Adaptive task offloading in vehicular edge computing networks: a reinforcement learning based scheme
In recent years, with the rapid development of Internet of Things (IoTs) and artificial
intelligence, vehicular networks have transformed from simple interactive systems to smart …
intelligence, vehicular networks have transformed from simple interactive systems to smart …
Deep learning-based computer vision for surveillance in its: Evaluation of state-of-the-art methods
Intelligent transportation system (ITS) collects numerous data for analysis of the
transportation system. The data can be used for providing services for travellers and traffic …
transportation system. The data can be used for providing services for travellers and traffic …
A distributed application placement and migration management techniques for edge and fog computing environments
M Goudarzi, M Palaniswami… - 2021 16th Conference on …, 2021 - ieeexplore.ieee.org
Fog/Edge computing model allows harnessing of resources in the proximity of the Internet of
Things (IoT) devices to support various types of latency-sensitive IoT applications. However …
Things (IoT) devices to support various types of latency-sensitive IoT applications. However …
Reinforcement learning for joint control of traffic signals in a transportation network
J Lee, J Chung, K Sohn - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
Reinforcement learning (RL) approaches have recently been spotlighted for use in adaptive
traffic-signal control on an area-wide level. Most researchers have employed multi-agent …
traffic-signal control on an area-wide level. Most researchers have employed multi-agent …
Decentralized scheduling for cooperative localization with deep reinforcement learning
Cooperative localization is a promising solution to the vehicular high-accuracy localization
problem. Despite its high potential, exhaustive measurement and information exchange …
problem. Despite its high potential, exhaustive measurement and information exchange …
Intelligent content precaching scheme for platoon-based edge vehicular networks
To provide various onboard entertainment services, the ever-increased Internet contents to
be exchanged among remote data centers, roadside units (RSUs), and vehicles demand …
be exchanged among remote data centers, roadside units (RSUs), and vehicles demand …
Federated deep reinforcement learning-based intelligent dynamic services in UAV-assisted mec
Unmanned aerial vehicles (UAVs)-assisted multiaccess edge computing (MEC) has
emerged as a promising solution in B5G/6G networks. The high flexibility and seamless …
emerged as a promising solution in B5G/6G networks. The high flexibility and seamless …
Reinforcement Learning for Optimizing Delay-Sensitive Task Offloading in Vehicular Edge-Cloud Computing
With the appearance of more and more devices connected to the Internet, the world has
witnessed an ever-growing number of data to be processed. Among those, many tasks …
witnessed an ever-growing number of data to be processed. Among those, many tasks …
Dynamic resource allocation for jointing vehicle-edge deep neural network inference
Q Wang, Z Li, K Nai, Y Chen, M Wen - Journal of Systems Architecture, 2021 - Elsevier
The emergence of mobile edge computing provides an efficient and stable computing
platform for intelligent applications of autonomous vehicles, and deep neural network (DNN) …
platform for intelligent applications of autonomous vehicles, and deep neural network (DNN) …
Efficient task scheduling for servers with dynamic states in vehicular edge computing
Vehicular edge computing has become an appealing paradigm to provide the delay-
sensitive and multimedia-rich services by densely deploying the roadside units (RSUs) …
sensitive and multimedia-rich services by densely deploying the roadside units (RSUs) …