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Location-based services in a wireless network require nodes to know their locations accurately. Conventional solutions rely on contention-based medium access, where only one node can successfully transmit at any time in any neighborhood. In…
Efficient service discovery is a cornerstone of the rapidly expanding Internet of Things (IoT) and edge computing ecosystems, where low latency and localized service provisioning are critical. This paper proposes a novel location-based DNS…
Understanding the locations of occupants in a commercial built environment is critical for realizing energy savings by delivering lighting, heating, and cooling only where it is needed. The key to achieving this goal is being able to…
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…
Integrated sensing, communication, and computation (ISCC) has been regarded as a prospective technology for the next-generation wireless network, supporting humancentric intelligent applications. However, the delay sensitivity of these…
Wireless sensor networks are deployed in many monitoring applications but still suffer from short lifetimes originating from limited energy sources and storages. Due to their low-power consumption and their on-demand communication ability,…
Accurate, resource-efficient localization and tracking enables numerous location-aware services in next-generation wireless networks. However, existing machine learning-based methods often require large labeled datasets while overlooking…
Spectrum scarcity has surfaced as a prominent concern in wireless radio communications with the emergence of new technologies over the past few years. As a result, there is growing need for better understanding of the spectrum occupancy…
Channel Charting (CC) has emerged as a promising framework for data-driven radio localization, yet existing approaches often struggle to scale globally and to handle the distortions introduced by non-line-of-sight (NLoS) conditions. In this…
Lightweight aerial swarms have potential applications in scenarios where larger drones fail to operate efficiently. The primary foundation for lightweight aerial swarms is efficient relative localization, which enables cooperation and…
Low power long-range networks like LoRa have become increasingly mainstream for Internet of Things deployments. Given the versatility of applications that these protocols enable, they support many data rates and bandwidths. Yet, for a given…
Synchronizing clocks on Internet of Things (IoT) devices is important for applications such as monitoring and real time control. In this paper, we describe a system for clock synchronization in IoT devices that is designed to be scalable,…
The advent of the Internet of Things (IoT) is boosting the proliferation of sensors and smart devices in industry and daily life. Continuous monitoring IoT systems are also finding applications in agriculture, particularly in the realm of…
With the success of deep learning, object recognition systems that can be deployed for real-world applications are becoming commonplace. However, inference that needs to largely take place on the `edge' (not processed on servers), is a…
The Internet of Things (IoT) enables numerous business opportunities in fields as diverse as e-health, smart cities, smart homes, among many others. The IoT incorporates multiple long-range, short-range, and personal area wireless networks…
Besides being part of the Internet of Things (IoT), drones can play a relevant role in it as enablers. The 3D mobility of UAVs can be exploited to improve node localization in IoT networks for, e.g., search and rescue or goods localization…
The integration of LoRa technologies with mesh topologies represents a robust alternative for off-grid communications in emergency scenarios within smart cities. Meshtastic firmware implements a decentralised mesh network over LoRa where…
This paper proposes a distributed Reinforcement Learning (RL) based framework that can be used for synthesizing MAC layer wireless protocols in IoT networks with low-complexity wireless transceivers. The proposed framework does not rely on…
The multichannel rendezvous problem (MRP) is a critical challenge for neighbor discovery in IoT applications, requiring two users to find each other by hopping among available channels over time. This paper addresses the MRP in scenarios…
The accelerating growth of the Internet of Things (IoT) and its integration with Low-Earth Orbit (LEO) satellites demand efficient, reliable, and scalable communication protocols. Among these, the Long-Range Frequency Hopping Spread…