Adaptive indexing of moving objects with highly variable update frequencies

  • Authors:

  • Nan Chen;Li-Dan Shou;Gang Chen;Jin-Xiang Dong

  • Affiliations:

  • College of Computer Science, Zhejiang University, Hangzhou, China;College of Computer Science, Zhejiang University, Hangzhou, China;College of Computer Science, Zhejiang University, Hangzhou, China;College of Computer Science, Zhejiang University, Hangzhou, China

  • Venue:
  • Journal of Computer Science and Technology
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

In recent years, management of moving objects has emerged as an active topic of spatial access methods. Various data structures (indexes) have been proposed to handle queries of moving points, for example, the well-known Bx-tree uses a novel mapping mechanism to reduce the index update costs. However, almost all the existing indexes for predictive queries are not applicable in certain circumstances when the update frequencies of moving objects become highly variable and when the system needs to balance the performance of updates and queries. In this paper, we introduce two kinds of novel indexes, named By-tree and αBy-tree. By associating a prediction life period with every moving object, the proposed indexes are applicable in the environments with highly variable update frequencies. In addition, the αBy-tree can balance the performance of updates and queries depending on a balance parameter. Experimental results show that the By-tree and αBy-tree outperform the Bx-tree in various conditions.