Abstract
PDRT is a prototype design tool which is currently being developed for database workload capture and analysis with an emphasis on performance. A major feature of this tool is a clustering facility which can be used to optimise the proximity between inter-related tuples on a hierarchy of secondary storage devices in order to enhance retrieval performance. As a step towards obtaining a good clustering method we have previously shown that simulated annealing, which is a derivative of the Metropolis Monte Carlo optimisation algorithm, provides an effective solution to this NP-complete placement problem. In this paper we discuss and evaluate new “flavours” of this heuristic methodology found in the literature and investigate the effect of the initial configuration upon the final result.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
