Energetical analysis of two different configurations of a liquid-gas compressed energy storage

In order to enhance the spreading of renewable energy sources in the Italian electric power market, as well as to promote self-production and to decrease the phase delay between energy production and consumption, energy storage solutions are catching on. Nowadays, in general, small size electric storage batteries represent a quite diffuse technology, while air liquid-compressed energy storage solutions are used for high size. The goal of this paper is the development of a numerical model for small size storage, environmentally sustainable, to exploit the higher efficiency of the liquid pumping to compress air. Two different solutions were analyzed, to improve the system efficiency and to exploit the heat produced by the compression phase of the gas. The study was performed with a numerical model implemented in Matlab, by analyzing the variation of hermodynamical parameters during the compression and the expansion phases, making an energetic assessment for the whole system. The results show a good global efficiency, thus making the system competitive with the smallest size storage batteries

Retrofit Proposals for Energy Efficiency and Thermal Comfort in Historic Public Buildings: The Case of the Engineering Faculty’s Seat of Sapienza University

The building sector greatly contributes to energy consumption and Greenhouse Gas emissions, relating to the whole building life cycle. Boasting a huge building heritage of historical and architectural value, Europe faces challenging retrofit perspectives, as the potential for high energy efficiency has to be exploited while preserving the buildings' original characteristics. The present work aims to feature the influence of a passive strategy on a heritage building in a mild climate. As historical its facade cannot be modified, its large glazing areas involve multiple issues, such as an increase in the heating (QH) and cooling (QC) energy demands and the risk of thermal discomfort. Thus, window replacement was proposed for retrofitting. A dynamic simulation model in TRNSYS was validated with experimental data collected by the continuous monitoring of walls of different thicknesses and orientations. Solutions from replacement with Double Glazing Units (DGUs) with improved thermal insulation, to internal shading activation were applied. All configurations were compared in terms of QH, QC, thermal performance of the building and user comfort (Fanger). Low-e DGU enabled the saving of up to 14% of the annual energy demand, and shading also offered good results in summer, reducing QC by 19%. In summer, DGU involved a maximum PPD reduction of 10 units

Performance evaluation of Attribute-Based Encryption on constrained IoT devices

The Internet of Things (IoT) is enabling a new generation of innovative services based on the seamless integration of smart objects into information systems. This raises new security and privacy challenges that require novel cryptographic methods. Attribute-Based Encryption (ABE) is a type of public-key encryption that enforces a fine-grained access control on encrypted data based on flexible access policies. The feasibility of ABE adoption in fully-fledged computing systems, i.e., smartphones or embedded systems, has been demonstrated in recent works. In this paper, we consider IoT devices characterized by strong limitations in terms of computing, storage, and power. Specifically, we assess the performance of ABE in typical IoT constrained devices. We evaluate the performance of three representative ABE schemes configured considering the worst-case scenario on two popular IoT platforms, namely ESP32 and RE-Mote. Our results show that, if we assume to employ up to 10 attributes in ciphertexts and to leverage hardware cryptographic acceleration, then ABE can indeed be adopted on devices with very limited memory and computing power, while obtaining a satisfactory battery lifetime. In our experiments, as also performed in other works in the literature, we consider only the worst-case configuration, which, however, might not be completely representative of the real working conditions of sensors employing ABE. For this reason, we complete our evaluation by proposing a novel benchmark method that we used to complement the experiments by evaluating the average performance. We show that by always considering the worst case, the current literature significantly overestimates the processing time and the energy consumption

Evaluation of Feasibility and Impact of Attacks against the 6top Protocol in 6TiSCH Networks

The 6TiSCH architecture has been gaining attraction as a promising solution to ensure reliability and security for communication in applications for the Industrial Internet of Things (IIoT). While many different aspects of the architecture have been investigated in literature, an in-depth analysis of the security features included in its design is still missing. In this paper, we assess the security vulnerabilities of the 6top protocol, a core component of the 6TiSCH architecture for enabling network nodes to negotiate communication resources. Our analysis highlights two possible attacks against the 6top protocol that can impair network performance and reliability in a significant manner. To prove the feasibility of the attacks in practice, we implemented both of them on the Contiki-NG Operating System and tested their effectiveness on a simple deployment with three Zolertia RE-Mote sensor nodes. Also, we carried out a set of simulations using Cooja in order to assess their impact on larger networks. Our results show that both attacks reduce reliability in the overall network and increase energy consumption of the network nodes

D2D Communications for Large-Scale Fog Platforms: Enabling Direct M2M Interactions

To many, fog computing is considered the next step beyond the current centralized cloud that will support the forthcoming Internet of Things (IoT) revolution. While IoT devices will still communicate with applications running in the cloud, localized fog clusters will appear with IoT devices communicating with application logic running on a proximate fog node. This will add proximity-based machine-to-machine (M2M) communications to standard cloud-computing traffic, and it calls for efficient mobility management for entire fog clusters and energy-efficient communication within them. In this context, long-term evolution-advanced (LTE-A) technology is expected to play a major role as a communication infrastructure that guarantees low deployment costs, native mobility support, and plug-and-play seamless configuration. We investigate the role of LTE-A in future large-scale IoT systems. In particular, we analyze how the recently standardized device-to-device (D2D) communication mode can be exploited to effectively enable direct M2M interactions within fog clusters, and we assess the expected benefits in terms of network resources and energy consumption. Moreover, we show how the fog-cluster architecture, and its localized-communication paradigm, can be leveraged to devise enhanced mobility management, building on what LTE-A already has to offer

Optimized energy and air quality management of shared smart buildings in the covid-19 scenario

Worldwide increasing awareness of energy sustainability issues has been the main driver in developing the concepts of (Nearly) Zero Energy Buildings, where the reduced energy consumptions are (nearly) fully covered by power locally generated by renewable sources. At the same time, recent advances in Internet of Things technologies are among the main enablers of Smart Homes and Buildings. The transition of conventional buildings into active environments that process, elaborate and react to online measured environmental quantities is being accelerated by the aspects related to COVID-19, most notably in terms of air exchange and the monitoring of the density of occupants. In this paper, we address the problem of maximizing the energy efficiency and comfort perceived by occupants, defined in terms of thermal comfort, visual comfort and air quality. The case study of the University of Pisa is considered as a practical example to show preliminary results of the aggregation of environmental data

Symbolic Melodic Similarity: State of the Art and Future Challenges

Fostered by the introduction of the Music Information Retrieval Evaluation eXchange (MIREX) competition, the number of systems which calculate Symbolic Melodic Similarity has recently increased considerably. In order to understand the state of the art, we provide a comparative analysis of existing algorithms. The analysis is based on eight criteria that help characterising the systems, and highlighting strengths and weaknesses. We also propose a taxonomy which classifies algorithms based on their approach. Both taxonomy and criteria are fruitfully exploited for providing input for new forthcoming research in the area

MECPerf: An Application-Level Tool for Estimating the Network Performance in Edge Computing Environments

Edge computing is an emerging architecture in 5G networks where computing power is provided at the edge of the fixed network, to be as close as possible to the end users. Computation offloading, better communication latency, and reduction of traffic in the core network are just some of the possible benefits. However, the Quality of Experience (QoE) depends significantly on the network performance of the user device towards the edge server vs. cloud server, which is not known a priori and may generally change very fast, especially in heterogeneous, dense, and mobile deployments. Building on the emergence of standard interfaces for the installation and operation of thirdparty edge applications in a mobile network, such as the MultiAccess Edge Computing (MEC) under standardization at the European Telecommunications Standards Institute (ETSI), we propose MECPerf, a tool for user-driven network performance measurements. Bandwidth and latency on different network segments are measured and stored in a central repository, from where they can be analyzed, e.g., by application and service providers without access to the underlying network management services, for run-time resource optimization

Automated Planning Techniques for Robot Manipulation Tasks Involving Articulated Objects

The goal-oriented manipulation of articulated objects plays an important role in real-world robot tasks. Current approaches typically pose a number of simplifying assumptions to reason upon how to obtain an articulated object’s goal configuration, and exploit ad hoc algorithms. The consequence is two-fold: firstly, it is difficult to generalise obtained solutions (in terms of actions a robot can execute) to different target object’s configurations and, in a broad sense, to different object’s physical characteristics; secondly, the representation and the reasoning layers are tightly coupled and inter-dependent. In this paper we investigate the use of automated planning techniques for dealing with articulated objects manipulation tasks. Such techniques allow for a clear separation between knowledge and reasoning, as advocated in Knowledge Engineering. We introduce two PDDL formulations of the task, which rely on conceptually different representations of the orientation of the objects. Experiments involving several planners and increasing size objects demonstrate the effectiveness of the proposed models, and confirm its exploitability when embedded in a real-world robot software architecture