A theoretical formulation for degrees of isolation in databases

doi:10.1016/0950-5849(96)01109-3

Information and Software Technology

Volume 39, Issue 1, 1997, Pages 47-53

https://doi.org/10.1016/0950-5849(96)01109-3 Get rights and content

Abstract

Although isolation is one of the desirable properties, most commercial database management systems do not provide complete isolation to transactions. They offer different degrees — 0, 1, 2, or 3 — of isolation, to transactions. By providing lower degrees of isolation, response time of a database system can be improved, although at the expense of consistency. Originally different degrees of isolation were defined in terms of lock-based protocols. This paper formulates these different degrees of isolation in terms of histories, as in the case of the usual serialization theory and proposes timestamp-based protocols for different degrees of isolation.

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There are more references available in the full text version of this article.

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Citation Excerpt :
Log-Manager – simulates the stable storage of a transactional server, i.e. the I/O costs for storage - retrieval of object states and the status of processed transactions. Concurrency Control – simulates the concurrency control and isolation guarantees [2]. As in [16], we do not consider resource consumption for concurrency control, since its CPU demands cannot be easily quantified.
Architecture is fundamental for fulfilling requirements related to the non-functional behavior of a software system such as the quality requirement that response time does not degrade to a point where it is noticeable. Approaches like the Architecture Tradeoff Analysis Method (ATAM) combine qualitative analysis heuristics (e.g. scenarios) for one or more quality metrics with quantitative analyses. A quantitative analysis evaluates a single metric such as response time. However, since quality metrics interact with each other, a change in the architecture can affect unpredictably multiple quality metrics.
This paper introduces a quantitative method that determines the impact of a design change on multiple metrics, thus reducing the risks in architecture design. As a proof of concept, the method is applied on a simulation model of transaction processing in client server architecture.
Factor analysis is used to unveil latent (i.e. not directly measurable) quality features represented by new variables that reflect architecture-specific correlations between metrics. Separate Analyses of Variance (ANOVA) are then applied to these variables, for interpreting the tradeoffs detected by factor analysis in terms of the quantified metrics.
The results for the examined transaction processing architecture show three latent quality features, the corresponding groups of strongly correlated quality metrics and the impact of architecture characteristics on the latent quality features.
The proposed method is a systematic way for relating the variability of quality metrics and the implied tradeoffs to specific architecture characteristics.
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¹: The work of E. Bertino was carried out while visiting George Mason University during summer 1994.

²: The work of S. Jajodia was partially supported by a grant from ARPA, administered by the Office of Naval Research under grant number N0014-92-J-4038, and by National Science Foundation under grant number IRI-9303416.

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A theoretical formulation for degrees of isolation in databases

Abstract

Granularity of locks and degrees of consistency in a shared data base

Transaction Processing: Concepts and Techniques

Transactions and consistency in distributed database systems

ACM Trans. on Database Systems

Concurrency Control and Recovery in Database Systems