Related papers: High-Accuracy and Efficient DV-Hop Localization fo…
We study a problem of fundamental importance to ICNs, namely, minimizing routing costs by jointly optimizing caching and routing decisions over an arbitrary network topology. We consider both source routing and hop-by-hop routing settings.…
Mobile ad-hoc networks demand routing algorithms able to adapt to network topologies subject to constant change. Moreover, with the advent of the Internet-of-Things (IoT), network nodes tend not only to show increased mobility, but also…
Satellite networks are booming to provide high-speed and low latency Internet access, but the transport layer becomes one of the main obstacles. Legacy end-to-end TCP is designed for terrestrial networks, not suitable for error-prone,…
As an extension of cloud computing, fog computing at the edge of networks provides low latency, location awareness, and real-time interactions. At the same time, millimeter wave (mmWave) communications are able to provide directional…
Heterogeneous Internet of Things (IoT) systems suffer from fragmentation across hardware architectures, networking stacks, and data serialization formats. Existing standards (such as MQTT, COAP, and DDS) rely on address-bound, imperative…
Industrial Internet of Things (I-IoT) enables fully automated production systems by continuously monitoring devices and analyzing collected data. Machine learning methods are commonly utilized for data analytics in such systems.…
In this paper, we consider decentralized federated learning (FL) over wireless networks, where over-the-air computation (AirComp) is adopted to facilitate the local model consensus in a device-to-device (D2D) communication manner. However,…
Industrial automation deployments constitute challenging environments where moving IoT machines may produce high-definition video and other heavy sensor data during surveying and inspection operations. Transporting massive contents to the…
The Internet of Things (IoT) requires a new processing paradigm that inherits the scalability of the cloud while minimizing network latency using resources closer to the network edge. Building up such flexibility within the edge-to-cloud…
In this paper we propose a parallel coordinate descent algorithm for solving smooth convex optimization problems with separable constraints that may arise e.g. in distributed model predictive control (MPC) for linear network systems. Our…
The low Earth orbit (LEO) mega-constellation network (LMCN), which uses thousands of satellites across multi-shell architectures to deliver different services, is facing challenges in inter-shell routing stability due to dynamic network…
Internet-of-Things (IoT) devices are low size, weight and power (SWaP), low complexity and include sensors, meters, wearables and trackers. Transmitting information with high signal power is exacting on device battery life, therefore an…
Nowadays, deep learning is the standard approach for a wide range of problems, including biometrics, such as face recognition and speech recognition, etc. Biometric problems often use deep learning models to extract features from images,…
Most recent network failure diagnosis systems focused on data center networks where complex measurement systems can be deployed to derive routing information and ensure network coverage in order to achieve accurate and fast fault…
The anticipated densification of contemporary communications infrastructure expects the use of drone small cells (DSCs). Thus, we experimentally evaluate the capability of providing local and personalized coverage with a drone mounted Wi-Fi…
The rapid expansion of Internet of Things (IoT) networks has introduced new security challenges, necessitating efficient and reliable methods for intrusion detection. In this study, a detection framework based on hyperdimensional computing…
Recent years have witnessed the rapid proliferation of backscatter technologies that realize the ubiquitous and long-term connectivity to empower smart cities and smart homes. Localizing such backscatter tags is crucial for IoT-based smart…
While deep learning has proven to be extremely successful at supervised classification tasks at the LHC and beyond, for practical applications, raw classification accuracy is often not the only consideration. One crucial issue is the…
In this paper, we study the problem of localizing the sensors' positions in presence of denial-of-service (DoS) attacks. We consider a general attack model, in which the attacker action is only constrained through the frequency and duration…
Drone cell (DC) is an emerging technique to offer flexible and cost-effective wireless connections to collect Internet-of-things (IoT) data in uncovered areas of terrestrial networks. The flying trajectory of DC significantly impacts the…