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Multi-Resolution Data Structures for Spherically Mapped Point Data

機(jī)譯：球形映射點(diǎn)數(shù)據(jù)的多分辨率數(shù)據(jù)結(jié)構(gòu)

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摘要

Data describing entities or objects whose locations may be treated as points on the surface of a sphere are said to be spherically mapped. A number of data structures specifically designed to store and access spherically mapped data have been developed. One of them, Hierarchical Equal Area iso-Latitude Pixelization (HEALPix), has been successfully used for numerous applications, notably including organizing and analyzing cosmic microwave background data. However, for applications involving relatively sparse spherically mapped point datasets, HEALPix has some drawbacks, including inefficient memory requirements due to fixed resolution, overwriting of data for closely proximate points, and return of spurious points in response to certain queries.;A multi-resolution variant of the HEALPix data structure optimized for point data was developed to address these issues. The new data structure is multi-resolution in that different portions of the sphere may be subdivided at different levels of resolution in the same data structure, depending on the data to be stored. It combines the best aspects of HEALPix with the advantages of multi-resolution, including reduced memory requirements, improved query efficiency, and flexible handling of proximate points. The new Multi-resolution HEALPix (MRH) data structure uses multiple quadtrees and the Morton cell addressing scheme.;An implementation of the MRH data structure was tested using four sets of spherically mapped point data from different scientific applications (warhead fragmentation trajectories, weather station locations, redshifted galaxy locations, and synthetic locations). A large set of randomly generated range queries of four different types (disc, polygon, latitude strip, and neighbor) was applied to each data structure for each dataset. MRH used from two to four orders of magnitude less memory than HEALPix to store the same data, and on average MRH queries executed 72% faster.;Additional effort to develop a three dimensional variant of MRH was explored. The new data structure, Multi-MRH, adds an additional degree of freedom (temporal or spatial) into an entirely new data and applications. In Multi-MRH, multiple instances of MRH are utilized to store either temporal, same data point locations at different times, or spatial, data points with spherical coordinates including radius, spherical data.;The Multi-MRH data structure consists of a sorted list of MRH maps. An implementation of the Multi-MRH data structure was tested using three sets of spherically mapped point data from different scientific applications (synthetic locations, warhead fragmentation trajectories, and NEXRAD wind velocity data). A large set of randomly generated range queries of four different types (cone, prism, band, and ray) was applied to each data structure for each data set. The average Multi-MRH query execution time was less than 7% greater than the average MRH query execution time.
機(jī)譯：可以將描述其位置可以視為球體表面上的點(diǎn)的實(shí)體或?qū)ο蟮臄?shù)據(jù)稱為球形映射。已經(jīng)開(kāi)發(fā)出許多專門(mén)設(shè)計(jì)用于存儲(chǔ)和訪問(wèn)球形映射數(shù)據(jù)的數(shù)據(jù)結(jié)構(gòu)。其中之一就是等距分層等高像素像素化（HEALPix），已成功用于眾多應(yīng)用，尤其是組織和分析宇宙微波背景數(shù)據(jù)。但是，對(duì)于涉及相對(duì)稀疏的球形映射點(diǎn)數(shù)據(jù)集的應(yīng)用程序，HEALPix有一些缺點(diǎn)，包括由于固定分辨率而導(dǎo)致的內(nèi)存需求低下，覆蓋緊鄰點(diǎn)的數(shù)據(jù)以及響應(yīng)某些查詢而返回虛假點(diǎn);多分辨率針對(duì)這些問(wèn)題開(kāi)發(fā)了針對(duì)點(diǎn)數(shù)據(jù)優(yōu)化的HEALPix數(shù)據(jù)結(jié)構(gòu)的變體。新的數(shù)據(jù)結(jié)構(gòu)是多分辨率的，其中根據(jù)要存儲(chǔ)的數(shù)據(jù)，可以在同一數(shù)據(jù)結(jié)構(gòu)中以不同的分辨率級(jí)別細(xì)分球體的不同部分。它結(jié)合了HEALPix的最佳方面和多分辨率的優(yōu)點(diǎn)，包括減少了內(nèi)存需求，提高了查詢效率以及靈活地處理了附近的點(diǎn)。新的多分辨率HEALPix（MRH）數(shù)據(jù)結(jié)構(gòu)使用多個(gè)四叉樹(shù)和Morton單元尋址方案。; MRH數(shù)據(jù)結(jié)構(gòu)的實(shí)現(xiàn)是使用來(lái)自不同科學(xué)應(yīng)用（彈頭破碎軌跡，氣象站的四組球形映射點(diǎn)數(shù)據(jù)）進(jìn)行測(cè)試的位置，紅移星系位置和合成位置）。大量隨機(jī)生成的四種不同類型（圓盤(pán)，多邊形，緯度帶和鄰域）的范圍查詢應(yīng)用于每個(gè)數(shù)據(jù)集的每個(gè)數(shù)據(jù)結(jié)構(gòu)。 MRH使用比HEALPix少2到4個(gè)數(shù)量級(jí)的內(nèi)存來(lái)存儲(chǔ)相同的數(shù)據(jù)，平均MRH查詢執(zhí)行速度提高了72％。；探索了開(kāi)發(fā)MRH的三維變體的其他工作。新的數(shù)據(jù)結(jié)構(gòu)Multi-MRH為全新的數(shù)據(jù)和應(yīng)用程序增加了額外的自由度（時(shí)間或空間）。在Multi-MRH中，利用MRH的多個(gè)實(shí)例來(lái)存儲(chǔ)不同時(shí)間的時(shí)間相同數(shù)據(jù)點(diǎn)位置，或存儲(chǔ)具有球形坐標(biāo)（包括半徑，球形數(shù)據(jù)）的空間數(shù)據(jù)點(diǎn); Multi-MRH數(shù)據(jù)結(jié)構(gòu)由排序列表組成MRH地圖。使用來(lái)自不同科學(xué)應(yīng)用的三組球形映射點(diǎn)數(shù)據(jù)（合成位置，戰(zhàn)斗部碎裂軌跡和NEXRAD風(fēng)速數(shù)據(jù)）測(cè)試了Multi-MRH數(shù)據(jù)結(jié)構(gòu)的實(shí)現(xiàn)。將大量隨機(jī)生成的四種不同類型（圓錐，棱鏡，波段和射線）的范圍查詢應(yīng)用于每個(gè)數(shù)據(jù)集的每個(gè)數(shù)據(jù)結(jié)構(gòu)。平均多MRH查詢執(zhí)行時(shí)間比平均MRH查詢執(zhí)行時(shí)間少7％。

著錄項(xiàng)

  • 作者

    Youngren, Robert William.;

  • 作者單位

    The University of Alabama in Huntsville.;

  • 授予單位 The University of Alabama in Huntsville.;
  • 學(xué)科 Computer science.
  • 學(xué)位 Ph.D.
  • 年度 2017
  • 頁(yè)碼 315 p.
  • 總頁(yè)數(shù) 315
  • 原文格式 PDF
  • 正文語(yǔ)種 eng
  • 中圖分類 TS97-4;
  • 關(guān)鍵詞

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