Energy-aware data delivery framework for safety-oriented mobile IoT
F Al-Turjman - IEEE Sensors Journal, 2017 - ieeexplore.ieee.org
The proliferation of wireless multimedia sensor networks has given rise to intelligent
transportation systems as a mobile data-sharing model. This vision can be extended under …
transportation systems as a mobile data-sharing model. This vision can be extended under …
Deep reinforcement learning-based mobility-aware robust proactive resource allocation in heterogeneous networks
Proactive resource allocation (PRA) is an essential technology boosting intelligent
communication, as it can make full use of prediction and significantly improve network …
communication, as it can make full use of prediction and significantly improve network …
ALSO-X#: Better convex approximations for distributionally robust chance constrained programs
This paper studies distributionally robust chance constrained programs (DRCCPs), where
the uncertain constraints must be satisfied with at least a probability of a prespecified …
the uncertain constraints must be satisfied with at least a probability of a prespecified …
Exploiting future radio resources with end-to-end prediction by deep learning
J Guo, C Yang, I Chih-Lin - IEEE Access, 2018 - ieeexplore.ieee.org
Machine learning is a powerful tool to predict user behavior and harness the vast amount of
data measured in cellular networks. Predictive resource allocation is a promising approach …
data measured in cellular networks. Predictive resource allocation is a promising approach …
An end-to-end trainable feature selection-forecasting architecture targeted at the Internet of Things
We develop a novel end-to-end trainable feature selection-forecasting (FSF) architecture for
predictive networks targeted at the Internet of Things (IoT). In contrast with the existing filter …
predictive networks targeted at the Internet of Things (IoT). In contrast with the existing filter …
Predictability of Internet of Things traffic at the medium access control layer against information-theoretic bounds
Most of the existing Medium Access Control (MAC) layer protocols for the Internet of Things
(IoT) model the traffic generated by each IoT device via random arrivals such as those in a …
(IoT) model the traffic generated by each IoT device via random arrivals such as those in a …
Accelerating deep reinforcement learning with the aid of partial model: Energy-efficient predictive video streaming
Predictive power allocation is conceived for energy-efficient video streaming over mobile
networks using deep reinforcement learning. The goal is to minimize the accumulated …
networks using deep reinforcement learning. The goal is to minimize the accumulated …
Interference coordination and resource allocation planning with predicted average channel gains for HetNets
K Guo, T Liu, C Yang, Z Xiong - IEEE Access, 2018 - ieeexplore.ieee.org
Future average channel gains are recently reported predictable within a minute-level
horizon for a mobile user. Predictive resource allocation for non-realtime service with future …
horizon for a mobile user. Predictive resource allocation for non-realtime service with future …
Energy efficient resource allocation for hybrid services with future channel gains
C She, C Yang - IEEE Transactions on Green Communications …, 2019 - ieeexplore.ieee.org
In this paper, we propose a framework to maximize energy efficiency (EE) of a system
supporting real-time (RT) and non-real-time services by exploiting future average channel …
supporting real-time (RT) and non-real-time services by exploiting future average channel …
Utilization of stochastic modeling for green predictive video delivery under network uncertainties
Predictive resource allocation (PRA) has gained momentum in the network research
community as a way to cope with the exponential increase in video traffic. Existing PRA …
community as a way to cope with the exponential increase in video traffic. Existing PRA …