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At first, a method called “lossy”—a name that implies it will
lose data—might not seem particularly attractive. There are types of
data, however, such as voice or video transmission, that are still
usable despite a certain amount of lost data. Allowing some lost
data significantly increases the factor by which data can be
compressed. JPEG and
MPEG are examples of lossy data
compression. In our case, though, we are building networks that need
to deliver data to computers that typically do not accept any
significant data loss. Lossless data compression comes either as
statistical or dictionary form. The statistical method is not particularly applicable here,
as it relies on the traffic that is being compressed to be
consistent and predictable, when internetwork traffic tends to be
neither. Cisco’s data compression methods, STAC and Predictor, are based on the dictionary style of
compression. These methods rely on the two communicating devices
sharing a common dictionary that maps special codes to actual
traffic patterns. STAC is based on the Lempel-Ziv algorithm that identifies commonly
transmitted sequences and replaces those sequences in the data
stream with a smaller code. This code is then recognized at the
receiving end, extracted from the data stream, and the original
sequence inserted in the data stream. In this manner, less data is
sent over the WAN link even as transmission of the same raw data is
permitted. |
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