Models to evaluate service Provisioning over Cloud Computing Environments - A Blockchain-As-A-Service case study

ThestrictnessoftheServiceLevelAgreements(SLAs)ismainlyduetoasetofconstraintsrelated to performance and dependability attributes, such as availability. This paper shows that system’s availability values may be improved by deploying services over a private environment, which may obtain better availability values with improved management, security, and control. However, how much a company needs to afford to keep this improved availability? As an additional activity, this paper compares the obtained availability values with the infrastructure deployment expenses and establishes a cost × benefit relationship. As for the system’s evaluation technique, we choose modeling; while for the service used to demonstrate the models’ feasibility, the blockchain-as-a-service was the selected one. This paper proposes and evaluate four different infrastructures hosting blockchains: (i) baseline; (ii) double redundant; (iii) triple redundant, and (iv) hyper-converged. The obtained results pointed out that the hyper-converged architecture had an advantage over a full triple redundant environment regarding availability and deployment cost

Redundant VoD Streaming Service in a Private Cloud: Availability Modeling and Sensitivity Analysis

For several years cloud computing has been generating considerable debate and interest within IT corporations. Since cloud computing environments provide storage and processing systems that are adaptable, efficient, and straightforward, thereby enabling rapid infrastructure modifications to be made according to constantly varying workloads, organizations of every size and type are migrating to web-based cloud supported solutions. Due to the advantages of the pay-per-use model and scalability factors, current video on demand (VoD) streaming services rely heavily on cloud infrastructures to offer a large variety of multimedia content. Recent well documented failure events in commercial VoD services have demonstrated the fundamental importance of maintaining high availability in cloud computing infrastructures, and hierarchical modeling has proved to be a useful tool for evaluating the availability of complex systems and services. This paper presents an availability model for a video streaming service deployed in a private cloud environment which includes redundancy mechanisms in the infrastructure. Differential sensitivity analysis was applied to identify and rank the critical components of the system with respect to service availability. The results demonstrate that such a modeling strategy combined with differential sensitivity analysis can be an attractive methodology for identifying which components should be supported with redundancy in order to consciously increase system dependability

The influence of Kinesio taping on muscle fatigue in individuals with low back pain: A randomised controlled trial

OBJECTIVE: To evaluate the effect of different taping techniques on back muscle fatigue in people with low back pain. METHODS: Sixty women with chronic non-specific low back pain were randomly assigned to four groups with 15 in each; control (CG), Kinesio Taping (KT) with tension (KTT), KT no tension (KTNT) and Micropore® (MP), which were applied over the erector spinae muscles. The median frequency (MF) fatigue slopes of the longissimus muscle and sustained contraction time during a trunk fatigue test (Ito test), and pain using the numerical pain rating scale (NPRS) were collected at three time points: pre-treatment, three and ten days after intervention at a university laboratory. RESULTS: Significant differences were seen in the MF slopes between groups (p=0.01, η2=0.20), with the KTT showing a mean difference (MD=0.31, p=0.04) and KTNT (MD= 0.28, p=0.04) compared with CG. Significant reductions in NPRS were seen between time points (p<0.001, η2=0.28), with a reduction between pre and 3 days (MD=1.87, p<0.001), and pre and 10 days (MD=1.38, p<0.001), with KTT and KTNT both showing clinically important changes. CONCLUSION: KT, with or without tension, has a tendency to reduce back muscle fatigue and reduce pain in individuals with chronic non-specific low back pain

RecArd: Robô baseado na plataforma Arduino como facilitador no processo de ensino-aprendizagem multidisciplinar

O presente trabalho tem por finalidade auxiliar e complementar o ensino-aprendizagem de disciplinas nas áreas de computação, eletrônica e mecânica com a utilização de um robô denominado RecArd. Na tentativa de contribuir para uma mudança por meio da viabilização de aulas práticas, utilizou-se a plataforma de prototipagem Arduino e através desta montou-se o robô controlado com um smartphone e com capacidade de desviar de obstáculos. A ferramenta apresentou potencialidades que são consideradas relevantes no processo de ensino-aprendizagem, principalmente, em áreas multidisciplinares. Com base nos experimentos e resultados, pode-se indicar que o uso da robótica na educação deve ser considerado como modelo reformulador de métodos de ensino

Dependability Impact in the Smart Solar Power Systems: An Analysis of Smart Buildings

The Internet has been going through significant transformations and changing the world around us. We can also see the Internet to be used in many areas, for innumerable purposes, and, currently, it is even used by objects. This evolution leads to the Internet of Things (IoT) paradigm. This new concept can be defined as a system composed of storage resources, sensor devices, controllers, applications, and network infrastructure, in order to provide specific services to its users. Since IoT comprises heterogeneous components, the creation of these systems, the communication, and maintenance of their components became a complex task. In this paper, we present a dependability model to evaluate an IoT system. Amid different systems, we chose to assess availability in a smart building. The proposed models allow us to calculate estimations of other measures besides steady-state availability, such as reliability. Thus, it was possible to notice that there was no considerable gain of availability in the system when applying grid-tie solar power or off-grid solar power. The grid-tie solar power system is cheaper than the off-grid solar power system, even though it produces more energy. However, in our research, we were able to observe that the off-grid solar power system recovers the applied financial investment in smaller interval of time

Performance-Cost Trade-Off in Auto-Scaling Mechanisms for Cloud Computing

Cloud computing has been widely adopted over the years by practitioners and companies with a variety of requirements. With a strong economic appeal, cloud computing makes possible the idea of computing as a utility, in which computing resources can be consumed and paid for with the same convenience as electricity. One of the main characteristics of cloud as a service is elasticity supported by auto-scaling capabilities. The auto-scaling cloud mechanism allows adjusting resources to meet multiple demands dynamically. The elasticity service is best represented in critical web trading and transaction systems that must satisfy a certain service level agreement (SLA), such as maximum response time limits for different types of inbound requests. Nevertheless, existing cloud infrastructures maintained by different cloud enterprises often offer different cloud service costs for equivalent SLAs upon several factors. The factors might be contract types, VM types, auto-scaling configuration parameters, and incoming workload demand. Identifying a combination of parameters that results in SLA compliance directly in the system is often sophisticated, while the manual analysis is prone to errors due to the huge number of possibilities. This paper proposes the modeling of auto-scaling mechanisms in a typical cloud infrastructure using a stochastic Petri net (SPN) and the employment of a well-established adaptive search metaheuristic (GRASP) to discover critical trade-offs between performance and cost in cloud services.The proposed SPN models enable cloud designers to estimate the metrics of cloud services in accordance with each required SLA such as the best configuration, cost, system response time, and throughput.The auto-scaling SPN model was extensively validated with 95% confidence against a real test-bed scenario with 18.000 samples. A case-study of cloud services was used to investigate the viability of this method and to evaluate the adoptability of the proposed auto-scaling model in practice. On the other hand, the proposed optimization algorithm enables the identification of economic system configuration and parameterization to satisfy required SLA and budget constraints. The adoption of the metaheuristic GRASP approach and the modeling of auto-scaling mechanisms in this work can help search for the optimized-quality solution and operational management for cloud services in practice