反群集模型在移动监控系统中的应用

Yun-Qian Miao, A. Khamis, M. Kamel
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引用次数: 31

摘要

本文讨论了全协调移动、全随机移动和应急移动三种移动模型在提高移动监控系统中一组移动传感器的区域覆盖和检测效率方面的作用。描述了一种新的模拟独居动物社会行为的反群集算法。通过一个基于多智能体的系统来检验不同移动模型的效率。仿真结果表明,反蜂拥迁移模型优于全随机迁移模型。与全协调移动模型相比,该模型具有可扩展性、鲁棒性和适应性等特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying anti-flocking model in mobile surveillance systems
This paper discusses the role of three mobility models namely, fully coordinated mobility, fully random mobility and emergent mobility models in improving area coverage and detection effectiveness of a set of mobile sensors in a mobile surveillance system. A novel anti-flocking algorithm that mimics solitary animal's social behavior is described. A multiagent-based system has been implemented to examine the efficiency of the different mobility model. The simulation results show that anti-flocking mobility model outperforms the fully random mobility model. This novel model provides additional features such as scalability, robustness and adaptivity comparing with fully coordinated mobility model.
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