Название: Big Data Platforms and Applications: Case Studies, Methods, Techniques, and Performance Evaluation
Автор: Florin Pop, Gabriel Neagu
Издательство: Springer
Год: 2021
Страниц: 300
Язык: английский
Формат: pdf (true), epub
Размер: 42.3 MB

This book provides a review of advanced topics relating to the theory, research, analysis and implementation in the context of big data platforms and their applications, with a focus on methods, techniques, and performance evaluation. The explosive growth in the volume, speed, and variety of data being produced every day requires a continuous increase in the processing speeds of servers and of entire network infrastructures, as well as new resource management models. This poses significant challenges (and provides striking development opportunities) for data intensive and high-performance computing, i.e., how to efficiently turn extremely large datasets into valuable information and meaningful knowledge.

The value of Big Data applications and their supporting infrastructure like Cloud/Fog/Edge systems lies in the fact that end-users always operate in a specific context: their role, intentions, locations, data handled, and working environment constantly change. According to the research perspective, the Big Data challenges include fundamental research and innovation problems addressing the efficiency, scalability, and responsiveness of analytics services, such as machine learning, language understanding, data mining, visualization, privacy-aware application, etc. The existing platforms create an ecosystem based on the convergence of Big Data and Cloud/Edge computing technologies, sometimes combined with HPC for advanced analytics, that in connection with the Internet of Things capabilities enable a wide range of innovations in such sectors as e-learning, healthcare, digitalization, manufacturing, energy, natural resource monitoring, finance and insurance, agri-food, space, and security. In this context, our book, coverage several models and use-cases that are strongly correlated with Big Data challenges.

The book provides, in this sense, an excellent venue for the dissemination of research efforts, analysis, implementation, and final results for Big Data platforms and applications being oriented on case studies, methods, techniques, and performance evaluation, being a flagship driver toward presenting and supporting advance research in the area of Big Data platforms and applications. We are convinced that all authors highlight the results obtained in their research projects and in collaboration with various researchers and practitioners. In the case that the presented work is an extension of already published results, we are more than happy to include the new results in our project.

Features:

* Presents a comprehensive review of the latest developments in big data platforms
* Proposes state-of-the-art technological solutions for important issues in big data processing, resource and data management, fault tolerance, and monitoring and controlling
* Covers basic theory, new methodologies, innovation trends, experimental results, and implementations of real-world applications

The task of context data management is further complicated by the variety of sources such data derives from, resulting in different data formats, with varying storage, transformation, delivery, and archiving requirements. At the same time rapid responses are needed for real-time applications. With the emergence of cloud infrastructures, achieving highly scalable data management in such contexts is a critical problem, as the overall application performance is highly dependent on the properties of the data management service.