Peer-to-peer multimedia communication

I sistemi Peer-to-Peer (P2P) sono stati inventi, messi in campo e studiati da più di dieci anni, andando al di là della semplice applicazione per scambio di file. Nelle reti P2P i partecipanti si organizzano in una rete "overlay" che è astratta rispetto alle caratteristiche della sottostante rete fisica. Scopo di questi sistemi è la distribuzione di risorse quali contenuti, spazio di memorizzazione o cicli macchina. Gli utenti quindi giocano un ruolo attivo e possono essere considerati come sia clienti che serventi allo stesso tempo per il particolare servizio che la rete P2P offre. Lo scopo di questa tesi di dottorato è lo studio di questi sistemi ed il dare un contributo nella loro analisi prestazionale. L'analisi mira a valutare le prestazioni raggiunte dai sistemi e/o i limiti teorici raggiungibili. Infatti, nonostante esistano diversi meccanismi per il peer-to-peer streaming, l'analisi prestazionale di questo tipo di sistemi può essere considerata ancora nella sua infanzia. A questo scopo, i contributi principali di questa tesi di dottorato sono: i)la derivazione di un limite teorico per il ritardo nei sistemi di P2P streaming, ii) la creazione di un algoritmo che sfrutti le conoscenze acquisite attraverso il lavoro teorico, iii) l'analisi prestazionale dell'algoritmo utilizzando un simulatore espressamente progettato per riprodurre le caratteristiche delle reti P2P reali composte da centinaia di migliaia di nodi che si connettono e disconnettono in continuazione.Peer-to-Peer (P2P) systems have been invented, deployed and researched for more than ten years and went far beyond the simple file sharing applications. In P2P networks, participants organize themselves in an overlay network that abstracts from the topological characteristics of the underlying physical network. Aim of these systems is the distribution of some kind of resources like contents, storage, or CPU cycles. Users, therefore, play an active role so that they can be considered as client and server at the same time, for the particular service that is provided through the P2P paradigm. Goal of this dissertation thesis is to study these systems, and give contributes in their performance evaluation. The analysis will aim to evaluate the achieved performance of a system and/or the performance bounds that could be achievable. In fact, even if there are several proposals of different systems, peer-to-peer streaming performance analysis can be considered still in its infancy and there is still a lot of work to do. To this aim, the main contributes of this dissertation thesis are i) the derivation of a theoretical delay bounds for P2P streaming system ii) II the creation of an algorithm that exploits the new insights that come out from the theoretical study iii) the performance evaluation of this algorithm using an ad-hoc simulator, expressly tailored to reproduce the characteristics of the real-world P2P streaming systems, composed by hundred thousands of intermittently connected users

Can AI be used ethically to assist peer review?

As the rate and volume of academic publications has risen, so too has the pressure on journal editors to quickly find reviewers to assess the quality of academic work. In this context the potential of Artificial Intelligence (AI) to boost productivity and reduce workload has received significant attention. Drawing on evidence from an experiment utilising AI to learn and assess peer review outcomes, Alessandro Checco, Lorenzo Bracciale, Pierpaolo Loreti, Stephen Pinfield, and Giuseppe Bianchi, discuss the prospects for AI for assisting peer review and the potential ethical dilemmas its application might produce

Privacy and Transparency in Blockchain-based Smart Grid Operations

In the past few years, blockchain technology has emerged in numerous smart grid applications, enabling the construction of systems without the need for a trusted third party. Blockchain offers transparency, traceability, and accountability, which lets various energy management system functionalities be executed through smart contracts, such as monitoring, consumption analysis, and intelligent energy adaptation. Nevertheless, revealing sensitive energy consumption information could render users vulnerable to digital and physical assaults. This paper presents a novel method for achieving a dual balance between privacy and transparency, as well as accountability and verifiability. This equilibrium requires the incorporation of cryptographic tools like Secure Mul- tiparty Computation and Verifiable Secret Sharing within the distributed components of a multi- channel blockchain and its associated smart contracts. We corroborate the suggested architecture throughout the entire process of a Demand Response scenario, from the collection of energy data to the ultimate reward. To address our proposal’s constraints, we present countermeasures against accidental crashes and Byzantine behavior while ensuring that the solution remains appropriate for low-performance IoT devices

Privacy-Aware Architectures for NFC and RFID Sensors in Healthcare Applications

World population and life expectancy have increased steadily in recent years, raising issues regarding access to medical treatments and related expenses. Through last-generation medical sensors, NFC (Near Field Communication) and radio frequency identification (RFID) technologies can enable healthcare internet of things (H-IoT) systems to improve the quality of care while reducing costs. Moreover, the adoption of point-of-care (PoC) testing, performed whenever care is needed to return prompt feedback to the patient, can generate great synergy with NFC/RFID H-IoT systems. However, medical data are extremely sensitive and require careful management and storage to protect patients from malicious actors, so secure system architectures must be conceived for real scenarios. Existing studies do not analyze the security of raw data from the radiofrequency link to cloud-based sharing. Therefore, two novel cloud-based system architectures for data collected from NFC/RFID medical sensors are proposed in this paper. Privacy during data collection is ensured using a set of classical countermeasures selected based on the scientific literature. Then, data can be shared with the medical team using one of two architectures: in the first one, the medical system manages all data accesses, whereas in the second one, the patient defines the access policies. Comprehensive analysis of the H-IoT system can be useful for fostering research on the security of wearable wireless sensors. Moreover, the proposed architectures can be implemented for deploying and testing NFC/RFID-based healthcare applications, such as, for instance, domestic PoCs

Assessment and validation of miniaturized technology for the remote tracking of critically endangered Galápagos pink land iguana (Conolophus marthae)

Abstract Background: Gathering ecological data for species of conservation concern inhabiting remote regions can be daunting and, sometimes, logistically infeasible. We built a custom-made GPS tracking device that allows to remotely and accurately collect animal position, environmental, and ecological data, including animal temperature and UVB radiation. We designed the device to track the critically endangered Galápagos pink land iguana, Conolophus marthae. Here we illustrate some technical solutions adopted to respond to challenges associated with such task and present some preliminary results from controlled trial experiments and field implementation. Results: Our tests show that estimates of temperature and UVB radiation are affected by the design of our device, in particular by its casing. The introduced bias, though, is systematic and can be corrected using linear and quadratic regressions on collected values. Our data show that GPS accuracy loss, although introduced by vegetation and orientation of the devices when attached to the animals, is acceptable, leading to an average error gap of less than 15 m in more than 50% of the cases. Conclusions: We address some technical challenges related to the design, construction, and operation of a custommade GPS tracking device to collect data on animals in the wild. Systematic bias introduced by the technological implementation of the device exists. Understanding the nature of the bias is crucial to provide correction models. Although designed to track land iguanas, our device could be used in other circumstances and is particularly useful to track organisms inhabiting locations that are difficult to reach or for which classic telemetry approaches are unattainable

Soil Biocementation via Enzyme Induced Carbonate Precipitation (eicp) Method Employing Soybeans as a Source of Cheap Enzyme

In this work, the soil improvement technique via Enzyme Induced Carbonate Precipitation (EICP) was investigated by employing, as an alternative to expensive pure enzymes, enzymes extracted from agro-food wastes (tomato, apple, and soybean) such that the process is economically viable and fully embraces the concept of the circular economy. The feasibility of the process was evaluated by monitoring calcium carbonate precipitation in a sand sample. The effect of selected operative parameters was investigated during the injection into different grain size sand samples. The optimal operating conditions in terms of sand grain size, temperature, Urea/Calcium concentration were found. Results demonstrated the effectiveness of this alternative solution for EICP method in term of acquired material strength and the possibility to operate sand consolidation through an economically sustainable process