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An evolutionary computation approach for optimizing connectivity in disaster response scenarios

机译:一种在灾难响应场景中优化连接性的进化计算方法

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摘要

This article presents an evolutionary computation approach for increasing connectivity in disaster scenarios. Connectivity is considered to be of critical importance in disaster scenarios due to constrained and mobile conditions. We propose the deployment of a number of auxiliary static nodes whose purpose is to increase the reachability of broadcast emergency packets among the nodes which are participating in the disaster scenario. These nodes represent people and vehicles acting in rescue operations. The main goal is to find the optimum positions for the auxiliary nodes, reinforcing the communications in points where certain lack of connectivity is found. These points will depend on the movements of the rescue teams, which are influenced by tactical reasons. Due to the complexity of the problem and the number of parameters to be considered, a genetic algorithm combined with the network simulator NS-2 is proposed to find the optimum positions of the auxiliary nodes. Specifically, NS-2 is used to model the communication layers and provide the fitness function guiding the genetic search. The proposed approach has been tested using the disaster mobility model included in the motion generator BonnMotion. The simulation results obtained demonstrate the feasibility of the proposed approach and illustrate its applicability in other scenarios where lack of connectivity is evident.
机译:本文提出了一种进化计算方法,用于增加灾难情况下的连接性。由于受到约束和移动条件的限制,连接在灾难情况下被认为至关重要。我们建议部署许多辅助静态节点,其目的是提高参与灾难场景的节点之间广播紧急数据包的可达性。这些节点代表从事救援行动的人员和车辆。主要目标是找到辅助节点的最佳位置,从而在发现某些缺乏连通性的点上加强通信。这些要点取决于救援队的行动,这受战术原因的影响。由于问题的复杂性和要考虑的参数数量,提出了一种与网络模拟器NS-2结合的遗传算法,以找到辅助节点的最佳位置。具体来说,NS-2用于对通信层进行建模并提供指导遗传搜索的适应度函数。已使用运动生成器BonnMotion中包含的灾难移动模型对提出的方法进行了测试。获得的仿真结果证明了该方法的可行性,并说明了其在缺乏连通性的其他情况下的适用性。

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