A State-of-the-art Integrated Transportation Simulation Platform

Nowadays, universities and companies have a huge need for simulation and modelling methodologies. In the particular case of traffic and transportation, making physical modifications to the real traffic networks could be highly expensive, dependent on political decisions and could be highly disruptive to the environment. However, while studying a specific domain or problem, analysing a problem through simulation may not be trivial and may need several simulation tools, hence raising interoperability issues. To overcome these problems, we propose an agent-directed transportation simulation platform, through the cloud, by means of services. We intend to use the IEEE standard HLA (High Level Architecture) for simulators interoperability and agents for controlling and coordination. Our motivations are to allow multiresolution analysis of complex domains, to allow experts to collaborate on the analysis of a common problem and to allow co-simulation and synergy of different application domains. This paper will start by presenting some preliminary background concepts to help better understand the scope of this work. After that, the results of a literature review is shown. Finally, the general architecture of a transportation simulation platform is proposed

Densifying the sparse cloud SimSaaS: The need of a synergy among agent-directed simulation, SimSaaS and HLA

Modelling & Simulation (M&S) is broadly used in real scenarios where making physical modifications could be highly expensive. With the so-called Simulation Software-as-a-Service (SimSaaS), researchers could take advantage of the huge amount of resource that cloud computing provides. Even so, studying and analysing a problem through simulation may need several simulation tools, hence raising interoperability issues. Having this in mind, IEEE developed a standard for interoperability among simulators named High Level Architecture (HLA). Moreover, the multi-agent system approach has become recognised as a convenient approach for modelling and simulating complex systems. Despite all the recent works and acceptance of these technologies, there is still a great lack of work regarding synergies among them. This paper shows by means of a literature review this lack of work or, in other words, the sparse Cloud SimSaaS. The literature review and the resulting taxonomy are the main contributions of this paper, as they provide a research agenda illustrating future research opportunities and trends

Constructing Reliable Computing Environments on Top of Amazon EC2 Spot Instances

Cloud provider Amazon Elastic Compute Cloud (EC2) gives access to resources in the form of virtual servers, also known as instances. EC2 spot instances (SIs) offer spare computational capacity at steep discounts compared to reliable and fixed price on-demand instances. The drawback, however, is that the delay in acquiring spots can be incredible high. Moreover, SIs may not always be available as they can be reclaimed by EC2 at any given time, with a two-minute interruption notice. In this paper, we propose a multi-workflow scheduling algorithm, allied with a container migration-based mechanism, to dynamically construct and readjust virtual clusters on top of non-reserved EC2 pricing model instances. Our solution leverages recent findings on performance and behavior characteristics of EC2 spots. We conducted simulations by submitting real-life workflow applications, constrained by user-defined deadline and budget quality of service (QoS) parameters. The results indicate that our solution improves the rate of completed tasks by almost 20%, and the rate of completed workflows by at least 30%, compared with other state-of-the-art algorithms, for a worse-case scenarioinfo:eu-repo/semantics/publishedVersio

Deadline-Budget constrained Scheduling Algorithm for Scientific Workflows in a Cloud Environment

Recently cloud computing has gained popularity among e-Science environments as a high performance computing platform. From the viewpoint of the system, applications can be submitted by users at any moment in time and with distinct QoS requirements. To achieve higher rates of successful applications attending to their QoS demands, an effective resource allocation (scheduling) strategy between workflow\u27s tasks and available resources is required. Several algorithms have been proposed for QoS workflow scheduling, but most of them use search-based strategies that generally have a higher time complexity, making them less useful in realistic scenarios. In this paper, we present a heuristic scheduling algorithm with quadratic time complexity that considers two important constraints for QoS-based workflow scheduling, time and cost, named Deadline-Budget Workflow Scheduling (DBWS) for cloud environments. Performance evaluation of some well-known scientific workflows shows that the DBWS algorithm accomplishes both constraints with higher success rate in comparison to the current state-of-the-art heuristic-based approaches

PIASA: A power and interference aware resource management strategy for heterogeneous workloads in cloud data centers

Cloud data centers have been progressively adopted in different scenarios, as reflected in the execution of heterogeneous applications with diverse workloads and diverse quality of service (QoS) requirements. Virtual machine (VM) technology eases resource management in physical servers and helps cloud providers achieve goals such as optimization of energy consumption. However, the performance of an application running inside a VM is not guaranteed due to the interference among co-hosted workloads sharing the same physical resources. Moreover, the different types of co-hosted applications with diverse QoS requirements as well as the dynamic behavior of the cloud makes efficient provisioning of resources even more difficult and a challenging problem in cloud data centers. In this paper, we address the problem of resource allocation within a data center that runs different types of application workloads, particularly CPU- and network-intensive applications. To address these challenges, we propose an interference- and power-aware management mechanism that combines a performance deviation estimator and a scheduling algorithm to guide the resource allocation in virtualized environments. We conduct simulations by injecting synthetic workloads whose characteristics follow the last version of the Google Cloud tracelogs. The results indicate that our performance-enforcing strategy is able to fulfill contracted SLAs of real-world environments while reducing energy costs by as much as 21%

Semi-automatic quantification of the epicardial fat in CT images

In this work we present a technique to automatically or semi-automatically quantify the epicardial fat in noncontrasted Computed Tomography (CT) images. In CT images, the epicardial fat is very close to the pericardial fat, distincted only by the pericardium. The pericardium appears in the image as a very thin line, very hard to discriminate. To enhance the pericardium line and to remove noise as well as higher intensities due to calcifications, some pre-processing was applied, namely region growing, thresholding and average filtering techniques. To detect the pericardium line an algorithm was developed that considerer the heart anatomy to find control points belonging to that line. From the points detected an interpolation was done based on the cubic spline method. This method was also improved to avoid incorrect interpolation that occurs when one of the coordinates of the points is repeated. After having the line delineation, the pixels bellow the line were counted, considering only the pixels in the fat window (-190 to -30 Hounsfiel Units). In 10 images tested, in 4 the system fully automatically returned the correct value for epicardial fat. In the other 6 the system needed a small correction by moving 1 or 2 points to return the correct value of epicardial fat. The values of the automatic quantification were compared to the values obtained by the manual process, having 10% as maximum error allowed. We concluded that this method is able to, automatically or with a small interaction, return the value of the epicardial fat, for the non contrast CT images tested

A Study on Cloud Cost Efficiency by Exploiting Idle Billing Period Fractions

In most of the current commercial Clouds, resources are billed based on a time interval equal to one hour, as is the case of virtual machine (VM) instances on Amazon EC2. Such time interval is usually long, and yet the user has to pay for the whole last hour, even if he/she has only used a fraction of it, contradicting the pay-as-you-go model of Clouds. In this paper, we analyse the advantages of adopting alternative scheduling policies that exploit idle last time intervals, in terms of service cost to Cloud users and operating costs to Cloud providers. Using a real-life astronomy workflow application, constrained by user-defined Deadline and Budget quality of service (QoS) parameters, a set of online state-ofthe- art-based scheduling algorithms try different execution and resource provisioning plans. Our results show that exploitation of partially idle last time intervals can reduce the cost of service to the end user, and augments providers competitiveness up to 21.6% through energy efficiency improvement and consequent lowering of operational costs.info:eu-repo/semantics/publishedVersio

Structural and magnetic properties of nanogranular BaTiO3-CoFe2O4 thin films deposited by laser ablation on Si/Pt substrates

Thin film nanogranular composites of cobalt ferrite (CoFe2O 4) dispersed in a barium titanate (BaTiO3) matrix were deposited by laser ablation with different cobalt ferrite concentrations (x). The films were polycrystalline and composed by a mixture of tetragonal- BáTiO3 and CoFe2O4 with the cubic spinnel structure. A slight (111) barium titanate phase orientation and (311) CoFe2O4 phase orientation was observed. As the concentration of the cobalt ferrite increased, the grain size of the BaTiO 3 phase decreased, from 91nm to 30nm, up to 50% CoFe 2O4 concentration, beyond which the BaTiO3 grain size take values in the range 30-35nm. On the other hand the cobalt ferrite grain size did not show a clear trend with increasing cobalt ferrite concentration, fluctuating in the range 25nm to 30nm. The lattice parameter of the CoFe2O4 phase increased with increasing x. However, it was always smaller than the bulk value indicating that, in the films, the cobalt ferrite was under compressive stress that was progressively relaxed with increasing CoFe2O4 concentration. The magnetic measurements showed a decrease of coercive field with increasing x, which was attributed to the relaxation of the stress in the films and to the increase of particle agglomeration in bigger polycrystalline clusters with increasing cobalt ferrite concentration.This work has been financially supported by the Portuguese Foundation for Science and Technology (FCT), through the project POCI/CTM/60181/2004

Immune-evasion strategies of mycobacteria and their implications for the protective immune response

Mycobacteria are intracellular pathogens that have macrophages as their main host cells. However, macrophages are also the primary line of defense against invading microorganisms. To survive in the intracellular compartment, virulent mycobacteria have developed several strategies to modulate the activation and the effector functions of macrophages. Despite this, antigen-specific T cells develop during infection. While T cell responses are critical for protection they can also contribute to the success of mycobacteria as human pathogens, as immunopathology associated with these responses facilitates transmission. Here, we provide a brief overview of different immune-evasion strategies of mycobacteria and their impact on the protective immune response. This understanding will further our knowledge in host-pathogen interactions and may provide critical insights for the development of novel host-specific therapies.Our work is funded by the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER); Infect-ERA grant BU_SPONT_HEAL; and the Fundação para a Ciência e Tecnologia (FCT) through the FCT investigator grant IF/01390/2014 to E.T. and the postdoctoral grant SFRH/BPD/112903/2015 to A.G.F.info:eu-repo/semantics/publishedVersio