Abstract
The data mining algorithms and tools have been employed in many engineering and non-engineering applications. This paper proposes a new practical application of data mining in the study of problems related to the Internet performance. Well-predicted performance is a key engineering issue in Internet-based processing, e.g. in peer-to-peer systems. The measurements of round-trip-time performed by the traceroute probing technique are used for Internet path performance evaluation. We show how data mining can be used by the end-users to evaluate the performance of the communication path between their location and a specific Internet host in a long-term performance prediction scale. The mining data is mined using the IBM Intelligent Miner for Data system. We discover how the round-trip times of the packets and the number of hops they pass vary with the day of the week and the time of the measurement and use this knowledge to built the decision tree that can be a useful guide to the future characteristics of relevant properties of given Internet path in a long-term scale.
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Borzemski, L. (2004). Data Mining in Evaluation of Internet Path Performance. In: Orchard, B., Yang, C., Ali, M. (eds) Innovations in Applied Artificial Intelligence. IEA/AIE 2004. Lecture Notes in Computer Science(), vol 3029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24677-0_66
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DOI: https://doi.org/10.1007/978-3-540-24677-0_66
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