Advancing Dynamic Evolutionary Optimization Using In-Memory Database Technology

Jordan, Julia; Cheng, Wei; Scheuermann, Bernd

doi:10.1007/978-3-319-55792-2_11

Cited by 1 publication

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, an additional possible viewpoint can also be highlighted in this section, which evinces even further how bio-inspired optimization methods can take advantage of NoSQL technologies. This is the concrete proposal of Jordan et al in [130]. In this paper, authors showcase how a system benefits from optimization knowledge persisted on a NoSQL database, serving as associative memory to better guide the optimizer through dynamic environments.…”

Section: Bio-inspired Computation and Nosql Databasesmentioning

confidence: 96%

Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions

Torre-Bastida

Díaz-de-Arcaya

Osaba

et al. 2021

Neural Comput & Applic

View full text Add to dashboard Cite

This overview gravitates on research achievements that have recently emerged from the confluence between Big Data technologies and bio-inspired computation. A manifold of reasons can be identified for the profitable synergy between these two paradigms, all rooted on the adaptability, intelligence and robustness that biologically inspired principles can provide to technologies aimed to manage, retrieve, fuse and process Big Data efficiently. We delve into this research field by first analyzing in depth the existing literature, with a focus on advances reported in the last few years. This prior literature analysis is complemented by an identification of the new trends and open challenges in Big Data that remain unsolved to date, and that can be effectively addressed by bio-inspired algorithms. As a second contribution, this work elaborates on how bio-inspired algorithms need to be adapted for their use in a Big Data context, in which data fusion becomes crucial as a previous step to allow processing and mining several and potentially heterogeneous data sources. This analysis allows exploring and comparing the scope and efficiency of existing approaches across different problems and domains, with the purpose of identifying new potential applications and research niches. Finally, this survey highlights open issues that remain unsolved to date in this research avenue, alongside a prescription of recommendations for future research.

show abstract

Section: Bio-inspired Computation and Nosql Databasesmentioning

confidence: 96%