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Part of book or chapter of book . 2005 . Peer-reviewed
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Modeling and analysis of transaction processing systems

Authors: Philip S. Yu;

Modeling and analysis of transaction processing systems

Abstract

In recent years, the demand for on-line transaction processing systems has grown rapidly with ever stringent performance requirements. In this paper, we examine several issues encountered in designing transaction processing systems and report some of the recent advancements in analytical performance modelling methodology on analyzing alternative design trade-offs. First of all, the Concurrency Control (CC) scheme employed can profoundly affect the performance of transaction processing systems. A general analytic modelling approach is presented that can be applied to analyze the various CC schemes under a unified framework, including locking, various optimistic schemes, and hybrid schemes. The analysis can capture the effect of skewed data access, different lock modes, variable length transactions and the buffer retention effect on rerun transactions. Next we consider the analysis of buffer hit probability. In a multi-node environment, whether in a cluster or client server environment, buffer coherency needs to be addressed. The cross invalidation phenomenon can have an adverse effect on the buffer hit probability. A general methodology to analyze various coherency control schemes is examined to predict the buffer hit probability. A hierarchical approach is used to decompose the modelling of transaction processing systems into three components: hardware resource, concurrency control and buffer models. The interaction among the components is then captured through a fixed point iteration.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
bronze