Название: Securing IoT and Big dаta: Next Generation Intelligence (Internet of Everything (IoE))Автор: Vijayalakshmi Saravanan, Alagan Anpalagan, T. Poongodi, Firoz Khan
Издательство: CRC Press
Год: 2021
Страниц: 191
Язык: английский
Формат: pdf (true), azw3, epub
Размер: 10.1 MB
This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems.
It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies.
Hadoop framework has been developed to handle the various issues with big data. It is an open source system that has potential to store heterogeneous and huge amounts of data and provides a solution for distributed and parallel processing to make the computation faster at low cost. This framework comprises two major components, namely the Hadoop distributed file system to accumulate data and the map reduce based programming model for processing the data. Further, the resource management in a cluster is typically handled by its resource manager YARN. However, these are not sufficient to tackle big data problems. Along with these, the Hadoop framework encompasses various other elements such as Hive, Pig, Mahout, Sqoop, Flume, Zookeeper, Oozie, and others to provide a complete solution to big data problems.
Spark is not the same as the Hadoop framework as it can be integrated with different file systems such as HDFS, Mongo DB, Amazon’s S3, and others. It is an open source cluster computing system, which is able to run data on a disk as well as in memory. Spark is built to execute onto HDFS and can use YARN. It is developed to do a lot of analytics by employing SQL, streaming, graph processing, R programming, and machine learning algorithms. The fast processing power of the Apache Spark is because of its in-memory cluster feature. In fact, it can run an application a hundred times quicker in memory and ten times quicker when executed on disk. Spark is powerful and very popular as it has a built-in application programming interface (API) in diverse languages such as Java, Python, and Scala, and it provides around 80 high-level operators for users' queries. It is a single integrated software that provides enormous functions for advanced data analytics; it has the ability to read data from any existing Hadoop data file or HBase or Cassandra, and many other data sources.
The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.
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