178 research outputs found
Feasibility of Floating Content in VANETs
No full textVANETs can benefit by using an infrastructure-less model such as Floating Content (FC) in absence of infrastructures or as support to these latter. This work presents FC performances
in vehicular context by using Random Waypoint mobility model
Online human assisted and cooperative pose estimation of 2D cameras
No full textAutonomous robots performing cooperative tasks need to know the relative pose of the other robots in the fleet. Deducing these poses might be performed through structure from motion methods in the applications where there are no landmarks or GPS, for instance, in non-explored indoor environments. Structure from motion is a technique that deduces the pose of cameras only given only the 2D images. This technique relies on a first step that obtains a correspondence between salient points of images. For this reason, the weakness of this method is that poses cannot be estimated if a proper correspondence is not obtained due to low quality of the images or images that do not share enough salient points. We propose, for the first time, an interactive structure-from-motion method to deduce the pose of 2D cameras. Autonomous robots with embedded cameras have to stop when they cannot deduce their position because the structure-from-motion method fails. In these cases, a human interacts by simply mapping a pair of points in the robots' images. Performing this action the human imposes the correct correspondence between them. Then, the interactive structure from motion is capable of deducing the robots' lost positions and the fleet of robots can continue their high level task. From the practical point of view, the interactive method allows the whole system to achieve more complex tasks in more complex environments since the human interaction can be seen as a recovering or a reset process
DeepFloat: Resource-Efficient Dynamic Management of Vehicular Floating Content
No full textOpportunistic communications are expected to playa crucial role in enabling context-aware vehicular services. Awidely investigated opportunistic communication paradigm forstoring a piece of content probabilistically in a geographicalarea is Floating Content (FC). A key issue in the practicaldeployment of FC is how to tune content replication and cachingin a way which achieves a target performance (in terms ofthe mean fraction of users possessing the content in a givenregion of space) while minimizing the use of bandwidth andhost memory. Fully distributed, distance-based approaches provehighly inefficient, and may not meet the performance target,while centralized, model-based approaches do not perform wellin realistic, inhomogeneous settings.In this work, we present a data-driven centralized approachto resource-efficient, QoS-aware dynamic management of FC.We propose a Deep Learning strategy, which employs a Con-volutional Neural Network (CNN) to capture the relationshipsbetween patterns of users mobility, of content diffusion andreplication, and FC performance in terms of resource utilizationand of content availability within a given area. Numericalevaluations show the effectiveness of our approach in derivingstrategies which efficiently modulate the FC operation in spaceand effectively adapt to mobility pattern changes over time
Design and Evaluation of Floating Content Services for Vehicular Applications
No full textBy offloading vehicular data transfers from the telecommunication infrastructure to direct vehicular-to-vehicular communication, opportunistic communications reduce infrastructure investment, overload, and latency. However, performance studies of opportunistic communication models in vehicular networks mainly focus on content persistence without accounting for the system conditions that enable desired performance, such as the effectiveness with which the content object is replicated and made available. Thus, how to efficiently engineer a vehicular application characterized by an opportunistic communication model remains an open and challenging issue, crucial for the provision of high quality-of-service for vehicular applications.
This thesis aims to provide the tools to efficiently engineer a vehicular application characterized by opportunistic network models. We leverage on Floating Content (FC), an infrastructure-less opportunistic communication scheme that binds the local dissemination of information. The contributions of this thesis are summarized as follows. First, we design an enhanced method for configuring FC schemes in vehicular ad hoc networks. Our results suggest that it is always possible to find a reasonable size of the communication area such that the content object persists for the whole target duration. Second, we propose approaches for fine-tuning FC parameters (e.g., replication and caching) to guarantee a minimum target performance level while minimizing resources used, such as bandwidth and storage. Numerical evaluations show that our deep learning architecture provides content replication and storage strategies much more efficient than analytical techniques. Third, we provide an efficient communication scheme for content retrieval in vehicular networks that adapts to a wide range of network topologies and settings. Our approach outperforms delay-tolerant models reducing the content storage by 30% and the content replication by 43% with designed content availability, success content delivery, and delay targets.
Our approaches lay the foundation for the practical use of vehicular applications based on FC schemes in real scenarios
Gender Budgeting in Italian Universities
No full textAlthough the literature has extensively investigated the reasons for inequalities in the academic field, few contributions analyze the strategic role of gender budgeting as a reporting and planning tool for gender policies regarding equality.
Given that, the purpose of this chapter is to analyze the state of the art of gender budgeting in a sample of Italian public universities to highlight the potential that gender budgeting can have from a gender equality perspective.
To achieve this goal, the authors intend to answer the following research questions:
What is the state of the art of the incidence of gender in the composition of Italian universities (students, postgraduates, research fellows, teaching staff, technical-administrative staff and directors)?
What are the positive actions taken by Italian universities in gender budgeting to improve gender equality?
What is the level of integration between the positive actions favoring gender equality and the planning of the financial resources necessary to carry out these actions in the gender budgets of the sample considered?
This paper aims at expanding the international literature about the connection between gender studies and academic context. Our literature review emphasizes the topic analyzed as an emerging issue, which allows us to identify new trends and future directions for research.
The major implication of the paper is to increase knowledge and practice in the area of balance gender in the academic contest.
The relevant evidence of the chapter consists of a better understanding of gender budgeting as a concrete tool for planning positive actions to improve gender equality in Italian universities
A Deep Learning Strategy for Vehicular Floating Content Management
No full textFloating Content (FC) is a communication paradigm for the local dissemination of contextualized information through D2D connectivity, in a way which minimizes the use of resources while achieving some specified performance target. Existing approaches to FC dimensioning are based on unrealistic system assumptions that make them, highly inaccurate and overly conservative when applied in realistic settings. In this paper, we present a first step towards the development of a cognitive approach to efficient dynamic management of FC. We propose a deep learning strategy for FC dimensioning, which exploits a Convolutional Neural Network (CNN) to efficiently modulate over time the resources employed by FC in a QoS-aware manner. Numerical evaluations show that our approach achieves a maximum rejection rate of 3%, and resource savings of 37.5% with respect to the benchmark strategy
Elogio del filo a piombo
No full textLe ragioni tecniche e la base razionale e collettiva dell'architettura vengono analizzate come fondamenti di continuità che permettono di portare la tradizione classica fino all'esperienza modern
Agent-based systems in healthcare
No full text: This Special Issue is dedicated to discussing which are the advantages, challenges and open issues in the application of the agent-based approach as a part of the digital transformation in the healthcare sector. Agent-based technology in healthcare optimises resource allocation and coordination and supports clinical decision-making. Challenges, such as model reliability and interdisciplinary collaboration, must be addressed for widespread adoption. Embracing this technology promises improved healthcare delivery and better patient outcomes. Six papers, out of the many submitted, have been accepted for publication, each one discussing an aspect of this broad field
Floater ::post-disaster communications via floating content
No full textIn the immediate aftermath of nature-based disasters such as earthquakes, fires, or floods, have a clear vision of the situation and the population involved is of main priority for rescue operations—it is a matter of life and death. But these disaster events may cause malfunctions in communication services making the exchange information impossible—the experienced delay sending a message in an overcrowded area is a shred of evidence.
In this demo, we introduce Floater, a mobile awareness-based communication application for the immediate aftermath of a disaster, when ad hoc infrastructure support has not been deployed yet. Floater enables communications between peers in a common area without requiring the support of a cellular network. The application is developed for Android and it does not require an account or an Internet connection. Floater exploits local knowledge and constraints opportunistic replication (peer to peer) of information to build a global view of the involved area efficiently.
The app is the first to implement Floating Content, an infrastructure-less communication paradigm based on opportunistic replication of a piece of content in a geographically constrained location and for a limited amount of time.
The demo illustrates the feasibility and the main functionalities of Floater and presents disaster assistance use cases for supporting rescue operations
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