Modified Pure Radix Sort for Large Heterogeneous Data Set

Abstract

We have proposed a Modified Pure Radix Sort for Large Heterogeneous Data Set. In this research paper we discuss the problems of radix sort, brief study of previous works of radix sort & present new modified pure radix sort algorithm for large heterogeneous data set. We try to optimize all related problems of radix sort through this algorithm. This algorithm works on the Technology of Distributed Computing which is implemented on the principal of divide & conquer method. I. Introduction Sorting is a computational building block of fundamental importance and is the most widely studied algorithmic problem. The importance of sorting has led to the design of efficient sorting algorithms for a variety of architectures. Many applications rely on the availability of efficient sorting routines as a basis for their own efficiency, while some algorithms can be conveniently phrased in terms of sorting. Radix sort is an algorithm that sorts numbers by processing individual digits. n numbers consisting of k digits each are sorted in O (n · k) time. Radix sort can either process digits of each number starting from the least significant digit (LSD) or the most significant digit (MSD). The LSD algorithm first sorts the list by the least significant digit while preserving their relative order using a stable sort. Then it sorts them by the next digit, and so on from the least significant to the most significant, ending up with a sorted list. While the LSD radix sort requires the use of a stable sort, the MSD radix sort algorithm does not (unless stable sorting is desired). MSD radix sort is not stable. It is common for the counting sort algorithm to be used internally by the radix sort; Hybrid sorting approach, such as using insertion sort for small bins improves performance of radix sort significantly.