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EP-4742037-A1 - A METHOD OF MANAGING HARDWARE RESOURCES IN AN OPEN RAN CLOUD PLATFORM, A CLOUD PLATFORM AND A COMPUTER PROGRAM

EP4742037A1EP 4742037 A1EP4742037 A1EP 4742037A1EP-4742037-A1

Abstract

A method of managing hardware resources in an Open Radio Access Network (Open RAN) cloud platform is provided. The cloud platform comprises a plurality of processor cores. The cloud platform is configured to host a plurality of application processes. The method comprises dynamically allocating zero or more processor cores of the plurality of processor cores to each of the plurality of application processes, based on processing requirements of the respective application process.

Inventors

  • LAW, ALAN
  • Lu, Zhanhong

Assignees

  • Vodafone Group Services Limited

Dates

Publication Date
20260513
Application Date
20251112

Claims (15)

  1. A method of managing hardware resources in an Open Radio Access Network, Open RAN, cloud platform, wherein the cloud platform comprises a plurality of processor cores, wherein the cloud platform is configured to host a plurality of application processes, the method comprising: dynamically allocating zero or more processor cores of the plurality of processor cores to each of the plurality of application processes, based on processing requirements of the respective application process.
  2. The method of claim 1, wherein dynamically allocating zero or more cores to each of the plurality of applications comprises allocating zero cores to an application process if the respective processing requirements of the application process are zero.
  3. The method of claim 1 or claim 2, wherein the cloud platform is a containerised cloud platform and wherein each of the application processes is hosted via a respective pod managed by the containerised cloud platform.
  4. The method of any preceding claim, wherein one or more of the plurality of processor cores are dedicated cores allocated to a scheduler of the cloud platform.
  5. The method of claim 4, wherein each of the plurality of processor cores that are not the one or more dedicated cores, form a resource pool, and wherein dynamically allocating zero or more processor cores of the plurality of processor cores to each of the plurality of application processes comprises dynamically allocating the zero or more processor cores from the resource pool to each of the plurality of application processes.
  6. The method of any preceding claim, wherein the processing requirements of each application process comprise forecasted processing requirements, wherein a model is used to forecast the processing requirements for the application processes.
  7. The method of claim 6: wherein the model is an artificial intelligence, AI, model; and/or wherein the model is trained using historical data of the processing requirements of the application processes or via synthetic training data.
  8. The method of claim 6 or claim 7, wherein each of the plurality of processor cores is operable in one or more processor idle sleep states, wherein the method further comprises: transitioning a processor core of the plurality of processor cores to an idle sleep state, based on the forecasted processing requirements of the respective application process to which the processor core is allocated.
  9. The method of any of claims 6 to 8, wherein each of the plurality of processor cores is operable in one or more power performance states, wherein the method further comprises: transitioning a processor core of the plurality of processor cores to a power performance state, based on the forecasted processing requirements of the respective application process to which the processor core is allocated.
  10. The method of any preceding claim, wherein the processing requirements comprise a data processing load and/or a network traffic load.
  11. The method of any preceding claim, wherein each of the plurality of processor cores is operable in a normal mode and one or more power-saving modes, the method further comprising: transitioning one or more of the plurality of processor cores to a power-saving mode, based on the processing requirements of the plurality of application processes; and/or transitioning one or more of the plurality of processor cores from a power-saving mode to normal mode, based on the processing requirements of the plurality of application processes.
  12. The method of claim 11, wherein the one or more power-saving modes comprise: one or more processor idle sleep states; and/or one or more power performance states.
  13. The method of any preceding claim, wherein the cloud platform comprises one or more servers, preferably a plurality of servers, wherein the plurality of processor cores comprises a respective plurality of processor cores from each server.
  14. A cloud platform configured to perform the method of any preceding claim.
  15. A computer program comprising instructions that, when executed on a processor, cause the processor to perform the method of any of claims 1 to 13.

Description

Field of the invention The present invention relates to management of hardware resources in an Open Radio Access Network cloud platform. In particular, the invention relates to methods of dynamically allocating CPU cores to application processes. Glossary RAN - Radio Access NetworkMNO - Mobile Network OperatorO-RAN - Open RAN AllianceO-DU - Open Distributed UnitO-CU - Open Central UnitO-RU - Open Radio UnitOS - Operating SystemGPU - Graphics Processing UnitAPI - Application Programming InterfaceSMO - Service Management and OrchestrationDMS - Deployment Management ServicesNF - Network FunctionIMS - Infrastructure Management ServicesCOTS - Commercial Off-The-ShelfCaaS - Containers as a ServiceCPU - Central Processing UnitTTI - Transmission Time IntervalMIMO - Multiple Input Multiple OutputUE - User EquipmentBS - Base StationABS - Advanced Base StationBTS - Base Transceiver StationBSS - Basic Service SetESS - Extended Service SetAP - Access PointNB - Node B (Radio Base Station Receiver)eNB - Evolved Node BgNB - Next-Generation Node BTRP - Transmission and Reception PointPS - Processing ServerTE - Terminal EquipmentMS - Mobile StationMT - Mobile TerminalUT - User TerminalSS - Subscriber StationPDA - Personal Digital AssistantCDMA - Code Division Multiple AccessFDMA - Frequency Division Multiple AccessTDMA - Time Division Multiple AccessOFDMA - Orthogonal Frequency Division Multiple AccessSC-FDMA - Single Carrier Frequency Division Multiple AccessMC-FDMA - Multicarrier Frequency Division Multiple AccessUTRA - Universal Terrestrial Radio AccessGSM - Global System for Mobile CommunicationsGPRS - General Packet Radio ServiceEDGE - Enhanced Data Rates for GSM EvolutionIEEE - Institute of Electrical and Electronics EngineersE-UTRA - Evolved UTRAUMTS - Universal Mobile Telecommunications SystemE-UMTS - Evolved UMTS3GPP - 3rd Generation Partnership ProjectDL - DownlinkUL - UplinkLTE - Long Term Evolution (4G)LTE-A - LTE-AdvancedNR - New Radio (5G)FDD - Frequency Division DuplexTDD - Time Division DuplexCRS - Cell-specific Reference SignalCSI-RS - Channel State Information Reference SignalFPGA - Field-Programmable-Gate-ArrayASIC - Application-Specific-Integrated-CircuitDSP - Digital-Signal-ProcessorCD-ROM - Compact Disc Read-Only MemoryDVD-ROM - Digital Versatile Disc Read-Only MemoryROM - Read-Only MemoryRAM - Random-Access MemoryEEPROM - Electrically Erasable Programmable Read-Only MemoryEPROM - Erasable Programmable Read-Only Memory Background Open RAN is a technology architecture concept directed to decoupling the hardware and software components of a Radio Access Network (RAN). It is a RAN that includes open interoperable interfaces and virtualization. In prior art (Non-Open) RANs, the hardware and software components are typically proprietary. Non-Open RAN equipment is generally obtained from a single vendor to ensure seamless functionality, security, and efficiency. In contrast, Open RAN introduces open standards for both hardware and software, enabling interoperability among various network elements. For Mobile Network Operators (MNOs), Open RAN holds strategic importance as it promotes vendor diversity, allowing the integration of new suppliers and enhancing supply chain resilience. It also brings energy efficiency gains by enabling targeted improvements in specific areas of the RAN. Furthermore, Open RAN facilitates innovation and competition by providing a more dynamic and efficient network environment. Additionally, it provides an opportunity for collaboration with specialist suppliers and facilitates resource optimization by allowing upgrades to software, without necessitating hardware replacements. Open RAN is important in the long-term network innovation strategy of MNOs, offering energy efficiency, supply chain diversification, resilience enhancement, and facilitating innovation and competition. Fig. 1 illustrates some of the elements of an example Open RAN system 100, which is implemented as a cloud computing platform (O-Cloud). The system 100 may be described with reference to different hardware and software layers of the platform. At the O-Cloud Node layer 110, the system comprises one or more physical infrastructure nodes 120A, 120N that meet O-RAN requirements. Each physical infrastructure node 120A comprises computing 121, networking 122, GPU 123, and storage 124 components, alongside acceleration technologies 125 for RAN operations (such as forward error correction and other computationally intensive operations that are offloaded to dedicated hardware). Each physical infrastructure node 120A, 120N is configured to host the relevant O-RAN network functions 150, 160, which are implemented at the Open RAN application layer 140. The network functions 150, 160 implemented at the Open RAN application layer 140 may include O-CU 160, O-DU 150, and O-RU. At the O-Cloud hypervisor or containers / OS layer 130, there exists a collection of cloud functions to enable the Open RAN applications 150, 160 to run o