RT Journal Article
T1 Self-healing in mobile networks with big data
A1 Khatib, Emil Jatib
A1 Barco-Moreno, Raquel
A1 Muñoz, Pablo
A1 De la Bandera Cascales, Isabel
A1 Serrano, Inmaculada
K1 Sistemas de telecomunicaciones
K1 Comunicación - Análisis de red
K1 Informática móvil
AB 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.
PB IEEE
YR 2016
FD 2016-01
LK https://hdl.handle.net/10630/34287
UL https://hdl.handle.net/10630/34287
LA eng
NO 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.
NO Optimi-Ericsson, Junta de Andalucia (Agencia IDEA, Consejeria de Ciencia, Innovacion y Empresa, ref. 59288; y Proyecto de Investigación de Excelencia PI2-TIC-2905), ERDF.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 27 ene 2026