Application Protocols enabling Internet of Remote Things via Random Access Satellite Channels

Nowadays, Machine-to-Machine (M2M) and Internet of Things (IoT) traffic rate is increasing at a fast pace. The use of satellites is expected to play a large role in delivering such a traffic. In this work, we investigate the use of two of the most common M2M/IoT protocols stacks on a satellite Random Access (RA) channel, based on DVB-RCS2 standard. The metric under consideration is the completion time, in order to identify the protocol stack that can provide the best performance level

A Federated Channel Modeling System using Generative Neural Networks

The paper proposes a data-driven approach to air-to-ground channel estimation in a millimeter-wave wireless network on an unmanned aerial vehicle. Unlike traditional centralized learning methods that are specific to certain geographical areas and inappropriate for others, we propose a generalized model that uses Federated Learning (FL) for channel estimation and can predict the air-to-ground path loss between a low-altitude platform and a terrestrial terminal. To this end, our proposed FL-based Generative Adversarial Network (FL-GAN) is designed to function as a generative data model that can learn different types of data distributions and generate realistic patterns from the same distributions without requiring prior data analysis before the training phase. To evaluate the effectiveness of the proposed model, we evaluate its performance using Kullback-Leibler divergence (KL), and Wasserstein distance between the synthetic data distribution generated by the model and the actual data distribution. We also compare the proposed technique with other generative models, such as FL-Variational Autoencoder (FL-VAE) and stand-alone VAE and GAN models. The results of the study show that the synthetic data generated by FL-GAN has the highest similarity in distribution with the real data. This shows the effectiveness of the proposed approach in generating data-driven channel models that can be used in different region

How Generative Models Improve LOS Estimation in 6G Non-Terrestrial Networks

With the advent of 5G and the anticipated arrival of 6G, there has been a growing research interest in combining mobile networks with Non-Terrestrial Network platforms such as low earth orbit satellites and Geosynchronous Equatorial Orbit satellites to provide broader coverage for a wide range of applications. However, integrating these platforms is challenging because Line-Of-Sight (LOS) estimation is required for both inter satellite and satellite-to-terrestrial segment links. Machine Learning (ML) techniques have shown promise in channel modeling and LOS estimation, but they require large datasets for model training, which can be difficult to obtain. In addition, network operators may be reluctant to disclose their network data due to privacy concerns. Therefore, alternative data collection techniques are needed. In this paper, a framework is proposed that uses generative models to generate synthetic data for LOS estimation in non-terrestrial 6G networks. Specifically, the authors show that generative models can be trained with a small available dataset to generate large datasets that can be used to train ML models for LOS estimation. Furthermore, since the generated synthetic data does not contain identifying information of the original dataset, it can be made publicly available without violating privac

Performance Analysis of WebRTC-based Video Streaming over Power Constrained Platforms

This work analyses the use of the WebRTC framework on resource-constrained platforms. WebRTC is a consolidated solution for real-time video streaming, and it is an appealing solution in a wide range of application scenarios. We focus our attention on those in which power consumption, size and weight are of paramount importance because of size, weight and power requirements, such as the use case of unmanned aerial vehicles delivering real-time video streams overWebRTC to peers on the ground. The testbed described in this work shows that the power consumption can be reduced by changing WebRTC default settings while maintaining comparable video quality

Compact high-brightness and highly manufacturable blue laser modules

Blue laser diode sources have already proved to be an effective alternative for material processing, especially of high reflective materials, such as copper; now the challenge is to increase their power while improving brightness and reducing the cost-per-watt. The paper presents the development of a family of blue laser modules that, making use of the same platform and assembly lines of similar 9xx nm modules, can achieve an unprecedented combination of power, brightness, compactness and cost reduction. These modules rely on a proprietary architecture to combine a plurality of chips through spatial and polarization multiplexing, obtaining up to 100W of output power in a 100 μm fiber. Preliminary experimental results for module making use of spatial multiplexing report 35W output power in a 50 μm fiber

Monitoring Ancient Buildings: Real Deployment of an IoT System Enhanced by UAVs and Virtual Reality

The historical buildings of a nation are the tangible signs of its history and culture. Their preservation deserves considerable attention, being of primary importance from a historical, cultural, and economic point of view. Having a scalable and reliable monitoring system plays an important role in the Structural Health Monitoring (SHM): therefore, this paper proposes an Internet Of Things (IoT) architecture for a remote monitoring system that is able to integrate, through the Virtual Reality (VR) paradigm, the environmental and mechanical data acquired by a wireless sensor network set on three ancient buildings with the images and context information acquired by an Unmanned Aerial Vehicle (UAV). Moreover, the information provided by the UAV allows to promptly inspect the critical structural damage, such as the patterns of cracks in the structural components of the building being monitored. Our approach opens new scenarios to support SHM activities, because an operator can interact with real-time data retrieved from a Wireless Sensor Network (WSN) by means of the VR environment

Characterizing SPDY over High Latency Satellite Channels

The increasing complexity ofWeb contents and the growing diffusion of mobile terminals, which use wireless and satellite links to get access to the Internet, impose the adoption of more specialized protocols. In particular, we focus on SPDY, a novel protocol introduced by Google to optimize the retrieval of complex webpages, to manage large Round Trip Times and high packet losses channels. In this perspective, the paper characterizes SPDY over high latency satellite links, especially with the goal of understanding whether it could be an efficient solution to cope with performance degradations typically affecting Web 2.0 services. To this aim, we implemented an experimental set-up, composed of an ad-hoc proxy, a wireless link emulator, and an instrumented Web browser. The results clearly indicate that SPDY can enhance the performances in terms of loading times, and reduce the traffic fragmentation. Moreover, owing to its connection multiplexing architecture, SPDY can also mitigate the transport layer complexity, which is critical when in presence of Performance Enhancing Proxies usually deployed to isolate satellite trunks

Quality of Experience in Satellite video streaming transmissions in urban vehicular environment

Abstract — In case of video streaming services via satellite towards vehicular clients, very long blockage periods due to road infrastructures, vegetation, and so on, may lead to a complete channel outage, which may result in the loss of all packets transmitted during that period, even in the presence of interleaving and FEC techniques. But if these periods are predictable, as in the presence of known routes traced by means of a GPS navigator, it may be advisable to alert the transmitter in advance, in order to counteract the incoming outage interval. We refer to this technique as Smart Mode. In the following we will detail how Smart Mode takes advantage of FEC and interleaving techniques, in order to improve the Quality of Experience and to reduce the waste of bandwidth in satellite multimedia streaming. Keywords—Video streaming, Satellite, Mobile, FEC

Supporting Privacy Preservation by Distributed and Federated Learning on the Edge

The H2020 TEACHING project puts forward a human-centered vision for adapting and optimising autonomous applications, leveraging users’ physiological, emotional and cognitive states. Such a goal can be achieved by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security, and privacy preservation

Simulating dynamic bandwidth allocation on satellite links

In the last years, DVB-RCS has emerged as a flexible technology offering broadband Internet access to a large community of users at a relatively low cost. At the same time, the spreading of networked multimedia applications has highlighted the need to investigate mechanisms that guarantee a certain level of Quality of Service (QoS) to the end users. In particular, the DVB-RCS standard specifies different capacity request categories to support QoS at the link layer. We describe Tdma-bod, an ns-2 improvement that implements generic bandwidth-on-demand allocation in TDMA satellite systems; the patch is available as free software. This simulator has been validated through experimental tests performed on the Skyplex satellite system. Specifically, we run CBR UDP flows to measure the characteristics of the satellite link in terms of throughput and delay and to verify that the simulative model output matches the experimental dynamic throughput and one-way delay behaviour. The simulations and experiments show that bandwidth-on-demand allocation mechanisms may cause large delays when sudden variations in the incoming traffic rate occur, a behaviour typical of multimedia flows