.png){kind=icon}
.png){kind=icon}
Return
Dynamic multidimensional index for large-scale cloud data
.png){kind=icon}
OA
AI
DOI：10.1186/s13677-016-0060-1.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Although several cloud storage systems have been proposed, most of them can provide highly efficient point queries only because of the key-value pairs storing mechanism. For these systems, satisfying complex multi-dimensional queries means scanning the whole dataset, which is inefficient. In this paper, we propose a multidimensional index framework, based on the Skip-list and Octree, which we refer to as Skip-Octree. Using a randomized skip list makes the hierarchical Octree structure easier to implement in a cloud storage system. To support the Skip-Octree, we also propose a series of index operation algorithms including range query algorithm, index maintenance algorithms, and dynamic index scaling algorithms. Through experimental evaluation, we show that the Skip-Octree index is feasible and efficient.
Keywords:
Cloud storage
Multidimensional index
Distributed index
Skip-Octree
Skip list
Octree
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
J
IF:
4.3
Papers:
738
Citations:
2.2K