Fog computing for next-generation internet of things: fundamental, state-of-the-art and research challenges
In recent times, the Internet of Things (IoT) applications, including smart transportation, smart
healthcare, smart grid, smart city, etc. generate a large volume of real-time data for decision …
healthcare, smart grid, smart city, etc. generate a large volume of real-time data for decision …
AI-based fog and edge computing: A systematic review, taxonomy and future directions
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
A QoS-aware technique for computation offloading in IoT-edge platforms using a convolutional neural network and Markov decision process
Offloading is one of the critical enablers of the Internet of Things (IoT) as it helps overcome
the resource limitations of individual objects. Offering enough computational power for IoT …
the resource limitations of individual objects. Offering enough computational power for IoT …
Federated domain generalization: A survey
Machine learning typically relies on the assumption that training and testing distributions are
identical and that data is centrally stored for training and testing. However, in real-world …
identical and that data is centrally stored for training and testing. However, in real-world …
ELECT: Energy-efficient intelligent edge–cloud collaboration for remote IoT services
Existing centralized cloud-based solution is challenging to cope with the explosive growth of
data generated from massive IoT devices to meet the requirements of critical services …
data generated from massive IoT devices to meet the requirements of critical services …
Relief: A reinforcement learning-based real-time task assignment strategy in emerging fault-tolerant fog computing
Due to the real-time requirements in several IoT applications, fog computing has emerged to
overcome the long latency and other constraints of cloud computing. Due to the high …
overcome the long latency and other constraints of cloud computing. Due to the high …
[HTML][HTML] Energy-efficient computation offloading using hybrid GA with PSO in internet of robotic things environment
Abstract The Internet of Robotic Things (IoRT) is an integration between autonomous robots
and the Internet of Things (IoT) based on smart connectivity. It's critical to have intelligent …
and the Internet of Things (IoT) based on smart connectivity. It's critical to have intelligent …
The promising role of representation learning for distributed computing continuum systems
The distributed computing continuum systems (DCCS) and representation learning (ReL)
are two diverse computer science technologies with their use cases, applications, and …
are two diverse computer science technologies with their use cases, applications, and …
Harvested energy prediction technique for solar-powered wireless sensor networks
Solar energy harvesting (EH) is one of the best promising approaches toward perpetual
network operation, and it is implemented in various regions of interest (RoIs). However …
network operation, and it is implemented in various regions of interest (RoIs). However …
Optimizing resource swap functionality in ioe-based grids using approximate reasoning reward-based adjustable deep double q-learning
HM Rouzbahani, H Karimipour… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The Energy Router (ER) concept as a compact intelligent power electronic device has been
proposed as the core of the Internet of Energy (IoE), maximizing energy efficiency …
proposed as the core of the Internet of Energy (IoE), maximizing energy efficiency …