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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在自组织网络控制中的应用

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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:有一个新兴的研究领域采用生物启发算法来自组织信息网络系统。尽管对它们的好处(即高鲁棒性,适应性和可伸缩性)有浓厚兴趣,但仍未很好地研究生物启发算法在不可忽略的扰动下的行为,例如在现实环境中观察到的信息丢失和节点故障。由于缺乏知识,没有人能清楚地识别出生物启发算法在挑战性信息网络问题上的应用范围。因此,为了解决该问题并加快该领域的研究,我们需要从网络控制的角度了解生物启发算法的特征。本文以响应阈值模型为例,讨论了生物启发模型的鲁棒性和适应性及其在网络控制中的应用。通过仿真实验和数学分析,证明了有损环境中平衡态的存在条件。我们还阐明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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