Handling Priority Inversion in Time-Constrained Distributed Databases - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handling Priority Inversion in Time-Constrained Distributed Databases write by Shanker, Udai. This book was released on 2020-02-14. Handling Priority Inversion in Time-Constrained Distributed Databases available in PDF, EPUB and Kindle. In the computer science industry, high levels of performance remain the focal point in software engineering. This quest has made current systems exceedingly complex, as practitioners strive to discover novel approaches to increase the capabilities of modern computer structures. A prevalent area of research in recent years is scalable transaction processing and its usage in large databases and cloud computing. Despite its popularity, there remains a need for significant research in the understanding of scalability and its performance within distributed databases. Handling Priority Inversion in Time-Constrained Distributed Databases provides emerging research exploring the theoretical and practical aspects of database transaction processing frameworks and improving their performance using modern technologies and algorithms. Featuring coverage on a broad range of topics such as consistency mechanisms, real-time systems, and replica management, this book is ideally designed for IT professionals, computing specialists, developers, researchers, data engineers, executives, academics, and students seeking research on current trends and developments in distributed computing and databases.
Handling Priority Inversion in Time-Constrained Distributed Databases
Handling Priority Inversion in Time-Constrained Distributed Databases - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handling Priority Inversion in Time-Constrained Distributed Databases write by . This book was released on 2020. Handling Priority Inversion in Time-Constrained Distributed Databases available in PDF, EPUB and Kindle. In the computer science industry, high levels of performance remain the focal point in software engineering. This quest has made current systems exceedingly complex, as practitioners strive to discover novel approaches to increase the capabilities of modern computer structures. A prevalent area of research in recent years is scalable transaction processing and its usage in large databases and cloud computing. Despite its popularity, there remains a need for significant research in the understanding of scalability and its performance within distributed databases. Handling Priority Inversion in Time-Constrained Distributed Databases provides emerging research exploring the theoretical and practical aspects of database transaction processing frameworks and improving their performance using modern technologies and algorithms. Featuring coverage on a broad range of topics such as consistency mechanisms, real-time systems, and replica management, this book is ideally designed for IT professionals, computing specialists, developers, researchers, data engineers, executives, academics, and students seeking research on current trends and developments in distributed computing and databases.
3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing
3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook 3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing write by Anandakumar Haldorai. This book was released on 2022-01-01. 3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing available in PDF, EPUB and Kindle. This book features the proceedings of The EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2020), which took place 18 – 19 December 2020. The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform.
Advanced Network Technologies and Intelligent Computing
Advanced Network Technologies and Intelligent Computing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Network Technologies and Intelligent Computing write by Isaac Woungang. This book was released on 2022-02-17. Advanced Network Technologies and Intelligent Computing available in PDF, EPUB and Kindle. This volume constitutes the selected papers presented at the First International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2021, hed in Varanasi, India, in December 2021. Due to the COVID-19 pandemic the conference was held online. The 61 papers presented were thoroughly reviewed and selected from 593 submissions. They are organized in topical sections on advanced network technologies and intelligent computing. ;
Advanced Deep Learning Applications in Big Data Analytics
Advanced Deep Learning Applications in Big Data Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Deep Learning Applications in Big Data Analytics write by Bouarara, Hadj Ahmed. This book was released on 2020-10-16. Advanced Deep Learning Applications in Big Data Analytics available in PDF, EPUB and Kindle. Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today’s digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.
