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Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions

ISBN-13: 9783031155413 / Angielski / Twarda / 2023 / 338 str.

Sarvesh Pandey; Udai Shanker; Vijayalakshmi Saravanan
Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions Sarvesh Pandey Udai Shanker Vijayalakshmi Saravanan 9783031155413 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions

ISBN-13: 9783031155413 / Angielski / Twarda / 2023 / 338 str.

Sarvesh Pandey; Udai Shanker; Vijayalakshmi Saravanan
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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. 

Kategorie:
Technologie
Kategorie BISAC:
Technology & Engineering > Telecommunications
Computers > Data Science - Data Analytics
Business & Economics > Information Management
Wydawca:
Springer
Seria wydawnicza:
Eai/Springer Innovations in Communication and Computing
Język:
Angielski
ISBN-13:
9783031155413
Rok wydania:
2023
Dostępne języki:
Numer serii:
000824465
Ilość stron:
338
Oprawa:
Twarda
Dodatkowe informacje:
Wydanie ilustrowane

Introduction.- One World One Identification Smart System.- Tiered Architectural View of IoT: Structural Analysis and Concerns.- Rethinking Real-Time Applications in the current big data perspective.- Accuracy of Machine Learning Algorithms in predicting Retinal Disease.- A Cloud Trustworthiness Assessment Algorithm.- Improving Security in IoT devices.- Data backup Techniques for Healthcare Systems.- Role of Distributed Mutual Exclusion Algorithm.- Anomaly detection system in health care system enabled in blockchain technology framework.- Artificial intelligence-based Outlier Prediction .- Machine Learning in OpenFlow Network.- Defense Machinery Against Sybil Attacks over Wireless Ad-hoc Network on IoT.- Decentralized application development for health care using smart contracts.- Role of IoT in Healthcare.- Improved Breast Cancer Classification Using K-Means & Logistic Regression.- Sentimental Analysis.- IoT and Smart city.- Blockchain technology-based applications.- Anomaly detection in cryptocurrencies framework.- Application of deep learning in blockchain enabled applications.- Conclusion.

Dr. Sarvesh Pandey is presently Assistant Professor in the Computer Science - MMV, BHU, Varanasi, India. He received his Ph.D. degree (2020) in Computer Science & Engineering from M. M. M. University of Technology, Gorakhpur, India. His broad research areas include distributed databases, cloud computing, blockchain and advanced data systems. He has published many research papers in journals/conferences. He served as a review member for various reputed journals, conferences, and book series.

 

Dr. Udai Shanker is presently Professor in the Department of Computer Sc. & Engineering of M. M. M. University of Technology, Gorakhpur-273010, India. For his imitation of the most modern of approaches and also for his exemplary devotion to the field of teaching, and sharing his profound knowledge with students to make better future citizen of globe, he has been a role model for the new generation of academicians. Besides introduced radical and revolutionary changes that have positively impacted the database world and student community, he is a man well versed with all the intricacies of academics. He is credited with PhD from Indian Institute of Technology Roorkee and is recipient of awards from Institution of Engineers (India), Calcutta, India twice for his technical papers. He is authors of 120 research papers, which have been published in various National & International Journals/Conferences. He is reviewer of many International Conferences/Journals and also Editorial Board Member of International Journals. He is currently engaged in extensive research in the fields of Real Time Systems, Distributed Real Time Database Systems, Mobile Distributed Real Time Database Systems and Grid Databases.

 

Dr.Vijayalakshmi Saravanan is currently working as Assistant Professor, Computer Science,  USD and was an Adjunct Faculty at Golisano College of Computing and Information Sciences, Rochester Institute of Technology, USA. Earlier she was a Postdoctoral Associate at University at Buffalo, The State University of New York, USA and University of Waterloo, Canada under the prestigious "Schlumberger Faculty for the Future" Fellowship award (2015-2017). She completed her Ph.D. under the prestigious Erasmus Mundus EU-Govt Fellowship award at Malardalen University, Sweden as a research exchange student. Prior to this she was Assistant Professor of Practice at UTSA, USA. She has 10 years of teaching experience and has published many technical articles in scholarly international journals and conferences. She is serving as technical reviewer and program committee member for reputed conferences & journals such as GHC, SIGCSE and Springer. Her research interests include Power-Aware Processor Design, Big Data, IoT, Computer Architecture, Multi-Core Architecture, SW and HW Co-Design of Multi-Core, Power-Performance Analysis of Multi-Core Architecture. She is also a lead editor for Pattern Recognition Letters (2020) Interactive Multimedia Communication with 6G. Special Issue of Multimedia Tools and Applications (2020) and CRC Press Taylor and Francis, USA. She is a Senior Member of IEEE, ACM, ACM Distinguished speaker and CSI. She was the Chair of IEEE WIE Affinity Group at VIT University during 2009-2015.  Also Chair of NPA (National Postdoctoral Association) Annual Meetings. She is an ACM Distinguished Speaker and a Board Member of N2WOMEN (Networking Women) and SRP-HPC ECP Fellow.

 

Dr. Rajinikumar Ramalingam is working as a Research Scientist at Wissenschaftliche Mitarbeiter, Hamburg, Germany. He received his Ph.D. from Indian Institute of Technology, Bombay. He has more than 10 years of research experience in sensors, process control & automation, test facility setup, testing & validation of various sensors, measurement system, Software architecture & Networking, HF Signal processing, NI Lab view, PLC programming, MATLAB & COMSOL simulations, Low temperature sensor calibration. He is serving as technical reviewer for reputed books, conferences & journals. He authored research articles in various Journals/Conferences. He also has a patent in his name. He served as session chair and technical committee member for many conferences.

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.



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