Capacity optimization (CO) is a technique for getting more data on a storage medium by analyzing the data for unique repetitive patterns that are then stored as shorter symbols. In capacity optimization, a small number of unique data units, called fundamental parts, are identified and stored. Because many such data units are duplicated in a typical file or set of files (called an object), storing a single copy of each fundamental part reduces the overall data volume by a significant amount. When read, the original object is reconstructed from the fundamental parts by a process called a plan. The same approach can be used for the transmission of data where the receiver understands the plan for reassembling it.
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On a basic level, capacity optimization technology is similar to conventional data compression. However, capacity optimization can provide a much greater compression factor. Conventional text compression can reduce the size of an object (in terms of megabytes or gigabytes) by a factor of up to about 2, but CO can reduce the size of an object by a factor of 20 or more. This means that a given object requires only about 5 percent as much storage space with CO as without, or 10 percent as much storage space with CO as with conventional compression. These factors also apply to data transmission time for a given bandwidth. Alternatively, an object that normally requires a broadband or high-speed connection for transfer can be sent over a narrowband connection in a reasonable length of time.
Capacity optimization technology has found applications in network communications, as well as in onsite and offsite data backup and archiving. Storage media, such as disk drives, that use CO are known as capacity-optimized storage (COS). The transmission of data using CO is called capacity-optimized transport (COT).
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- On SearchStorage.com, Brad O'Neill provides a white paper about capacity optimization (free registration may be required).