Self-Healing in Mobile Networks with Big Data

被引：34

作者：

Khatib, Emil J. ^{[1
]}

Barco, Raquel ^{[2
]}

Munoz, Pablo ^{[2
]}

de la Bandera, Isabel ^{[3
]}

Serrano, Immaculada ^{[4
]}

机构：

[1] Univ Malaga, Dept Syst Engn & Automat, E-29071 Malaga, Spain

[2] Univ Malaga, E-29071 Malaga, Spain

[3] Univ Malaga, Dept Commun Engn, Radiofrequency Identificat Projects, E-29071 Malaga, Spain

[4] Ericsson V, Berlin, Germany

来源：

IEEE COMMUNICATIONS MAGAZINE | 2016年 / 54卷 / 01期

关键词：

SYSTEMS;

D O I：

10.1109/MCOM.2016.7378435

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：114 / 120

页数：7

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