Estudo de impacto de técnicas de IA e comunicação para aplicações edge

O seguinte trabalho apresenta uma avaliação do impacto da tecnologia 5G nas aplicações de reconhecimento de imagens em tempo real tomando por caso concreto o algoritmo You Only Look Once (YOLO) (REDMON; FARHADI, 2016a). É construída uma aplicação em nuvem de forma a verificar os impactos da tecnologia 5G no provimento de visão computacional. Tendo sido realizado no contexto da pandemia, o trabalho buscou aplicar o algoritmo YOLO na solução do problema real de reconhecimento e extração de dados documentais no contexto de atendimento remoto. Essa necessidade vem de encontro aos novos mode los de cadastro biométrico e documental de vários órgãos governamentais como Tribunal Superior Eleitoral, Auxílio Brasil, Portal Gov.Br entre outros. Para isso foi construída uma aplicação Python capaz de rodar em conteineres da plata forma Cuda executados em Graphical Processing Units NVIDIA. A aplicação tem como entrada a imagem de um documento e como saída o conjunto de informações nele con tido. O projeto prevê grande escalabilidade capaz de atender as demandas de uma solução digital para a totalidade da sociedade brasileira. Neste trabalho focou-se na criação de um serviço de reconhecimento e validação de documentos através de visão computacional, tomando como técnica fundamental o algoritmo You Only Look Once (YOLO). Tal escolha foi baseada na versatilidade e alta perfor mance apresentada pelo algoritmo, a qual se mostrou ideal para a classe de problema encontrado no atendimento dessa demanda. O resultado final deste estudo foi o viabili zador da solução Cognitive Document Validation(CDV) do sistema Datavalid disponível em: https://www.loja.serpro.gov.br/datavalid. Esse cenário foi motivado por demandas excepcionais como a pandemia de Covid-19 e a migração das bases de dados documentais dos registros físicos para a núvem. Surge nesse contexto a necessidade da verificação dos dados documentais em grande velocidade para atender a população, essa verificação precisa ser oferecida de maneira transparente para uma série de dispotivos que acessam aplicativos como o auxílio brasil e sistemas de embarque de companias aéreas. Tem-se como resultado final a elaboração de uma arqui tetura de serviço implementada como um sistema publicamente disponível no barramento de aplicações do Serviço Federal de Processamento de Dados (SERPRO).The following work presents an evaluation of the alternatives for object recognition in videos through the YOLO (You Only Look Once) algorithm (REDMON; FARHADI, 2016a). Cloud computing, mobile and local processing approaches are explored on dif ferent platforms. Being made in the pandemic context this works aims to apply the YOLO algorithm into a real world case study to recognize and extract documental data in the remote office sce nario. This needs comex towards the new models of biometric registration and documen tal validation of many governmental offices as the Tribunal Superior Eleitoral, Auxílio Brasil, Portal Gov.Br among others. Starting from a implementation of the Darknet Neural Network running the YOLO algo rithm until transform it into and API avaliable on the cloud

SLA-aware resource scaling for energy efficiency

Cloud data centers (CDCs) with abundant resource capacities have prevailed in the past decade. However, these CDCs often struggle to efficiently deal with resource provisioning in terms of performance and energy efficiency. In this paper, we present Energy-Based Auto Scaling (EBAS) as a new resource auto-scaling approach - that takes into account Service Level Agreement (SLA) - for CDCs. EBAS proactively scales resources at the CPU core level in terms of both the number and frequency of cores. It incorporates the dynamic voltage and frequency scaling (DVFS) technique to dynamically adjust CPU frequencies. The proactive decisions on resource scaling are enabled primarily by the CPU usage prediction model and the workload consolidation model of EBAS. The experimental results show that EBAS can save energy on average by 14% compared with the Linux governor. In particular, EBAS contributes to enhancing DVFS by making it aware of SLA conditions, which leads to savings of computing power and in turn energy.8 page(s

Service level agreement specification for IoT application workflow activity deployment, configuration and monitoring

PhD ThesisCurrently, we see the use of the Internet of Things (IoT) within various domains such as healthcare, smart homes, smart cars, smart-x applications, and smart cities. The number of applications based on IoT and cloud computing is projected to increase rapidly over the next few years. IoT-based services must meet the guaranteed levels of quality of service (QoS) to match users’ expectations. Ensuring QoS through specifying the QoS constraints using service level agreements (SLAs) is crucial. Also because of the potentially highly complex nature of multi-layered IoT applications, lifecycle management (deployment, dynamic reconfiguration, and monitoring) needs to be automated. To achieve this it is essential to be able to specify SLAs in a machine-readable format. currently available SLA specification languages are unable to accommodate the unique characteristics (interdependency of its multi-layers) of the IoT domain. Therefore, in this research, we propose a grammar for a syntactical structure of an SLA specification for IoT. The grammar is based on a proposed conceptual model that considers the main concepts that can be used to express the requirements for most common hardware and software components of an IoT application on an end-to-end basis. We follow the Goal Question Metric (GQM) approach to evaluate the generality and expressiveness of the proposed grammar by reviewing its concepts and their predefined lists of vocabularies against two use-cases with a number of participants whose research interests are mainly related to IoT. The results of the analysis show that the proposed grammar achieved 91.70% of its generality goal and 93.43% of its expressiveness goal. To enhance the process of specifying SLA terms, We then developed a toolkit for creating SLA specifications for IoT applications. The toolkit is used to simplify the process of capturing the requirements of IoT applications. We demonstrate the effectiveness of the toolkit using a remote health monitoring service (RHMS) use-case as well as applying a user experience measure to evaluate the tool by applying a questionnaire-oriented approach. We discussed the applicability of our tool by including it as a core component of two different applications: 1) a contextaware recommender system for IoT configuration across layers; and 2) a tool for automatically translating an SLA from JSON to a smart contract, deploying it on different peer nodes that represent the contractual parties. The smart contract is able to monitor the created SLA using Blockchain technology. These two applications are utilized within our proposed SLA management framework for IoT. Furthermore, we propose a greedy heuristic algorithm to decentralize workflow activities of an IoT application across Edge and Cloud resources to enhance response time, cost, energy consumption and network usage. We evaluated the efficiency of our proposed approach using iFogSim simulator. The performance analysis shows that the proposed algorithm minimized cost, execution time, networking, and Cloud energy consumption compared to Cloud-only and edge-ward placement approaches