Query Cost Model Constructed and Analyzed in a Dynamic Environment

Abstract

Query processing over the Internet involving multiple data sources has been proven one of the most difficult and important problems in modern e-data sharing society. In this new data processing environment, three major factors affect the cost of a query: network congestion situation, server states (server workload), and data/query complexity. In this paper, we construct cost models for estimating the cost of query and split query cost into data searched cost and data transmitted cost. We also study how to capture the changes of the query system in order to update the cost models whenever it needs, and use a real discrete fourier transform method to filter the noise in the main trend of the network and the query system for the more accurate cost models. So we can choose the best query plan according to the updated cost model.