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oai:riuma.uma.es:10630/342872026-02-03T10:53:26Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Khatib, Emil Jatib author Barco-Moreno, Raquel author Muñoz, Pablo author De la Bandera Cascales, Isabel author Serrano, Inmaculada author 2016-01 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. 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 Sistemas de telecomunicaciones Comunicación - Análisis de red Informática móvil Self-healing in mobile networks with big data