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ABSTRACT: The highly efficient and stable collaborative computation platform for geospatial information can be constructed on the basis
of Grid computing technology, combined with Peer-to-Peer (P2P) computing technology and geospatial database technology. This
paper proposed the architecture and key technologies of the Grid GIS (Geographic Information System) incorporated with P2P
structure, and correspondingly a Grid GIS prototype named Nebula was designed and then implemented. Nebula is a suite of middleware
for geospatial Grid computing, which could be deployed onto various service nodes in network. Based on Grid protocols and
infrastructure, Nebula provides invocation interfaces to users in form of Grid services. By using P2P message based communication
mechanism, complex geospatial computation tasks could be accomplished by Nebula in a collaborative way. This paper introduced
Nebula’s architecture and key modules, and according to experimental data, we discussed the Grid GIS’s advantages, application
scenarios and future directions.
Science in China Series E Technological Sciences 04/2012; 51:102-113. · 1.02 Impact Factor
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International Journal of Geographical Information Science. 01/2011; 25:1117-1145.
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2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011, Vancouver, BC, Canada, July 24-29, 2011; 01/2011
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ABSTRACT: DGIP (Distributed Geographic Information Processing) has become a new tendency of GIS (Geographic Information System) recently. DGIP focuses on how to organize and process a series of geographic resources in distributed computing environment and now existing research is mainly carried out from a global point of view. But it is noticeable that each computing node in distributed computing environment will carry a heavy load with growth of data quantity. So this paper concentrates on how to make each computing node fulfill the subtask more quickly to achieve efficient local acceleration. The paper designs a prototype for distributed remote sensing image processing and achieves local acceleration in each computing node with CUDA (Compute Unified Device Architecture). Firstly, the paper introduces the distributed procedure of the prototype and overviews the architecture and programming model of CUDA. Then the paper takes Mean Filter as an example to design and implement the parallel program with CUDA to accelerate the procedure of remote sensing image processing in each node. To evaluate the performance of the local acceleration, the paper carries out a group of comparative tests between the parallel implementation with CUDA and the conventional implementation. The results demonstrate that the local acceleration with CUDA runs more than 20 times faster than conventional process.
Geoinformatics, 2010 18th International Conference on; 07/2010
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ABSTRACT: The Barn project, a spatial data grid prototype under development currently, provides a grid environment for applications of the nationwide geological survey data. Within Barn, in order to reduce data access latency, avoid a single point of failure, and increase the performance and load-balance of the system, we have designed and implemented a set of replica management services. These services, based on WSRF, offer users a convenient way to partition a large logical layer into multiple fragments, enable replication and management of the tiled spatial data, maintenance of replica consistency, catalog consistency and replica synchronization. This paper describes the framework and design of the replica management and evaluate its performance under the context of the Barn project.
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on; 01/2010
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The 18th International Conference on Geoinformatics: GIScience in Change, Geoinformatics 2010, Peking University, Beijing, China, June, 18-20, 2010; 01/2010
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The 18th International Conference on Geoinformatics: GIScience in Change, Geoinformatics 2010, Peking University, Beijing, China, June, 18-20, 2010; 01/2010
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ABSTRACT: The Barn project, a spatial data grid prototype under development currently, provides a grid environment for applications of the nationwide geological survey data. In order to save and manage raster data in the grid environment, we should take many factors into account, such as massive data, multisource, index rebuilding, pyramid re-creating and etc. All these factors influence the logical and physical storage framework of the raster data. We discuss the Hilbert index to help re-create the index dynamically on partitioned tiles. Also, we present the global raster catalog framework in the grid environment.
Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on; 10/2009
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ABSTRACT: Rapid evolutions in Earth Information, network, visualization and virtual world technologies create opportunities for a new era of information systems and Internet applications. These technologies' advances enable new capabilities for creation of dynamic contents, visualization of multiple and higher dimensions, distributed collaboration and cognition, immersive participant and interaction, and high level understanding of situations, activities and events. The present paper explores these technology advances, describes the concept of immersive virtual university and community of virtual education, identifies research issues that need to be addressed to effectively utilize these new technologies and concepts, and develops an approach exploring these enhancements to multiuser immersive virtual environment applications and conducts experiments of constructing Second Campus of Peking University based on Open Simulator and Second Life Viewer.
Geoinformatics, 2009 17th International Conference on; 09/2009
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Eighth International Conference on Grid and Cooperative Computing, GCC 2009, Lanzhou, Gansu, China, August 27-29, 2009; 01/2009
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ABSTRACT: Spatial data grid allows for solving larger problems and executing applications that traditional Web GIS (Geographic Information System) can not handle efficiently. In spatial data grid, all functions of GIS are encapsulated as stateful Web services. The purpose of this paper is to design and implement a new mechanism to organize miscellaneous vector map services, built on GT4 (Globus Toolkit 4), and based on WSRF (Web services resource framework). In this paper, we demonstrate the general procedure to build a grid vector map service (spatial query, buffer analysis, overlay analysis, etc) based on GT4. We design and implement two kinds of vector map services: domain service and node service, which can be chosen by users after they log in the grid portal correctly. Finally, we present some experimental results and draw some conclusions. The new mechanism allows more flexible usage of available resources in the Grid and is expected to decrease the efforts needed to configure and maintain nodes in the Grid, and it buffers some frequently accessed information in resources, in this way, access times of GIS server will be sharply decreased and query time will be reduced.
01/2009;
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ABSTRACT: The research on the sharing and interoperation of geospatial information is always a hotspot in GIS field. Many methods have been proposed such as data format transform, data direct access, Web GIS and data interoperation. These technologies have made great progresses in the sharing and interoperability of geospatial information. But there are many unconquerable problems such as the process of the distributed massive spatial data, providing integrated and transparent services, capability of geocomputing and migration of geospatial information services for users. In this paper, we combine grid and OGC web service to research how to realize the sharing and interoperation of geospatial information. We introduce the grid technology and OGC web service specifications. Then we design the architecture of integrated Grid and OGC. At last based on grid middleware Gloubs Toolkit 4 and Java technology, we develop and deploy Grid map services which encapsulate OGC Web Map Service.
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International; 08/2008
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IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2008, July 8-11, 2008, Boston, Massachusetts, USA, Proceedings; 01/2008
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IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2008, July 8-11, 2008, Boston, Massachusetts, USA, Proceedings; 01/2008
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ABSTRACT: Spatial Information Grid is an ideal infrastructure to handle the data-intensive and computing-intensive geo-spatial processing. In order that each agency could ad hoc connect to this computing environment and make autonomous decision, we build a Geospatial Data Grid in peer-to-peer way. The query processor module in each peer can decompose the user's query into sub-queries that executed in different nodes. One problem in the parallel spatial join query optimization is how to determine an appropriate node group to disseminate the sub-queries. Especially, if there is more than one node sharing the same area of interest, there is a dilemma: on the one hand, the task scheduler tends to decompose this query into sub-queries and disseminate them to as many as possible nodes so that they could process the user's query in parallel; on the other hand, recruiting too many nodes will also bring in overhead in repetitive computing, redundant data transmission, and the result merging. Based on the study of trade-off between increasing parallelism and reducing redundancy using the Utility Theory in economics, we put forward a fast node selection algorithm for the parallel spatial join query dissemination. The test in our system shows this strategy could balance the above two conflict demands and is appropriate for use in Data Grid.
Grid and Cooperative Computing, 2007. GCC 2007. Sixth International Conference on; 09/2007
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ABSTRACT: In order to integrate heterogeneous spatial data sources to enhance spatial data share and interoperation, the P2P computing technologies were introduced to implement a prototype system of cooperative spatial database named NEBULA. By dynamic and self-cooperative features derived from P2P computing, this cooperative spatial database prototype made individual spatial databases united to achieve users' global spatial queries. Many P2P middleware technologies such as global resource directory, global query decomposing and sub-queries execution management were introduced to achieve the P2P spatial database system. Benefited from the P2P cooperative system, users can submit spatial queries in a global view regardless of where the spatial data store and how the spatial processing occurs. Lastly, a sample was also provided to show the entire workflow of the P2P spatial database prototype.
Grid and Cooperative Computing, 2007. GCC 2007. Sixth International Conference on; 09/2007
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ABSTRACT: Data Grid, which consists of several geographically distributed datacenters linked by high speed network, is an ideal platform for the data-intensive and computing-intensive scientific computing. Besides improving the computing performance and the data processing capabilities, the replication service among the nodes improves failure resistance and increase system availability. Replica selection is one important problem in replication optimization, because Grid application may need to retrieve data from many distributed nodes and do computation on their own local machine in parallel. In this paper, we focus on how to determine an appropriate set of replicas that at least cover the data, and farthest utilize the system parallel computing capacity. As we believe there is a trade-off between increasing parallelism and reducing redundancy as more replicas involved in computation, we put forward a fast replica selection algorithm inspired by the Utility Theory in economics to balance the two conflict demands.
Computer Software and Applications Conference, 2007. COMPSAC 2007. 31st Annual International; 08/2007
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IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2007, July 23-28, 2007, Barcelona, Spain, Proceedings; 01/2007
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Computational Science - ICCS 2007, 7th International Conference, Beijing, China, May 27 - 30, 2007, Proceedings, Part III; 01/2007
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ABSTRACT: Most GIS (Geographic Information System) applications tend to have heterogeneous and autonomous geospatial information resources, and the availability of these local resources is unpredictable and dynamic under a distributed computing environment. In order to make use of these local resources together to solve larger geospatial information processing problems that are related to an overall situation, in this paper, with the support of peer-to-peer computing technologies, we propose a geospatial data distributed computing mechanism that involves loosely coupled geospatial resource directories and a term named as Equivalent Distributed Program of global geospatial queries to solve geospatial distributed computing problems under heterogeneous GIS environments. First, a geospatial query process schema for distributed computing as well as a method for equivalent transformation from a global geospatial query to distributed local queries at SQL (Structured Query Language) level to solve the coordinating problem among heterogeneous resources are presented. Second, peer-to-peer technologies are used to maintain a loosely coupled network environment that consists of autonomous geospatial information resources, thus to achieve decentralized and consistent synchronization among global geospatial resource directories, and to carry out distributed transaction management of local queries. Finally, based on the developed prototype system, example applications of simple and complex geospatial data distributed queries are presented to illustrate the procedure of global geospatial information processing.
Computers & Geosciences.
