相关论文: An Energy-Efficient Ensemble Approach for Mitigati…

The rapid development in ubiquitous computing has enabled the use of microcontrollers as edge devices. These devices are used to develop truly distributed IoT-based mechanisms where machine learning (ML) models are utilized. However,…

This article investigates the energy efficiency issue in non-orthogonal multiple access (NOMA)-enhanced Internet-of-Things (IoT) networks, where a mobile unmanned aerial vehicle (UAV) is exploited as a flying base station to collect data…

The development of Internet of Things (IoT) technology enables the rapid growth of connected smart devices and mobile applications. However, due to the constrained resources and limited battery capacity, there are bottlenecks when utilizing…

Microservice architectures are increasingly used to modularize IoT applications and deploy them in distributed and heterogeneous edge computing environments. Over time, these microservice-based IoT applications are susceptible to…

The rapid growth of the Internet of Things (IoT) has transformed industries by enabling seamless data exchange among connected devices. However, IoT networks remain vulnerable to security threats such as denial of service (DoS) attacks,…

This paper presents InfiniteEn, a multi-source energy harvesting platform designed for the Internet of Batteryless Things (IoBT). InfiniteEn incorporates an efficient energy combiner to combine energy from different harvesting sources. The…

The Internet of Things (IoT) plays a major role today in smart building infrastructures, from simple smart-home applications, to more sophisticated industrial type installations. The vast amounts of data generated from relevant systems can…

Currently, the world experiences an unprecedentedly increasing generation of application data, from sensor measurements to video streams, thanks to the extreme connectivity capability provided by 5G networks. Going beyond 5G technology,…

Energy efficiency has emerged as a defining constraint in the evolution of sustainable Internet of Things (IoT) networks. This work moves beyond simulation-based or device-centric studies to deliver measurement-driven, network-level smart…

A spurt of progress in wireless power transfer (WPT) and mobile edge computing (MEC) provides a promising approach for Industrial Internet of Things (IIoT) to enhance the quality and productivity of manufacturing. Scheduling in such a…

Successful machine learning involves a complete pipeline of data, model, and downstream applications. Instead of treating them separately, there has been a prominent increase of attention within the constrained optimization (CO) and machine…

An Intelligent IoT Environment (iIoTe) is comprised of heterogeneous devices that can collaboratively execute semi-autonomous IoT applications, examples of which include highly automated manufacturing cells or autonomously interacting…

Security issues are threatened in various types of networks, especially in the Internet of Things (IoT) environment that requires early detection. IoT is the network of real-time devices like home automation systems and can be controlled by…

Today's IoT devices rely on batteries, which offer stable energy storage but contain harmful chemicals. Having billions of IoT devices powered by batteries is not sustainable for the future. As an alternative, batteryless devices run on…

Through the generalization of deep learning, the research community has addressed critical challenges in the network security domain, like malware identification and anomaly detection. However, they have yet to discuss deploying them on…

Generally, the risks associated with malicious threats are increasing for the IIoT and its related applications due to dependency on the Internet and the minimal resource availability of IoT devices. Thus, anomaly-based intrusion detection…

Internet of Things (IoT) sensors in smart buildings are becoming increasingly ubiquitous, making buildings more livable, energy efficient, and sustainable. These devices sense the environment and generate multivariate temporal data of…

Building Management Systems (BMS) are crucial in the drive towards smart sustainable cities. This is due to the fact that they have been effective in significantly reducing the energy consumption of buildings. A typical BMS is composed of…

Multi-sensor ML models for EO aim to enhance prediction accuracy by integrating data from various sources. However, the presence of missing data poses a significant challenge, particularly in non-persistent sensors that can be affected by…

Edge computing is a promising solution to enable low-latency IoT applications, by shifting computation from remote data centers to local devices, less powerful but closer to the end user devices. However, this creates the challenge on how…