Transparent Bandwidth Aggregation for Residential Access Networks

We propose, implement, and evaluate a bandwidth aggregation service for residential users that allows to improve the upload throughput of the asymmetric digital subscriber line connection by leveraging the unused bandwidth of neighboring users. The residential access gateway adopts the 802.11 radio interface to simultaneously serve the local home users and to share the broadband connectivity with neighboring access gateways. Differently from previous works, our aggregation scheme is transparent both for local users, who are not required to modify their applications or device drivers, and for neighboring users, who do not experience any meaningful performance degradation. To evaluate the achievable performance and tune the parameters driving the traffic balancing, we developed a fluid model that was shown experimentally to be very accurate. Our proposed scheme is amenable to efficient implementation on Linux networking stack. Indeed, we implemented it and tested in some realistic scenarios, showing an efficient exploitation of the whole available bandwidth, also for legacy cloud storage applications

Mobile RF Scenario Design for Massive-Scale Wireless Channel Emulators

Large-scale wireless emulation is gaining momentum nowadays, thanks to its potential in the development and deployment of advanced use cases for next-generation wireless networks. Several novel use cases are indeed emerging, including massive MIMO, millimeter wave beamforming and AI-based Vehicle-to-Everything (V2X) optimized communication. The development and testing of a wireless application, especially at a large scale and when dealing with mobile nodes, faces several challenges that cannot be solved by simulation frameworks alone. Thus, massive-scale channel emulators are emerging, enabling the emulation of realistic scenarios which leverage real hardware and radio signals. However, this is a complex task due to the lack of realistic scenarios based on real datasets. We thus propose a novel framework for the design and generation of channel emulation scenarios starting from real mobility traces, either generated by means of dedicated tools, or collected on the field. Our framework provides a practical way of generating mobility scenarios with vehicles, pedestrians, drones and other mobile entities. We detail all the steps foreseen by our framework, from the provision of the traces and radio parameters, to the generation of a matrix describing the delay and IQ samples for each time instant and node in the scenario. We also showcase the potentiality of our proposal by designing and creating a vehicular 5G scenario with 13 vehicles, starting from a recently-disclosed open dataset. This scenario is then validated on the Colosseum channel emulator, proving how our framework can provide an effective tool for large-scale wireless networking evaluation

Profiling Performance of Application Partitioning for Wearable Devices in Mobile Cloud and Fog Computing

Wearable devices have become essential in our daily activities. Due to battery constrains the use of computing, communication, and storage resources is limited. Mobile Cloud Computing (MCC) and the recently emerged Fog Computing (FC) paradigms unleash unprecedented opportunities to augment capabilities of wearables devices. Partitioning mobile applications and offloading computationally heavy tasks for execution to the cloud or edge of the network is the key. Offloading prolongs lifetime of the batteries and allows wearable devices to gain access to the rich and powerful set of computing and storage resources of the cloud/edge. In this paper, we experimentally evaluate and discuss rationale of application partitioning for MCC and FC. To experiment, we develop an Android-based application and benchmark energy and execution time performance of multiple partitioning scenarios. The results unveil architectural trade-offs that exist between the paradigms and devise guidelines for proper power management of service-centric Internet of Things (IoT) applications

Multi-Analyte MS Based Investigation in Relation to the Illicit Treatment of Fish Products with Hydrogen Peroxide

Fishery products are perishable due to the action of many enzymes, both endogenous and exogenous. The latter are produced by bacteria that may contaminate the products. When fishes age, there is a massive bacteria growth that causes the appearance of off-flavor. In order to obtain “false” freshness of fishery products, an illicit treatment with hydrogen peroxide is reported to be used. Residues of hydrogen peroxide in food may be of toxicology concern. We developed two mass spectrometry based methodologies to identify and quantify molecules related to the treatment of fishes with hydrogen peroxide. With ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS) we evaluated the concentration of trimethylamine-N-oxide (TMAO), trimethylamine (TMA), dimethylamine (DMA), and cadaverine (CAD) in fish products. After evaluating LOQ, we measured and validated the lower limits of quantification (LLOQs as first levels of calibration curves) values of 50 (TMAO), 70 (TMA), 45 (DMA), and 40 (CAD) ng/mL. A high ratio between TMAO and TMA species indicated the freshness of the food. With a GC-MS method we confirmed the illicit treatment measuring the levels of H2O2 after an analytical reaction with anisole to give 2-hydroxyanisole as a marker. This latter product was detected in the headspace of the homogenized sample with simplification of the work-up. A LLOQ of 50 ng/mL was checked and validated. When fish products were whitened and refreshed with hydrogen peroxide, the detected amount of the product 2-hydroxyanisole could be very important, (larger than 100 mg/kg). The developed analytical methods were suitable to detect the illicit management of fishery products with hydrogen peroxide; they resulted as sensitive, selective, and robust

Data Connectivity and Smart Group Formation in Wi-Fi Direct Multi-group Networks

Users of Device-to-Device (D2D) communication need efficient content discovery mechanisms to steer their requests toward the node in their neighborhood that is most likely to satisfy them. The problem is further compounded by the lack of a central coordination entity as well as by the inherent mobility of devices, which leads to volatile topologies. In this paper, we first discuss group-based communication among non-rooted Android devices using Wi-Fi Direct, a protocol recently standardized by the Wi-Fi Alliance. We propose intra- and inter-group communication methodologies, which we validate through a simple testbed where content-centric routing is used. Next, we address the autonomous formation of groups with the goal of achieving efficient device resource utilization as well as full connectivity. Finally, we evaluate the performance of our group formation procedure both in simulation and in a real testbed involving Android devices in different topologies