Network data compression

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Networks[1]

Data compression involves encoding information using fewer bits than the original representation. Compression can be either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. The process of reducing the size of a data file is often referred to as data compression. [2]


A good video to help you understand this[edit]

The video below is used with gratitude from code.org[3]

Compression has enabled information to be disseminated more rapidly.

Data compression involves encoding information using fewer bits than the original representation.[4]

Lossless Compression

Algorithms exploit data redundancy o reduce file size. Common algorithms are Lempel Ziv Welch (LZW), DEFLATE, Lempel Ziv Renau. File asociated with this type of compression are PNG, GIF, ZIP files.

Lossy Compression

In this case some loss of information is acceptable. Typical uses are: LOSSY.GIF MP3 MP4 JPG

Why use compression Backups and Archiving So backup files don't take as much space as the original ones. File Transfer If the file is smaller it will take less time to upload/download. Web use of media Files Download of MP3 files(smaller music files) File encryption and protection Compressed files which their data is mixed up and has no meaning.



A good introductory video[edit]

See Also[edit]


Standards[edit]

These standards are used from the IB Computer Science Subject Guide[5]

  • Explain why compression of data is often necessary when transmitting across a network.

References[edit]

  1. http://www.flaticon.com/
  2. https://en.wikipedia.org/wiki/Data_compression
  3. https://www.youtube.com/watch?v=By30SCp-Tsw
  4. http://compsci2014.wikispaces.com/3.1.9+Compression+of+data
  5. IB Diploma Programme Computer science guide (first examinations 2014). Cardiff, Wales, United Kingdom: International Baccalaureate Organization. January 2012.