Related papers: An Algorithm to Determine Energy-aware Maximal Lea…

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random…

In this paper, we introduce the first machine learning framework for predicting optimal processing times in Single-Level Tree Network (SLTN) architectures for the Divisible Load Theory (DLT) paradigm. Using a feedforward neural network(FNN)…

A Wireless Sensor Network(WSN) can be described as a collection of untethered sensor nodes. An important application of WSNs is in the field of real-time communication. Real-time communication is a critical service which requires a…

State-of-the-art machine learning solutions mainly focus on creating highly accurate models without constraints on hardware resources. Stream mining algorithms are designed to run on resource-constrained devices, thus a focus on low power…

The constantly increasing number of power generation devices based on renewables is calling for a transition from the centralized control of electrical distribution grids to a distributed control scenario. In this context, distributed…

Achieving reliable communication over different channels and modes is one of the main goals of Mode Division Multiplexing-Wavelength Division Multiplexing (MDM-WDM) communication networks. The reliability can be described by minimum Signal…

This paper advocates the use of the emerging distributed compressive sensing (DCS) paradigm in order to deploy energy harvesting (EH) wireless sensor networks (WSN) with practical network lifetime and data gathering rates that are…

One of the most important issues in Wireless Sensor Networks (WSNs) is severe energy restrictions. As the performance of Sensor Networks is strongly dependence to the network lifetime, researchers seek a way to use node energy supply…

We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be…

Energy harvesting is increasingly gaining importance as a means to charge battery powered devices such as sensor nodes. Efficient transmission strategies must be developed for Wireless Energy Harvesting Nodes (WEHNs) that take into account…

Graph Neural Networks (GNNs) are becoming a promising technique in various domains due to their excellent capabilities in modeling non-Euclidean data. Although a spectrum of accelerators has been proposed to accelerate the inference of…

As an entirely-new paradigm to design the communication systems, deep learning (DL), an approach that the machine learns the desired wireless function, has received much attention recently. In order to fully realize the benefit of DL-aided…

Millimeter wave (mmWave) communication technologies have recently emerged as an attractive solution to meet the exponentially increasing demand on mobile data traffic. Moreover, ultra dense networks (UDNs) combined with mmWave technology…

In Wireless Sensor Networks (WSN), typically composed of nodes with resource constraints, leveraging efficient processes is crucial to enhance the network lifetime and, consequently, the sustainability in ultra-dense and heterogeneous…

We present EnergyLens, an end-to-end framework for energy-aware large language model (LLM) inference optimization. As LLMs scale, predicting and reducing their energy footprint has become critical for sustainability and datacenter…

The explosive growth of global mobile traffic has lead to a rapid growth in the energy consumption in communication networks. In this paper, we focus on the energy-aware design of the network selection, subchannel, and power allocation in…

We present the design and implementation of a shortest path tree based, energy efficient data collection wireless sensor network to sense various parameters in an agricultural farm using in-house developed low cost sensors. Nodes follow a…

A wireless sensor network has a wide application domain which is expanding everyday and they have been deployed pertaining to their application area. An application independent approach is yet to come to terms with the ongoing exploitation…

Despite rapid advancements in sensor networks, conventional battery-powered sensor networks suffer from limited operational lifespans and frequent maintenance requirements that severely constrain their deployment in remote and inaccessible…

Energy is one of the most important and scarce resources in Wireless Sensor Networks (WSN). WSN nodes work with the embedded operating system called TinyOS, which addresses the constrains of the WSN nodes such as limited processing power,…