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Round-Trip Time Anomaly Detection
Infoflex Connect AB, Stockholm, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-0611-2655
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-8009-9052
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5032-2310
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2018 (English)In: ICPE '18 Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering, 2018, p. 107-114Conference paper, Published paper (Refereed)
Abstract [en]

Mobile text messages (SMS) are sometimes used for authentication, which requires short and reliable delivery times. The observed round-trip times when sending an SMS message provide valuable information on the quality of the connection. In this industry paper, we propose a method for detecting round-trip time anomalies, where the exact distribution is unknown, the variance is several orders of magnitude, and there are lots of shorter spikes that should be ignored. In particular, we show that using an adaption of Double Seasonal Exponential Smoothing to reduce the content dependent variations, followed by the Remedian to find short-term and long-term medians, successfully identifies larger groups of outliers. As training data for our method we use log files from a live SMS gateway. In order to verify the effectiveness of our approach, we utilize simulated data. Our contributions are a description on how to isolate content dependent variations, and the sequence of steps to find significant anomalies in big data.

Place, publisher, year, edition, pages
2018. p. 107-114
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-41840DOI: 10.1145/3184407.3184436Scopus ID: 2-s2.0-85048196185ISBN: 978-1-4503-5095-2 (print)OAI: oai:DiVA.org:mdh-41840DiVA, id: diva2:1274058
Conference
2018 ACM/SPEC International Conference on Performance Engineering, Berlin, Germany — April 09 - 13, 2018
Available from: 2018-12-27 Created: 2018-12-27 Last updated: 2018-12-27Bibliographically approved

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Afzal, WasifCausevic, AdnanDaniel, SundmarkBjörkman, Mats

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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