Internet域间路由动态特性中的长程相关性和记忆性
Long-Range Correlations and Memory in the Dynamics of Internet Interdomain Routing
摘要：
数据传输是互联网的主要功能之一。互联网由大量互连的子网或域组成，称为自治系统。由于隐私和其他原因，关于使用什么路线到达其他自治系统内的设备的信息对于任何给定的自治系统都是不容易获得的。边界网关协议负责发现并将此可达性信息分发给所有自治系统。由于互联网的拓扑结构是高度动态的，所有自治系统不断地交换和更新小块的可达性信息，称为路由控制分组或边界网关协议更新。出于可扩展性和可预测性的问题，这些更新的动态在快速增长的互联网，我们进行了系统的时间序列分析边界网关协议的更新率。我们发现，边界网关协议更新时间序列是非常不稳定的，表现出长期的相关性和记忆效应，类似于地震时间序列，或温度和股票市场价格波动。边界网关协议更新动态的统计特性，可以作为一个地面真理验证现有的和发展更好的互联网域间路由模型。
英文摘要：
Data transfer is one of the main functions of the Internet. The Internet consists of a large number of interconnected subnetworks or domains, known as Autonomous Systems. Due to privacy and other reasons the information about what route to use to reach devices within other Autonomous Systems is not readily available to any given Autonomous System. The Border Gateway Protocol is responsible for discovering and distributing this reachability information to all Autonomous Systems. Since the topology of the Internet is highly dynamic, all Autonomous Systems constantly exchange and update this reachability information in small chunks, known as routing control packets or Border Gateway Protocol updates. Motivated by scalability and predictability issues with the dynamics of these updates in the quickly growing Internet, we conduct a systematic time series analysis of Border Gateway Protocol update rates. We find that Border Gateway Protocol update time series are extremely volatile, exhibit long-term correlations and memory effects, similar to seismic time series, or temperature and stock market price fluctuations. The presented statistical characterization of Border Gateway Protocol update dynamics could serve as a ground truth for validation of existing and developing better models of Internet interdomain routing.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
