2022
Authors
Serrano, MA; Marín, CA; Queralt, A; Cordeiro, C; Gonzalez, M; Pinho, LM; Quiñones, E;
Publication
Technologies and Applications for Big Data Value
Abstract
This chapter describes a software architecture for processing big-data analytics considering the complete compute continuum, from the edge to the cloud. The new generation of smart systems requires processing a vast amount of diverse information from distributed data sources. The software architecture presented in this chapter addresses two main challenges. On the one hand, a new elasticity concept enables smart systems to satisfy the performance requirements of extreme-scale analytics workloads. By extending the elasticity concept (known at cloud side) across the compute continuum in a fog computing environment, combined with the usage of advanced heterogeneous hardware architectures at the edge side, the capabilities of the extreme-scale analytics can significantly increase, integrating both responsive data-in-motion and latent data-at-rest analytics into a single solution. On the other hand, the software architecture also focuses on the fulfilment of the non-functional properties inherited from smart systems, such as real-time, energy-efficiency, communication quality and security, that are of paramount importance for many application domains such as smart cities, smart mobility and smart manufacturing. © The Author(s) 2022. All rights reserved.
2022
Authors
Sousa, R; Nogueira, L; Rodrigues, F; Pinho, LM;
Publication
ICPS
Abstract
Smart systems increasingly demand the processing of a massive amount of data generated by heterogeneous and distributed data sources. Due to the inherent cyber-physical nature of these systems, many applications require that this processing respects a set of non-functional requirements (such as timeliness, or energy-efficiency). To cope with this challenge, edge-cloud architectures need to provide flexible mechanisms to support varying processing needs, whilst guaranteeing the minimum level of quality of service required by these smart applications. This paper addresses this challenge in the context of the ELASTIC software architecture, which has been developed integrating responsive data-in-motion (edge computing) and latent data-at-rest analytics (cloud computing) into a single solution, satisfying extreme-scale analytics' performance requirements. The paper focuses on how the architecture fulfils the non-functional properties inherited from the applications, namely real-time and energy-efficiency, whilst ensuring the performance of the software architecture. © 2022 IEEE.
2022
Authors
Paladini, J; Schlemmer, E;
Publication
Revista Diálogos em Educação Matemática
Abstract
2022
Authors
Maquieira, JdS; Sena, LdS; Schlemmer, E;
Publication
fólio - Revista de Letras
Abstract
2022
Authors
Cézar de Oliveira, L; De Andrade, F; Schlemmer, E;
Publication
Video Journal of Social and Human Research
Abstract
2022
Authors
MOREIRA, JA; SCHLEMMER, E;
Publication
Revista de Educação Pública
Abstract
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