The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dengan peningkatan peranti IoT, platform IoT berasaskan P2P telah menarik perhatian kerana keupayaan mereka membina dan mengekalkan rangkaian mereka secara autonomi dengan cara terpencar. Khususnya, Skip Graph, yang mempunyai kos pembinaan semula rangkaian yang rendah dan membolehkan carian julat, sesuai untuk platform. Walau bagaimanapun, apabila data yang diperhatikan pada titik yang rapat secara geografi mempunyai nilai yang sama (iaitu apabila data mempunyai autokorelasi spatial yang kuat), jenis Graf Langkau yang sedia ada merendahkan prestasi cariannya. Dalam kertas kerja ini, kami mencadangkan kaedah pemindahan pertanyaan yang membolehkan carian cekap walaupun untuk data autokorelasi spatial dengan menggunakan dua jenis Graf Langkau secara adaptif bergantung pada jarak kunci ke kunci sasaran. Keputusan simulasi menunjukkan bahawa kaedah yang dicadangkan boleh mengurangkan jarak pemindahan pertanyaan berbanding kaedah sedia ada walaupun untuk data autokorelasi spatial.
Yuuki FUJITA
Wakayama University
Akihiro FUJIMOTO
Wakayama University
Hideki TODE
Osaka Prefecture University
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Salinan
Yuuki FUJITA, Akihiro FUJIMOTO, Hideki TODE, "Query Transfer Method Using Different Two Skip Graphs for Searching Spatially-Autocorrelated Data" in IEICE TRANSACTIONS on Communications,
vol. E105-B, no. 2, pp. 205-214, February 2022, doi: 10.1587/transcom.2021CEP0010.
Abstract: 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 adaptively 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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2021CEP0010/_p
Salinan
@ARTICLE{e105-b_2_205,
author={Yuuki FUJITA, Akihiro FUJIMOTO, Hideki TODE, },
journal={IEICE TRANSACTIONS on Communications},
title={Query Transfer Method Using Different Two Skip Graphs for Searching Spatially-Autocorrelated Data},
year={2022},
volume={E105-B},
number={2},
pages={205-214},
abstract={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 adaptively 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.},
keywords={},
doi={10.1587/transcom.2021CEP0010},
ISSN={1745-1345},
month={February},}
Salinan
TY - JOUR
TI - Query Transfer Method Using Different Two Skip Graphs for Searching Spatially-Autocorrelated Data
T2 - IEICE TRANSACTIONS on Communications
SP - 205
EP - 214
AU - Yuuki FUJITA
AU - Akihiro FUJIMOTO
AU - Hideki TODE
PY - 2022
DO - 10.1587/transcom.2021CEP0010
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E105-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2022
AB - 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 adaptively 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.
ER -