Performance evaluation of multi-stratum resources optimization with network functions virtualization for cloud-based...

Area of Science:

• Telecommunications Engineering
• Optical Networking
• Cloud Computing

Background:

• Cloud Radio Access Network (C-RAN) enables high-performance services and real-time cloud computing using cloud Baseband Units (BBUs).
• Previous work focused on cross-stratum optimization of optical network and application resources.
• The 5G era necessitates optimization across multiple dimensions: radio, optical, and BBU processing.

Purpose of the Study:

• To propose a novel multi-stratum resources optimization (MSRO) architecture for cloud-based radio over optical fiber networks (C-RoFN).
• To introduce a global evaluation scheme (GES) for MSRO in C-RoFN.
• To enhance responsiveness to dynamic user demands and optimize radio frequency, optical, and BBU resources for maximum radio coverage.

Main Methods:

• Developed a novel MSRO architecture incorporating network functions virtualization and software-defined control.
• Introduced a Global Evaluation Scheme (GES) for comprehensive performance assessment.
• Experimentally demonstrated the architecture on an OpenFlow-based Software-Defined Networking (SDN) testbed.

Main Results:

• The MSRO architecture effectively optimizes radio frequency, optical, and BBU resources.
• Experimental validation confirmed the efficiency and feasibility of the proposed architecture.
• GES performance evaluation under heavy traffic showed improved resource occupation rate and path provisioning latency compared to other schemes.

Conclusions:

• The proposed MSRO architecture with GES provides an effective solution for resource optimization in C-RoFN.
• This approach enhances end-to-end service responsiveness and maximizes radio coverage in 5G networks.
• The study demonstrates a significant advancement in managing complex resources for future wireless and optical networks.