A simulator for drones and Fanet management supporting multimedia traffic under human mobility

In this paper a simulator for the management of a team of Unmanned Aerial Vehicles (UAVs) and drones has been proposed. This new network is known as Fly Ad-Hoc Network (FANET), and it is a particular type of Mobile Ad-Hoc Network (MANET) but with some specific aspects that allow to provide new services in future generation networks. One of the possible applications is emergency situations or scenario where drones can provide an additional or complementary access networks supporting web services and multimedia traffic. In this paper a simulator for FANET deploying has been proposed providing the possibility to simulate different scenarios with different coverage areas. New coverage model has been included in the features and also interesting human mobility model to support more realistic users mobility. Moreover, additional modules for traffic pattern generation have been implemented to create scenario where mobile users can activate multimedia calls and traffic on FANET. Some simulations have been led out to show how the simulator works

Managing emergency situations in VANET through heterogeneous technologies cooperation

Nowadays, the research on vehicular computing enhanced a very huge amount of services and protocols, aimed to vehicles security and comfort. The investigation of the IEEE802.11p, Wireless Access in Vehicular Environments (WAVE) and Dedicated Short Range Communication (DSRC) standards gave to the scientific world the chance to integrate new services, protocols, algorithms and devices inside vehicles. This opportunity attracted the attention of private/public organizations, which spent lot of resources and money to promote vehicular technologies. In this paper, the attention is focused on the design of a new approach for vehicular environments able to gather information during mobile node trips, for advising dangerous or emergency situations by exploiting on-board sensors. It is assumed that each vehicle has an integrated on-board unit composed of several sensors and Global Position System (GPS) device, able to spread alerting messages around the network, regarding warning and dangerous situations/conditions. On-board units, based on the standard communication protocols, share the collected information with the surrounding road-side units, while the sensing platform is able to recognize the environment that vehicles are passing through (obstacles, accidents, emergencies, dangerous situations, etc.). Finally, through the use of the GPS receiver, the exact location of the caught event is determined and spread along the network. In this way, if an accident occurs, the arriving cars will, probably, avoid delay and danger situations

On packet marking and Markov modeling for IP Traceback: A deep probabilistic and stochastic analysis

From many years, the methods to defend against Denial of Service attacks have been very attractive from different point of views, although network security is a large and very complex topic. Different techniques have been proposed and so-called packet marking and IP tracing procedures have especially demonstrated a good capacity to face different malicious attacks. While host-based DoS attacks are more easily traced and managed, network-based DoS attacks are a more challenging threat. In this paper, we discuss a powerful aspect of the IP traceback method, which allows a router to mark and add information to attack packets on the basis of a fixed probability value. We propose a potential method for modeling the classic probabilistic packet marking algorithm as Markov chains, allowing a closed form to be obtained for evaluating the correct number of received marked packets in order to build a meaningful attack graph and analyze how marking routers must behave to minimize the overall overhead

A new FANET simulator for managing drone networks and providing dynamic connectivity

In the last decade, the attention on unmanned aerial vehicles has rapidly grown, due to their ability to help in many human activities. Among their widespread benefits, one of the most important uses regards the possibility of distributing wireless connectivity to many users in a specific coverage area. In this study, we focus our attention on these new kinds of networks, called flying ad-hoc networks. As stated in the literature, they are suitable for all emergency situations where the traditional networking paradigm may have many issues or difficulties to be implemented. The use of a software simulator can give important help to the scientific community in the choice of the right UAV/drone parameters in many different situations. In particular, in this work, we focus our main attention on the new ways of area covering and human mobility behaviors with the introduction of a UAV/drone behavior model to take into account also drones energetic issues. A deep campaign of simulations was carried out to evaluate the goodness of the proposed simulator illustrating how it works

A New Distributed Predictive Congestion Aware Re-Routing Algorithm for CO2 Emissions Reduction

In the last years, vehicular networking has grown up in terms of interest and transmission capability, due to the possibility of exploiting the distributed communication paradigm in a mobile scenario, where moving nodes are represented by vehicles. The different existing standards for vehicular ad-hoc networks, such as dedicate short range communication (DSRC), wireless access for vehicular environment (WAVE)/IEEE802.11p, have given to the research community the possibility of developing new medium access control (MAC) and routing schemes, in order to enhance the quality and the comfort of mobile users who are driving their vehicles. In this paper, we focus our attention on the optimization of traffic flowing in a vehicular environment with vehicle-2-roadside capability. As shown later, the proposed idea exploits the information that is gathered by road-side units to redirect traffic flows (in terms of vehicles) to less congested roads, with an overall system optimization, also in terms of carbon dioxide emissions reduction. An analytical model, as well as a set of pseudo-code instructions, have been introduced in the paper. A deep campaign of simulations has been carried out to give more effectiveness to our proposal

Extraction of shear viscosity in stationary states of relativistic particle systems

Starting from a classical picture of shear viscosity we construct a stationary velocity gradient in a microscopic parton cascade. Employing the Navier-Stokes ansatz we extract the shear viscosity coefficient $\eta$. For elastic isotropic scatterings we find an excellent agreement with the analytic values. This confirms the applicability of this method. Furthermore for both elastic and inelastic scatterings with pQCD based cross sections we extract the shear viscosity coefficient $\eta$ for a pure gluonic system and find a good agreement with already published calculations.Comment: 17 pages, 7 figure

Enhanced Dopamine D1 and BDNF Signaling in the Adult Dorsal Striatum but not Nucleus Accumbens of Prenatal Cocaine Treated Mice

Previous work from our group and others utilizing animal models have demonstrated long-lasting structural and functional alterations in the meso-cortico-striatal dopamine pathway following prenatal cocaine (PCOC) treatment. We have shown that PCOC treatment results in augmented D1-induced cyclic AMP (cAMP) and cocaine-induced immediate-early gene expression in the striatum of adult mice. In this study we further examined basal as well as cocaine or D1-induced activation of a set of molecules known to be mediators of neuronal plasticity following psychostimulant treatment, with emphasis in the dorsal striatum (Str) and nucleus accumbens (NAc) of adult mice exposed to cocaine in utero. Basally, in the Str of PCOC treated mice there were significantly higher levels of (1) CREB and Ser133 P-CREB (2) Thr34 P-DARPP-32 and (3) GluA1 and Ser 845 P-GluA1 when compared to prenatal saline (PSAL) treated mice. In the NAc there were significantly higher basal levels of (1) CREB and Ser133 P-CREB, (2) Thr202/Tyr204 P-ERK2, and (3) Ser845 P-GluA1. Following acute administration of cocaine (15 mg/kg, i.p.) or D1 agonist (SKF 82958; 1 mg/kg, i.p.) there were significantly higher levels of Ser133 P-CREB, Thr34 P-DARPP-32, and Thr202/Tyr204 P-ERK2 in the Str that were evident in all animals tested. However, these cocaine-induced increases in phosphorylation were significantly augmented in PCOC mice compared to PSAL mice. In sharp contrast to the observations in the Str, in the NAc, acute administration of cocaine or D1 agonist significantly increased P-CREB and P-ERK2 in PSAL mice, a response that was not evident in PCOC mice. Examination of Ser 845 P-GluA1 revealed that cocaine or D1 agonist significantly increased levels in PSAL mice, but significantly decreased levels in the PCOC mice in both the Str and NAc. We also examined changes in brain-derived neurotrophic factor (BDNF). Our studies revealed significantly higher levels of the BDNF precursor, pro-BDNF, and one of its receptors, TrkB in the Str of PCOC mice compared to PSAL mice. These results suggest a persistent up-regulation of molecules critical to D1 and BDNF signaling in the Str of adult mice exposed to cocaine in utero. These molecular adaptations may underlie components of the behavioral deficits evident in exposed animals and a subset of exposed humans, and may represent a therapeutic target for ameliorating aspects of the PCOC-induced phenotype

A decentralized ITS architecture for efficient distribution of traffic task management

In this paper, the attention is focused on the design of a new multi-layered architecture for vehicular environment. System will be able to gather information from vehicular devices. This will allow system to faster respond at emergency situation such as traffic jams or collisions. Distributed entities work at different layers exploiting cloud and fog computing in order to better distribute tasks along the infrastructure. Lower layer is composed of On-Board Units (OBUs) and RoadSide Units (RSUs) that exploits Vehicular Ad-hoc Network (VANET) protocols for inner VANET communications. At the Edge layer we propose fog computing nodes that gather data from RSUs for local processing and after an aggregation step they send data to an Intelligent Transportation System (ITS) management system. The proposed architecture has the main goal to better respond to the network and traffic dynamics by improving performances of the ITS system

Analysis of gut microbiota in rheumatoid arthritis patients. Disease-related dysbiosis and modifications induced by etanercept

A certain number of studies were carried out to address the question of how dysbiosis could affect the onset and development of rheumatoid arthritis (RA), but little is known about the reciprocal influence between microbiota composition and immunosuppressive drugs, and how this interaction may have an impact on the clinical outcome. The aim of this study was to characterize the intestinal microbiota in a groups of RA patients treatment-naïve, under methotrexate, and/or etanercept (ETN). Correlations between the gut microbiota composition and validated immunological and clinical parameters of disease activity were also evaluated. In the current study, a 16S analysis was employed to explore the gut microbiota of 42 patients affected by RA and 10 healthy controls. Disease activity score on 28 joints (DAS-28), erythrocyte sedimentation rate, C-reactive protein, rheumatoid factor, anti-cyclic citrullinated peptides, and dietary and smoking habits were assessed. The composition of the gut microbiota in RA patients free of therapy is characterized by several abnormalities compared to healthy controls. Gut dysbiosis in RA patients is associated with different serological and clinical parameters; in particular, the phylum of Euryarchaeota was directly correlated to DAS and emerged as an independent risk factor. Patients under treatment with ETN present a partial restoration of a beneficial microbiota. The results of our study confirm that gut dysbiosis is a hallmark of the disease, and shows, for the first time, that the anti-tumor necrosis factor alpha (TNF-α) ETN is able to modify microbial communities, at least partially restoring a beneficial microbiota