Deep reinforcement learning-based computation offloading in uav swarm-enabled edge computing for surveillance applications
The rapid development of the Internet of Things and wireless communication has resulted in
the emergence of many latency-constrained and computation-intensive applications such as …
the emergence of many latency-constrained and computation-intensive applications such as …
Task offloading and trajectory control for UAV-assisted mobile edge computing using deep reinforcement learning
L Zhang, ZY Zhang, L Min, C Tang, HY Zhang… - IEEE …, 2021 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) has been widely employed to support various Internet of
Things (IoT) and mobile applications. By leveraging the advantages of easily deployed and …
Things (IoT) and mobile applications. By leveraging the advantages of easily deployed and …
Multi-objective deep reinforcement learning for computation offloading in UAV-assisted multi-access edge computing
X Liu, ZY Chai, YL Li, YY Cheng, Y Zeng - Information Sciences, 2023 - Elsevier
Unmanned aerial vehicle-assisted multi-access edge computing (UAV-MEC) plays an
important role in some complex environments such as mountainous and disaster areas …
important role in some complex environments such as mountainous and disaster areas …
Enabling efficient scheduling in large-scale UAV-assisted mobile-edge computing via hierarchical reinforcement learning
Due to the high maneuverability and flexibility, unmanned aerial vehicles (UAVs) have been
considered as a promising paradigm to assist mobile edge computing (MEC) in many …
considered as a promising paradigm to assist mobile edge computing (MEC) in many …
Deep Reinforcement Learning Based Computation Offloading in UAV-Assisted Edge Computing
Traditional multi-access edge computing (MEC) often has difficulty processing large
amounts of data in the face of high computationally intensive tasks, so it needs to offload …
amounts of data in the face of high computationally intensive tasks, so it needs to offload …
Distributed deep learning-based task offloading for UAV-enabled mobile edge computing
Unmanned Aerial Vehicle (UAV)-enabled mobile edge computing (MEC) is considered to
offer computational capabilities to the resource-constraints end-users. In this paper, we …
offer computational capabilities to the resource-constraints end-users. In this paper, we …
Computation offloading over multi-UAV MEC network: A distributed deep reinforcement learning approach
Unmanned aerial vehicle (UAV)-assisted computation offloading allows mobile devices
(MDs) to process computation-intensive and latency-sensitive tasks with limited or no …
(MDs) to process computation-intensive and latency-sensitive tasks with limited or no …
Deep reinforcement learning for computation offloading and resource allocation in unmanned-aerial-vehicle assisted edge computing
S Li, X Hu, Y Du - Sensors, 2021 - mdpi.com
Computation offloading technology extends cloud computing to the edge of the access
network close to users, bringing many benefits to terminal devices with limited battery and …
network close to users, bringing many benefits to terminal devices with limited battery and …
A deep learning approach for task offloading in multi-UAV aided mobile edge computing
MA Ebrahim, GA Ebrahim, HK Mohamed… - IEEE …, 2022 - ieeexplore.ieee.org
Computation offloading has proven to be an effective method for facilitating resource-
intensive tasks on IoT mobile edge nodes with limited processing capabilities. Additionally …
intensive tasks on IoT mobile edge nodes with limited processing capabilities. Additionally …
Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing
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 …
by offloading computation-intensive tasks to the edges of wireless networks. Due to the …
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