Journal of the Korea Institute of Military Science and Technology (한국군사과학기술학회지)

The Korea Institute of Military Science and Technology (한국군사과학기술학회)
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A Study on Bottom-Up Update of TPR-Tree for Target Indexing in Naval Combat Systems

함정전투체계 표적 색인을 위한 TPR-Tree 상향식 갱신 기법

  • Go, Youngkeun (The 6th Research and Development Institute, Agency for Defense Development)
  • 고영근 (국방과학연구소 제6기술연구본부)
  • Received : 2018.10.16
  • Accepted : 2019.03.08
  • Published : 2019.04.05
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Abstract

In modern warfare, securing time for preemptive response is recognized as an important factor of victory. The naval combat system, the core of naval forces, also strives to increase the effectiveness of engagement by improving its real-time information processing capabilities. As part of that, it is considered to use the TPR-tree in the naval combat system's target indexing because spatio-temporal searches can be performed quickly even as the number of target information increases. However, because the TPR-tree is slow to process updates, there is a limitation to handling frequent updates. In this paper, we present a method for improving the update performance of TPR-tree by applying the bottom-up update scheme, previously proposed for R-tree, to the TPR-tree. In particular, we analyze the causes of overlaps occurring when applying the bottom-up updates and propose ways to limit the MBR expansion to solve it. Our experimental results show that the proposed technique improves the update performance of TPR-tree from 3.5 times to 12 times while maintaining search performance.

Keywords

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Fig. 1. Example R-tree

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Fig. 2. Entry representations in a TPR-tree

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Fig. 3. Problems caused by VBR comparison

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Fig. 4. Comparison of naive bottom-up algorithm and proposed update algorithm

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Fig. 5. Update performance for varying update frequency and number of objects

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Fig. 6. Updated ratio for each tree type

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Fig. 7. Underflow ratio for each tree type

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Fig. 8. Search performance for varying update frequency, number of objects and search range

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Fig. 9. MBR and overlap size for each tree type

Table 1. TPR-trees for comparison

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Table 2. Simulation parameters

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Algorithm 1. Naive bottom-up update for TPR-tree

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Algorithm 2. Update process proposed in this paper

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