Mar 14, 2024 · We here discuss the main principles and features of Distributed Machine Learning and Distributed Deep Learning frameworks. The main contribution of this work is a survey of solutions proposed in the literature, through the investigation of selected features and capabilities.

Apr 18, 2021 · Upon learning the big data concepts, we will get a vivid picture of the need for clusters of machines (distributed systems), and appreciate the use of this architecture in solving critical problems associated with storing and processing humungous data.

Dec 21, 2022 · This paper explores the application of distributed computing systems for the processing and analysis of large data sets, also referred to as big data. The paper outlines the various...

The chapters tackle the essential concepts and patterns of distributed computing widely used in big data analytics. This book discusses also covers the main technologies which support distributed processing.

Aug 31, 2017 · Distributed Computing together with management and parallel processing principle allow to acquire and analyze intelligence from Big Data making Big Data Analytics a reality. Different aspects of the distributed computing paradigm resolve different types of challenges involved in Analytics of Big Data.

Aug 31, 2017 · In this chapter we have discussed various technologies related to big data technology – NoSQL database, distributed file system, map-reduce and spark based distributed computation, distributed communication platform, distributed caching, search platform and visualization technologies.

2 days ago · Detection of faulted phases in a medium-voltage main feeder using the cyber grid guard system with distributed ledger technology[J]. International Journal of Electrical Power and Energy Systems, 2024, 161 110162-110162. ... Vlachos Ilias. Big data analytics in supply chain decarbonisation: a systematic literature review and future research ...

May 27, 2024 · Distributed computing systems address big data challenges by distributing data and processing it across multiple nodes. Thanks to the parallel processing capabilities of these systems, data processing and analysis become significantly faster.

Apr 30, 2024 · Cloud-based distributed systems for big data analytics are an advanced technological integration that facilitates the handling, examination, and control of enormous volumes of data...

Discover this multi-disciplinary and insightful work, which integrates machine learning, edge computing, and big data. Presents the basics of training machine learning models, key challenges and issues, as well as comprehensive techniques …