VIoLET: A Large-scale Virtual Environment for Internet of Things

IoT deployments have been growing manifold, encompassing sensors, networks, edge, fog and cloud resources. Despite the intense interest from researchers and practitioners, most do not have access to large-scale IoT testbeds for validation. Simulation environments that allow analytical modeling are a poor substitute for evaluating software platforms or application workloads in realistic computing environments. Here, we propose VIoLET, a virtual environment for defining and launching large-scale IoT deployments within cloud VMs. It offers a declarative model to specify container-based compute resources that match the performance of the native edge, fog and cloud devices using Docker. These can be inter-connected by complex topologies on which private/public networks, and bandwidth and latency rules are enforced. Users can configure synthetic sensors for data generation on these devices as well. We validate VIoLET for deployments with > 400 devices and > 1500 device-cores, and show that the virtual IoT environment closely matches the expected compute and network performance at modest costs. This fills an important gap between IoT simulators and real deployments.Comment: To appear in the Proceedings of the 24TH International European Conference On Parallel and Distributed Computing (EURO-PAR), August 27-31, 2018, Turin, Italy, europar2018.org. Selected as a Distinguished Paper for presentation at the Plenary Session of the conferenc

EPOBF: Energy Efficient Allocation of Virtual Machines in High Performance Computing Cloud

Cloud computing has become more popular in provision of computing resources under virtual machine (VM) abstraction for high performance computing (HPC) users to run their applications. A HPC cloud is such cloud computing environment. One of challenges of energy efficient resource allocation for VMs in HPC cloud is tradeoff between minimizing total energy consumption of physical machines (PMs) and satisfying Quality of Service (e.g. performance). On one hand, cloud providers want to maximize their profit by reducing the power cost (e.g. using the smallest number of running PMs). On the other hand, cloud customers (users) want highest performance for their applications. In this paper, we focus on the scenario that scheduler does not know global information about user jobs and user applications in the future. Users will request shortterm resources at fixed start times and non interrupted durations. We then propose a new allocation heuristic (named Energy-aware and Performance per watt oriented Bestfit (EPOBF)) that uses metric of performance per watt to choose which most energy-efficient PM for mapping each VM (e.g. maximum of MIPS per Watt). Using information from Feitelson's Parallel Workload Archive to model HPC jobs, we compare the proposed EPOBF to state of the art heuristics on heterogeneous PMs (each PM has multicore CPU). Simulations show that the EPOBF can reduce significant total energy consumption in comparison with state of the art allocation heuristics.Comment: 10 pages, in Procedings of International Conference on Advanced Computing and Applications, Journal of Science and Technology, Vietnamese Academy of Science and Technology, ISSN 0866-708X, Vol. 51, No. 4B, 201

Alteracoes limnologicas no Rio Paraguai ("dequada") e o fenomeno natural de mortandade de peixes no Pantanal Mato-Grossense - MS.

No Pantanal, ocorre um fenomeno natural de deterioracao da qualidade da agua, denominado regionalmente como "Dequada", relacionado a decomposicao da grande massa de materia organica submersa no inicio do processo de inundacao. Sua magnitude e dependente das caracteristicas do pulso de inundacao, ou seja, caracteristicas da fase de seca anterior e do periodo de inundacao subsequente (volume e velocidade). De acordo com essa magnitude, pode provocar mortandade massiva de peixes (podendo alcancar a ordem de milhares de toneladas), docorrente da deplecao de oxigenio e do aumento da concentracao de gas carbonico, resultantes dos processos de oxidacao da materia organica, tanto nos campos inundados, quanto na coluna d'agua dos rios. Os peixes moribundos apresentam comportamento tipico de estresse respiratorio. Outros fatores, como gas sulfidrico, amonia, aluminio, sodio e potassio (solidos dissolvidos), alteracoes de pH e compostos provenientes da atividade fitoplanctonica foram descardados, pois nao foram encontrados em niveis considerados toxicos para peixes. Pesticidas e matais pesados nao foram analisados, mas seus niveis dificilmente poderiam ser responsaveis por mortandades tao grandes em uma area tao extensa, onde a atividade antropica ainda e reduzida. Em 1995, o fenomeno foi muito expressivo, devido a rapidez e ao grande volume da onda de cheia, chegando a provocar a total anoxia e/ou manter sub hipoxia o rio Paraguai por mais dois meses e apresentar valores de gas carbonico dissociado de ate 79mg/L, nunca antes obtidos.bitstream/item/37450/1/BP07.pd

HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges

High Performance Computing (HPC) clouds are becoming an alternative to on-premise clusters for executing scientific applications and business analytics services. Most research efforts in HPC cloud aim to understand the cost-benefit of moving resource-intensive applications from on-premise environments to public cloud platforms. Industry trends show hybrid environments are the natural path to get the best of the on-premise and cloud resources---steady (and sensitive) workloads can run on on-premise resources and peak demand can leverage remote resources in a pay-as-you-go manner. Nevertheless, there are plenty of questions to be answered in HPC cloud, which range from how to extract the best performance of an unknown underlying platform to what services are essential to make its usage easier. Moreover, the discussion on the right pricing and contractual models to fit small and large users is relevant for the sustainability of HPC clouds. This paper brings a survey and taxonomy of efforts in HPC cloud and a vision on what we believe is ahead of us, including a set of research challenges that, once tackled, can help advance businesses and scientific discoveries. This becomes particularly relevant due to the fast increasing wave of new HPC applications coming from big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR

Meat, beyond the plate: data-driven hypotheses for understanding consumer willingness to adopt a more plant-based diet

A shift towards reduced meat consumption and a more plant-based diet is endorsed to promote sustainability, improve public health, and minimize animal suffering. However, large segments of consumers do not seem willing to make such transition. While it may take a profound societal change to achieve significant progresses on this regard, there have been limited attempts to understand the psychosocial processes that may hinder or facilitate this shift. This study provides an in-depth exploration of how consumer representations of meat, the impact of meat, and rationales for changing or not habits relate with willingness to adopt a more plant-based diet. Multiple Correspondence Analysis was employed to examine participant responses (N = 410) to a set of open-ended questions, free word association tasks and closed questions. Three clusters with two hallmarks each were identified: (1) a pattern of disgust towards meat coupled with moral internalization; (2) a pattern of low affective connection towards meat and willingness to change habits; and (3) a pattern of attachment to meat and unwillingness to change habits. The findings raise two main propositions. The first is that an affective connection towards meat relates to the perception of the impacts of meat and to willingness to change consumption habits. The second proposition is that a set of rationales resembling moral disengagement mechanisms (e.g., pro-meat justifications; self-exonerations) arise when some consumers contemplate the consequences of meat production and consumption, and the possibility of changing habits.info:eu-repo/semantics/acceptedVersio

Attached to meat? (Un)Willingness and intentions to adopt a more plant-based diet

In response to calls to expand knowledge on consumer willingness to reduce meat consumption and to adopt a more plant-based diet, this work advances the construct of meat attachment and the Meat Attachment Questionnaire (MAQ). The MAQ is a new measure referring to a positive bond towards meat consumption. It was developed and validated through three sequential studies following from an in-depth approach to consumer representations of meat. The construct and initial pool of items were firstly developed drawing on qualitative data from 410 participants in a previous work on consumers’ valuation of meat. Afterwards, 1023 participants completed these items and other measures, providing data to assess item selection, factor structure, reliability, convergent and concurrent validity, and predictive ability. Finally, a sample of 318 participants from a different cultural background completed the final version of the MAQ along with other measures to assess measurement invariance, reliability and predictive ability. Across samples, a four-factor solution (i.e., hedonism, affinity, entitlement, and dependence) with 16 items and a second-order global dimension of meat attachment fully met criteria for good model fit. The MAQ subscales and global scale were associated with attitudes towards meat, subjective norm, human supremacy beliefs, eating habits, and dietary identity. They also provided additional explanatory variance above and beyond the core TPB variables (i.e. attitudes, subjective norm and perceived behavioral control) in willingness and intentions concerning meat substitution. Overall, the findings point towards the relevance of the MAQ for the study of meat consumption and meat substitution, and lend support to the idea that holding a pattern of attachment towards meat may hinder a shift towards a more plant-based diet.info:eu-repo/semantics/acceptedVersio

Sentiment classification of consumer generated online reviews using topic modeling

The development of the Internet and mobile devices enabled the emergence of travel and hospitality review sites, leading to a large number of customer opinion posts. While such comments may influence future demand of the targeted hotels, they can also be used by hotel managers to improve customer experience. In this article, sentiment classification of an eco-hotel is assessed through a text mining approach using several different sources of customer reviews. The latent Dirichlet allocation modeling algorithm is applied to gather relevant topics that characterize a given hospitality issue by a sentiment. Several findings were unveiled including that hotel food generates ordinary positive sentiments, while hospitality generates both ordinary and strong positive feelings. Such results are valuable for hospitality management, validating the proposed approach.info:eu-repo/semantics/acceptedVersio

Socioeconomic status, multiple autonomy support attunement, and early adolescents' social development

This study explores the relationship between socioeconomic status (SES), Multiple Autonomy Support Attunement (MASA) and social development indicators (antisocial behavior, prosociality, and self-regulation), considering the concurrent effects of structural (gender and age) and social factors (social networks' size and orientation). MASA describes patterns of autonomy support provided by different sources, which in this case were parents, teachers, and mentors. Participants were 645 adolescents (M = 12.30; SD = .60; 55.35% girls). Using Latent Class Analysis LCA), a four-class solution for MASA presented the best fit. A Generalized Linear Model (GLM) approach revealed that lower SES was associated with greater antisocial behavior, while MASA was linked to improved prosociality and self-regulation when youths were included in a high-attuned multiple autonomy support class, compared to other MASA classes. Thus, optimal levels of MASA can represent an asset for training, implementation, and assessment stages of interventions aimed at improving early adolescents' positive social development.info:eu-repo/semantics/acceptedVersio

Why are women less likely to support animal exploitation than men? The mediating roles of social dominance orientation and empathy

Women tend to be more concerned about the welfare of (human/nonhuman) animals and the natural environment than men. A growing literature has shown that gender differences in environmental exploitation can be explained partially by the fact that women and men differ in their social dominance and empathic orientations. We extend past studies by examining whether social dominance orientation (SDO; ‘Superior groups should dominate inferior groups’) and empathy (‘I feel others’ emotions’) also help explain gender differences in attitudes towards nonhuman animals. Our mediation model confirmed that SDO and empathy partially and independently mediate gender differences in human supremacy beliefs (‘Animals are inferior to humans’) and/or speciesism (‘I think it is perfectly acceptable for cattle, chickens and pigs to be raised for human consumption’) among 1002 individuals (57% female; Mage?=?26.44) from the general population in Portugal. These findings provide evidence that traits referring to human–human relations can help explain gender differences in human–animal relations. The cumulative evidence suggests that exploitative tendencies towards the natural environment and (human/nonhuman) animals may be built upon shared psychological mechanisms.info:eu-repo/semantics/acceptedVersio