Although several cloud storage systems have been proposed, most of them can provide highly efficient point\nqueries only because of the key-value pairs storing mechanism. For these systems, satisfying complex\nmulti-dimensional queries means scanning the whole dataset, which is inefficient. In this paper, we propose a\nmultidimensional index framework, based on the Skip-list and Octree, which we refer to as Skip-Octree. Using a\nrandomized skip list makes the hierarchical Octree structure easier to implement in a cloud storage system. To\nsupport the Skip-Octree, we also propose a series of index operation algorithms including range query algorithm,\nindex maintenance algorithms, and dynamic index scaling algorithms. Through experimental evaluation, we show\nthat the Skip-Octree index is feasible and efficient.
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