Proc. of 27th ACM/IEEE Hawaii Int'l Conf. on Syst. Sci., pp 263 - 72, 
Feb. 1994
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          Establishing a Fuzzy Cost Model for Query Optimization 
                      in a Multidatabase System

 
                     Qiang Zhu    Per-Ake Larson
                    Department of Computer Science
                         University of Waterloo
                   Waterloo, Ontario N2L 3G1, Canada
 
 
                               ABSTRACT

One of the challenges for query optimization in a multidatabase system
(MDBS) is that some local optimization information may not be accurately known 
at the global level because of local autonomy. Traditional query optimization 
techniques using a crisp cost model may not be suitable for an MDBS because 
precise information is required. In this paper we present a new technique 
that performs query optimization using a fuzzy cost model that allows fuzzy 
information. We discuss methods for establishing a fuzzy cost model and 
introduce two fuzzy optimization criteria that can be used with a fuzzy cost 
model. We illustrate the benefits of such fuzzy query optimization. We also 
analyze the computational complexity for the fuzzy query optimization approach 
and suggest a simple method to reduce the complexity.