Scheduling IoT applications in edge and fog computing environments: a taxonomy and future directions
Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the
network with low latency and high-access bandwidth to support a diverse range of IoT …
network with low latency and high-access bandwidth to support a diverse range of IoT …
Applications of multi-agent reinforcement learning in future internet: A comprehensive survey
Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
Ppo2: Location privacy-oriented task offloading to edge computing using reinforcement learning for intelligent autonomous transport systems
AI-empowered 5G/6G networks play a substantial role in taking full advantage of the Internet
of Things (IoT) to perform complex computing by offloading tasks to edge services deployed …
of Things (IoT) to perform complex computing by offloading tasks to edge services deployed …
RL/DRL meets vehicular task offloading using edge and vehicular cloudlet: A survey
The last two decades have seen a clear trend toward crafting intelligent vehicles based on
the significant advances in communication and computing paradigms, which provide a safer …
the significant advances in communication and computing paradigms, which provide a safer …
Digital twin-driven vehicular task offloading and irs configuration in the internet of vehicles
Digital mymargin Twin (DT) and Intelligent Reflective Surface (IRS), the most two promising
technologies of 6G make the Internet of Vehicles (IoV) more adaptive. However, future …
technologies of 6G make the Internet of Vehicles (IoV) more adaptive. However, future …
Edge intelligence: A computational task offloading scheme for dependent IoT application
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 …
edge devices in Internet of Things (IoT), is considered as a promising emerging paradigm for …
Deep reinforcement learning techniques for vehicular networks: Recent advances and future trends towards 6G
Employing machine learning into 6G vehicular networks to support vehicular application
services is being widely studied and a hot topic for the latest research works in the literature …
services is being widely studied and a hot topic for the latest research works in the literature …
[HTML][HTML] A survey on vehicular task offloading: Classification, issues, and challenges
Emerging vehicular applications with strict latency and reliability requirements pose high
computing requirements, and current vehicles' computational resources are not adequate to …
computing requirements, and current vehicles' computational resources are not adequate to …
[Retracted] Deep and Reinforcement Learning Technologies on Internet of Vehicle (IoV) Applications: Current Issues and Future Trends
L Elmoiz Alatabani, E Sayed Ali… - Journal of Advanced …, 2022 - Wiley Online Library
Recently, artificial intelligence (AI) technology has great attention in transportation systems,
which led to the emergence of a new concept known as Internet of Vehicles (IoV). The IoV …
which led to the emergence of a new concept known as Internet of Vehicles (IoV). The IoV …
Psdf: Privacy-aware iov service deployment with federated learning in cloud-edge computing
Through the collaboration of cloud and edge, cloud-edge computing allows the edge that
approximates end-users undertakes those non-computationally intensive service processing …
approximates end-users undertakes those non-computationally intensive service processing …