The explosive growth of the Internet has ushered in a new area in which information is exchanged and accessed on a constant basis. In response to this growth, there has been an increase in the size of data that is being shared. Users are demanding more than standard HTML documents, wanting access to a variety of data, such as, audio data, video data, image data, and programming data. Thus, there is a need for data storage that can accommodate large sets of data, while at the same time provide fast and reliable access to the data.
One response has been to utilize single storage devices which may store large quantities of data but have difficulties providing high throughput rates. As data capacity increases, the amount of time it takes to access the data increases as well. Processing speed and power has improved, but disk I/O (Input/Output) operation performance has not improved at the same rate making I/O operations inefficient, especially for large data files.
Another response has been to allow multiple servers access to shared disks using architectures, such as, Storage Area Network solutions (SANs), but such systems are expensive and require complex technology to set up and to control data integrity. Further, high speed adapters are required to handle large volumes of data requests.
One problem with conventional approaches is that they are limited in their scalability. Thus, as the volume of data increases, the systems need to grow, but expansion is expensive and highly disruptive.
Another common problem with conventional approaches is that they are limited in their flexibility. The systems are often configured to use predefined error correction control. For example, a RAID system may be used to provide redundancy and mirroring of data files at the physical disk level giving administrators little or no flexibility in determining where the data should be stored or the type of redundancy parameters that should be used.