Applications of deep reinforcement learning in communications and networking: A survey
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
A survey on deep learning for human mobility
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …
such as disease spreading, urban planning, well-being, pollution, and more. The …
Dynamic digital twin and distributed incentives for resource allocation in aerial-assisted internet of vehicles
W Sun, P Wang, N Xu, G Wang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Internet of Vehicles (IoV), when empowered by aerial communications, provides vehicles
with seamless connections and proximate computing services. The unpredictable network …
with seamless connections and proximate computing services. The unpredictable network …
A comprehensive survey on mobility-aware D2D communications: Principles, practice and challenges
Device-to-device (D2D) communication proposes a new epitome in mobile networking to
avail data exchange between physically proximate devices. The exploitation of D2D …
avail data exchange between physically proximate devices. The exploitation of D2D …
Learning-based energy-efficient data collection by unmanned vehicles in smart cities
Mobile crowdsourcing (MCS) is now an important source of information for smart cities,
especially with the help of unmanned aerial vehicles (UAVs) and driverless cars. They are …
especially with the help of unmanned aerial vehicles (UAVs) and driverless cars. They are …
An efficient prediction-based user recruitment for mobile crowdsensing
Mobile crowdsensing is a new paradigm in which a group of mobile users exploit their smart
devices to cooperatively perform a large-scale sensing job. One of the users' main concerns …
devices to cooperatively perform a large-scale sensing job. One of the users' main concerns …
Truthful incentive mechanism for nondeterministic crowdsensing with vehicles
In this paper, we focus on the incentive mechanism design for a vehicle-based,
nondeterministic crowdsensing system. In this crowdsensing system, vehicles move along …
nondeterministic crowdsensing system. In this crowdsensing system, vehicles move along …
Task offloading in vehicular edge computing networks via deep reinforcement learning
Given the rapid increase of various applications in vehicular networks, it is crucial to
consider a flexible architecture to improve the Quality of Service (QoS). Utilizing Multi-access …
consider a flexible architecture to improve the Quality of Service (QoS). Utilizing Multi-access …
A UAV-assisted multi-task allocation method for mobile crowd sensing
Mobile crowd sensing (MCS) with human participants has been proposed as an efficient
way of collecting data for smart cities applications. However, there often exist situations …
way of collecting data for smart cities applications. However, there often exist situations …
A mobility-aware vehicular caching scheme in content centric networks: Model and optimization
Edge caching is being explored as a promising technology to alleviate the network burden
of cellular networks by separating the computing functionalities away from cellular base …
of cellular networks by separating the computing functionalities away from cellular base …