Analyzing network log files using big data techniques

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Abstract

The IT Department of the Universidad de La Laguna (ULL, Tenerife, Spain) provides service to 26 buildings with more than 1,000 network devices (wireless and wired), and access to more than 10,000 devices (computers, tablets, smartphones, etc.) which generate around 200 MB/day of data that is stored mainly in the DHCP log, the Apache HTTP log, and the WiFi log files. Within this context, the chapter addresses the design and development of an application that uses Big Data techniques to analyze those log files in order to track information on the device (date, time, MAC address, and georeferenced position), as well as the number and type of network accesses for each building. In a near future, this application will help the IT Department to analyze all these logs in real time.

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Plaza-Martín, V., Pérez-González, C. J., Colebrook, M., Roda-García, J. L., González-Dos-Santos, T., & González-González, J. C. (2016). Analyzing network log files using big data techniques. In Big Data Management (pp. 227–256). Springer International Publishing. https://doi.org/10.1007/978-3-319-45498-6_10

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