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Edexcel GCSE. Computer Science. Topic 11 - Data Storage and Compression. Units. Bit (b) = 1 or 0. Megabyte = 1024 kilobytes (2 2 0 bytes). Nibble = Four bits e.g. 1011. Gigabyte = 1024 megabytes (2 30 bytes). Byte = Eight bits (or two nibbles) e.g. 1011 1001.
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Edexcel GCSE Computer Science Topic 11 - Data Storage and Compression
Units • Bit (b) = 1 or 0 • Megabyte = 1024 kilobytes (220 bytes) • Nibble = Four bits e.g. 1011 • Gigabyte = 1024 megabytes (230 bytes) • Byte = Eight bits (or two nibbles) e.g. 1011 1001 • Terabyte = 1024 gigabytes (240 bytes) Technically these are the values associated with the binary prefixes, but Edexcel seem to deal with them in terms of 1024 instead of 1000 like it probably should be • Kilobyte (KB) = 1024 bytes (210 bytes) • E.g. how many bytes are there in 34MB? • E.g. how many megabytes are there in 7TB? • Files storage is measured in terms of bytes, and data transmission is measured in bits per second (though often with prefixes, e.g. Mbps) • E.g. find the time taken to transfer 30KB with a rate of 8192bps
Data Compression …the reduction of file size whilst retaining the underlying information • This is important for transmission and storage, as the compression process means fewer bits are needed to the represent the original information. Upload, download and file transfer times can therefore be reduced. Lossy compression • In lossy compression, some of the original data is removed from the file during compression, in order to reduce the size. As a result of this, these compression algorithms are used on media such as audio, video and images where although we can detect a decrease in quality, important information is not lost. • After a file is decompressed after lossy compression the file isn’t the same as before. • Two examples of lossy algorithms are MP3 for audio and JPEG for image: MP3 JPEG • Eyes are more complex than ears and so JPEG compression uses many complicated and especially mathematical methods to reduce the file size. • Part of the way the MP3 compression works is by removing the data for the audio that is deemed to be outside the normal human pitch range • Perhaps the most easy to understand as just an example is the deletion of certain colours and properties of colour are eyes are least sensitive to. • The audio quality might be reduced, but not because integral data has been deleted.
Lossless compression • These algorithms compress the data without any loss of data meaning when decompressed it is the same. • They are however not as effective as the lossy counterparts, as they work by making the storage more efficient. • Lossless compression is used in situations where all the data is essential to its purpose, such as source code or a text document, where you would not want any of the data to be lost. • The run-length encoding (RLE) algorithm is a popular method of lossless compression and it works by replacing long sequences of repeated data values (the ‘run’) by a code indicating what exactly has been repeated and how many times it was repeated. Using a graphical example: …Identical pixels are grouped to save storage space • For RLE to be effective, it must be used on files likely to have repeated data. • For example, a text document is unlikely to have many repeated characters in a row, so RLE would have little effect. • Instead, it is used on files such as images and animations where repeated data values are frequent (like blocks of colour)
