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Cloud computing based bushfire prediction for cyber-physical emergency applications


Garg, S and Aryal, J and Wang, H and Shah, T and Kecskemeti, G and Ranjan, R, Cloud computing based bushfire prediction for cyber-physical emergency applications, Future Generation Computer Systems pp. 1-10. ISSN 0167-739X (2017) [Refereed Article]

Copyright Statement

Copyright 2016 Elsevier Ltd.

DOI: doi:10.1016/j.future.2017.02.009


In the past few years, several studies proposed to reduce the impact of bushfires by mapping their occurrences and spread. Most of these prediction/mapping tools and models were designed to run either on a single local machine or a High performance cluster, neither of which can scale with usersí needs. The process of installing these tools and models their configuration can itself be a tedious and time consuming process. Thus making them, not suitable for time constraint cyber-physical emergency systems. In this research, to improve the efficiency of the fire prediction process and make this service available to several users in a scalable and cost-effective manner, we propose a scalable Cloud based bushfire prediction framework, which allows forecasting of the probability of fire occurrences in different regions of interest. The framework automates the process of selecting particular bushfire models for specific regions and scheduling usersí requests within their specified deadlines. The evaluation results show that our Cloud based bushfire prediction system can scale resources and meet user requirements.

Item Details

Item Type:Refereed Article
Keywords:cloud computing, bushfire, scheduling, resource management
Research Division:Information and Computing Sciences
Research Group:Distributed Computing
Research Field:Distributed and Grid Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
Author:Garg, S (Dr Saurabh Garg)
Author:Aryal, J (Dr Jagannath Aryal)
Author:Wang, H (Mr Hao Wang)
ID Code:115514
Year Published:2017
Deposited By:Computing and Information Systems
Deposited On:2017-03-29
Last Modified:2017-05-15

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