Edge AI: On-demand accelerating deep neural network inference via edge computing

E Li, L Zeng, Z Zhou, X Chen - IEEE Transactions on Wireless …, 2019 - ieeexplore.ieee.org
As a key technology of enabling Artificial Intelligence (AI) applications in 5G era, Deep
Neural Networks (DNNs) have quickly attracted widespread attention. However, it is …

Edge-enabled two-stage scheduling based on deep reinforcement learning for internet of everything

X Zhou, W Liang, K Yan, W Li, I Kevin… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Nowadays, the concept of Internet of Everything (IoE) is becoming a hotly discussed topic,
which is playing an increasingly indispensable role in modern intelligent applications. These …

Resource allocation and task scheduling in fog computing and internet of everything environments: A taxonomy, review, and future directions

B Jamil, H Ijaz, M Shojafar, K Munir… - ACM Computing Surveys …, 2022 - dl.acm.org
The Internet of Everything paradigm is being rapidly adopted in develo** applications for
different domains like smart agriculture, smart city, big data streaming, and so on. These IoE …

Deadline-aware and energy-efficient IoT task scheduling in fog computing systems: A semi-greedy approach

S Azizi, M Shojafar, J Abawajy, R Buyya - Journal of network and computer …, 2022 - Elsevier
With the rapid advancement of Internet of Things (IoT) devices, a variety of IoT applications
that require a real-time response and low latency have emerged. Fog computing has …

Smart healthcare IoT applications based on fog computing: architecture, applications and challenges

VK Quy, NV Hau, DV Anh, LA Ngoc - Complex & Intelligent Systems, 2022 - Springer
The history of human development has proven that medical and healthcare applications for
humanity always are the main driving force behind the development of science and …

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 …

Partial offloading scheduling and power allocation for mobile edge computing systems

Z Kuang, L Li, J Gao, L Zhao… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising technique to enhance computation capacity at
the edge of mobile networks. The joint problem of partial offloading decision, offloading …