A cloud computing approach to on-demand and scalable CyberGIS analytics

Pierre Riteau, Yizhao Gao, Myunghwa Hwang, Yan Liu, Shaowen Wang, Anand Padmanabhan, Kate Keahey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Spatial data analysis has become ubiquitous as geographic information systems (GIS) are widely used to support scientific investigations and decision making in many fields of science, engineering, and humanities (e.g., ecology, emergency management, environmental engineering and sciences, geosciences, and social sciences). Tremendous data and computational capabilities are needed to handle and analyze massive quantities of spatial data that are collected across multiple spatiotemporal scales and used for diverse purposes. CyberGIS has emerged as a new-generation GIS based on advanced cyberinfrastructure to seamlessly integrate such capabilities into scalable geospatial analytics and modeling tools. One of the key challenges and opportunities of CyberGIS research is to build an on-demand service framework that can manage underlying cyberinfrastructure resources dynamically, in order to provide responsive support for interactive online CyberGIS analytics for which users can generate massive service requests in a short amount of time. This paper presents a cloud computing approach to implementing CyberGIS analytics using cloud computing services in the CyberGIS Gateway, a multiuser and collaborative online problem-solving environment. The primary purpose of this research is to address the question of how to achieve on-demand and scalable CyberGIS analytics that provide a stable response time to the user. We do that through integration with the Nimbus Phantom cloud platform. We then investigate how the cloud platform is able to adaptively handle fluctuating requests for analytics while providing a stable response time.

Original languageEnglish (US)
Title of host publicationScienceCloud 2014 - Proceedings of the 2014 ACM International Workshop on Scientific Cloud Computing, Co-located with HPDC 2014
PublisherAssociation for Computing Machinery
Pages17-24
Number of pages8
ISBN (Print)9781450329118
DOIs
StatePublished - Jan 1 2014
Event5th ACM Workshop on Scientific Cloud Computing, ScienceCloud 2014 - Vancouver, BC, Canada
Duration: Jun 23 2014Jun 27 2014

Publication series

NameScienceCloud 2014 - Proceedings of the 2014 ACM International Workshop on Scientific Cloud Computing, Co-located with HPDC 2014

Other

Other5th ACM Workshop on Scientific Cloud Computing, ScienceCloud 2014
CountryCanada
CityVancouver, BC
Period6/23/146/27/14

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Keywords

  • Auto-scaling
  • Cloud computing
  • CyberGIS
  • Geographic information systems (GIS)

ASJC Scopus subject areas

  • Software

Cite this

Riteau, P., Gao, Y., Hwang, M., Liu, Y., Wang, S., Padmanabhan, A., & Keahey, K. (2014). A cloud computing approach to on-demand and scalable CyberGIS analytics. In ScienceCloud 2014 - Proceedings of the 2014 ACM International Workshop on Scientific Cloud Computing, Co-located with HPDC 2014 (pp. 17-24). (ScienceCloud 2014 - Proceedings of the 2014 ACM International Workshop on Scientific Cloud Computing, Co-located with HPDC 2014). Association for Computing Machinery. https://doi.org/10.1145/2608029.2608032