PRESS RELEASE: 5G SA has been put into large-scale commercial use worldwide. As an engine for digital and intelligent transformation of thousands of industries, 5G network faces the challenges and opportunities in the dual-carbon era. It is necessary to continuously adopt innovative technologies to build green infrastructure. In addition, advanced network energy saving and consumption reducing technologies are required to provide a driving force for the green development of thousands of industries, thus bringing greater development opportunities.

As the core and brain of 5G network, it faces great challenges on how to save energy and reduce consumption because of multiple types of NEs, a large number of MOCs, distributed deployment, and redundant resources. In addition, CN, as the brain of the network, needs to be smarter and more agile so as to accurately perceive the congestion status, service type, and UE location of network data upload and delivery, and can schedule and orchestrate the network in real time and dynamically. Additionally, CN can collaborate with other network domains to empower different industries and achieve end-to-end energy saving and consumption reducing. Therefore, the research and applications of the energy-saving and consumption-reducing technologies of CN are indispensable.

Green Engine Solution

Facing the opportunities and challenges of green development, ZTE launches the Green Engine solution on the basis of the 5G Common Core. The solution is guided by the ideas of energy saving, enabling, and empowering, oriented to ToC and ToB scenarios, and based on four key technologies of cloud native, hyper-convergence, hardware acceleration, and AI/automation. With this solution, ZTE achieves green transformation of NFVI, VNFs, and MANO, promotes the capability construction and continuous evolution of CNs, builds a green engine, saves energy for operators’ networks, enables thousands of industries, empowers digital and intelligent production, and helps thousands of industries achieve the dual-carbon goal in the era of Internet of Everything (IoE).

NFVI: Green Base

The NFVI includes two key components: server hardware and cloud platform. The goal of the Green Base is to build green servers and a green cloud platform.

Green server: As the basis of the Green Base, ZTE provides efficient computing through efficient power supply, heat dissipation, and architecture to optimize bit power consumption, reduce unnecessary power consumption, and greatly reduce PUE.

  • Efficient power supply: Multiple power supply modes, such as direct battery supply and titanium power supply, are supported to improve power supply efficiency. Intelligent peak-shift power-on avoids a sharp increase in instantaneous power consumption.
  • Efficient heat dissipation: A full series of liquid-cooled servers are provided to efficiently dissipate heat for high-energy components. The use of immersive liquid cooling in the data center resource pool size will allow PUE to approach 1.01, saving significant power in the core equipment room.
  • Efficient architecture: New architectures such as in-memory computing and near-memory computing are gradually introduced, and new materials such as resistance random access memory (RRAM) and phase change memories (PCM) are also introduced to reduce power consumption by more than 50%.
  • Efficient computing: Based on service characteristics, the system implements efficient coordination of multiple computing powers. For example, with combination of CPU and FPGA, FPGAs can directly forward packets without being sent to CPUs and memories, reducing data copy energy consumption and bit power consumption.

Green Cloud Platform: As a unified management platform, the Green Cloud Platform shields the complexity of resources in terms of scale, type, and layout, and provides AIO abstract computing power for applications. The Green Cloud Platform aims to achieve energy saving and consumption reducing while improving the Green Cloud Platform for various applications.

  • Energy saving and consumption reducing: Dynamic resource adjustment based on power management and service requirements can effectively reduce energy consumption. At the same time, intelligent capacity prediction is implemented to plan and adjust the resource pool capacity in advance to save resource consumption.
  • Green empowering: The platform provides accurate resources based on differentiated application requirements (such as acceleration and low latency) to achieve optimal resource adaptation. In addition, core basic capabilities (such as database and load balancing) are shared to reduce application energy consumption.

VNF: Green Enabling

In terms of Green Enabling, CN VNFs act as the Green Enabling role through multi-dimensional energy saving, including the following three aspects:

Cloud native design and energy saving native: The VNF architecture is stateless in design, and resources can be saved by 20%. Microservices are used to implement service sharing, and the common service layer of cloud native VNFs is built, reducing energy consumption by a maximum of 10%.

High-performance UPFs and intelligent energy-saving: Hardware acceleration, CPU core binding, and DPDK technologies are used to implement high-efficiency UPFs. In addition, the built-in energy-saving mode is used to power on or sleep CPUs as required in accordance with the network traffic load. Intelligent on-duty observation has no impact on service smoothing. The forwarding plane requires only one physical CPU core for on-duty observation, thus reducing energy consumption by up to 90%.

Full-scenario private network equipment, green Enabling: Cloud-network hyper-convergence, accurate IoT, and other features are introduced to help IoT terminals such as smart electricity meters, water meters, and public bike smart locks achieve energy saving. For example, the precision IoT negotiates with terminals to deliver a hierarchical power-saving policy on demand, and instructs terminals to sleep periodically at the second, hour, and day levels, extending the standby time of IoT terminals by ten to 1,000 times.

MANO: Green Brain

It is another challenge on how to accurately monitor and manage the CN while saving energy and reducing consumption. For example, these problems require a green brain for precise monitoring and management.

The “Green Brain” of ZTE’s CN is based on the whole O&M workflow (plan, construction, maintenance, and optimization). Through intelligent automation on the whole workflow, the green transformation of O&M is promoted, and a complete set of solutions for green construction, energy consumption management, intelligent O&M, and energy consumption optimization are built, so that energy saving can be easily seen and touched and can be intelligently automated to enable green operation.

Through continuous cooperation with industry-leading operators, ZTE 5GC Green Engine Solution is playing an increasingly important role in the dual-carbon goal. By virtue of its leading products and solutions, ZTE has carried out in-depth cooperation with many operators and industry enterprises around the world to build low-carbon CNs as green engines to improve the energy efficiency of data centers, speed up the exit of old network equipment with high energy consumption, and build a new information infrastructure that is green, low-carbon, efficient, and intelligent, to help operators and industry customers achieve the goal of green transformation in the dual-carbon era, and contribute to the construction of a green earth.