Abstract
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 (ASes). Due to privacy and other reasons the information about what route to use to reach devices within other ASes is not readily available to any given AS. The Border Gateway Protocol (BGP) is responsible for discovering and distributing this reachability information to all ASes. Since the topology of the Internet is highly dynamic, all ASes constantly exchange and update this reachability information in small chunks, known as routing control packets or BGP updates. In the view of the quick growth of the Internet there are significant concerns with the scalability of the BGP updates and the efficiency of the BGP routing in general. Motivated by these issues we conduct a systematic time series analysis of BGP update rates. We find that BGP 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 BGP update dynamics could serve as a basis for validation of existing and developing better models of Internet interdomain routing.
Highlights
On large scale, the Internet is a global system of approximately 40,000 interlinked computer networks connecting billions of users and devices worldwide [1]
The network section, which is known as Internet Protocol (IP) prefix, identifies a group of hosts, while the host section identifies a particular device
We note that the standard deviations of the intraday and intraweek patterns, sdðtÞ and swðtÞ, tend to exceed the corresponding average values of the intra-day and the intra-week patterns by an order of magnitude, which is consistent with the extreme burstiness of the Border Gateway Protocol (BGP) updates (Fig 2d and 2e)
Summary
The Internet is a global system of approximately 40,000 interlinked computer networks connecting billions of users and devices worldwide [1]. We note that the standard deviations of the intraday and intraweek patterns, sdðtÞ and swðtÞ, tend to exceed the corresponding average values of the intra-day and the intra-week patterns by an order of magnitude, which is consistent with the extreme burstiness of the BGP updates (Fig 2d and 2e). Long-range correlations may imply the presence of memory effects in the inter-domain Internet routing To probe for the latter we ask, what is a typical time interval τ separating two large events. ^t is independent of preceding return interval τ0 for randomized data (open symbols in Fig 5f and S3 Fig)
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