Theory
Data Compression
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Servo-tracking Faults
During a write operation, if the servo system detects an error that may result in adjacent data tracks
being over-written, the write operation is aborted. The write operation will not continue until the cor-
rect servo tracking is re-established.
Data Compression
Typical data streams of text, graphics, software code, or other forms of data contain repeated infor-
mation of some sort, whether it is at the text level where you can readily recognize regular repeti-
tions of a single word, or at the binary level where the repetitions are in bits or bytes. Although most
data is unique and random, the binary level data exhibits patterns of various sizes that repeat with
varying degrees of regularity.
Storage efficiency is increased if the redundancies or repetition in the data are removed before the
data is recorded to tape. Data compression technology significantly reduces or eliminates redundan-
cies in data before recording the information to tape. This increases the amount of data that can be
stored on a finite medium and increases the overall storage efficiency of the system.
With data compression, the redundant information in a data stream is identified and represented by
codewords or symbols, which allow the same data to be recorded in a fewer number of bits. These
codewords or symbols point back to the original data string, using fewer characters to represent the
strings. Because these smaller symbols are substituted for the longer strings of data, more data can
be stored in the same physical space.
Some important benefits result from data compression in tape drives:
•
The same amount of information can be stored on a smaller length of tape.
•
More data can be stored on a given length of tape.
•
Performance can more closely parallel to that of high-transfer-rate computers.
•
More information can be transferred in the same time interval.
Data Compression Considerations
In an effective data-compression method, several factors are important:
•
The amount of compression. The amount of compression is measured by the compression
ratio. This ratio compares the amount of uncompressed data to the amount of compressed
data. It is obtained by dividing the size of the uncompressed data by the size of the com-
pressed data)
•
The speed with which data is compressed and decompressed relative to the host transfer rate.
•
The types of data to be compressed.
•
The data integrity of the compressed data.
The amount of compression possible in a data stream depends on factors such as:
•
Data pattern
•
Compression algorithm
•
Pattern repetition length
