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An efficient framework for ensemble of natural disaster simulations as a service


K C, U and Garg, S and Hilton, J, An efficient framework for ensemble of natural disaster simulations as a service, Geoscience Frontiers, 11, (5) pp. 1859-1873. ISSN 1674-9871 (2020) [Refereed Article]

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Copyright Statement

2020 China University of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V. This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license (

DOI: doi:10.1016/j.gsf.2020.02.002


Calculations of risk from natural disasters may require ensembles of hundreds of thousands of simulations to accurately quantify the complex relationships between the outcome of a disaster and its contributing factors. Such large ensembles cannot typically be run on a single computer due to the limited computational resources available. Cloud Computing offers an attractive alternative, with an almost unlimited capacity for computation, storage, and network bandwidth. However, there are no clear mechanisms that define how to implement these complex natural disaster ensembles on the Cloud with minimal time and resources. As such, this paper proposes a system framework with two phases of cost optimization to run the ensembles as a service over Cloud. The cost is minimized through efficient distribution of the simulations among the cost-efficient instances and intelligent choice of the instances based on pricing models. We validate the proposed framework using real Cloud environment with real wildfire ensemble scenarios under different user requirements. The experimental results give an edge to the proposed system over the bag-of-task type execution on the Clouds with less cost and better flexibility.

Item Details

Item Type:Refereed Article
Keywords:wildfire prediction, ensemble simulation, cloud computing, natural disaster models, bushfire, disaster management
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Cloud computing
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Applied computing
UTAS Author:K C, U (Mr Ujjwal K C)
UTAS Author:Garg, S (Dr Saurabh Garg)
ID Code:142780
Year Published:2020
Web of Science® Times Cited:3
Deposited By:Information and Communication Technology
Deposited On:2021-02-11
Last Modified:2021-04-21
Downloads:14 View Download Statistics

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