Exploring Real‐Time Geoprocessing in Cloud Computing: Navigation Services Case Study
Identifieur interne : 000795 ( Main/Exploration ); précédent : 000794; suivant : 000796Exploring Real‐Time Geoprocessing in Cloud Computing: Navigation Services Case Study
Auteurs : Hassan Ali Karimi [États-Unis] ; Duangduen Roongpiboonsopit [États-Unis] ; Haopeng Wang [États-Unis]Source :
- Transactions in GIS [ 1361-1682 ] ; 2011-10.
Abstract
Today, many real‐time geospatial applications (e.g. navigation and location‐based services) involve data‐ and/or compute‐intensive geoprocessing tasks where performance is of great importance. Cloud computing, a promising platform with a large pool of storage and computing resources, could be a practical solution for hosting vast amounts of data and for real‐time processing. In this article, we explored the feasibility of using Google App Engine (GAE), the cloud computing technology by Google, for a module in navigation services, called Integrated GNSS (iGNSS) QoS prediction. The objective of this module is to predict quality of iGNSS positioning solutions for prospective routes in advance. iGNSS QoS prediction involves the real‐time computation of large Triangulated Irregular Networks (TINs) generated from LiDAR data. We experimented with the Google App Engine (GAE) and stored a large TIN for two geoprocessing operations (proximity and bounding box) required for iGNSS QoS prediction. The experimental results revealed that while cloud computing can potentially be used for development and deployment of data‐ and/or compute‐intensive geospatial applications, current cloud platforms require improvements and special tools for handling real‐time geoprocessing, such as iGNSS QoS prediction, efficiently. The article also provides a set of general guidelines for future development of real‐time geoprocessing in clouds.
Url:
DOI: 10.1111/j.1467-9671.2011.01263.x
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: 000533
- to stream Istex, to step Curation: 000533
- to stream Istex, to step Checkpoint: 000215
- to stream Main, to step Merge: 000797
- to stream Main, to step Curation: 000795
Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Exploring Real‐Time Geoprocessing in Cloud Computing: Navigation Services Case Study</title>
<author><name sortKey="Karimi, Hassan Ali" sort="Karimi, Hassan Ali" uniqKey="Karimi H" first="Hassan Ali" last="Karimi">Hassan Ali Karimi</name>
</author>
<author><name sortKey="Roongpiboonsopit, Duangduen" sort="Roongpiboonsopit, Duangduen" uniqKey="Roongpiboonsopit D" first="Duangduen" last="Roongpiboonsopit">Duangduen Roongpiboonsopit</name>
</author>
<author><name sortKey="Wang, Haopeng" sort="Wang, Haopeng" uniqKey="Wang H" first="Haopeng" last="Wang">Haopeng Wang</name>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">ISTEX</idno>
<idno type="RBID">ISTEX:F71128D1A6D3F95712B17E5216632789293D1DCF</idno>
<date when="2011" year="2011">2011</date>
<idno type="doi">10.1111/j.1467-9671.2011.01263.x</idno>
<idno type="url">https://api.istex.fr/document/F71128D1A6D3F95712B17E5216632789293D1DCF/fulltext/pdf</idno>
<idno type="wicri:Area/Istex/Corpus">000533</idno>
<idno type="wicri:Area/Istex/Curation">000533</idno>
<idno type="wicri:Area/Istex/Checkpoint">000215</idno>
<idno type="wicri:doubleKey">1361-1682:2011:Karimi H:exploring:real:time</idno>
<idno type="wicri:Area/Main/Merge">000797</idno>
<idno type="wicri:Area/Main/Curation">000795</idno>
<idno type="wicri:Area/Main/Exploration">000795</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Exploring Real‐Time Geoprocessing in Cloud Computing: Navigation Services Case Study</title>
<author><name sortKey="Karimi, Hassan Ali" sort="Karimi, Hassan Ali" uniqKey="Karimi H" first="Hassan Ali" last="Karimi">Hassan Ali Karimi</name>
<affiliation wicri:level="4"><country>États-Unis</country>
<placeName><settlement type="city">Pittsburgh</settlement>
<region type="state">Pennsylvanie</region>
</placeName>
<orgName type="university">Université de Pittsburgh</orgName>
</affiliation>
</author>
<author><name sortKey="Roongpiboonsopit, Duangduen" sort="Roongpiboonsopit, Duangduen" uniqKey="Roongpiboonsopit D" first="Duangduen" last="Roongpiboonsopit">Duangduen Roongpiboonsopit</name>
<affiliation wicri:level="4"><country>États-Unis</country>
<placeName><settlement type="city">Pittsburgh</settlement>
<region type="state">Pennsylvanie</region>
</placeName>
<orgName type="university">Université de Pittsburgh</orgName>
</affiliation>
</author>
<author><name sortKey="Wang, Haopeng" sort="Wang, Haopeng" uniqKey="Wang H" first="Haopeng" last="Wang">Haopeng Wang</name>
<affiliation wicri:level="4"><country>États-Unis</country>
<placeName><settlement type="city">Pittsburgh</settlement>
<region type="state">Pennsylvanie</region>
</placeName>
<orgName type="university">Université de Pittsburgh</orgName>
</affiliation>
</author>
</analytic>
<monogr></monogr>
<series><title level="j">Transactions in GIS</title>
<idno type="ISSN">1361-1682</idno>
<idno type="eISSN">1467-9671</idno>
<imprint><publisher>Blackwell Publishing Ltd</publisher>
<pubPlace>Oxford, UK</pubPlace>
<date type="published" when="2011-10">2011-10</date>
<biblScope unit="volume">15</biblScope>
<biblScope unit="issue">5</biblScope>
<biblScope unit="page" from="613">613</biblScope>
<biblScope unit="page" to="633">633</biblScope>
</imprint>
<idno type="ISSN">1361-1682</idno>
</series>
<idno type="istex">F71128D1A6D3F95712B17E5216632789293D1DCF</idno>
<idno type="DOI">10.1111/j.1467-9671.2011.01263.x</idno>
<idno type="ArticleID">TGIS1263</idno>
</biblStruct>
</sourceDesc>
<seriesStmt><idno type="ISSN">1361-1682</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass></textClass>
<langUsage><language ident="en">en</language>
</langUsage>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Today, many real‐time geospatial applications (e.g. navigation and location‐based services) involve data‐ and/or compute‐intensive geoprocessing tasks where performance is of great importance. Cloud computing, a promising platform with a large pool of storage and computing resources, could be a practical solution for hosting vast amounts of data and for real‐time processing. In this article, we explored the feasibility of using Google App Engine (GAE), the cloud computing technology by Google, for a module in navigation services, called Integrated GNSS (iGNSS) QoS prediction. The objective of this module is to predict quality of iGNSS positioning solutions for prospective routes in advance. iGNSS QoS prediction involves the real‐time computation of large Triangulated Irregular Networks (TINs) generated from LiDAR data. We experimented with the Google App Engine (GAE) and stored a large TIN for two geoprocessing operations (proximity and bounding box) required for iGNSS QoS prediction. The experimental results revealed that while cloud computing can potentially be used for development and deployment of data‐ and/or compute‐intensive geospatial applications, current cloud platforms require improvements and special tools for handling real‐time geoprocessing, such as iGNSS QoS prediction, efficiently. The article also provides a set of general guidelines for future development of real‐time geoprocessing in clouds.</div>
</front>
</TEI>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Pennsylvanie</li>
</region>
<settlement><li>Pittsburgh</li>
</settlement>
<orgName><li>Université de Pittsburgh</li>
</orgName>
</list>
<tree><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Karimi, Hassan Ali" sort="Karimi, Hassan Ali" uniqKey="Karimi H" first="Hassan Ali" last="Karimi">Hassan Ali Karimi</name>
</region>
<name sortKey="Roongpiboonsopit, Duangduen" sort="Roongpiboonsopit, Duangduen" uniqKey="Roongpiboonsopit D" first="Duangduen" last="Roongpiboonsopit">Duangduen Roongpiboonsopit</name>
<name sortKey="Wang, Haopeng" sort="Wang, Haopeng" uniqKey="Wang H" first="Haopeng" last="Wang">Haopeng Wang</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/CyberinfraV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000795 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000795 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= CyberinfraV1 |flux= Main |étape= Exploration |type= RBID |clé= ISTEX:F71128D1A6D3F95712B17E5216632789293D1DCF |texte= Exploring Real‐Time Geoprocessing in Cloud Computing: Navigation Services Case Study }}
This area was generated with Dilib version V0.6.25. |