Agent-as-a-service-based geospatial service aggregation in the cloud: A case study of flood response. Tan, X., Di, L., Deng, M., Huang, F., Ye, X., Sha, Z., Sun, Z., Gong, W., Shao, Y., & Huang, C. Environmental Modelling & Software, 84:210–225, October, 2016.
Paper doi abstract bibtex An Agent-as-a-Service (AaaS)-based geospatial service aggregation is proposed to build a more efficient, robust and intelligent geospatial service system in the Cloud for flood emergency response. It involves an AaaS infrastructure, encompassing the mechanisms and algorithms for geospatial Web Processing Service (WPS) generation, geoprocessing and aggregation. The method has the following advantages: 1) it allows separately hosted services and data to work together, avoiding transfers of large volumes of spatial data over the network; 2) it enriches geospatial service resources in the distributed environment by utilizing the agent cloning, migration and service regeneration capabilities of the AaaS, solving issues associated with lack of geospatial services to a certain extent; 3) it enables the migration of services to target nodes to finish a task, strengthening decentralization and enhancing the robustness of geospatial service aggregation; and 4) it helps domain experts and authorities solve interdisciplinary emergency issues using various Agent-generated geospatial services.
@article{tan_agent-as--service-based_2016,
title = {Agent-as-a-service-based geospatial service aggregation in the cloud: {A} case study of flood response},
volume = {84},
issn = {1364-8152},
shorttitle = {Agent-as-a-service-based geospatial service aggregation in the cloud},
url = {http://www.sciencedirect.com/science/article/pii/S1364815216303048},
doi = {10.1016/j.envsoft.2016.07.001},
abstract = {An Agent-as-a-Service (AaaS)-based geospatial service aggregation is proposed to build a more efficient, robust and intelligent geospatial service system in the Cloud for flood emergency response. It involves an AaaS infrastructure, encompassing the mechanisms and algorithms for geospatial Web Processing Service (WPS) generation, geoprocessing and aggregation. The method has the following advantages: 1) it allows separately hosted services and data to work together, avoiding transfers of large volumes of spatial data over the network; 2) it enriches geospatial service resources in the distributed environment by utilizing the agent cloning, migration and service regeneration capabilities of the AaaS, solving issues associated with lack of geospatial services to a certain extent; 3) it enables the migration of services to target nodes to finish a task, strengthening decentralization and enhancing the robustness of geospatial service aggregation; and 4) it helps domain experts and authorities solve interdisciplinary emergency issues using various Agent-generated geospatial services.},
urldate = {2018-06-04},
journal = {Environmental Modelling \& Software},
author = {Tan, Xicheng and Di, Liping and Deng, Meixia and Huang, Fang and Ye, Xinyue and Sha, Zongyao and Sun, Ziheng and Gong, Weishu and Shao, Yuanzheng and Huang, Cheng},
month = oct,
year = {2016},
pages = {210--225},
file = {ScienceDirect Full Text PDF:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/ZTI3KHZD/Tan et al. - 2016 - Agent-as-a-service-based geospatial service aggreg.pdf:application/pdf;ScienceDirect Snapshot:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/2V7WSPJZ/S1364815216303048.html:text/html}
}
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It involves an AaaS infrastructure, encompassing the mechanisms and algorithms for geospatial Web Processing Service (WPS) generation, geoprocessing and aggregation. The method has the following advantages: 1) it allows separately hosted services and data to work together, avoiding transfers of large volumes of spatial data over the network; 2) it enriches geospatial service resources in the distributed environment by utilizing the agent cloning, migration and service regeneration capabilities of the AaaS, solving issues associated with lack of geospatial services to a certain extent; 3) it enables the migration of services to target nodes to finish a task, strengthening decentralization and enhancing the robustness of geospatial service aggregation; and 4) it helps domain experts and authorities solve interdisciplinary emergency issues using various Agent-generated geospatial services.","urldate":"2018-06-04","journal":"Environmental Modelling & Software","author":[{"propositions":[],"lastnames":["Tan"],"firstnames":["Xicheng"],"suffixes":[]},{"propositions":[],"lastnames":["Di"],"firstnames":["Liping"],"suffixes":[]},{"propositions":[],"lastnames":["Deng"],"firstnames":["Meixia"],"suffixes":[]},{"propositions":[],"lastnames":["Huang"],"firstnames":["Fang"],"suffixes":[]},{"propositions":[],"lastnames":["Ye"],"firstnames":["Xinyue"],"suffixes":[]},{"propositions":[],"lastnames":["Sha"],"firstnames":["Zongyao"],"suffixes":[]},{"propositions":[],"lastnames":["Sun"],"firstnames":["Ziheng"],"suffixes":[]},{"propositions":[],"lastnames":["Gong"],"firstnames":["Weishu"],"suffixes":[]},{"propositions":[],"lastnames":["Shao"],"firstnames":["Yuanzheng"],"suffixes":[]},{"propositions":[],"lastnames":["Huang"],"firstnames":["Cheng"],"suffixes":[]}],"month":"October","year":"2016","pages":"210–225","file":"ScienceDirect Full Text PDF:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/ZTI3KHZD/Tan et al. - 2016 - Agent-as-a-service-based geospatial service aggreg.pdf:application/pdf;ScienceDirect Snapshot:/Volumes/mini-disk1/Google Drive/_lib/zotero/storage/2V7WSPJZ/S1364815216303048.html:text/html","bibtex":"@article{tan_agent-as--service-based_2016,\n\ttitle = {Agent-as-a-service-based geospatial service aggregation in the cloud: {A} case study of flood response},\n\tvolume = {84},\n\tissn = {1364-8152},\n\tshorttitle = {Agent-as-a-service-based geospatial service aggregation in the cloud},\n\turl = {http://www.sciencedirect.com/science/article/pii/S1364815216303048},\n\tdoi = {10.1016/j.envsoft.2016.07.001},\n\tabstract = {An Agent-as-a-Service (AaaS)-based geospatial service aggregation is proposed to build a more efficient, robust and intelligent geospatial service system in the Cloud for flood emergency response. 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