Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions
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Beschreibung
This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.
This book discusses the application of data systems and data-driven infrastructure in existing industrial systems in order to optimize workflow, utilize hidden potential, and make existing systems free from vulnerabilities. The book discusses application of data in the health sector, public transportation, the financial institutions, and in battling natural disasters, among others. Topics include real-time applications in the current big data perspective; improving security in IoT devices; data backup techniques for systems; artificial intelligence-based outlier prediction; machine learning in OpenFlow Network; and application of deep learning in blockchain enabled applications. This book is intended for a variety of readers from professional industries, organizations, and students.
Focuses on data systems and data-driven infrastructure improvements within a variety of institutions Proposes better collaborations through cooperation between facilities through data applications at various levels Ideal for readers from professional industries, organizations, researchers, and students
Autor*in
Sarvesh Pandey
Themen in »Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions«
Data driven Smart Cities IoT Security Data Forecasting Machine Learning based Dynamic Toll Collection Machine Learning Algorithms