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Revisiting pitfalls of DTN datasets statistical analysis
Author(s) -
Gwilherm Baudic,
Tanguy Pérennou,
Emmanuel Lochin
Publication year - 2014
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2645672.2645683
Subject(s) - computer science , usable , preprocessor , checklist , statistical analysis , artificial intelligence , data mining , machine learning , data science , data pre processing , information retrieval , world wide web , statistics , psychology , mathematics , cognitive psychology
Contact traces collected in real situations represent a popular material to assess the performance of a Delay Tolerant Network. These traces usually require some preprocessing to be fully usable. Especially, several assumptions can be made prior to performing the statistical analysis of contact and inter-contact times. We first classify these assumptions, and analyze their impact on the statistical characterization of three well-known datasets. We also identify some pitfalls in dataset analysis that might strongly influence the conclusion made by the experimenter. Based on our own experience, we subsequently propose a preliminary checklist to help researchers avoid undesired ambiguities or misunderstandings in further studies

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