Referenced Items are not available for this document.
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 as required. 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.<
Published in:
System Sciences, 1994. Proceedings of the Twenty-Seventh Hawaii International Conference on
(Volume:2
)
Date of Conference: 4-7 Jan. 1994
- Page(s):
- 263 - 272
- Print ISBN:
- 0-8186-5090-7
- INSPEC Accession Number:
- 4687835
- Conference Location :
- Wailea, HI, USA
- Digital Object Identifier :
- 10.1109/HICSS.1994.323257
- Product Type:
- Conference Publications
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