Communication cost modeling for federated database systems

Federated database systems are a useful tool for businesses and researchers around the world. These systems allow data from multiple remote data sources to be logically combined into one unified local data source. Using this system, queries that would traditionally require query fragments to be submitted to multiple sites can be performed by submitting one query to a central site. This central site can make use of data stored at the different remote sources as though the central site were simply an application requesting data. Currently, the performance of global queries in most federated database systems is much worse than the performance of local queries.; These so-called global queries must be optimized, but many additional factors combine to make global query optimization complicated. Beyond the problems of local query optimization, additional costs, including the cost of communication and the cost of remote site optimization must be factored into cost models.; This thesis presents benchmarking experiments performed at iAnywhere Solutions, Inc. during a cooperative work term and at the University of Waterloo. A discussion of the results of this benchmarking as well as a model for estimating communication cost is presented. The results of testing the model are also provided.