Impact of lower layers on measurements Sample Clauses

Impact of lower layers on measurements. ‌ In recent years, progress has been done on the techniques for measuring the capacity and available bandwidth of a path. Many studies are supported by theoretical analysis, often employing fluid models which nicely show the effect of the probes and the im- pact of competing cross-traffic. However, the Internet is composed of different types of networks employing very different technologies. While at Layer 3 (L3) the IP protocol is universally adopted, at lower layers (L1 and L2) different architectures are adopted, spanning from DSL to Fiber to Wireless. Thus, when undertaking the measurements, being them passive or active, it must be kept in mind that packets can traverse various infrastructures which might introduce some unknown bias which depend on the tech- niques used. Additionally, the vast majority of the tools assume FIFO queuing and do not consider rate regulation mechanisms such as token buckets. For example, in [36] the authors show that some tools produce biased results when measuring access net- works because of the presence of a WiFi link or of a token bucket on Cable links. In [9] it has been shown that the Packet Pairs technique is not suitable for ADSL environ- ments because of significant granularity in the Inter-Arrival Time (IAT) of the packets (see Fig. 3.1), and in [6] this IAT granularity is even used for the characterization of networks employing different technologies. Therefore, when measuring an Internet path, it is very important either to acquire knowledge of the traversed networks, or to employ measurement techniques which are robust enough to work in different environ- ments. In particular, the VPS technique and the Packet Pairs-based tools are likely to be the most affected because they employ few packets in the estimation and thus are more sensitive to bias introduced by lower layers. 3000 Interarrival Time between packets (us) 2500 2000 1500 1000 500 Time (s) ∼
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