Title: The skip-octree: a dynamic cloud storage index framework for multidimensional big data systems

Authors: Yunyun Dong; Jing He; Shaowen Yao; Wei Zhou

Addresses: Research Center of Western Yunnan Development, Yunnan University, Kunming, Yunnan, 65091, China ' National Pilot School of Software, Yunnan University, Kunming, Yunnan, 65091, China ' National Pilot School of Software, Yunnan University, Kunming, Yunnan, 65091, China ' National Pilot School of Software, Yunnan University, Kunming, Yunnan, 65091, China

Abstract: Nowadays the information explosion have generated a large amount of data. To utilise these data, there is a trend of setup efficient data index, especially for multidimensional data indexing. However, most of the current cloud storage systems build data indexing based on the distributed hash (DHT), where data are stored by the key-value. This module is not very suitable for range queries in multidimensional data indexing. To solve these problems, this paper builds a multidimensional data index based on skip lists and octree structure. Firstly, this architecture adopts the structure of octree to store data and establish the corresponding index mechanism, it can make use of the idea of different dimensional space partitioning to achieve a multi-dimensional index. Secondly, the relevant algorithms are designed to sustain the characteristics of this framework in this paper. Finally, the simulation experiment shows that the skip-octree architecture is feasible and efficient.

Keywords: multidimensional data indexing; distributed indexes; skip lists; skip octree; dynamic cloud storage; multidimensional big data; cloud computing; simulation.

DOI: 10.1504/IJWET.2015.073952

International Journal of Web Engineering and Technology, 2015 Vol.10 No.4, pp.393 - 407

Published online: 30 Dec 2015 *

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