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Characteristic Analysis of Response Threshold Model and Its Application for Self-organizing Network Control

机译：响应阈值模型的特征分析及其对自组织网络控制的应用

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摘要

There is an emerging research area to adopt bio-inspired algorithms to self-organize an information network system. Despite strong interests on their benefits, i.e. high robustness, adaptability, and scalability, the behavior of bio-inspired algorithms under non-negligible perturbation such as loss of information and failure of nodes observed in the realistic environment is not well investigated. Because of lack of knowledge, none can clearly identify the range of application of a bio-inspired algorithm to challenging issues of information networks. Therefore, to tackle the problem and accelerate researches in this area, we need to understand characteristics of bio-inspired algorithms from the perspective of network control. In this paper, taking a response threshold model as an example, we discuss the robustness and adaptability of bio-inspired model and its application to network control. Through simulation experiments and mathematical analysis, we show an existence condition of the equilibrium state in the lossy environment. We also clarify the influence of the environmental condition and control parameters on the transient behavior and the recovery time.
机译：还有就是要采用仿生算法，一个新兴的研究领域自我组织的信息网络系统。尽管在他们的利益浓厚的兴趣，即高鲁棒性，适应性和可扩展性的仿生算法下不可忽略的干扰行为等信息，并在现实的环境中观察到的节点的故障损失没有得到很好的研究。由于认识不足，没有可以清楚地识别出仿生算法的应用范围，以具有挑战性的信息网络的问题。因此，要解决这个问题，并在这一领域加快研究，我们需要从网络控制的角度去理解的仿生算法的特点。在本文中，以响应阈值模型为例，我们讨论的鲁棒性和仿生模型的适应性及其应用网络控制。通过仿真实验和数学分析，我们展示了平衡状态在有损环境的生存状态。我们还明确了环境条件和控制参数对瞬态行为和恢复时间的影响。

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