Deep reinforcement learning based task offloading in SDN-enabled industrial Internet of Things

J Wang, Y Cao, J Liu, Y Zhang - … , AICON 2019, Harbin, China, May 25–26 …, 2019 - Springer
Recent advances in communication and sensor network technologies make Industrial
Internet of Things (IIoT) a major driving force for future industry. Various devices in wide …

BLSO: Broad Learning System-Based Scheme for Adaptive Task Offloading in Industrial IoT

J Chi, Z Cui, Y Lim - 2023 Fourteenth International Conference …, 2023 - ieeexplore.ieee.org
In the Industrial Internet of Things (IIoT) enabled by multi-access edge computing (MEC),
numerous heterogeneous devices are capable to offload computing-heavy tasks to MEC …

Federated Deep Reinforcement Learning-based task offloading system in edge computing environment

H Merakchi, M Bagaa, AO Messaoud… - … 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Nowadays, Internet of Things (IoT) devices are gaining momentum globally. However, due
to their limited size, these devices have limited battery capacity, computational resources …

Multitask multiobjective deep reinforcement learning-based computation offloading method for industrial Internet of Things

J Cai, H Fu, Y Liu - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Edge computing has emerged as a promising paradigm to deploy computing resources to
the network edge. However, most existing computation offloading strategies consider only …

Energy-aware task scheduling and offloading using deep reinforcement learning in SDN-enabled IoT network

B Sellami, A Hakiri, SB Yahia, P Berthou - Computer Networks, 2022 - Elsevier
Abstract The fifth-generation (5G) mobile network services have made tremendous growth in
the Internet of Things (IoT) network. A counters number of battery-powered IoT devices are …

Dynamic task offloading for internet of things in mobile edge computing via deep reinforcement learning

Y Chen, W Gu, K Li - International Journal of Communication …, 2022 - Wiley Online Library
With the development of Internet of Things (IoT), more and more computation‐intensive
tasks are generated by IoT devices. Due to the limitation of battery and computing capacity …

Deep Reinforcement Learning-Based Task Offloading Over In-Network Computing and Multi-Access Edge Computing

Z Ming, Q Guo, H Yu, T Taleb - 2023 International Conference …, 2023 - ieeexplore.ieee.org
With the blooming of information technology and network applications/services, emerging
multi-access edge computing (MEC) and in-network computing (INC) are regarded as key …

Multi-Objective Computation Offloading based on Decentralized Deep Reinforcement Learning in Industrial Internet of Things

Y Zhao, Z Chai, Y Li, H Huang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the increasing scale of industrial equipments, delay and energy consumption have
emerged as critical concerns within the Industrial Internet of Things (Industrial IoT). Mobile …

Cost-AoI Aware Task Scheduling in Industrial IOT Based on Serverless Edge Computing

M Li, Z Wang - 2024 IEEE Wireless Communications and …, 2024 - ieeexplore.ieee.org
Wireless Industrial IoT plays a crucial role in smart factories, where many sensors are rapidly
generating task requests scheduled for timely responses. Maintaining information freshness …

Edge intelligence-driven joint offloading and resource allocation for future 6G industrial Internet of Things

Y Gong, H Yao, J Wang, M Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The 6G will undergo an unprecedented transformation to revolutionize the wireless system
evolution from connected things to connected intelligence. Additionally, data scattered …