End-to-End Data Analytics Framework for 5G Architecture

被引:44
|
作者
Pateromichelakis, Emmanouil [1 ]
Moggio, Fabrizio [2 ]
Mannweiler, Christian [3 ]
Arnold, Paul [4 ]
Shariat, Mehrdad [5 ]
Einhaus, Michael [6 ]
Wei, Qing [1 ]
Bulakci, Omer [1 ]
De Domenico, Antonio [7 ]
机构
[1] Huawei GRC, D-80992 Munich, Germany
[2] Telecom Italia, I-20123 Milan, Italy
[3] Nokia Bell Labs, D-81541 Munich, Germany
[4] Deutsch Telekom, D-64295 Darmstadt, Germany
[5] Samsung Elect R&D Inst, Staines TW18 4QE, England
[6] Leipzig Univ Telecommun, Dept Commun Engn, D-04277 Leipzig, Germany
[7] CEA LETI, F-38054 Grenoble, France
来源
IEEE ACCESS | 2019年 / 7卷
基金
欧盟地平线“2020”;
关键词
5G; architecture; data analytics; network slicing; MANAGEMENT;
D O I
10.1109/ACCESS.2019.2902984
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Data analytics can be seen as a powerful tool for the fifth-generation (5G) communication system to enable the transformation of the envisioned challenging 5G features into a reality. In the current 5G architecture, some first features toward this direction have been adopted by introducing new functions in core and management domains that can either run analytics on collected communication-related data or can enhance the already supported network functions with statistics collection and prediction capabilities. However, possible further enhancements on 5G architecture may be required, which strongly depend on the requirements as set by vertical customers and the network capabilities as offered by the operator. In addition, the architecture needs to be flexible in order to deal with network changes and service adaptations as requested by verticals. This paper explicitly describes the requirements for deploying data analytics in a 5G system and subsequently presents the current status of standardization activities. The main contribution of this paper is the investigation and design of an integrated data analytics framework as a key enabling technology for the service-based architectures (SBAs). This framework introduces new functional entities for application-level, data network, and access-related analytics to be integrated into the already existing analytics functionalities and examines their interactions in a service-oriented manner. Finally, to demonstrate predictive radio resource management, we showcase a particular implementation for application and radio access network analytics, based on a novel database for collecting and analyzing radio measurements.
引用
收藏
页码:40295 / 40312
页数:18
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