A survey on computation offloading in edge systems: From the perspective of deep reinforcement learning approaches

P Peng, W Lin, W Wu, H Zhang, S Peng, Q Wu… - Computer Science …, 2024 - Elsevier
Driven by the demand of time-sensitive and data-intensive applications, edge computing
has attracted wide attention as one of the cornerstones of modern service architectures. An …

SNR re-verification-based routing, band, modulation, and spectrum assignment in hybrid C-C+ L optical networks

Q Yao, H Yang, B Bao, J Zhang, H Wang… - Journal of Lightwave …, 2022 - ieeexplore.ieee.org
Band division multiplexing technology is a promising medium-term transitional solution to
deal with the traffic flood, by leveraging the existing optical fiber transmission infrastructure …

Federated hierarchical trust-based interaction scheme for cross-domain industrial IoT

C Li, H Yang, Z Sun, Q Yao, B Bao… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) is considered to be one of the most promising
revolutionary technologies to increase productivity. With the refined development of …

Energy-efficient computation offloading strategy with task priority in cloud assisted multi-access edge computing

Z He, Y Xu, D Liu, W Zhou, K Li - Future Generation Computer Systems, 2023 - Elsevier
Multi-access edge computing (MEC) provides cloud-like services at the edge of the radio
access network close to mobile devices (MDs). This infrastructure can provide low-latency …

Anomaly prediction with hybrid supervised/unsupervised deep learning for elastic optical networks: a multi-index correlative approach

H Yang, Y Wan, Q Yao, B Bao, C Li, Z Sun… - Journal of Lightwave …, 2022 - opg.optica.org
With the emergence of new services, the complex optical network environment makes it
more difficult to predict network anomalies. This paper proposes a multi-index anomaly …

Efficient Task Offloading Strategy for Energy-Constrained Edge Computing Environments: A Hybrid Optimization Approach

D Alsadie - IEEE Access, 2024 - ieeexplore.ieee.org
Edge Computing (EC) has emerged as a pivotal paradigm, offering solutions to address the
challenges posed by latency-sensitive applications and to enhance overall network …

High-precision cluster federated learning for smart home: An edge-cloud collaboration approach

C Li, H Yang, Z Sun, Q Yao, J Zhang, A Yu… - IEEE …, 2023 - ieeexplore.ieee.org
Owing to the strong protection of data privacy, federated learning (FL) has become a key
method to achieve intelligent decision making in smart homes. However, under realistic …

Differentially Private Federated Tensor Completion for Cloud-Edge Collaborative AIoT Data Prediction

Z Yang, B Xiong, K Chen, LT Yang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Artificial Intelligence of Things (AIoT) is an emerging paradigm that integrates artificial
intelligence (AI) and Internet of Things (IoT) technologies to provide intelligent IoT solutions …

Joint optimization of sequential task offloading and service deployment in end-edge-cloud system for energy efficiency

M Teng, X Li, K Zhu - IEEE Transactions on Sustainable …, 2023 - ieeexplore.ieee.org
Intelligent terminal devices (TDs) usually request delay-sensitive and resource-demanding
jobs, which are consisted of many sequential tasks. Mobile edge computing (MEC) offloads …

Emergency task offloading strategy based on cloud-edge-end collaboration for smart factories

X Qu, H Wang - Computer Networks, 2023 - Elsevier
The realization of smart factories is becoming increasingly possible due to the rapid
development of edge computing technology and 5G communication technology. Smart …