Blockchain to improve security, knowledge and collaboration inter-agent communication over restrict domains of the internet infrastructure, with human interaction / Blockchain para melhorar a segurança, o conhecimento e a colaboração entre os agentes de comunicação sobre domínios restritos da infraestrutura da Internet, com interação humana

This paper describes the development and implementation of a  blockchain to improve security,  knowledge and intel ligence during the communication and col laboration processes between agents under restricted Internet Infrastructure domains. It is a work that proposes the application of a blockchain, independent of platform, in a particular model of agents, but that can be used  in similar proposals, since the results in the specific model were satisfactory. Additional ly, the model al lows interaction and, also, col laboration between humans and agents

Modelling and simulation of ElasticSearch using CloudSim

Simulation can be a powerful technique for evaluating the performance of large-scale cloud computing services in a relatively low cost, low risk and time-sensitive manner. Largescale data indexing, distribution and management is complex to analyse in a timely manner. In this paper, we extend the CloudSim cloud simulation framework to model and simulate a distributed search engine architecture and its workload characteristics. To test the simulation framework, we develop a model based on a real-world ElasticSearch deployment on Linknovate.com. An experimental evaluation of the framework, comparing simulated and actual query response time, precision and resource utilisation, suggests that the proposed framework is capable of predicting performance at different scales in a precise, accurate and efficient manner. The results can assist ElasticSearch users to manage their scalability and infrastructure requirement

Optimizing the cloud data center availability empowered by surrogate models

Making data centers highly available remains a challenge that must be considered since the design phase. The problem is selecting the right strategies and components for achieving this goal given a limited investment. Furthermore, data center designers currently lack reliable specialized tools to accomplish this task. In this paper, we disclose a formal method that chooses the components and strategies that optimize the availability of a data center while considering a given budget as a constraint. For that, we make use of stochastic models to represent a cloud data center infrastructure based on the TIA-942 standard. In order to improve the computational cost incurred to solve this optimization problem, we employ surrogate models to handle the complexity of the stochastic models. In this work, we use a Gaussian process to produce a surrogate model for a cloud data center infrastructure and we use three derivative-free optimization algorithms to explore the search space and to find optimal solutions. From the results, we observe that the Differential Evolution (DE) algorithm outperforms the other tested algorithms, since it achieves higher availability with a fair usage of the budget

Sorting the Healthy Diet Signal from the Social Media Expert Noise: Preliminary Evidence from the Healthy Diet Discourse on Twitter

: Over 2.8 million people die each year from being overweight or obese, a largely preventable disease. Social media has fundamentally changed the way we communicate, collaborate, consume, and create content. The ease with which content can be shared has resulted in a rapid increase in the number of individuals or organisations that seek to influence opinion and the volume of content that they generate. The nutrition and diet domain is not immune to this phenomenon. Unfortunately, from a public health perspective, many of these ‘influencers’ may be poorly qualified in order to provide nutritional or dietary guidance, and advice given may be without accepted scientific evidence and contrary to public health policy. In this preliminary study, we analyse the ‘healthy diet’ discourse on Twitter. While using a multi-component analytical approach, we analyse more than 1.2 million English language tweets over a 16-month period in order to identify and characterise the influential actors and discover topics of interest in the discourse. Our analysis suggests that the discourse is dominated by non-health professionals. There is widespread use of bots that pollute the discourse and seek to create a false equivalence on the efficacy of a particular nutritional strategy or diet. Topic modelling suggests a significant focus on diet, nutrition, exercise, weight, disease, and quality of life. Public health policy makers and professional nutritionists need to consider what interventions can be taken in order to counteract the influence of non-professional and bad actors on social media