Research Grants 15/01657-9 - Sistemas complexos, Sistemas distribuídos - BV FAPESP
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Multi-dimensional analysis of online data stream processing systems

Abstract

The concept of Big Data refers to a large array of data (large volume), produced at a high-speed rate (velocity) and in a variety of different formats. Big Data requires systems to process this volume of data quickly. There are systems that work with offline data, i.e. data that have been collected and are stored in non-structured databases. However, other more complex systems treat this data online, in real time, as soon as produced. These systems for online data stream processing are relatively new and have less than five years in production. In addition, currently they are distributed systems in order to increase their processing power. However, these systems still require improvements, especially in the following dimensions: elasticity, scalability, fault tolerance, high availability and processing speed. This project will develop studies to establish metrics for performance analysis of these systems and propose strategies to increase the availability and fault tolerance in components of such systems, without much sacrifice in their performance. One of the expected results is the creation of a benchmark system that will serve as a tool to analyze the behavior of online data stream processing systems in a controlled environment. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
GRADVOHL, ANDRE LEON S.; AWAN, I; YOUNAS, M; PORTELA, F. Metrics and Tool for Evaluating Data Stream Processing Systems. 2018 IEEE 6TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (W-FICLOUD 2018), v. N/A, p. 8-pg., . (15/01657-9)

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