Age of processing-based data offloading for autonomous vehicles in multirats open ran
A Ndikumana, KK Nguyen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Today, vehicles use smart sensors to collect data from the road environment. This data is
often processed onboard of the vehicles, using expensive hardware. Such onboard …
often processed onboard of the vehicles, using expensive hardware. Such onboard …
Static Deep Q-Learning for Green Downlink C-RAN
Power saving is a main pillar in the operation of wireless communication systems. In this
paper, we investigate cloud radio access network (C-RAN) capability to reduce power …
paper, we investigate cloud radio access network (C-RAN) capability to reduce power …
Semi-Supervised Learning Approach for Efficient Resource Allocation with Network Slicing in O-RAN
S Nouri, MK Motalleb, V Shah-Mansouri… - arXiv preprint arXiv …, 2024 - arxiv.org
The Open Radio Access Network (O-RAN) technology has emerged as a promising solution
for network operators, providing them with an open and favorable environment. Ensuring …
for network operators, providing them with an open and favorable environment. Ensuring …
Maximizing Fog Computing Efficiency with Federated Multi-Agent Deep Reinforcement Learning
G Anitha, A Jegatheesan - Handbook on Federated Learning, 2024 - taylorfrancis.com
To accomplish efficient task offloading decisions, the authors present a DRL-based
federated offloading architecture that uses multi-tiered collective learning to offload jobs. The …
federated offloading architecture that uses multi-tiered collective learning to offload jobs. The …
Analyzing Dueling Q-Learning for Workload Balancing in Edge Computing with Random Workload Distribution
VN Thatha, K Kalaivani, VSN Reddy, K Ramakrishna… - 2024 - researchsquare.com
Edge computing is an emerging computing paradigm that enables data processing to be
performed closer to where the data is generated, instead of relying on centralized cloud …
performed closer to where the data is generated, instead of relying on centralized cloud …