Measurements and analysis of end-to-end Internet dynamics
Measurements and analysis of end-to-end Internet dynamics
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Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
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IEEE Transactions on Information Theory
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High-level approach to modeling of observed system behavior
ACM SIGMETRICS Performance Evaluation Review
High-level approach to modeling of observed system behavior
Performance Evaluation
Towards an automatic modeling tool for observed system behavior
EPEW'07 Proceedings of the 4th European performance engineering conference on Formal methods and stochastic models for performance evaluation
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This paper introduces a methodology for interpreting measurement obtained over Internet. The paper is motivated by the fact that a large number of published papers in empirical networking analysis follow a generic framework that might be formalized and generalized to a large class of problem. The objective of this paper is to present an interpretation framework and to illustrate it by examples coming from the networking literature. The aim of the paper is rather to give to the researcher who is confronted to measurements coming from a network some guidelines on how to formalize the way to address interpretation of observations.The paper is based on the remark that interpretation is essentially a matter of relating observed effects to hidden causes. This problem might be formalized in its most general setting as an inverse statistical inference problem. The paper illustrates this inverse statistical problem in the context of two well-referred problems: interpretation of active measurement and network tomography. It shows that even if at first glance these two problems are different, the solution framework is the same. We will also give description about how to solve that inverse statistical inference problem by the EM method or the Bayesian framework.The framework provided in this paper is a powerful solution to address the complex problem of interpreting measurement over Internet and network modelling.