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In many systems, such as P2P systems, the dynamicity of participating elements, or churn, has a strong impact. As a consequence, many efforts have been made to characterize it, and in particular to capture the session length distribution. However in most cases, estimating it rigorously is difficult. One of the reasons is that, because the observation window is by definition finite, parts of the sessions that begin before the window and/or end after it are missed. This induces a bias. Although it tends to decrease when the observation window length increases, it is difficult to quantify its importance, or how fast it decreases.
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