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The production of large amounts of sensitive data raises grow-ing concerns on confidentiality guarantees. Considering this, it isnatural that data owners have an interest in how their data arebeing used. In this work, we propose Data aNd Application Track-ing (DNAT), a trustworthy platform for tracking the executionsof applications over sensitive data in...
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Federated clouds address many problems of scientific and industrial applications, such as legal restrictions and efficient data access. Despite these benefits, its natural geographical distribution and complex software stack challenges the developers and operators aiming to harness this kind of infrastructure. This article...
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We here focus on the task of learning Granger causality matrices for multivariate point processes. In order to accomplish this task, our work is the first to explorethe use of Wold processes. By doing so, we are able to develop asymptotically fast MCMC learning algorithms. With Nbeing the total number of events and K the number of processes, our learning algorithm has aO(N( log(N) + log(K)))costper...
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Abstract: In the Amazon EC2 cloud provider, the price of spot instances is much lower than on demand instances, however, at the cost of availability issues of the former. Recently, several strategies were proposed to analyze the Amazon EC2 spot pricing model employing techniques such as statistical and probabilistic modeling and neural networks. To the best of our knowledge, there is no work in the literature that...
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Abstract: Recent years saw an increasing success in the application of deep learning methods across various domains and for tackling different problems, ranging from image recognition and classification to text processing and speech recognition. In this paper we propose, discuss, and validate a black box approach to model the execution time for training convolutional neural networks (CNNs), with a particular focus on...
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Abstract: Big data applications are among the most suitable applications to be executed on cluster resources because of their high requirements of computational power and data storage. Correctly sizing the resources devoted to their execution does not guarantee they will be executed as...
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Abstract: Cloud federation, in the last years, has grown rapidly in literature because to its multiple advantages to coordinate and re-use different services across multiple sites, different geographic locations or cloud providers. This article presents a federated network architecture and focuses on the multi-tenant overlay...
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Abstract: The adoption of cloud computing is continuously increasing due to the attractiveness of low costs of infrastructure acquisition and maintenance, as well as having virtually infinite resources available for scaling applications based on demand. Due to the increasing interest in this topic, there is a continuos search for better, more cost-effective ways to manage such infrastructures. One...
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Abstract: This paper describes the development of applications in the frame of the ATMOSPHERE platform. ATMOSPHERE provides means for developing container-based applications over a federated cloud offering measuring the...
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Cloud services consumers deal with a major challenge in selecting services from several providers. Facilitating these choices has become critical, and an important factor is the service trustworthiness. To be trusted by users, cloud providers should explicitly communicate their capabilities to ensure important functional and non-functional requirements (such as security, privacy, dependability,...
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ATMOSPHERE is funded by the European Union under the Cooperation Programme, Horizon 2020 grant agreement No 777154. Este projeto é resultante da 4ª Chamada Coordenada BR-UE em Tecnologias da Informação e Comunicação (TIC), anunciada pela Rede Nacional de Ensino e Pesquisa (RNP) e pelo Ministério da Ciência, Tecnologia, Inovações e Comunicações (MCTIC), no âmbito to acordo de cooperação Número 51119. Privacy Policy | Disclaimer / Terms of use
