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Optimal charging of electric vehicle fleets for a car sharing system with power sharing
No full textElectric car sharing services have been growing in popularity in the last years but operators are striving to reduce the costs of deploying and managing their charging infrastructure. Charging technologies that offer power sharing have the potential to achieve this goal but at the cost of increasing management complexity. In order to address this problem, in this work we propose an efficient optimized charging methodology that minimizes recharging costs when power sharing is used and also takes into account customer satisfaction. To this aim, we formulate the recharging problem as a two-step optimization problem, considering a realistic energy pricing scheme, and we evaluate this solution using real traces of parking times in a French station-based car sharing system. We show that significant cost savings can be achieved without impacting customer satisfaction and also reducing the strain on the grid with respect to a baseline approach
Logical Key Hierarchy for Groups Management in Distributed Online Social Network
No full textDistributed Online Social Networks (DOSNs) have recently been proposed to shift the control over user data from a unique entity to the users of the DOSN themselves.In this paper, we focus our attention on the problem of privacy preserving content sharing to a large group of users of the DOSNs.Several solutions, based on cryptographic techniques, have been recently proposed.The main challenge here is the definition of a scalable and decentralized approach that: i) minimizes the re-encryption of the contents published in a group when the composition of the group changes and ii) enables a fast distribution of the cryptographic keys to all the members (n) of a group, each time a new user is added or removed from the group by the group owner. Our solution achieves the above goals, providing performance unattained by our competitors. In particular, our approach requires only O(d log n) encryption operations when the group membership changes (eviction), and only O(2 log n) when a join occurs (where d is a input parameter of the system). The effectiveness of our approach is evaluated by an experimental campaign carried out over a set of traces from a real online social network
Characterising demand and usage patterns in a large station-based car sharing system
No full textCar sharing is a new mode of transportation that is gaining increasing popularity with its promise to reduce traffic congestion, parking demands and pollution in our cities. Despite this potential, the properties of car sharing systems, e.g., in terms of spatiotemporal characterisation of how customers use the service, remain largely unexplored in the research literature. In order to fill this gap, in this work we analyse one month of online car-sharing map data from a large station-based carsharing operator in France, which has 960 stations and more than 2700 electric cars. First, we study the spatial and temporal patterns of station utilisation, uncovering a dichotomy in station usage (stations that attract cars mostly in the morning vs. stations attracting cars mostly in the evening). We also find that this dichotomy is linked to the destination (residential or business) of the zone in which the station is located. In addition, we statistically model the users\u27 demand in terms of drop-off and pickup rates, and the parking times of vehicles. Finally, we propose a classifier that exploits simple average statistics (average pickup rate and car availability of a station) in order to understand whether the station is profitable or not for the operator
Internet of Things: Research challenges and Solutions
No full textThe past decade has witnessed a significant proliferation of Internet-capable devices. While its greatest commercial impact has been in the area of consumer electronics, with the smartphone revolution and the uptake of wearables, connecting humans is only part of a greater trend toward the interconnection of the physical world with the digital world.While the Internet is a communication network connecting people to information, the Internet of Things (IoT) is an interconnected ecosystem of uniquely addressable physical objects with varying degrees of sensing, processing, and actuation capabilities, sharing the ability to communicate and interoperate through the Internet as their common denominator [1].With the IoT paradigm, sensor-equipped devices can provide fine-grained information about the physical world, allowing cloud-based resources to extract value from such information and possibly make decisions to be implemented by actuator-equipped devices, blurring the line between the IoT and the broader concept of Cyber-Physical Systems [2], [3] and [4], which does not necessarily presuppose Internet connectivity per se.The vagueness of the term ?Things?makes it hard to define the ever expanding boundaries of the IoT, but at the same time offers a clear idea of its heterogeneity and its virtually limitless application potential. This has spawned very encouraging projections from market analysts and corporate players who envision a multi-trillion dollar market for the IoT.As commercial success materializes, the IoT continues to offer a seemingly boundless supply of opportunities for both business and research. This special issue of Computer Communications is dedicated to the latter, offering a varied collection of research contributions to cutting-edge themes within the IoT space. This special issue complements [5], which focused on architectures, protocols, and services
IEEE 802.11p VANets: Experimental Evaluation of Packet Inter-Reception Time
No full textWe start by showing that PIR cannot be reliably estimated from PDR, since the two metrics are only weakly correlated. Motivated by this finding, we present a thorough characterization of the PIR time distribution, which is shown to be a power law in a variety of configurations. The shape of the PIR time distribution indicates that potentially dangerous "situational awareness" blackouts are relatively frequent and positively time correlated.We then evaluate the effect of vehicle configuration and line-of-sight conditions on the PIR time, and show that relatively simple multi-hop beaconing techniques can substantially improve PIR statistics and, hence, safety. A final contribution of this paper is promoting the Gilbert-Elliot model, previously proposed to model bit-error bursts in packet switched networks, as a very accurate model of beacon reception behavior observed in real-world scenarios
In-silico prediction and deep-DNA sequencing validation indicate phase variation in 115 Neisseria meningitidis genes
No full textBackgroundThe Neisseria meningitidis (Nm) chromosome shows a high abundance of simple sequence DNA repeats (SSRs) that undergo stochastic, reversible mutations at high frequency. This mechanism is reflected in an extensive phenotypic diversity that facilitates Nm adaptation to dynamic environmental changes. To date, phase-variable phenotypes mediated by SSRs variation have been experimentally confirmed for 26?Nm genes.ResultsHere we present a population-scale comparative genomic analysis that identified 277 genes and classified them into 52 strong, 60 moderate and 165 weak candidates for phase variation. Deep-coverage DNA sequencing of single colonies grown overnight under non-selective conditions confirmed the presence of high-frequency, stochastic variation in 115 of them, providing circumstantial evidence for their phase variability.We confirmed previous observations of a predominance of variable SSRs within genes for components located on the cell surface or DNA metabolism. However, in addition we identified an unexpectedly broad spectrum of other metabolic functions, and most of the variable SSRs were predicted to induce phenotypic changes by modulating gene expression at a transcriptional level or by producing different protein isoforms rather than mediating on/off translational switching through frameshifts.Investigation of the evolutionary history of SSR contingency loci revealed that these loci were inherited from a Nm ancestor, evolved independently within Nm, or were acquired by Nm through lateral DNA exchange.ConclusionsOverall, our results have identified a broader and qualitatively different phenotypic diversification of SSRs-mediated stochastic variation than previously documented, including its impact on central Nm metabolism
INQUINAMENTO DELLE ACQUE SOTTERRANEE DA SOSTANZE ORGANICHE CLORURATE NELL\u27AREA VASTA DEI TERRITORI DEI COMUNI DI POMEZIA E ARDEA Rapporto di un Tavolo Tecnico istituito dalla Regione Lazio
No full textReport produced by the study commission of the Lazio Region for: - study of a vast area affected by the pollution of groundwater.Rapporto prodotto nell\u27ambito della commissione di studio istituita presso la Regione Lazio per lo studio di una vasta area interessata a fenomeni di inquinamento delle acque sotterranee
A proposito di acqua: la newsletter del CNR Istituto per lo Studio degli Ecosistemi di Verbania Pallanza
No full textNo abstract availableITTIORTA: un progetto al servizio del Lago d\u27Orta e della sua comunit?; Le azioni COST: reti europee di ricercatori per la scienza e la tecnologia; Curiosit? dall\u27Archivio Storico: l\u27Istituto Italiano di Idrobiologia e il cinema; Alcune immagini dall\u27IS
Random walks in swarm robotics: an experiment with Kilobots
No full textRandom walks represent fundamental search strategies for both animal and robots, especially when there are no environmental cues that can drive motion, or when the cognitive abilities of the searching agent do not support complex localisation and mapping behaviours. In swarm robotics, random walks are basic building blocks for the individual behaviour and support the emergent collective pattern. However, there has been limited account for the correct parameterisation to be used in different search scenarios, and the relationship between search efficiency and information transfer within the swarm has been often overlooked. In this study, we analyse the efficiency of random walk patterns for a swarm of Kilobots searching a static target in two different environmental conditions entailing a bounded or an open space. We study the search efficiency and the ability to spread information within the swarm through numerical simulations and real robot experiments, and we determine what kind of random walk best fits each experimental scenario
GRAIL: a Goal-Discovering Robotic Architecture for Intrinsically-Motivated Learning
No full textIn this paper, we present goal-discovering robotic architecture for intrisically-motivated learning (GRAIL), a four-level architecture that is able to autonomously: 1) discover changes in the environment; 2) form representations of the goals corresponding to those changes; 3) select the goal to pursue on the basis of intrinsic motivations (IMs); 4) select suitable computational resources to achieve the selected goal; 5) monitor the achievement of the selected goal; and 6) self-generate a learning signal when the selected goal is successfully achieved. Building on previous research, GRAIL exploits the power of goals and competence-based IMs to autonomously explore the world and learn different skills that allow the robot to modify the environment. To highlight the features of GRAIL, we implement it in a simulated iCub robot and test the system in four different experimental scenarios where the agent has to perform reaching tasks within a 3-D environment