A Statistical Performance Model of Homogeneous Raidb Clusters A Statistical Performance Model of Homogeneous Raidb Clusters

by Rogers, Brandon Lamar

The continual growth of the Internet and e-commerce is driving demand for speed, reliability and processing power. With the rapid development and maturation of e-commerce, the need for a quick access to large amounts of information is steadily rising. Traditionally, database systems have been used for information storage and retrieval. However, with online auctions, rapid Internet searches, and data archival, the need for more powerful database systems is also growing.

One type of distributed database is called Redundant Arrays of Inexpensive Databases (RAIDb). RAIDb clusters are middleware-driven to promote interoperability and portability. RAIDb clusters allow for multiple levels of data replication and publish the clustered system as a single, coherent database system.

In this thesis, performance models are created for RAIDb level 1 and level 2 clusters. A statistical three-factor, two-level factorial design is used to evaluate the significance of several factors in a RAIDb cluster. These significant factors are then used to create a regression analysis, and eventually a regression equation, that can be used to predict the performance of RAIDb clusters. This performance model should be a useful predictive tool since the results have a 99% confidence interval.