Lu, C Gu, F Luo, W Ding, X Liu - Future Generation Computer Systems, 2020 - Elsevier
With the maturity of 5G technology and the popularity of intelligent terminal devices, the
traditional cloud computing service model cannot deal with the explosive growth of business …

Offloading optimization in edge computing for deep-learning-enabled target tracking by internet of UAVs

B Yang, X Cao, C Yuen, L Qian - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The empowering unmanned aerial vehicles (UAVs) have been extensively used in providing
intelligence such as target tracking. In our field experiments, a pretrained convolutional …

Mobile-edge-computing-based hierarchical machine learning tasks distribution for IIoT

B Yang, X Cao, X Li, Q Zhang… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
In this article, we propose a novel framework of mobile edge computing (MEC)-based
hierarchical machine learning (ML) tasks distribution for the Industrial Internet of Things. It is …

Task scheduling for mobile edge computing using genetic algorithm and conflict graphs

AA Al-Habob, OA Dobre, AG Armada… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we consider parallel and sequential task offloading to multiple mobile edge
computing servers. The task consists of a set of inter-dependent sub-tasks, which are …