The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Ali Mansourian

Ali Mansourian

Professor

Ali Mansourian

Multi-Agent Planning for Automatic Geospatial Web Service Composition in Geoportals

Author

  • Mahdi Farnaghi
  • Ali Mansourian

Summary, in English

Automatic composition of geospatial web services increases the possibility of taking full advantage of spatial data and processing capabilities that have been published over the internet. In this paper, a multi-agent artificial intelligence (AI) planning solution was proposed, which works within the geoportal architecture and enables the geoportal to compose semantically annotated Open Geospatial Consortium (OGC) Web Services based on users’ requirements. In this solution, the registered Catalogue Service for Web (CSW) services in the geoportal along with a composition coordinator component interact together to synthesize Open Geospatial Consortium Web Services (OWSs) and generate the composition workflow. A prototype geoportal was developed, a case study of evacuation sheltering was implemented to illustrate the functionality of the algorithm, and a simulation environment, including one hundred simulated OWSs and five CSW services, was used to test the performance of the solution in a more complex circumstance. The prototype geoportal was able to generate the composite web service, based on the requested goals of the user. Additionally, in the simulation environment, while the execution time of the composition with two CSW service nodes was 20 s, the addition of new CSW nodes reduced the composition time exponentially, so that with five CSW nodes the execution time reduced to 0.3 s. Results showed that due to the utilization of the computational power of CSW services, the solution was fast, horizontally scalable, and less vulnerable to the exponential growth in the search space of the AI planning problem.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • MECW: The Middle East in the Contemporary World
  • Middle Eastern Studies

Publishing year

2018-10-12

Language

English

Publication/Series

ISPRS International Journal of Geo-Information

Volume

7

Issue

10

Document type

Journal article

Publisher

MDPI AG

Topic

  • Physical Geography
  • Geosciences, Multidisciplinary

Keywords

  • multi-agent artificial intelligence (AI) planning
  • automatic web service composition
  • OGC web service
  • semantic web
  • geoportal
  • Artificial Intelligence (AI)

Status

Published

ISBN/ISSN/Other

  • ISSN: 2220-9964