An extendible data structure for handling large multidimensional data sets

Abstract

Multidimensional array is widely used in large number of scientific research and engineering applications for handling large multidimensional data. There exist many data structures to represent multidimensional data. But most of these data structures are static (such as traditional multidimensional array) and can not handle the dynamic extension or reduction of the array. The Traditional Multidimensional Array (TMA) is efficient in terms of accessing the elements of the array by random computing the addressing function but TMA is not extendible during run time. In this paper we propose a new scheme, Karnaugh Representation of Extendible Array (KEA), to represent the multidimensional data. The main idea of this scheme is to represent n dimensional array by a set of two dimensional extendible arrays. The scheme can be extended in any direction during run time. To evaluate our proposed scheme, we implement and compare with the existing systems for different operations with the Traditional Multidimensional Array (TMA), and Traditional Extendible Array (TEA). Our experimental result shows that the KEA scheme outperforms TMA and TEA.