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Dynamic Data Normalization (Erl, Naserpour)

How can redundant data within cloud storage devices be automatically avoided?

Dynamic Data Normalization

Problem

Cloud consumers may store large volumes of redundant data within cloud storage devices, thereby bloating the storage architecture and compromising data access performance.

Solution

Data received by cloud consumers is automatically normalized so that redundant data is avoided and cloud storage device capacity and performance is optimized.

Application

Data de-duplication technology is used to detect and eliminate redundant data at block or file-based levels.
Dynamic Data Normalization: In Part A, datasets containing redundant data unnecessarily bloat data storage. The Dynamic Data Normalization pattern results in the constant and automatic streamlining of data as shown in Part B, regardless of how denormalized the data received from the cloud consumer is.

In Part A, datasets containing redundant data unnecessarily bloat data storage. The Dynamic Data Normalization pattern results in the constant and automatic streamlining of data as shown in Part B, regardless of how denormalized the data received from the cloud consumer is.

NIST Reference Architecture Mapping

This pattern relates to the highlighted parts of the NIST reference architecture, as follows:

Dynamic Data Normalization: NIST Reference Architecture Mapping
Dynamic Data Normalization: NIST Reference Architecture Mapping
CCP Module 5: Advanced Cloud Architecture

This pattern is covered in CCP Module 5: Advanced Cloud Architecture.

For more information regarding the Cloud Certified Professional (CCP) curriculum, visit www.arcitura.com/ccp.

CCP Module 14: Advanced Cloud Storage

This pattern is covered in CCP Module 14: Advanced Cloud Storage.

For more information regarding the Cloud Certified Professional (CCP) curriculum, visit www.arcitura.com/ccp.

Cloud Computing: Concepts, Technology & Architecture

This cloud computing mechanism is covered in:

Cloud Computing: Concepts, Technology & Architecture by Thomas Erl, Zaigham Mahmood,
Ricardo Puttini

(ISBN: 9780133387520, Hardcover, 260+ Illustrations, 528 pages)

For more information about this book, visit www.arcitura.com/books.