Wireless sensor networks (WSNs) have been adopted in many fields of application, such as
industrial, civil, smart cities, health, and the surveillance domain, to name a few. Fateway …

Introducing mobility to Wireless Sensor Networks (WSNs) puts new challenges particularly
in designing of routing protocols. Mobility can be applied to the sensor nodes and/or the sink …

We propose a novel federated learning method for distributively training neural network
models, where the server orchestrates cooperation between a subset of randomly chosen …

The wireless sensor networks (WSNs) are used for the real-life implementation of the
Internet of Things (IoT) in smart agriculture, smart buildings, smart cities, and online …

Data heterogeneity across clients is a key challenge in federated learning. Prior works
address this by either aligning client and server models or using control variates to correct …

We propose a novel federated learning method for distributively training neural network
models, where the server orchestrates cooperation between a subset of randomly chosen …

The emergent paradigm of fog computing advocates that the computational resources can
be extended to the edge of the network, so that the transmission latency and bandwidth …

This article studies the data collection problem in an Internet-of-Things (IoT) network with
multiple unmanned aerial vehicles (UAVs) where UAVs first power multiple IoT devices by …

Energy efficiency is one of the critical challenges in wireless sensor networks (WSNs).
WSNs collect and transmit data through sensor nodes. However, the energy carried by the …

Wireless Body Area Network (WBAN) is a promising cost-effective technology for the privacy
confined military applications and healthcare applications like remote health monitoring …