Autonomous IoT systems require the development of good automation algorithms capable of handling a huge number of IoT devices such as in smart cities. Deep Reinforcement Learning (DRL) is a powerful automation technique that can be used in massive systems thanks to its ability to deal with big state spaces. Moreover, it adapts quickly to changes in the system by reinforcement learning, making the automation algorithm very flexible. However, using DRL relies generally on centralized agent architecture making it more exposed to communication failures. In this paper, we propose a distributed architecture to solve the task offloading problem in autonomous IoT systems where learning is achieved in a master agent while decision making is delegate...
Internet of Things (IoT) devices are increasingly popular due to their wide array of application dom...
Fog and Edge computing extend cloud services to the proximity of end users, allowing many Internet o...
Context-aware and pervasive systems are growing in the market segments. This is due to the expansion...
IoT systems grow quickly and are massively present in urban areas. Their successful deployment requi...
The Internet of Things (IoT) is coined by many different standards, protocols, and data formats that...
The high number of devices with limited computational resources as well as limited communication res...
Reinforcement learning (RL) is capable of managing wireless, energy-harvesting IoT nodes by solving ...
Sustainable cities are envisioned to have economic and industrial steps toward reducing pollution. M...
Reinforcement learning (RL) is a new propitious research space that is well-known nowadays on the in...
Load balancing is directly associated with the overall performance of a parallel and distributed com...
Event processing is the cornerstone of the dynamic and responsive Internet of Things (IoT). Recent a...
In mobile edge computing, there are usually relevant dependencies between different tasks, and tradi...
International audienceThis paper considers the Multiple Access problem where N Internet of Things (I...
Currently, the deep integration of the Internet of Things (IoT) and edge computing has improved the ...
Mobile devices could augment their ability via cloud resources in mobile cloud computing environment...
Internet of Things (IoT) devices are increasingly popular due to their wide array of application dom...
Fog and Edge computing extend cloud services to the proximity of end users, allowing many Internet o...
Context-aware and pervasive systems are growing in the market segments. This is due to the expansion...
IoT systems grow quickly and are massively present in urban areas. Their successful deployment requi...
The Internet of Things (IoT) is coined by many different standards, protocols, and data formats that...
The high number of devices with limited computational resources as well as limited communication res...
Reinforcement learning (RL) is capable of managing wireless, energy-harvesting IoT nodes by solving ...
Sustainable cities are envisioned to have economic and industrial steps toward reducing pollution. M...
Reinforcement learning (RL) is a new propitious research space that is well-known nowadays on the in...
Load balancing is directly associated with the overall performance of a parallel and distributed com...
Event processing is the cornerstone of the dynamic and responsive Internet of Things (IoT). Recent a...
In mobile edge computing, there are usually relevant dependencies between different tasks, and tradi...
International audienceThis paper considers the Multiple Access problem where N Internet of Things (I...
Currently, the deep integration of the Internet of Things (IoT) and edge computing has improved the ...
Mobile devices could augment their ability via cloud resources in mobile cloud computing environment...
Internet of Things (IoT) devices are increasingly popular due to their wide array of application dom...
Fog and Edge computing extend cloud services to the proximity of end users, allowing many Internet o...
Context-aware and pervasive systems are growing in the market segments. This is due to the expansion...