Fragmentation and allocation are database distribution design techniques used to improve the system performance by increasing data localisation and reducing data transportation costs between different network sites. Often fragmentation and allocation are considered separately, disregarding that they are using the same input information to achieve the same objective. Vertical fragmentation is often considered a complicated problem, because the huge number of alternatives make it nearly impossible to obtain an optimal solution. Therefore, many researchers seek for heuristic solutions, among which affinity-based vertical fragmentation approaches form a main stream in the literature. However, using attribute affinities to perform fragmentation can not really reflect the local needs of data at each site. Therefore it is not guaranteed that the remote data transportation costs can be reduced. This paper addresses vertical fragmentation and allocation simultaneously in the context of the relational data model. The core of the paper is a heuristic approach to vertical fragmentation, which uses a cost model and is targeted at globally minimising these costs. Further, based on the proposed vertical fragmentation, an integrated methodology is proposed by applying vertical and horizontal fragmentation simultaneously to produce mixed fragmentation schemata.
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