Cooperative UAV resource allocation and task offloading in hierarchical aerial computing systems: A MAPPO-based approach
This article investigates a hierarchical aerial computing system, where both high-altitude
platforms (HAPs) and unmanned aerial vehicles (UAVs) provision computation services for …
platforms (HAPs) and unmanned aerial vehicles (UAVs) provision computation services for …
Dynamic and intelligent edge server placement based on deep reinforcement learning in mobile edge computing
In the era of 5G and beyond, Mobile Edge Computing (MEC) has emerged as a technology
that seamlessly integrates wireless networks and the Internet, enabling low-latency and high …
that seamlessly integrates wireless networks and the Internet, enabling low-latency and high …
Optimal priority rule-enhanced deep reinforcement learning for charging scheduling in an electric vehicle battery swapping station
For a battery swapping station (BSS) with solar generation, charging bays, and an inventory
of batteries, we study the charging scheduling problem under random EV arrivals …
of batteries, we study the charging scheduling problem under random EV arrivals …
Evolutionary multitask optimization in real-world applications: A survey
Because of its strong ability to solve problems, evolutionary multitask optimization (EMTO)
algorithms have been widely studied recently. Evolutionary algorithms have the advantage …
algorithms have been widely studied recently. Evolutionary algorithms have the advantage …
Multi-Hop Task Offloading and Relay Selection for IoT Devices in Mobile Edge Computing
To bridge the gap of conventional single-hop task offloading schemes in infrastructure-free
scenarios, multi-hop task offloading schemes for IoT devices in Mobile Edge Computing …
scenarios, multi-hop task offloading schemes for IoT devices in Mobile Edge Computing …
Slice admission control in 5G cloud radio access network using deep reinforcement learning: A survey
M Khani, S Jamali, MK Sohrabi… - International Journal …, 2024 - Wiley Online Library
The emergence of 5G networks has increased the demand for network resources, making
efficient resource management crucial. Slice admission control (SAC) is a process that …
efficient resource management crucial. Slice admission control (SAC) is a process that …
Device-Specific QoE Enhancement Through Joint Communication and Computation Resource Scheduling in Edge-Assisted IoT Systems
With rapid adoption in vertical industries and further assistance of edge computing, Internet
of Things (IoT) applications are experiencing phenomenal growth. However, the …
of Things (IoT) applications are experiencing phenomenal growth. However, the …
Comprehensive Survey of Reinforcement Learning: From Algorithms to Practical Challenges
M Ghasemi, AH Mousavi, D Ebrahimi - arXiv preprint arXiv:2411.18892, 2024 - arxiv.org
Reinforcement Learning (RL) has emerged as a powerful paradigm in Artificial Intelligence
(AI), enabling agents to learn optimal behaviors through interactions with their environments …
(AI), enabling agents to learn optimal behaviors through interactions with their environments …
An online transfer learning based multifactorial evolutionary algorithm for solving the clustered Steiner tree problem
The rapid increase in the number and computing power of devices interacting through the
network over the past few years has led to a growing trend of decentralized clustering …
network over the past few years has led to a growing trend of decentralized clustering …
Meta reinforcement learning-based computation offloading in RIS-aided MEC-enabled cell-free ran
In this paper, the computation offloading problem in reconfigurable intelligent surface (RIS)-
aided mobile edge computing (MEC)-enabled cell-free radio access network (CF-RAN) is …
aided mobile edge computing (MEC)-enabled cell-free radio access network (CF-RAN) is …