This paper presents the design and implementation of a proof of concept digital twin for an innovative ultrasonicenhanced beer-fermentation system, developed to enable intelligent monitoring, prediction, and actuation in yeast-growth environments. A traditional fermentation tank is equipped with a piezoelectric transducer able to irradiate the tank with ultrasonic waves, providing an external abiotic stimulus to enhance the growth of yeast and accelerate the fermentation process. At its core, the digital twin incorporates a predictive model that estimates yeast's culture density over time based on the surrounding environmental conditions. To this end, we implement, tailor and extend the model proposed in [1], allowing us to effectively handle the limited number of available training samples by using temperature, ultrasonic frequency, and duty cycle as inputs. The results obtained, along with the assessment of model performance, demonstrate the feasibility of the proposed approach.

The Internet has plenty of images that are transformations (e.g., resize, blur) of confidential original images. Several scenarios (e.g., selling images over the Internet, fighting disinformation, detecting deep fakes) would highly benefit from systems allowing to verify that an image is the result of a transformation applied to a confidential authentic image. In this paper, we focus on systems for proving and verifying the correctness of transformations of authentic images guaranteeing: 1) confidentiality (i.e., the original image remains private), 2) efficient proof generation (i.e., the proof certifying the correctness of the transformation can be computed with a common laptop) even for high-resolution images, 3) authenticity (i.e., only the advertised transformations have been applied) and 4) fast detection of fraud proofs.. Our contribution consists of new definitions modelling confidentiality and adaptive adversaries, techniques to speed up the prover of a ZK-snark, an efficient construction relying on ad-hoc signatures and hashes, and a less efficient construction that works according to signatures and hashes included in the C2PA specifications. Experimental results confirm the viability of our approach, allowing to compute an authentic transformation of a high-resolution image on a common computer. Prior results instead either require expensive computing resources or provide unsatisfying confidentiality.

The Interested Party Information (IPI) system uniquely identifies the rights holders worldwide, making it possible to know for each subject and at any time which rights are protected, by whom and for which territories. Currently, this service is provided in a centralized way but in 2021, the Italian Society of Authors and Editors (SIAE) deployed a blockchain-based solution to completely decentralize this database to (a) provide greater guarantees to the rights holders as well as end users and (b) make a first tangible step in the path towards an all in-chain solution decentralizing a relevant component of the current architecture. This solution relied on early versions of Algorand smart contracts, delegating some off-chain verification to trusted third parties in many practical scenarios. Moreover, the Algorand technology has developed new tools, allowing us to design new techniques to reduce some of the trust assumptions of the original solution and enhance its efficiency at the same time. In this paper, we present the evolution of the solutions we designed to issue new on-chain non-conflicting rights representations, namely representations that are consistent with those already available on-chain. Our solution relies on smart contracts that have been implemented to run our experiments to prove (a) the feasibility of the proposed approach, (b) the scalability of the proposed solutions, and (c) the sustainability in terms of costs.

Monitoring business processes within complex supply chains demands efficient data collection and analytics tailored to diverse phenomena. Traditional centralized solutions face limitations in adapting to the dynamic nature of supply chains. This calls for distributed solutions which break the usual architectural assumption to have a central entity in charge of collecting, integrating and offering tools for the analysis. This project, embedded in a larger initiative called MICS, proposes an inno-vative distributed monitoring solution integrating blockchain for a trustworthy and efficient data analytics strategy that preserves data sovereignty in complex collaborative environments. Leveraging the cloud -edge continuum, the solution aims to ensure secure data exchange, adherence to agreements, and real-time analytics. Expected outcomes include an innovative federated architecture, 5G slice management solutions, an adversarial analysis of supply chain security, and a proof-of-concept implementation of the blockchain-based data flow tracking system. These developments aim to enhance the reliability, security, and efficiency of supply chain monitoring in dynamic industrial environments.

Ethereum's founder Buterin raised the challenge of solving the blockchain Trilemma towards a decentralized computer that could together achieve high degrees of security, scalability, and decentralization. Later on, Algorand claimed to have resolved Buterin's blockchain Trilemma and is nowadays increasingly adopted by designers of decentralized computations. Motivated by the need of selecting a blockchain to run some decentralized computations, we observe the limitations of using the Trilemma as benchmark, and we propose as alternative a Quadrilemma that takes into account also computational effectiveness, namely the capability of running non-trivial decentralized computations at affordable costs. For concreteness, motivated by the current trends of using blockchains for the management of non-fungible tokens (NFTs) related to highly desired items (i.e., NFTs for art), we consider the use case of decentralized auctions in various scenarios that mainly differ on the desired degree of confidentiality. Our contribution gives the following insights. Except very limited cases where also Bitcoin can be taken into account (i.e., when latency is not a big deal and only notarization is required), Algorand can often be the right choice as long as decentralized computations consist of basic operations only. Instead, Ethereum is advisable when more sophisticated computations are required, in particular when ad-hoc cryptographic tasks are essential, and one can afford the involved costs and latency. Focusing on those three blockchains, the state of affairs about resolving the blockchain Quadrilemma is somewhat unsatisfying. Even in natural cases where computations and storage requirements for a smart contract are low (e.g., public-key encryption), none of those decentralized computers achieves simultaneously low cost and fast transaction confirmations.

In many applications, identity management (IdM) is used to associate a subject public key with an endpoint at which the subject can be contacted (telephone number, email, etc.). In decentralized applications based on blockchains, it is desirable for the IdM to be decentralized as well. In certain applications, it is paramount to be certain that an endpoint actually belong to a specific subject. Currently, when this is needed, endpoints are either verified by who needs it, which is impractical in blockchain-based applications, or by a centralized authority, which contrasts with the spirit of the blockchain.In this paper, we show two layer-two blockchain-based protocols to prove the association between a subject and an endpoint in a decentralized manner. Our protocols are compatible with a wide variety of endpoints and contribute to fill the gap of the current self sovereign IdM approaches with respect to decentralization. We analyze the security of our proposals and evaluate performances and costs against the common approaches.

The arising of new technologies ranging from smartphones to social networks is constantly increasing interactions between people. In the Information and Communications Technology (ICT) community, adapting technology to human nature is the key concern of User-Centered Design (UCD). However, UCD tends to neglect the emerging social dimension of technology: users are consulted in the design process, but they do not have any direct involvement or creative control over the developed technological solutions. On the other hand, the collaborative and social nature of the design process is getting increasingly explicit in the Product Design community, where well-established participatory approaches are applied to involve stakeholders, designers, and end-users in the creative process of new products. In this paper, we first provide a deep analysis of the state of the art of participatory approaches in the research literature. Then, we investigate how their integration with UCD leads not only to empower the role of end-users as active collaborators of designers towards a more democratic crowd-based UCD process, but also to create innovation in the design process. We advocate that such innovation can be obtained by giving the right voice not only to the users who reach consensus in the design process but also to the marginals. We provide an explorative model, some experiments, and a sketch of the user interface to support our claim.

Online social networks, formed by cyber interactions between users, are nowadays explored in a number of papers. In this work, we present our experimental activity on Face-To-Face (F2F) social networks tracing physical interactions of humans in real-world scenarios. We briefly present the technologies to observe F2F social networks focusing on the SocioPatterns platform that we have employed in our real-world experiments. Motivated by the requirements of heterogeneous applications, we discuss how to tune the SocioPatterns collection protocol parameters in order to better capture fast interactions between users; carried out experiments confirm the effectiveness of such tuning.

In this paper we consider Delay Tolerant Network (DTN) as a technology to implement a future network in a People Centric Networking paradigm, using Active RFID carried by people that exchange information with each other. We propose a novel and real Neighbor Discovery (ND) phase on active RFID based DTN using Open Beacon devices. In particular, we propose a solution using the Sift distribution on a probabilistic persistent approach called Sift-Persistent. We simulated P-Persistent, Aloha and our solution using our customized Java simulator. We implemented Sift-Persistent and P-Persistent on Open-Beacon devices, comparing the simulation results and test-beds. Moreover, simulations and real testbed show a coherent behavior validating our proposal in the RFID context. Performance evaluations have been tested in terms of discovered neighbors.

In this paper we analyze the interaction between two communication protocols implemented in TinyOS 2.x: Deluge T2, an over-the-air programming protocol, and the Low Power Listening (LPL) implementation provided with the standard Medium Access Control layer, BoX-MAC. We show how the characteristics of the two layers deeply diverge, leading to a sensible performance degradation. We present REACTIVE, a simple algorithm that, integrated in Deluge, is able to dynamically disable and re-enable LPL in order to boost Deluge performance, leveraging on the critical aspects of the layers integration. REACTIVE is able to increase the performance of Deluge, compared to its standard implementation, by a factor of 2.6 in terms of energy efficiency and 7 in terms of dissemination time.

ProvinciaSense is a proof-of-concept of the integration of both static and mobile sensor nodes with ProvinciaWiFi, a network which currently hosts more than 1100 WiFi Access Points (APs) serving Rome and other 120 cities with about 4.5 millions of citizens. The simple and cost effective integration of sensor nodes with a big number of ProvinciaWiFi APs will allow us to deploy one among the biggest available testbeds for wireless sensor networks and to support the implementation of effective smart cities services.

This poster presents the work done to monitor the structural health of a Rome B1 underground construction site through a battery-powered Wireless Sensor Network (WSN). We illustrate the specific requirements and challenges of working with wireless sensors underground, and we describe the solutions adopted for obtaining a working WSN that provides a robust solution of on line monitoring. We conclude by presenting an assessment and testing of these solutions, along with the design insights and the lessons we learned during this on-the-field experience.

The purpose of this demo is to introduce a new low-power wireless device for Wireless Sensor Networks (WSN) operating in the ISM 2.4Ghz band: the MagoNode. Thanks to a highly efficient RF front-end, that extends the radio range and increases link reliability, the MagoNode features out-standing RF performance, still containing energy consumption. The platform has been designed at the Department of Computer, Control, and Management Engineering Antonio Ruberti of the University of Rome La Sapienza in collaboration with the spin-off WSense [1].

In this paper we discuss the first results of the PLEASED project [1] which aims at employing plants as biosensors of a new generation of pervasive and organic wireless sensor networks.

In this paper we propose a fully decentralized approach for recommending new contacts in the social network of mobile phone users. With respect to existing solutions, our approach is characterized by some distinguishing features. In particular, the application we propose does not assume any centralized coordination: it transparently collects and processes user information that is accessible in any mobile phone, such as the log of calls, the list of contacts or the inbox/outbox of short messages and exchanges it with other users. This information is used to recommend new friendships to other users. Furthermore, the information needed to perform recommendation is collected and exchanged between users in a privacy preserving way. Finally, information necessary to implement the application is exchanged transparently and opportunistically, by using the residual space in standard short messages occasionally exchanged between users. As a consequence, we do not ask users to change their habits in using SMS.

A sensor network consists of sensing devices which may exchange data through wireless communication; sensor networks are highly energy constrained since they are usually battery operated. Data aggregation is a possible way to save energy consumption: nodes may delay data in order to aggregate them into a single packet before forwarding them towards some central node (sink). However, many applications impose constraints on the maximum delay of data; this translates into latency constraints for data arriving at the sink. We study the problem of data aggregation to minimize maximum energy consumption under latency constraints on sensed data delivery, and we assume unique communication paths that form an intree rooted at the sink. We prove that the offline problem is strongly NP-hard and we design a 2-approximation algorithm. The latter uses a novel rounding technique. Almost all real-life sensor networks are managed online by simple distributed algorithms in the nodes. In this context we consider both the case in which sensor nodes are synchronized or not. We assess the performance of the algorithm by competitive analysis. We also provide lower bounds for the models we consider, in some cases showing optimality of the algorithms we propose. Most of our results also hold when minimizing the total energy consumption of all nodes.

The paper presents IRIS, an Integrated Routing and Interest dissemination System for wireless sensor networks. The proposed protocols are designed to work under very low duty cycle operations and are jointly optimized for improved efficiency. Routing towards the sink is achieved by exploiting hop count information which is proactively distributed during the interest dissemination phase. Node densities are locally and dynamically estimated at each node and exploited at the MAC layer by means of a cost based probabilistic scheme. A cross-layer routing/MAC scheme is defined where relays to the sink are selected based on nodes' resources (including energy and queue occupancy). The proposed solution is a step towards the definition of complete, self-adapting and autonomous sensor network systems.

Abstract Next‐generation 3G/4G wireless data networks allow multiple codes (or channels) to be allocated to a single user, where each code can support multiple data rates. Providing fine‐grained QoS to users in such networks poses the two‐dimensional challenge of assigning both power (rate) and codes to every user. This gives rise to a new class of parallel scheduling problems. We abstract general downlink scheduling problems suitable for proposed next‐generation wireless data systems. Our contribution includes a communication‐theoretic model for multirate wireless channels. In addition, while conventional focus has been on throughput maximization, we attempt to optimize the maximum response time of jobs, which is more suitable for streams of user requests. We present provable results on the algorithmic complexity of these scheduling problems. In particular, we are able to provide very simple, on‐line algorithms for approximating the optimal maximum response time. We also perform an experimental study with realistic data of channel conditions and user requests that strengthens our theoretical results. © 2004 Wiley Periodicals, Inc. NETWORKS, Vol. 45(1), 9–22 2005

Next generation 3G/4G wireless data networks allow multiple codes (or channels) to be allocated to a single user, where each code can support multiple data rates. Providing fine-grained QoS to users in such networks poses the two dimensional challenge of assigning both power (rate) and codes for every user. This gives rise to a new class of parallel scheduling problems. We abstract general downlink scheduling problems suitable for proposed next generation wireless data systems. This includes a communication-theoretic model for multirate wireless channels. In addition, while conventional focus has been on throughput maximization, we attempt to optimize the maximum response time of jobs, which is more suitable for stream of user requests. We present provable results on the algorithmic complexity of these scheduling problems. In particular, we are able to provide very simple, online algorithms for approximating the optimal maximum response time. This relies on resource augmented competitive analysis. We also perform an experimental study with realistic data of channel conditions and user requests to show that our algorithms are more accurate than our worst case analysis shows, and they provide fine-grained QoS to users effectively.