Abstract
A linear mapping is a technique that stores objects with multi-dimensional properties in data storage in a certain order. The mapping aims at preserving spatial locality, which means that objects in the same cluster are likely to be accessed together. Locality is a crucial property to improve performance of accessing data. The level of efficiency of a linear mapping relies on distance metric. Existing linear mapping techniques such as Hilbert curve may maximize their efficiency in Euclidean space. For linear mapping, objects in indoor spaces should be dealt with in a different manner because distance measurement in indoor space differs from that in Euclidean space. In this paper, we specify requirements of linear mappings in indoor space and suggest a linear mapping based on heuristics for indoor space objects.
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