Database migration is an ubiquitous need faced by enterprises that generate and use vast amount of data. This is due to database software updates, or from changes to hardware, project standards, and other business factors [1]. Migrating a large collection of databases is a way more challenging task than migrating a single database, due to the presence of additional constraints. These constraints include capacities of shifts, sizes of databases, and timing relationships. In this paper, we present a comprehensive framework that can be used to model database migration problems of different enterprises with customized constraints, by appropriately instantiating the parameters of the framework. We establish the computational complexities of a number of instantiations of this framework. We present fixed-parameter intractability results for various relevant parameters of the database migration problem. Finally, we discuss a randomized approximation algorithm for an interesting instantiation.
CITATION STYLE
Subramani, K., Caskurlu, B., & Velasquez, A. (2019). Minimization of Testing Costs in Capacity-Constrained Database Migration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11409 LNCS, pp. 1–12). Springer Verlag. https://doi.org/10.1007/978-3-030-19759-9_1
Mendeley helps you to discover research relevant for your work.