Reinforcement learning in the sky: A survey on enabling intelligence in ntn-based communications
Non terrestrial networks (NTN) involving 'in the sky'objects such as low-earth orbit satellites,
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
high altitude platform systems (HAPs) and Unmanned Aerial Vehicles (UAVs) are expected …
Joint secure offloading and resource allocation for vehicular edge computing network: A multi-agent deep reinforcement learning approach
The mobile edge computing (MEC) technology can simultaneously provide high-speed
computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) …
computing services for multiple vehicular users (VUs) in vehicular edge computing (VEC) …
Contemporary advances in multi-access edge computing: A survey of fundamentals, architecture, technologies, deployment cases, security, challenges, and directions
M Mahbub, RM Shubair - Journal of Network and Computer Applications, 2023 - Elsevier
With advancements of cloud technologies Multi-Access Edge Computing (MEC) emerged as
a remarkable edge-cloud technology to provide computing facilities to resource-restrained …
a remarkable edge-cloud technology to provide computing facilities to resource-restrained …
Enhancing resilience in mobile edge computing under processing uncertainty
Task offloading is a powerful tool in Mobile Edge Computing (MEC). However, in many
practical scenarios, the number of required processing cycles of a task is unknown …
practical scenarios, the number of required processing cycles of a task is unknown …
D2D-Assisted Multi-User Cooperative Partial Offloading in MEC Based on Deep Reinforcement Learning
Mobile edge computing (MEC) and device-to-device (D2D) communication can alleviate the
resource constraints of mobile devices and reduce communication latency. In this paper, we …
resource constraints of mobile devices and reduce communication latency. In this paper, we …
A survey on deep reinforcement learning-driven task offloading in aerial access networks
Internet of Things computation offloading is a challenging problem, particularly in distant
places where mobile edge computing (MEC) or cloud infrastructure is absent. Fortunately …
places where mobile edge computing (MEC) or cloud infrastructure is absent. Fortunately …
Federated Deep Reinforcement Learning for Joint AeBSs Deployment and Computation Offloading in Aerial Edge Computing Network
L Liu, Y Zhao, F Qi, F Zhou, W Xie, H He, H Zheng - Electronics, 2022 - mdpi.com
In the 6G aerial network, all aerial communication nodes have computing and storage
functions and can perform real-time wireless signal processing and resource management …
functions and can perform real-time wireless signal processing and resource management …
Deep reinforcement learning-based partial task offloading in high altitude platform-aided vehicular networks
Compared with traditional terrestrial access networks, a mobile edge computing-enabled
aerial access network is a potential paradigm for performing complicated computations by …
aerial access network is a potential paradigm for performing complicated computations by …
Satellite-based ITS data offloading & computation in 6G networks: A cooperative multi-agent proximal policy optimization DRL with attention approach
The proliferation of intelligent transportation systems (ITS) has led to increasing demand for
diverse network applications. However, conventional terrestrial access networks (TANs) are …
diverse network applications. However, conventional terrestrial access networks (TANs) are …
Data security enhancement in 4G vehicular networks based on reinforcement learning for satellite edge computing
The vehicular network provides the dedicated short-range communication (DSRC) with IEEE
802.11 p standard. The VANET model comprises of cellular vehicle-to-everything …
802.11 p standard. The VANET model comprises of cellular vehicle-to-everything …