Space/aerial-assisted computing offloading for IoT applications: A learning-based approach

N Cheng, F Lyu, W Quan, C Zhou, H He… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Internet of Things (IoT) computing offloading is a challenging issue, especially in remote
areas where common edge/cloud infrastructure is unavailable. In this paper, we present a …

MR-DRO: A fast and efficient task offloading algorithm in heterogeneous edge/cloud computing environments

Z Zhang, N Wang, H Wu, C Tang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the rapid development of Internet of Things (IoT) and next-generation communication
technologies, resource-constrained mobile devices (MDs) fail to meet the demand of …

Energy-efficient space–air–ground integrated edge computing for internet of remote things: A federated DRL approach

Y Liu, L Jiang, Q Qi, S Xie - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Space–air–ground integrated edge computing is expecting to provide pervasive
computation services for Internet of Things (IoT), especially in remote areas. However, the …

Edge intelligence: A computational task offloading scheme for dependent IoT application

H Xiao, C Xu, Y Ma, S Yang, L Zhong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Computational offloading, as an effective way to extend the capability of resource-limited
edge devices in Internet of Things (IoT), is considered as a promising emerging paradigm for …

Delay-aware IoT task scheduling in space-air-ground integrated network

C Zhou, W Wu, H He, P Yang, F Lyu… - 2019 IEEE Global …, 2019 - ieeexplore.ieee.org
Due to the versatile networking capability, space-air-ground integrated network (SAGIN)
becomes a prominent future architecture to support the ever-increasing Internet of Things …

Joint multi-task offloading and resource allocation for mobile edge computing systems in satellite iot

F Chai, Q Zhang, H Yao, X Xin, R Gao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
For multi-task mobile edge computing (MEC) systems in satellite Internet of Things (IoT),
there are dependencies between different tasks, which need to be collected and jointly …

Unmanned-aerial-vehicle-assisted computation offloading for mobile edge computing based on deep reinforcement learning

H Wang, H Ke, W Sun - IEEE Access, 2020 - ieeexplore.ieee.org
Users in heterogeneous wireless networks may generate massive amounts of data that are
delay-sensitive or require computation-intensive processing. Owing to computation ability …

Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing

N Zhao, Z Ye, Y Pei, YC Liang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Mobile edge computing can effectively reduce service latency and improve service quality
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …

Optimizing computation offloading in satellite-UAV-served 6G IoT: A deep learning approach

B Mao, F Tang, Y Kawamoto, N Kato - Ieee Network, 2021 - ieeexplore.ieee.org
Satellite networks can provide Internet of Things (IoT) devices in remote areas with
seamless coverage and downlink multicast transmissions. However, the large transmission …

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 …