[HTML][HTML] Edge AI: a survey

R Singh, SS Gill - Internet of Things and Cyber-Physical Systems, 2023 - Elsevier
Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …

Edge-computing-enabled smart cities: A comprehensive survey

LU Khan, I Yaqoob, NH Tran… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Recent years have disclosed a remarkable proliferation of compute-intensive applications in
smart cities. Such applications continuously generate enormous amounts of data which …

Joint service caching and task offloading for mobile edge computing in dense networks

J Xu, L Chen, P Zhou - IEEE INFOCOM 2018-IEEE Conference …, 2018 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized
cloud to the network edge, thereby meeting the latency requirements of many emerging …

Toward massive machine type communications in ultra-dense cellular IoT networks: Current issues and machine learning-assisted solutions

SK Sharma, X Wang - IEEE Communications Surveys & …, 2019 - ieeexplore.ieee.org
The ever-increasing number of resource-constrained machine-type communication (MTC)
devices is leading to the critical challenge of fulfilling diverse communication requirements …

Multi-access edge computing: A survey

A Filali, A Abouaomar, S Cherkaoui, A Kobbane… - IEEE …, 2020 - ieeexplore.ieee.org
Multi-access Edge Computing (MEC) is a key solution that enables operators to open their
networks to new services and IT ecosystems to leverage edge-cloud benefits in their …

Task offloading in fog computing: A survey of algorithms and optimization techniques

N Kumari, A Yadav, PK Jana - Computer Networks, 2022 - Elsevier
The exponential growth in Internet of Things (IoT) devices and the limitations of cloud
computing in terms of latency and quality of service for time-sensitive applications have led …

NOMA-assisted multi-access mobile edge computing: A joint optimization of computation offloading and time allocation

Y Wu, K Ni, C Zhang, LP Qian… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Multi-access mobile edge computing (MEC), which enables mobile users (MUs) to offload
their computation-workloads to the computation-servers located at the edge of cellular …

Energy-efficient edge computing service provisioning for vehicular networks: A consensus ADMM approach

Z Zhou, J Feng, Z Chang, X Shen - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In vehicular networks, in-vehicle user equipment (UE) with limited battery capacity can
achieve opportunistic energy saving by offloading energy-hungry workloads to vehicular …

Resource allocation for ultra-dense networks: A survey, some research issues and challenges

Y Teng, M Liu, FR Yu, VCM Leung… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Driven by the explosive data traffic and new quality of service requirement of mobile users,
the communication industry has been experiencing a new evolution by means of network …

Collaborative service placement for edge computing in dense small cell networks

L Chen, C Shen, P Zhou, J Xu - IEEE Transactions on Mobile …, 2019 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized
cloud to the proximity of data sources, thereby reducing service provision latency and saving …