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

Farnaghi, Mahdi LU and Mansourian, Ali LU (2018) In ISPRS International Journal of Geo-Information 7(10).
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
multi-agent artificial intelligence (AI) planning, automatic web service composition, OGC web service, semantic web, geoportal
in
ISPRS International Journal of Geo-Information
volume
7
issue
10
article number
404
pages
20 pages
publisher
MDPI AG
external identifiers
  • scopus:85056640729
ISSN
2220-9964
DOI
10.3390/ijgi7100404
language
English
LU publication?
yes
id
8c520ad4-9c60-4d36-861c-f34f307c0b4b
date added to LUP
2018-10-14 16:12:20
date last changed
2021-10-06 04:06:13
@article{8c520ad4-9c60-4d36-861c-f34f307c0b4b,
  abstract     = {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.},
  author       = {Farnaghi, Mahdi and Mansourian, Ali},
  issn         = {2220-9964},
  language     = {eng},
  month        = {10},
  number       = {10},
  publisher    = {MDPI AG},
  series       = {ISPRS International Journal of Geo-Information},
  title        = {Multi-Agent Planning for Automatic Geospatial Web Service Composition in Geoportals},
  url          = {http://dx.doi.org/10.3390/ijgi7100404},
  doi          = {10.3390/ijgi7100404},
  volume       = {7},
  year         = {2018},
}