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Dynamic Resource Scheduling in Emergency Environment

Yuankun Yan1,*, Yan Kong1, Zhangjie Fu1,2

1 School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing, China.
2 Jiangsu Engineering Center of Network Monitoring, School of Computer and Software, Nanjing, China.
* Corresponding Author: Yuankun Yan. Email: yanyuankun@163.com.

Journal of Information Hiding and Privacy Protection 2019, 1(3), 143-155. https://doi.org/10.32604/jihpp.2019.07772

Abstract

Nowadays, emergency accidents could happen at any time. The accidents occur unpredictably and the accidents requirements are diversely. The accidents happen in a dynamic environment and the resource should be cooperative to solve the accidents. Most methods are focusing on minimizing the casualties and property losses in a static environment. However, they are lack in considering the dynamic and unpredictable event handling. In this paper, we propose a representative environmental model in representation of emergency and dynamic resource allocation model, and an adaptive mathematical model based on Genetic Algorithm (GA) to generate an optimal set of solution domain. The experimental results show that the proposed algorithm can get a set of better candidate solutions.

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Cite This Article

APA Style
Yan, Y., Kong, Y., , Z.F. (2019). Dynamic resource scheduling in emergency environment. Journal of Information Hiding and Privacy Protection, 1(3), 143-155. https://doi.org/10.32604/jihpp.2019.07772
Vancouver Style
Yan Y, Kong Y, ZF. Dynamic resource scheduling in emergency environment. J Inf Hiding Privacy Protection . 2019;1(3):143-155 https://doi.org/10.32604/jihpp.2019.07772
IEEE Style
Y. Yan, Y. Kong, and Z.F. "Dynamic Resource Scheduling in Emergency Environment," J. Inf. Hiding Privacy Protection , vol. 1, no. 3, pp. 143-155. 2019. https://doi.org/10.32604/jihpp.2019.07772



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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