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SparkCloud: a cloud-based elastic bushfire simulation service
Citation
Garg, S and Forbes-Smith, N and Hilton, J and Prakash, M, SparkCloud: a cloud-based elastic bushfire simulation service, Remote Sensing, 10, (1) Article 74. ISSN 2072-4292 (2018) [Refereed Article]
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Copyright Statement
© 2018 The Authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
Abstract
The accurate modeling of bushfires is not only complex and contextual but also a computationally intensive task. Ensemble predictions, involving several thousands to millions of simulations, can be required to capture and quantify the uncertain nature of bushfires. Moreover, users’ requirement and configuration may change in different situations requiring either more computational resources or modeling to be completed with a stricter time constraint. For example, during emergency situations, the user may need to make time-critical decisions that require the execution of bushfire-spread models within a deadline. Currently, most operational tools are not flexible and scalable enough to consider different users’ time requirements. In this paper, we propose the SparkCloud service, which integrates features of user-defined customizable configuration for bushfire simulations and scalability/elasticity features of the cloud to handle computation requirements. The proposed cloud service utilizes Data61’s Spark, which is a significantly flexible and scalable software system for bushfire-spread prediction and has been used in practical scenarios. The effectiveness of the SparkCloud service is demonstrated using real cases of bushfires and on real cloud computing infrastructure.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | bush fire, cloud computing, ensemble predictions, deadline-based resource allocation |
| Research Division: | Information and Computing Sciences |
| Research Group: | Distributed computing and systems software |
| Research Field: | Distributed systems and algorithms |
| Objective Division: | Information and Communication Services |
| Objective Group: | Information systems, technologies and services |
| Objective Field: | Information systems, technologies and services not elsewhere classified |
| UTAS Author: | Garg, S (Dr Saurabh Garg) |
| UTAS Author: | Forbes-Smith, N (Mr Nicholas Forbes-Smith) |
| ID Code: | 125155 |
| Year Published: | 2018 |
| Web of Science® Times Cited: | 5 |
| Deposited By: | Information and Communication Technology |
| Deposited On: | 2018-04-03 |
| Last Modified: | 2019-02-25 |
| Downloads: | 71 View Download Statistics |
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