Machine learning in wireless sensor networks: Algorithms, strategies, and applications
Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over
time. This dynamic behavior is either caused by external factors or initiated by the system …
time. This dynamic behavior is either caused by external factors or initiated by the system …
A survey on machine learning in Internet of Things: Algorithms, strategies, and applications
In the IoT and WSN era, large number of connected objects and sensing devices are
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
dedicated to collect, transfer, and generate a huge amount of data for a wide variety of fields …
A low duty cycle efficient MAC protocol based on self-adaption and predictive strategy
D Zhang, S Zhou, Y Tang - Mobile Networks and Applications, 2018 - Springer
In the medium access control layer (MAC) of WSN, the scheduling mechanism of nodes
based on the periodical listen/sleep is an effective way of saving node energy consumption …
based on the periodical listen/sleep is an effective way of saving node energy consumption …
A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer
This paper presents a systematic and comprehensive survey that reviews the latest research
efforts focused on machine learning (ML) based performance improvement of wireless …
efforts focused on machine learning (ML) based performance improvement of wireless …
Data-driven design of intelligent wireless networks: An overview and tutorial
Data science or “data-driven research” is a research approach that uses real-life data to gain
insight about the behavior of systems. It enables the analysis of small, simple as well as …
insight about the behavior of systems. It enables the analysis of small, simple as well as …
Neural network based instant parameter prediction for wireless sensor network optimization models
Optimal operation configuration of a Wireless Sensor Network (WSN) can be determined by
utilizing exact mathematical programming techniques such as Mixed Integer Programming …
utilizing exact mathematical programming techniques such as Mixed Integer Programming …
FD-PaS: A fully distributed packet scheduling framework for handling disturbances in real-time wireless networks
Along with the rapid growth of Industrial Internet-of-Things (IIoT) applications and their
penetration into many industry sectors, real-time wireless networks (RTWNs) have been …
penetration into many industry sectors, real-time wireless networks (RTWNs) have been …
Distributed dynamic packet scheduling for handling disturbances in real-time wireless networks
Real-time wireless networks (RTWNs) are fundamental to many Internet-of-Things (IoT)
applications. Packet scheduling in an RTWN plays a critical role for achieving desired …
applications. Packet scheduling in an RTWN plays a critical role for achieving desired …
Evolution of MAC protocols in the machine learning decade: A comprehensive survey
M Hussien, IATF Taj-Eddin, MFA Ahmed… - arXiv preprint arXiv …, 2023 - arxiv.org
The last decade,(2012-2022), saw an unprecedented advance in machine learning (ML)
techniques, particularly deep learning (DL). As a result of the proven capabilities of DL, a …
techniques, particularly deep learning (DL). As a result of the proven capabilities of DL, a …
Towards to intelligent routing for DTN protocols using machine learning techniques
The communication protocols of wireless networks have experienced great advances in
recent years, specifically with the evolution of new technologies such as the Internet of …
recent years, specifically with the evolution of new technologies such as the Internet of …