Abstract
The Internet is the product of interconnecting a large number of administratively independent networks. Each such network is referred to as an autonomous system (AS). Moving data traffic between these networks necessitates the presence of a global routing protocol that describes what path needs to be followed to reach a particular destination. The border gateway protocol (BGP) is the de-facto standard global routing protocol and hence the glue that binds the Internet together. Routing devices that use BGP store the current state of the routing systems and dynamically inform neighboring devices, via update messages, upon changes. The stability of BGP is clearly of a paramount importance to the stability of the entire Internet ecosystem. In this work, we aim to better understand BGP dynamics and stability by investigating empirical BGP updates timeseries for regularities. More specifically, we study BGP update timeseries from 4 large autonomous systems that span a four-months period from July 2011 to November 2011. To this end, we employ relevant data analysis methods like Local variation and Lempel and Ziv complexity measure calculations as well as Detrended Fluctuation analysis which allow for assessing the extent of regularity in the considered time series. We also employ the Mahalanobis distance to identify outliers. We find that BGP updates dynamics is characterized by both regular and random-like variability, with the latter coinciding with stronger changes. Furthermore, both regularity assessment and outlier detection methods revealed days with increased extent of order that were common to all four timeseries. Examining these days further indicates the presence of a common global cause. Hence, these methods can be used as a first step for detecting BGP routing anomalies.
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More From: Physica A: Statistical Mechanics and its Applications
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