延迟布尔网络的非对称稳定性,随机数据丢失
IEEE transactions on neural networks and learning systems
|August 15, 2023
概括
本研究通过建模时间延迟和随机数据丢失来解决布尔网络 (BNs) 中的通信限制. 一种新方法确保了网络稳定性,尽管存在这些限制,提供了收率.
科学领域:
- 计算机科学 计算机科学
- 网络科学 网络科学
- 控制理论 控制理论
背景情况:
- 现实世界的网络面临着不可避免的通信限制,包括信息延迟和数据包丢失.
- 布尔网络 (BNs) 广泛用于模拟复杂系统,但对通信缺陷敏感.
研究的目的:
- 调查布尔网络 (BNs) 的非对称稳定性,包括时间延迟和随机丢失的数据.
- 提出一个新的数据发送规则,以考虑这些通信约束.
主要方法:
- 用Bernoulli随机变量对每个节点进行数据包丢失的建模.
- 用独立随机变量表示时间延迟和缺失的数据.
- 开发一个包含当前状态,延迟信息和传输数据的增强系统.
- 使用半传感器产物 (STP) 进行理论分析.
主要成果:
- 导出延迟的BN与随机数据丢失的非对称稳定性的必要和充分条件.
- 在这些条件下获取网络的收率.
结论:
- 提出的方法有效地分析并确保面临现实的通信限制的布尔网络的稳定性.
- 这些发现为设计具有延迟和不可靠通信的强大的分布式系统提供了理论框架.
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