Sorted r-Train: An Improved Dynamic Data Structure for Handling Big Data

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Mohd Abdul Ahad 1,* Ranjit Biswas 1

1. Department of Computer Science and Engineering, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi-110062, India

* Corresponding author.


Received: 19 Mar. 2018 / Revised: 16 May 2018 / Accepted: 12 Jul. 2018 / Published: 8 Nov. 2018

Index Terms

r-Train, trie, HAT, Linked List, Arrays, Big Data, larray


In today’s computing era, the world is dealing with big data which has enormously expanded in terms of 7Vs (volume, velocity, veracity, variability, value, variety, visualization). The conventional data structures like arrays, linked list, trees, graphs etc. are not able to effectively handle these big data. Therefore new and dynamic tools and techniques which can handle these big data effectively and efficiently are the need of the hour. This paper aims to provide an enhancement to the recently proposed “dynamic” data structure “r-Train” for handling big data. With the emergence of the “Internet of Things (IoT)” technology, real-time handling of requests and services are pivotal. Therefore it becomes necessary to promptly fetch the required data as and when required from the enormous piles of big data that are generally located at different sites. Therefore an effective searching and retrieval mechanism must be provided that can handle these challenging issues. The primary aim of this proposed refinement is to provide an effective means of insertion, deletion and searching techniques to efficiently handle the big data.

Cite This Paper

Mohd Abdul Ahad, Ranjit Biswas, "Sorted r-Train: An Improved Dynamic Data Structure for Handling Big Data", International Journal of Intelligent Systems and Applications(IJISA), Vol.10, No.11, pp.27-35, 2018. DOI:10.5815/ijisa.2018.11.04


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