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 …
Performance analysis of deep learning-based routing protocol for an efficient data transmission in 5G WSN communication
For the past few years, huge interest and dramatic development have been shown for the
Internet of Things (IoT) based constrained Wireless sensor network (WSN) to achieve …
Internet of Things (IoT) based constrained Wireless sensor network (WSN) to achieve …
A survey on node clustering in cognitive radio wireless sensor networks
Cognitive radio wireless sensor networks (CR-WSNs) have attracted a great deal of
attention recently due to the emerging spectrum scarcity issue. This work attempts to provide …
attention recently due to the emerging spectrum scarcity issue. This work attempts to provide …
A novel dynamic spectrum access framework based on reinforcement learning for cognitive radio sensor networks
Y Lin, C Wang, J Wang, Z Dou - Sensors, 2016 - mdpi.com
Cognitive radio sensor networks are one of the kinds of application where cognitive
techniques can be adopted and have many potential applications, challenges and future …
techniques can be adopted and have many potential applications, challenges and future …
[HTML][HTML] Energy aware Q-learning AODV (EAQ-AODV) routing for cognitive radio sensor networks
Wireless sensor networks (WSNs) play an important role in various real-time applications
such as health monitoring, security application, military applications, etc. However, these …
such as health monitoring, security application, military applications, etc. However, these …
A spectrum-aware clustering algorithm based on weighted clustering metric in cognitive radio sensor networks
Clustering organizes nodes into groups in order to enhance the connectivity and stability of
cognitive radio sensor networks. Mainly depending on the channel availability, many …
cognitive radio sensor networks. Mainly depending on the channel availability, many …
Novel learning algorithms for efficient mobile sink data collection using reinforcement learning in wireless sensor network
Generally, wireless sensor network is a group of sensor nodes which is used to continuously
monitor and record the various physical, environmental, and critical real time application …
monitor and record the various physical, environmental, and critical real time application …
A dynamic harmony search-based fuzzy clustering protocol for energy-efficient wireless sensor networks
OM Alia - Annals of Telecommunications, 2018 - Springer
In the development of cluster-based energy-efficient protocols for wireless sensor networks
(WSNs), a particularly challenging problem is the dynamic organization of sensors into a …
(WSNs), a particularly challenging problem is the dynamic organization of sensors into a …
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 …
Energy-Efficient Infrastructure Sensor Network for Ad Hoc Cognitive Radio Network
M Usman, D Har, I Koo - IEEE Sensors Journal, 2016 - ieeexplore.ieee.org
We propose an energy-efficient network architecture that consists of ad hoc (mobile)
cognitive radios (CRs) and infrastructure wireless sensor nodes. The sensor nodes within …
cognitive radios (CRs) and infrastructure wireless sensor nodes. The sensor nodes within …