The skip-octree: a dynamic cloud storage index framework for multidimensional big data systems Online publication date: Wed, 30-Dec-2015
by Yunyun Dong; Jing He; Shaowen Yao; Wei Zhou
International Journal of Web Engineering and Technology (IJWET), Vol. 10, No. 4, 2015
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Web Engineering and Technology (IJWET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook