A Study on Query Transfer Using Different Two Skip Graphs for Searching Spatially-Autocorrelated Data

• Yuuki Fujita

  Wakayama University

• Akihiro Fujimoto

  Wakayama University

• Hideki Tode

  Osaka Prefecture University

抄録

With the increase of IoT devices, P2P-based IoT platforms have been attracting attention because of their capabilities of building and maintaining their networks autonomously in a decentralized way. In particular, Skip Graph, which has a low network rebuilding cost and allows range search, is suitable for the platform. However, when data observed at geographically close points have similar values (i.e. when data have strong spatial autocorrelation), existing types of Skip Graph degrade their search performances. In this paper, we propose a query transfer method that enables efficient search even for spatially autocorrelated data by using two-types of Skip Graph depending on the key-distance to the target key. Simulation results demonstrate that the proposed method can reduce the query transfer distance compared to the existing method even for spatially autocorrelated data.

収録刊行物

• IEICE Proceeding Series

  IEICE Proceeding Series 63 E2-5-, 2020-12-02

  The Institute of Electronics, Information and Communication Engineers

キーワード

• Skip Graph
• Spatial Autocorrelation
• Geographic proximity
• P2P

詳細情報

• CRID: 1390287673853899008
• NII論文ID: 230000012391
• DOI: 10.34385/proc.63.e2-5
• ISSN: 21885079
• 本文言語コード: en
• データソース種別:
  • JaLC
  • CiNii Articles
  • KAKEN
• 抄録ライセンスフラグ: 使用不可