INECiD: internet and the new age of data science

• Grant number: 15/24493-1
• Support Opportunities: Regular Research Grants
• Start date: October 01, 2017
• End date: September 30, 2020
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Agreement: MCTI/MC
• Principal Investigator: Artur Ziviani
• Grantee: Artur Ziviani
• Host Institution: Laboratório Nacional de Computação Científica (LNCC). Ministério da Ciência, Tecnologia e Inovação (Brasil). Petrópolis , SP, Brazil
• Associated researchers: Alex Borges Vieira
• Associated scholarship(s): 20/05371-0 - Characterization and analysis from internet in the age of data science, BP.TT; 18/02255-0 - Multilayer model for IoT, BP.TT; 18/03259-9 - Characterization and analysis of the Internet characteristics in the era of data science, BP.TT

Abstract

The world expects a new age of services-oriented data on the Internet, a trend that has already begun, but the all evidence points to a further significant growth in data volumes in the coming years. While the Internet and its services evolve, the Internet usage pattern also changes dramatically. In the face of such changes, the characterization and current models, especially regarding the behavior of users and traffic, may not reflect the near future the Internet. Characterizations performed poorly and inaccurate models can induce mistakes and losses, both in the creation of applications and in the capacity planning of the necessary services and communications structure. For the future of the Internet, issues related to storage, interconnection, search, and organization are challenging and can only be overcome with the help of informative characterizations and accurate models.This project has two main parts. The first one includes the characterization of the user behavior and the workload that will impact the future of the Internet. Thus, researchers, developers, and service providers will have an arsenal for the next wave of the Internet, the new age of Data Science, whose main driver in this context is the phenomenon known as the Internet of Things (IoT). As a first instance, video transmission applications will be characterized on the Internet during major events. The second part of the project involves the creation of tools that support data-driven systems based on a single mathematical object to allow an integrated modeling of such systems, thus simplifying the analysis of large-scale objects associated with the IoT . Therefore, appropriate data structures will be created for the IoT analysis, able to convey the huge volume of data that is expected in these networks. (AU)

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)

ABRAHAO, FELIPE S.; WEHMUTH, KLAUS; ZIVIANI, ARTUR. Algorithmic networks: Central time to trigger expected emergent open-endedness. THEORETICAL COMPUTER SCIENCE, v. 785, p. 83-116, SEP 20 2019. (15/24493-1)

DE SOUZA, R. C.; FIGUEIREDO, D. R.; ROCHA, A. A. DE A.; ZIVIANI, A.. Efficient network seeding under variable node cost and limited budget for social networks. INFORMATION SCIENCES, v. 514, p. 369-384, APR 2020. (15/24493-1)

GAVIAO MASCARENHAS, JULIANA ZANELATTO; ZIVIANI, ARTUR; WEHMUTH, KLAUS; VIEIRA, ALEX BORGES. On the transaction dynamics of the Ethereum-based cryptocurrency. JOURNAL OF COMPLEX NETWORKS, v. 8, n. 4, AUG 2020. (15/24493-1)