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Sustainability 2015, 7(10), 14245-14258; doi:10.3390/su71014245

Building an Elastic Parallel OGC Web Processing Service on a Cloud-Based Cluster: A Case Study of Remote Sensing Data Processing Service

1
Spatial Information and Digital Technology Department, International School of Software, Wuhan University, 37, Luoyu Road, Wuhan 430079, China
2
Center for Spatial Information and Science Systems, George Mason University, 4087 University Dr, Fairfax, VA 22030, USA
3
China Electric Power Research Institution, 143, Luoyu Road, Wuhan 430079, China
4
International School of Software, Wuhan University, 37, Luoyu Road, Wuhan 430079, China
5
Department of Geography, Kent State University, Kent, OH 44242, USA
6
Yunnan Provincial Geomatics Center, 404, Huanchengxi Road, Kunming 650034, China
*
Author to whom correspondence should be addressed.
Academic Editors: Marc A. Rosen and Yichun Xie
Received: 3 September 2015 / Revised: 4 October 2015 / Accepted: 14 October 2015 / Published: 21 October 2015
(This article belongs to the Special Issue Geo-Informatics in Resource Management & Sustainable Ecosystem)
View Full-Text   |   Download PDF [1517 KB, uploaded 21 October 2015]   |  

Abstract

Since the Open Geospatial Consortium (OGC) proposed the geospatial Web Processing Service (WPS), standard OGC Web Service (OWS)-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the dominant challenge for OWSs. This paper presents the construction of an elastic parallel OGC WPS service on a cloud-based cluster and the designs of a high-performance, cloud-based WPS service architecture, the scalability scheme of the cloud, and the algorithm of the elastic parallel geoprocessing. Experiments of the remote sensing data processing service demonstrate that our proposed method can provide a higher-performance WPS service that uses less computing resources. Our proposed method can also help institutions reduce hardware costs, raise the rate of hardware usage, and conserve energy, which is important in building green and sustainable geospatial services or applications. View Full-Text
Keywords: Open Geospatial Consortium (OGC); geospatial service; cloud computing; parallel computing Open Geospatial Consortium (OGC); geospatial service; cloud computing; parallel computing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Tan, X.; Di, L.; Deng, M.; Fu, J.; Shao, G.; Gao, M.; Sun, Z.; Ye, X.; Sha, Z.; Jin, B. Building an Elastic Parallel OGC Web Processing Service on a Cloud-Based Cluster: A Case Study of Remote Sensing Data Processing Service. Sustainability 2015, 7, 14245-14258.

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