Deep reinforcement learning for delay-oriented IoT task scheduling in SAGIN
In this article, we investigate a computing task scheduling problem in space-air-ground
integrated network (SAGIN) for delay-oriented Internet of Things (IoT) services. In the …
integrated network (SAGIN) for delay-oriented Internet of Things (IoT) services. In the …
Delay-aware IoT task scheduling in space-air-ground integrated network
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 …
becomes a prominent future architecture to support the ever-increasing Internet of Things …
Multi-agent DRL for task offloading and resource allocation in multi-UAV enabled IoT edge network
The Internet of Things (IoT) edge network has connected lots of heterogeneous smart
devices, thanks to unmanned aerial vehicles (UAVs) and their groundbreaking emerging …
devices, thanks to unmanned aerial vehicles (UAVs) and their groundbreaking emerging …
Deep-graph-based reinforcement learning for joint cruise control and task offloading for aerial edge internet of things (edgeiot)
This article puts forth an aerial edge Internet of Things (EdgeIoT) system, where an
unmanned aerial vehicle (UAV) is employed as a mobile-edge server to process mission …
unmanned aerial vehicle (UAV) is employed as a mobile-edge server to process mission …
Multi-agent learning-based optimal task offloading and UAV trajectory planning for AGIN-power IoT
P Qin, Y Fu, Y Xie, K Wu, X Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
UAV-based air-ground integrated computing networks (AGIN) have gained significant
traction in remote areas for the Power Internet of Things (PIoT). This paper considers an …
traction in remote areas for the Power Internet of Things (PIoT). This paper considers an …
Optimizing computation offloading in satellite-UAV-served 6G IoT: A deep learning approach
Satellite networks can provide Internet of Things (IoT) devices in remote areas with
seamless coverage and downlink multicast transmissions. However, the large transmission …
seamless coverage and downlink multicast transmissions. However, the large transmission …
Computation offloading optimization for UAV-assisted mobile edge computing: a deep deterministic policy gradient approach
Abstract Unmanned Aerial Vehicle (UAV) can play an important role in wireless systems as it
can be deployed flexibly to help improve coverage and quality of communication. In this …
can be deployed flexibly to help improve coverage and quality of communication. In this …
Joint multi-task offloading and resource allocation for mobile edge computing systems in satellite iot
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 …
there are dependencies between different tasks, which need to be collected and jointly …
Deep reinforcement learning-based task scheduling in iot edge computing
Edge computing (EC) has recently emerged as a promising paradigm that supports resource-
hungry Internet of Things (IoT) applications with low latency services at the network edge …
hungry Internet of Things (IoT) applications with low latency services at the network edge …
Energy minimization in UAV-aided networks: Actor-critic learning for constrained scheduling optimization
In unmanned aerial vehicle (UAV) applications, the UAV's limited energy supply and storage
have triggered the development of intelligent energy-conserving scheduling solutions. In this …
have triggered the development of intelligent energy-conserving scheduling solutions. In this …