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.
Highlights
Bushfires are known for their incredibly destructive potential
Current bushfire simulators are designed to either work on desktop machines or Graphics Processing Units (GPUs) [7], which cannot be changed, reconfigured or scaled in a timely manner according to the requirements of an end user
Estimations are calculated on the basis of the instance region, the instance flavour
Summary
Bushfires are known for their incredibly destructive potential. With the current increase in urbanization and changing climate conditions, these fires are increasingly becoming a major threat.To minimize the impact of these fires, it is important to understand the dynamics of bushfires and to be able to predict their propagation. Despite there being so many simulation modeling tools available, it is still a computationally challenging task, as bushfires are a very complex phenomenon—involving interactions with several factors, including vegetation, climatic condition and altitude at very broad temporal and spatial scales. These include considerations that range from chemical reactions at the molecular scale, through the micro-scale physics of pyrolysis, to the macro-scale turbulent interactions with the surrounding atmosphere [5,6].
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