CellOS: Zero-touch Softwarized Open Cellular Networks

被引:31
作者
Bonati, Leonardo [1 ]
D'Oro, Salvatore [1 ]
Bertizzolo, Lorenzo [1 ]
Demirors, Emrecan [1 ]
Guan, Zhangyu [2 ]
Basagni, Stefano [1 ]
Melodia, Tommaso [1 ]
机构
[1] Northeastern Univ, Inst Wireless Internet Things, Boston, MA 02115 USA
[2] State Univ New York SUNY Buffalo, Dept Elect Engn, Buffalo, NY 14260 USA
基金
美国国家科学基金会;
关键词
Software-defined Networking; Zero-touch; 5G; OPTIMIZATION;
D O I
10.1016/j.comnet.2020.107380
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Current cellular networks rely on closed and inflexible infrastructure tightly controlled by a handful of vendors. Their configuration requires vendor support and lengthy manual operations, which prevent Telco Operators (TOs) from unlocking the full network potential and from performing fine grained performance optimization, especially on a per-user basis. To address these key issues, this paper introduces CellOS, a fully automated optimization and management framework for cellular networks that requires negligible intervention ("zero-touch "). CellOS leverages softwarization and automatic optimization principles to bridge Software-Defined Networking (SDN) and cross-layer optimization. Unlike state-of-the-art SDN-inspired solutions for cellular networking, CellOS: (i) Hides low-level network details through a general virtual network abstraction ; (ii) allows TOs to define high-level control objectives to dictate the desired network behavior without requiring knowledge of optimization techniques, and (iii) automatically generates and executes distributed control programs for simultaneous optimization of heterogeneous control objectives on multiple network slices. CellOS has been implemented and evaluated on an indoor testbed with two different LTE-compliant implementations: OpenAirInterface and srsLTE. We further demonstrated CellOS capabilities on the long-range outdoor POWDER-RENEW PAWR 5G platform. Results from scenarios with multiple base stations and users show that CellOS is platform-independent and self-adapts to diverse network deployments. Our investigation shows that CellOS outperforms existing solutions on key metrics, including throughput (up to 86% improvement), energy efficiency (up to 84%) and fairness (up to 29%).
引用
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页数:13
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