Abstract
Current web-based GIS or RS applications generally rely on centralized structure, which has inherent drawbacks such as single points of failure, network congestion, and data inconsistency, etc. The inherent disadvantages of traditional GISs need to be solved for new applications on Internet or Web. Decentralized orchestration offers performance improvements in terms of increased throughput and scalability and lower response time. This paper investigates build time and runtime issues related to decentralized orchestration of composite geospatial processing services based on OGC WPS standard specification. A case study of dust storm detection was demonstrated to evaluate the proposed method and the experimental results indicate that the method proposed in this study is effective for its ability to produce the high quality solution at a low cost of communications for geospatial processing service composition problem.
Highlights
The evolutions in computing science and Web technology offer the geoscience community with continuously expanding resources for geospatial data collection and processing
Web service composition refers to the mechanisms that promote the collaboration and interoperability of individual web service to create software applications with a functionality that is the result of integration of the individual functionalities provided by each participating service, which has the potential to reduce development time and effort for new applications (Rao and Su, 2004)
The geospatial processes can generate a lot of data that is irrelevant to the composite service, yet this data will be transferred to the coordinator node where it is discarded, thereby putting an unnecessary load on the network
Summary
The evolutions in computing science and Web technology offer the geoscience community with continuously expanding resources for geospatial data collection and processing. The traditional approach for composing web services is mainly constructed in a centralized manner, whereby an orchestrator component running on a single server is responsible for the execution of all process instances, while all relevant data are maintained at a single location. These centralized web service composition approaches suffer from performance bottleneck (high communication burden and high computational load) both the geospatial sciences and the cloud computing environment are spatiotemporal intensive. The double-blind peer-review was conducted on the basis of the full paper
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