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 …
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 …
Multi-parametric analysis of reliability and energy consumption in IoT: A deep learning approach
Small-to-medium scale smart buildings are an important part of the Internet of Things (IoT).
Wireless Sensor Networks (WSNs) are the major enabler for smart control in such …
Wireless Sensor Networks (WSNs) are the major enabler for smart control in such …
Predicting delay in IoT using deep learning: A multiparametric approach
The proliferation of the Internet of Things (IoT) requires to accommodate diverse applications
with stringent performance requirements. Delay is one of the key metrics in the IoT …
with stringent performance requirements. Delay is one of the key metrics in the IoT …
Link quality estimation method for wireless sensor networks based on stacked autoencoder
X Luo, L Liu, J Shu, M Al-Kali - IEEE Access, 2019 - ieeexplore.ieee.org
In wireless sensor networks, effective link quality estimation is the basis of topology
management and routing control. Effective link quality estimation can guarantee the …
management and routing control. Effective link quality estimation can guarantee the …
An investigation on the impact of machine learning in wireless sensor networks and its application specific challenges
Abstract The importance of Machine Learning (ML) in advanced system technologies are
proven in literature. This chapter investigates the role of ML in Wireless Sensor Networks …
proven in literature. This chapter investigates the role of ML in Wireless Sensor Networks …
Neural Network Based Forecasting Technique for Wireless Sensor Networks
P Chaturvedi, AK Daniel - Neural Processing Letters, 2023 - Springer
The diversified and huge applicability of sensor networks has attracted the researchers in
this field. The nodes in the sensor networks are distinguished by the scarce resources; …
this field. The nodes in the sensor networks are distinguished by the scarce resources; …
Innovative techniques to robust wireless sensors networks
M Al-Mazaideh - 2021 - search.proquest.com
Abstract Recently, Wireless Sensor Networks (WSNs)-as a subset of IoT systems-have
become the backbone of several applications targeting different aspects of data acquisition …
become the backbone of several applications targeting different aspects of data acquisition …
Minimizing collision of fading channel using machine learning
MH ALhaddad, S Sati… - 2021 IEEE Microwave …, 2021 - ieeexplore.ieee.org
Energy consumption is considered the main challenge of MAC protocol design. Especially
when MAC protocol is employed in an environment of limited energy resources as a …
when MAC protocol is employed in an environment of limited energy resources as a …
[PDF][PDF] A predictive maintenance system for wireless sensor networks: a machine learning approach
M Almazaideh, J Levendovszky - Indonesian Journal of Electrical …, 2022 - academia.edu
Predictive maintenance system (PdM) is a new concept that helps system operators
evaluate the current status of their systems, and it also assists in predicting the future quality …
evaluate the current status of their systems, and it also assists in predicting the future quality …