2026-06-04T06:13:19Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/342872026-02-03T10:53:26Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Khatib, Emil Jatib
author
Barco-Moreno, Raquel
author
Muñoz, Pablo
author
De la Bandera Cascales, Isabel
author
Serrano, Inmaculada
2024-10-03T11:22:36Z
2024-10-03T11:22:36Z
2016-01
E. J. Khatib, R. Barco, P. Munoz, I. De La Bandera and I. Serrano, "Self-healing in mobile networks with big data," in IEEE Communications Magazine, vol. 54, no. 1, pp. 114-120, January 2016, doi: 10.1109/MCOM.2016.7378435.
https://hdl.handle.net/10630/34287
10.1109/MCOM.2016.7378435
Mobile networks have rapidly evolved in recent years due to the increase in multimedia traffic and offered services. This has led to a growth in the volume of control data and measurements that are used by self-healing systems. To maintain a certain quality of service, self-healing systems must complete their tasks in a reasonable time. The conjunction of a big volume of data and the limitation of time requires a big data approach to the problem of self-healing. This article reviews the data that self-healing uses as input and justifies its classification as big data. Big data techniques applied to mobile networks are examined, and some use cases along with their big data solutions are surveyed.
eng
Sistemas de telecomunicaciones
Comunicación - Análisis de red
Informática móvil
Self-healing in mobile networks with big data
journal article
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URL
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File
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485471
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Paper_Big_Data.pdf