The state of AI-empowered backscatter communications: A comprehensive survey
The Internet of Things (IoT) is undergoing significant advancements, driven by the
emergence of backscatter communication (BC) and artificial intelligence (AI). BC is an …
emergence of backscatter communication (BC) and artificial intelligence (AI). BC is an …
Joint computation offloading and multiuser scheduling using approximate dynamic programming in NB-IoT edge computing system
The Internet of Things (IoT) connects a huge number of resource-constraint IoT devices to
the Internet, which generate massive amount of data that can be offloaded to the cloud for …
the Internet, which generate massive amount of data that can be offloaded to the cloud for …
The state of ai-empowered backscatter communications: A comprehensive survey
This paper brings these two technologies together to investigate the current state of AI-
powered BC. We begin with an introduction to BC and an overview of the AI algorithms …
powered BC. We begin with an introduction to BC and an overview of the AI algorithms …
Q-learning algorithm for joint computation offloading and resource allocation in edge cloud
The advent of 5G technology along with the high proliferation of mobile devices entail an
explosion of mobile traffic. Due to their resource-limitation constraint, mobile devices resort …
explosion of mobile traffic. Due to their resource-limitation constraint, mobile devices resort …
Reinforcement R-learning model for time scheduling of on-demand fog placement
On the fly deployment of fog nodes near users provides the flexibility of pushing services
anywhere and whenever needed. Nevertheless, taking a real-life scenario, the cloud might …
anywhere and whenever needed. Nevertheless, taking a real-life scenario, the cloud might …
An energy efficient reinforcement learning based cooperative channel sensing for cognitive radio sensor networks
Abstract In Cognitive Radio (CR), the conventional narrow band spectrum sensing requires
either random channel sensing order or predefined channel sensing sequence to sense all …
either random channel sensing order or predefined channel sensing sequence to sense all …
An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
It is well-known that clustering partitions network into logical groups of nodes in order to
achieve energy efficiency and to enhance dynamic channel access in cognitive radio …
achieve energy efficiency and to enhance dynamic channel access in cognitive radio …
Comparative study for coordinating multiple unmanned HAPS for communications area coverage
O Anicho, PB Charlesworth, GS Baicher… - 2019 International …, 2019 - ieeexplore.ieee.org
This work compares the application of Reinforcement Learning (RL) and Swarm Intelligence
(SI) based methods for resolving the problem of coordinating multiple High Altitude Platform …
(SI) based methods for resolving the problem of coordinating multiple High Altitude Platform …
Detecting and responding to concept drift in business processes
Concept drift, which refers to changes in the underlying process structure or customer
behaviour over time, is inevitable in business processes, causing challenges in ensuring …
behaviour over time, is inevitable in business processes, causing challenges in ensuring …
Reinforcement learning versus swarm intelligence for autonomous multi-HAPS coordination
This work analyses the performance of Reinforcement Learning (RL) versus Swarm
Intelligence (SI) for coordinating multiple unmanned High Altitude Platform Stations (HAPS) …
Intelligence (SI) for coordinating multiple unmanned High Altitude Platform Stations (HAPS) …