SYSTEM AND METHOD FOR PROVIDING CLOUD RESOURCE OPTIMIZATION POLICIES IN A TELECOMMUNICATIONS SYSTEM - Patent application

Abstract

A system for implementing an Open Cloud (O-Cloud) optimization policy by an application hosted in a Near Real-Time Radio Access Network Intelligent Controller (nRT-RIC) of a telecommunications network, the system including: a memory storing instructions; and at least one processor configured to implement the nRT-RIC within an Open Radio Access Network (O-RAN) architecture, the at least one processor configured to execute instructions to receive an O-Cloud optimization policy from a Non-Real-Time Radio Access Network Intelligent Controller (NRT-RIC) within a Service Management and Orchestration (SMO) framework of the telecommunications network, and to control implementing the O-Cloud optimization policy in an O-Cloud computing environment within the O-RAN.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to Singapore Provisional Patent Application No. 10202250828F, filed in the Singapore Patent Office on August 25, 2022, the disclosure of which is incorporated herein by reference in its entirety.

[0002] Systems and methods consistent with exemplary embodiments of the present disclosure relate to providing an open radio access network (O-RAN) architecture for near real-time (nRT-RIC) open cloud (O-Cloud) resource optimization. In particular, the systems and methods relate to implementing an O-Cloud optimization policy of a non-real-time radio access network (RAN) intelligent controller (NRT-RIC) within a Service Management and Orchestration (SMO) framework of a telecommunication network by an application hosted in a near real-time radio access network intelligent controller (nRT-RIC) of the telecommunication network. [Background technology]

[0003] The Radio Access Network (RAN) is a key component in telecommunication systems because it connects end-user devices (or user equipment) to the rest of the network. The RAN includes a combination of various network elements (NEs) that connect end-user devices to the core network. Traditionally, the hardware and / or software of a particular RAN is vendor-specific.

[0004] Open RAN (O-RAN) technology has emerged to allow multiple vendors to provide hardware and / or software for telecommunication systems. For this purpose, O-RAN divides RAN functions into a centralized unit (CU), a distributed unit (DU), and a radio unit (RU). The CU is a logical node for hosting the Radio Resource Control (RRC), Service Data Adaptation Protocol (SDAP), and / or Packet Data Convergence Protocol (PDCP) sublayers of the RAN. The DU is a logical node that hosts the Radio Link Control (RLC), Media Access Control (MAC), and Physical (PHY) sublayers of the RAN. The RU is a physical node that converts radio signals from the antennas into digital signals that can be transmitted to the DU via the fronthaul. These entities have open protocols and interfaces between them, so they can be developed by different vendors.

[0005] Figure 1 illustrates a prior art O-RAN architecture. Referring to Figure 1, RAN functions in the O-RAN architecture are controlled and optimized by RICs. RICs are software-defined components that implement modular applications to facilitate multi-vendor operability required in O-RAN systems and to automate and optimize RAN operations. RICs are divided into two types: non-real-time RICs (NRT-RICs) and near-real-time RICs (nRT-RICs).

[0006] The NRT-RIC is the control point for non-real-time control loops, operating on sub-second timescales within a Service Management and Orchestration (SMO) framework. Its functionality is implemented through modular applications called rApps. The functions include providing policies (i.e., a set of rules used to manage and control the change and / or maintenance of the state of one or more managed objects) based on guidance and enrichment over the A1 interface, which is an interface that enables communication between the NRT-RIC and the nRT-RIC (i.e., A1 policies, which according to the prior art are a type of declarative policy expressed using formal descriptions that enable the NRT-RIC in the SMO to guide the nRT-RIC, and therefore the RAN, towards better fulfillment of the RAN intent); performing data analytics, Artificial Intelligence / Machine Learning (AI / ML) training and inference for RAN optimization; and / or recommending configuration management actions over the O1 interface for managing operations and maintenance (OAM), which is an interface that connects the SMO to RAN managed elements (e.g., nRT-RIC, O-RAN Centralized Unit (O-CU), O-RAN Distributed Unit (O-DU), etc.).

[0007] The nRT-RIC sits at the edge of the RAN and operates on a timescale of 10 ms to 1 s. The nRT-RIC connects to the O-DU, O-CU (split into O-CU Control Plane (O-CU-CP) and O-CU User Plane (O-CU-UP)), and Open evolved NodeB (O-eNB) via the E2 interface. The nRT-RIC uses the E2 interface to control the underlying RAN elements (E2 nodes / Network Functions (NF)) via near real-time control loops. The nRT-RIC monitors, pauses / stops, overrides, and controls the E2 nodes (O-CU-CP, O-CU-UP, O-DU, and O-eNB) via policies, and the O-DU connects to the O-RU via a fronthaul that includes the Control User Synchronization (CUS) plane and the Management (M) plane. For example, nRT sets policy parameters for activated features of E2 node. In addition, nRT-RIC hosts xApps to implement features such as Quality of Service (QoS) optimization, mobility optimization, slice optimization, interference mitigation, load balancing, security, etc. The two types of RICs work together to optimize O-RAN. For example, NRT-RIC provides policies, data, and AI / ML models to be enforced and used by nRT-RIC for RAN optimization via A1 interface, and nRT returns policy feedback (i.e., how the policies set by NRT-RIC work).

[0008] The SMO framework manages and orchestrates the RAN elements. Specifically, the SMO includes Federated O-Cloud Orchestration and Management (FOCOM), Network Function Orchestrator (NFO) that manages Virtual Machines (VM)-based Virtual Network Functions (VNFs) and container (i.e., instance)-based VNFs, and OAM as part of the SMO that manages and orchestrates what is called the O-Ran Cloud (O-Cloud). The O-Cloud is a collection of physical RAN nodes that host RIC, O-CU, and O-DU, supporting software components (e.g., operating systems and runtime environments), and the SMO itself. In other words, the SMO manages the O-Cloud from within. The O2 interface is the interface between the SMO and the O-Cloud in which it resides. Through the O2 interface, SMO provides Infrastructure Management Services (IMS) and Deployment Management Services (DMS).

[0009] According to the prior art as illustrated in FIG. 1, the NRT-RIC creates a RAN optimization policy (i.e., A1 policy for RAN optimization to satisfy RAN intent). The NRT-RIC then passes the policy (i.e., A1 policy) to the nRT-RIC on the A1 interface. Upon receiving the A1 policy, the nRT-RIC controls to implement the policy and enforces it in the control loop according to the policy guidance.

[0010] Furthermore, according to the prior art, there is no near real-time interface for connecting the nRT-RIC to the O-Cloud (i.e., an interface between the nRT-RIC and O2 management services such as IMS and / or DMS). As a result, the prior art A1 policy management is limited to RAN optimization and does not provide O-Cloud optimization policies for the nRT-RIC. This lack of near real-time interface prevents the nRT-RIC from controlling O-Cloud resources in near real-time as described above, which can lead to high latency responses and disproportionate utilization of O-Cloud computational and hardware resources. Summary of the Invention

[0011] According to an embodiment, a system and method are provided for implementing an open cloud (O-Cloud) optimization policy of a non-real-time radio access network intelligent controller (NRT-RIC) in a service management and orchestration (SMO) framework of a telecommunication network by an application hosted in a near real-time radio access network intelligent controller (nRT-RIC) of the telecommunication network, the nRT-RIC receiving the O-Cloud optimization policy from the NRT-RIC and controlling the implementation of the O-Cloud optimization policy in an O-Cloud computing environment in the O-RAN via a direct interface between the nRT-RIC and the O-Cloud computing environment. In particular, the system and method provide an O-RAN architecture for O-Cloud resource optimization via the nRT-RIC by including an interface between the nRT-RIC and the O-Cloud that allows a defined response time of 10ms to 1s and reduces O-Cloud resource control latency. Low latency O-Cloud resource control results in faster implementation of O-Cloud optimization policies, which has the advantage of achieving energy-efficient network operation of the O-Cloud computing environment.

[0012] According to an embodiment, a system for implementing an Open Cloud (O-Cloud) optimization policy by an application hosted in a near real-time Radio Access Network Intelligent Controller (nRT-RIC) of a telecommunications network includes a memory storing instructions and at least one processor configured to implement the nRT-RIC within an Open Radio Access Network (O-RAN) architecture, the at least one processor configured to execute instructions to receive an O-Cloud optimization policy from a non-real-time Radio Access Network Intelligent Controller (NRT-RIC) within a Service Management and Orchestration (SMO) framework of the telecommunications network and control implementation of the O-Cloud optimization policy in an O-Cloud computing environment within the O-RAN.

[0013] The at least one processor may be further configured to execute instructions to receive an O-Cloud optimization policy from an NRT-RIC in the SMO framework via an A1 interface.

[0014] The at least one processor may be further configured to execute instructions to control implementation of an O-Cloud optimization policy in an O-Cloud computing environment in the O-RAN via an O2 interface.

[0015] The at least one processor may be further configured to execute instructions to receive data comprising at least one of performance data and event data from at least one physical host in the O-Cloud computing environment in the O-RAN via the O2 interface.

[0016] The at least one processor may be further configured to execute instructions to send and receive data for at least one O2 managed service in the O-Cloud computing environment via the O2 interface.

[0017] The at least one processor may be further configured to execute instructions to control implementation of the O-Cloud optimization policy via at least one O2 management service in the O-Cloud computing environment via the O2 interface.

[0018] The performance data of the at least one physical host may include processor load, memory usage, and hard disk drive usage of the at least one physical host.

[0019] According to an embodiment, a method for implementing an Open Cloud (O-Cloud) optimization policy by an application hosted in a Near Real-Time Radio Access Network Intelligent Controller (nRT-RIC) of a telecommunications network includes receiving, by the nRT-RIC, an O-Cloud optimization policy from a Non-Real-Time Radio Access Network Intelligent Controller (NRT-RIC) within a Service Management and Orchestration (SMO) framework of the telecommunications network, and controlling, by the nRT-RIC, implementation of the O-Cloud optimization policy in an O-Cloud computing environment within the O-RAN.

[0020] The method may include receiving, by the nRT-RIC, an O-Cloud optimization policy from the NRT-RIC within the SMO framework via an A1 interface.

[0021] The method may include controlling, by the nRT-RIC, to implement an O-Cloud optimization policy in an O-Cloud computing environment in the O-RAN via an O2 interface.

[0022] The method may include receiving, by the nRT-RIC, data including at least one of performance data and event data from at least one physical host in an O-Cloud computing environment in the O-RAN via an O2 interface.

[0023] The method may include transmitting, by the nRT-RIC, data for at least one O2 managed service in the O-Cloud computing environment via an O2 interface.

[0024] The method may include controlling, by the nRT-RIC, to implement the O-Cloud optimization policy via at least one O2 management service in the O-Cloud computing environment via an O2 interface.

[0025] The performance data of the at least one physical host may include processor load, memory usage, and hard disk drive usage of the at least one physical host.

[0026] According to an embodiment, a non-transitory computer-readable recording medium has recorded thereon instructions executable by at least one processor configured to perform a method for implementing a near real-time radio access network intelligent controller (nRT-RIC) within an open radio access network (O-RAN) architecture to implement an open cloud (O-Cloud) optimization policy by an application hosted on the nRT-RIC, the method including receiving, by the nRT-RIC, an O-Cloud optimization policy from a non-real-time radio access network intelligent controller (NRT-RIC) within a service management and orchestration (SMO) framework of a telecommunications network, and controlling, by the nRT-RIC, implementing the O-Cloud optimization policy in an O-Cloud computing environment within the O-RAN.

[0027] The method may include receiving, by the nRT-RIC, an O-Cloud optimization policy from the NRT-RIC within the SMO framework via an A1 interface.

[0028] The method may include controlling, by the nRT-RIC, to implement an O-Cloud optimization policy in an O-Cloud computing environment in the O-RAN via an O2 interface.

[0029] The method may include receiving, by the nRT-RIC, data including at least one of performance data and event data from at least one physical host in an O-Cloud computing environment in the O-RAN via an O2 interface.

[0030] The method may include transmitting, by the nRT-RIC, data for at least one O2 managed service in the O-Cloud computing environment via an O2 interface.

[0031] The method may include controlling, by the nRT-RIC, to implement the O-Cloud optimization policy via at least one O2 management service in the O-Cloud computing environment via an O2 interface.

[0032] Additional aspects will be set forth in part in the description that follows, and in part will be apparent from the description, or may be realized by practice of illustrative embodiments of the present disclosure. [Brief description of the drawings]

[0033] Features, aspects, and advantages of certain exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which like reference numerals refer to like elements.

[0034] [Figure 1] FIG. 1 illustrates an O-RAN architecture according to the prior art. [Diagram 2] FIG. 1 illustrates a system for O-Cloud resource optimization via nRT-RIC in an O-RAN architecture, according to one or more embodiments. [Diagram 3] FIG. 1 is a flowchart of a method for implementing an Open Cloud (O-Cloud) optimization policy using an interface between an nRT-RIC and an O-Cloud, according to an embodiment. [Figure 4] FIG. 1 illustrates an example environment in which the systems and / or methods described herein may be implemented. [Diagram 5] FIG. 2 is a diagram of exemplary components of a device, according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0035] The following detailed description of the exemplary embodiments refers to the accompanying drawings, in which the same reference numbers in different drawings may identify the same or similar elements, and in which:

[0036] The foregoing disclosure provides illustrations and descriptions, but is not intended to be exhaustive or to limit the implementations to the precise forms disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations. Furthermore, one or more features or components of one embodiment may be incorporated into or combined with another embodiment (or one or more features of another embodiment). In addition, in the flowcharts and descriptions of operations provided below, it should be understood that one or more operations may be omitted, one or more operations may be added, one or more operations may be performed (at least partially) simultaneously, and the order of one or more operations may be rearranged.

[0037] It will be apparent that the systems and / or methods described herein may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not intended to limit the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code. It should be understood that software and hardware may be designed to implement the systems and / or methods based on the description herein.

[0038] Even if particular combinations of features are recited in a claim and / or disclosed herein, these combinations are not intended to limit the disclosure of possible implementations. Indeed, many of these features may be combined in ways not specifically recited in the claims and / or disclosed herein. Although each dependent claim listed below may depend directly on only one claim, the disclosure of possible implementations includes each dependent claim in combination with all other claims in the claim set.

[0039] No element, act, or instruction used herein should be construed as critical or essential unless expressly described as such. Also, as used herein, the articles "a" and "an" are intended to include one or more items and may be used synonymously with "one or more." When only one item is intended, the term "one" or similar phrases are used. Also, as used herein, terms such as "has," "have," "having," "include," "including," and the like are intended to be open-ended terms. Furthermore, the phrase "based on" is intended to mean "based, at least in part, on," unless specifically noted otherwise. Furthermore, phrases such as "at least one of [A] and [B]" or "at least one of [A] or [B]" should be understood to include only A, only B, or both A and B.

[0040] 2 illustrates a system for O-Cloud resource optimization via nRT-RIC in an O-RAN architecture, according to one or more embodiments. With reference to FIG. 2, the key components of the O-RAN architecture are similar to FIG. 1.

[0041] In FIG. 2, the nRT-RIC connects to the E2 node (i.e., O-CU-CP, O-CU-UP, O-DU, etc.) via the E3 interface. The nRT-RIC includes multiple applications, so-called xApps, and services required to support the execution of the xApps. The xApps may be one or more microservices that can be used to implement radio resource management through the interface and service model. The prior art xApp receives data from the RAN (e.g., Key Performance Indicators (KPIs) of the E2 node) and, if necessary, calculates and sends back (e.g., to the E2 node) control actions according to the A1 policies for RAN optimization received from the NRT-RIC via the A1 interface.

[0042] The nRT-RIC is deployed at the edge of the RAN and operates control loops and analysis functions with a defined periodicity of 10 ms to 1 s. This defined response time periodicity (i.e., defined latency) allows the nRT-RIC to realize the analysis and control functions of the RAN in near real-time. Furthermore, the defined latency of the nRT-RIC has an upper latency limit equal to or less than that of the NRT-RIC in the SMO (i.e., the minimum response time of the NRT-RIC is 1 second, and no upper latency limit is defined).

[0043] Furthermore, since the nRT-RIC is located at the edge of the O-RAN network, it is also closer to the O-Cloud computing and hardware resources that host E2 node applications (i.e., applications such as O-CU-CP, O-CU-UP, O-DU, etc. that are launched in the O-Cloud).

[0044] Referring to FIG. 2, the nRT-RIC includes one or more xApps that receive data (i.e., performance data and / or event data) from the O-Cloud computing environment and, if necessary, calculate and send back control actions to implement Open Cloud (O-Cloud) optimization policies (e.g., O-Cloud resource optimization policies, O-Cloud infrastructure optimization policies, etc.) in the O-Cloud computing environment.

[0045] To this end, the O2 interface extends to or terminates at the nRT-RIC, In another exemplary embodiment, the O2 interface may branch to the nRT-RIC.

[0046] According to one embodiment, the O2 interface between the nRT-RIC and the O-Cloud computing environment enables low latency data communication between the nRT-RIC and the O-Cloud computing environment (i.e., the O-Cloud computing resources that host applications of the E2 node).

[0047] In an example embodiment, the nRT-RIC (e.g., one or more xApps of the nRT-RIC) may obtain O2 interface data via an Application Programming Interface (API) of the O2 interface. The O2 interface data may include O-Cloud resource data, such as O-Cloud infrastructure data of the O-Cloud environment from O2 management services (i.e., Infrastructure Management Services (IMS) and Deployment Management Services (DMS)).

[0048] For example, the IMS connects with the nRT-RIC and the O2 interface provides functionality responsible for deploying and managing cloud infrastructure resources (i.e., the IMS orchestrates the O-Cloud infrastructure).

[0049] In another example, the DMS may interface with the nRT-RIC, and the O2 interface provides a set of interface functions responsible for managing virtualized / containerized deployments on the O-Cloud infrastructure (i.e., the DMS orchestrates virtualized / containerized deployments of E2 node applications).

[0050] As a result, one of the two service-based interfaces (SBIs) of the O2 interface (IMS and / or DMS) between the SMO framework and the O-Cloud platform (FOCOM-IMS and NFO-DMS) through the O2 interface in Figure 2 communicates with and / or terminates in the nRT-RIC.

[0051] With further reference to FIG. 2, the NRT-RIC in the SMO also provides A1 policies for optimization of the O-Cloud (e.g., O-Cloud resource policies, O-Cloud infrastructure policies, etc.) in addition to A1 policies to guide the nRT-RIC towards better fulfillment of the RAN intent (i.e., RAN optimization policies).

[0052] For this purpose, the NRT-RIC according to FIG. 2 provides an A1 policy to guide the nRT-RIC towards optimization of the O-Cloud computing environment in the O-RAN (i.e., an O-Cloud optimization policy), and the nRT-RIC, based on receiving the A1 policy, acts on the policy to control implementation of the O-Cloud resource optimization policy in the O-Cloud computing environment via an O2 interface with an O2 management service in the O-Cloud (e.g., the nRT-RIC may start acting on the policy and implement a control loop of implementation of the O-Cloud resource optimization policy for the O-Cloud computing resources).

[0053] In an exemplary embodiment, the interface between the nRT-RIC and the O-Cloud computing environment according to FIG. 2 (i.e., the O2 management service orchestrates either the virtualized / containerized deployment of physical hosts such as servers or server clusters or the E2 node applications of the O-RAN) may be a bidirectional interface that allows the nRT-RIC to control the implementation of O-Cloud optimization policies in the O-Cloud computing environment in the O-RAN. The nRT-RIC receives data including at least one of performance data and event data from at least one physical host in the O-Cloud computing environment in the O-RAN via the O2 interface. In an exemplary embodiment, the performance data and event data of the at least one physical host in the O-Cloud computing environment may include O-Cloud infrastructure data such as processor load, memory usage, hard disk drive usage, etc. of the at least one physical host.

[0054] Furthermore, the interface between the nRT-RIC and the O-Cloud computing environment according to FIG. 2 enables the SMO framework (e.g., the NRT-RIC) to more efficiently apply the O-Cloud optimization policy (i.e., the A1 policy received from the NRT-RIC).

[0055] The technical advantage of the O2 interface according to FIG. 2 as described above over the prior art O2 interface is that it enables O-Cloud optimization policy implementation in the nRT-RIC, thereby achieving a significant reduction in response time latency (i.e., periodicity of the control loop) by interfacing the nRT-RIC with the O-Cloud computing environment (i.e., management services orchestrating O-Cloud resources).

[0056] In particular, the O2 interface according to the O-RAN architecture of FIG. 2 allows the nRT-RIC to access the O2 interface data (i.e., non-RAN data) and take action (or implement) on the A1 policy (i.e., O-Cloud resource optimization policy) received from the nRT-RIC.

[0057] The defined response latency of the nRT-RIC has the technical effect that changes (i.e., optimizations) in the O-Cloud can be achieved between 10 ms and 1 s, where 1 s is the maximum period of the nRT-RIC control loop for implementing the A1 policy (i.e., O-Cloud resource optimization policy) in the O-Cloud computing environment in near real-time.

[0058] As a result, the interface between nRT-RIC and O-Cloud with the O-RAN architecture for O-Cloud resource optimization via nRT-RIC (i.e., management services orchestrate O-Cloud resources) allows for a significant reduction in O-Cloud resource control latency. Low latency O-Cloud resource control results in faster implementation of O-Cloud optimization policies, which has the advantage of being able to achieve energy-efficient network operation of the O-Cloud computing environment.

[0059] FIG. 3 is a diagram of a flowchart of a method for implementing an O-Cloud optimization policy using an interface between an nRT-RIC and an O-Cloud, according to an embodiment.

[0060] 3, in operation 301, the NRT-RIC creates an O-Cloud optimization policy (i.e., an A1 policy for optimization of the O-Cloud). To this end, the NRT-RIC in the SMO framework controls the O-Cloud strategy through AI / ML learning from network data (e.g., performance data and event data from at least one physical host in the O-Cloud computing environment received via the O2 interface, performance data and / or event data from the O-RAN function via the O1 interface, etc.).

[0061] In operation 302, the nRT-RIC receives an O-Cloud optimization policy from the NRT-RIC. For example, the nRT-RIC receives the O-Cloud optimization policy in the form of an A1 policy.

[0062] In operation 303, upon receiving the policy for O-Cloud optimization, the nRT-RIC begins to act based on the policy. In an example embodiment of FIG. 3, the nRT-RIC may control the implementation of the O-Cloud optimization policy to the O-Cloud computing environment in the O-RAN. For example, one or more xApps in the nRT-RIC may connect to an O2 management service (i.e., IMS and / or DMS) that orchestrates the O-Cloud computing environment, and the xApps via the O2 interface API may receive data from the O2 management service (i.e., performance data and / or event data such as non-RAN data) and, if necessary, calculate and send back control actions to implement the O-Cloud optimization policy in the O-Cloud computing environment.

[0063] In operation 304, the O-Cloud computing environment in the O-RAN (i.e., the O2 management service (IMS and / or DMS) orchestrating the O-Cloud computing environment) implements the O-Cloud optimization policy. For example, the O2 management service may implement auto-scaling of O-Cloud instances (i.e., auto-scaling of virtualized / containerized deployment of E2 node applications) according to the O-Cloud optimization policy, and the IMS orchestrates resource management policies according to the use cases manifested in the O-Cloud optimization policy provided by the NRT-RIC.

[0064] In operation 305, the nRT-RIC receives data including at least one of performance data and event data from at least one physical host in an O-Cloud computing environment in the O-RAN to control implementation of O-Cloud optimization policies as requested (e.g., an O2 management service (IMS and / or DMS) may provide non-RAN data to the nRT-RIC).

[0065] For example, operations 303, 304, and 305 of FIG. 3 may be performed over the O2 interface of FIG. 2 and may be performed sequentially, simultaneously, or in a different order, continuously, periodically, etc.

[0066] According to the embodiment of FIG. 3, access to the O2 interface allows the nRT-RIC to control the adaptation of various scenarios and objectives; in particular, the fast response time of the nRT-RIC over the O2 interface allows RAN operators (i.e., Mobile Network Operators (MNOs)) to specify different objectives for network function placement according to a wide variety of scenarios, allowing for more flexible configuration of optimization policies within the SMO.

[0067] 4 is a diagram of an example environment 400 in which the systems and / or methods described herein may be implemented. As shown in FIG. 4, environment 400 may include a user device 410, a platform 420, and a network 430. The devices of environment 400 may be interconnected via wired connections, wireless connections, or a combination of wired and wireless connections. In an embodiment, any of the functions and operations described with reference to FIG. 1 above may be implemented by any combination of elements illustrated in FIG. 4.

[0068] The user device 410 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information related to the platform 420. For example, the user device 410 may include a computing device (e.g., a desktop computer, a laptop computer, a tablet computer, a handheld computer, a smart speaker, a server, etc.), a mobile phone (e.g., a smartphone, a wireless telephone, etc.), a wearable device (e.g., smart glasses or a smart watch), or a similar device. In some implementations, the user device 410 may receive information from and / or transmit information to the platform 420.

[0069] Platform 420 includes one or more devices capable of receiving, generating, storing, processing, and / or providing information. In some implementations, platform 420 may include a cloud server or a group of cloud servers. In some implementations, platform 420 may be designed to be modular, such that certain software components may be swapped in or out depending on particular needs. Thus, platform 420 may be easily and / or quickly reconfigured for different uses.

[0070] In some implementations, as shown, platform 420 may be hosted in a cloud computing environment 422. In particular, although the implementations described herein describe platform 420 as being hosted within cloud computing environment 422, in some implementations platform 420 may not be cloud-based (i.e., may be implemented outside of a cloud computing environment) or may be partially cloud-based.

[0071] Cloud computing environment 422 includes an environment that hosts platform 420. Cloud computing environment 422 may provide services such as computing, software, data access, storage, etc. that do not require end-user (e.g., user device 410) knowledge of the physical location and configuration of the systems and / or devices that host platform 420. As shown, cloud computing environment 422 may include a collection of computational resources 424 (collectively referred to as “computational resources 424” and individually referred to as “computational resource 424”).

[0072] The computational resources 424 include one or more personal computers, clusters of computing devices, workstation computers, server devices, or other types of computing and / or communication devices. In some implementations, the computational resources 424 may host the platform 420. Cloud resources may include computing instances executing within the computational resources 424, storage devices provided within the computational resources 424, data transfer devices provided by the computational resources 424, etc. In some implementations, the computational resources 424 may communicate with other computational resources 424 via wired connections, wireless connections, or a combination of wired and wireless connections.

[0073] As further shown in FIG. 4, the computing resources 424 include a group of cloud resources, such as one or more applications ("APP (Application)") 424-1, one or more virtual machines ("VM (Virtual Machine)") 424-2, virtualized storage ("VS (Virtualized Storage)") 424-3, and one or more hypervisors ("HYP (Hypervisor)") 424-4.

[0074] Applications 424-1 include one or more software applications that may be provided to or accessed by user device 410. Applications 424-1 may eliminate the need to install and run software applications on user device 410. For example, applications 424-1 may include software related to platform 420 and / or any other software that may be provided via cloud computing environment 422. In some implementations, one application 424-1 may send information to or receive information from one or more other applications 424-1 via virtual machine 424-2.

[0075] Virtual machine 424-2 includes a software-implemented machine (e.g., a computer) that executes programs like a physical machine. Virtual machine 424-2 can be either a system virtual machine or a process virtual machine, depending on the use and the degree to which virtual machine 424-2 matches any real machine. A system virtual machine can provide a complete system platform that supports the execution of a complete operating system ("OS"). A process virtual machine can execute a single program and support a single process. In some implementations, virtual machine 424-2 can run on behalf of a user (e.g., user device 410) and manage the infrastructure of cloud computing environment 422, such as data management, synchronization, or long-term data transfer.

[0076] Virtualized storage 424-3 includes one or more storage systems and / or one or more devices that use virtualization technology within the storage systems or devices of the computing resources 424. In some implementations, in the context of storage systems, types of virtualization may include block virtualization and file virtualization. Block virtualization may refer to the abstraction (or separation) of logical storage from physical storage such that the storage system may be accessed without regard to the physical storage or heterogeneous structure. The separation may allow administrators flexibility in the storage system as to how they manage the storage for end users. File virtualization may eliminate the dependency between data accessed at the file level and where the file is physically stored. This may enable optimization of storage usage, server consolidation, and / or implementation of non-disruptive file movement.

[0077] The hypervisor 424-4 may provide hardware virtualization technology that allows multiple operating systems (e.g., "guest operating systems") to run simultaneously on a host computer, such as the computing resource 424. The hypervisor 424-4 may present a virtual operating platform to the guest operating systems and may manage the execution of the guest operating systems. Multiple instances of different operating systems may share virtualized hardware resources.

[0078] Network 430 may include one or more wired and / or wireless networks, such as, for example, a cellular network (e.g., a Fifth Generation (5G) network, a Long-Term Evolution (LTE) network, a Third Generation (3G) network, a Code Division Multiple Access (CDMA) network, etc.), a Public Land Mobile Network (PLMN), a Local Area Network (LAN), a Wide Area Network (WAN), a Metropolitan Area Network (MAN), a telephone network (e.g., a Public Switched Telephone Network (PSTN)), a private network, an ad-hoc network, an intranet, the Internet, an optical fiber-based network, etc., and / or any of these or other types of networks.

[0079] It may include a combination of networks.

[0080] The number and arrangement of devices and networks shown in Figure 4 are provided as an example. In practice, there may be more devices and / or networks than those shown in Figure 4, fewer devices and / or networks, different devices and / or networks than those shown in Figure 4, or differently arranged devices and / or networks. Furthermore, two or more devices shown in Figure 4 may be implemented within a single device, or a single device shown in Figure 4 may be implemented as multiple distributed devices. Additionally, or instead, a set of devices (e.g., one or more devices) of environment 400 may perform one or more functions that are described as being performed by another set of devices of environment 400.

[0081] 5 is a diagram of example components of a device 500. The device 500 may correspond to a user device 510 and / or a platform 520. As shown in FIG. 5, the device 500 may include a bus 510, a processor 520, a memory 530, a storage component 540, an input component 550, an output component 560, and a communication interface 570.

[0082] The bus 510 includes components that enable communication between the components of the device 500. The processor 520 may be implemented in hardware, firmware, or a combination of hardware and software. The processor 520 may be a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Accelerated Processing Unit (APU), a microprocessor, a microcontroller, a Digital Signal Processor (DSP), a Field-Programmable Gate Array (FPGA), an Application-Specific Integrated Circuit (ASIC), or another type of processing component. In some implementations, the processor 520 includes one or more processors that can be programmed to perform functions. Memory 530 may include Random Access Memory (RAM), Read-Only Memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions for use by processor 520.

[0083] The storage component 540 stores information and / or software related to the operation and use of the device 500. For example, the storage component 540 may include a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optical disk, and / or a solid-state disk), a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and / or another type of non-transitory computer-readable medium along with a corresponding drive. The input component 550 includes components that enable the device 500 to receive information via user input (e.g., a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, and / or a microphone), and the like. Additionally or alternatively, the input component 550 may include sensors for sensing information (e.g., a Global Positioning System (GPS) component, an accelerometer, a gyroscope, and / or an actuator). Output components 560 include components that provide output information from device 500, such as a display, a speaker, and / or one or more Light-Emitting Diodes (LEDs).

[0084] The communications interface 570 includes transceiver-like components (e.g., a transceiver and / or a separate receiver and transmitter) that enable the device 500 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. The communications interface 570 may enable the device 500 to receive information from another device and / or provide information to another device. For example, the communications interface 570 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a Radio Frequency (RF) interface, a Universal Serial Bus (USB) interface, a Wi-Fi interface, a cellular network interface, etc.

[0085] The device 500 may perform one or more processes described herein. The device 500 may perform these processes in response to the processor 520 executing software instructions stored by a non-transitory computer-readable medium, such as the memory 530 and / or the storage component 540. A computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices.

[0086] The software instructions may be loaded into the memory 530 and / or storage component 540 from another computer-readable medium or from another device via the communications interface 570. When executed, the software instructions stored in the memory 530 and / or storage component 540 may cause the processor 520 to perform one or more processes described herein.

[0087] Additionally, or instead, hardwired circuitry may be used in place of or in combination with software instructions to implement one or more processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software.

[0088] The number and arrangement of components shown in Figure 5 are provided as an example. In practice, device 500 may include more, fewer, different, or differently arranged components than those shown in Figure 5. Additionally or alternatively, a set of components (e.g., one or more components) of device 500 may include:

[0089] One or more of the functions described as being performed by different sets of components of device 500 may be performed.

[0090] In an embodiment, any one of the operations or processes of Figures 1, 2, and 3 may be implemented by or using any one of the elements illustrated in Figures 4 and 5.

[0091] According to an embodiment, a system and method for implementing an O-Cloud optimization policy is provided, in which an nRT-RIC controls an O-Cloud computing environment in an O-RAN to implement the O-Cloud optimization policy through a direct interface between the nRT-RIC and the O-Cloud computing environment. The direct interface nRT-RIC and the O-Cloud reduces latency to near real-time. As a result, low-latency resource control enables energy-efficient network operation of the RAN.

[0092] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementations to the precise forms disclosed. Modifications and variations may be possible in light of the above disclosure or may be acquired from practice of the implementations.

[0093] Some embodiments may relate to systems, methods, and / or computer-readable media in any possible level of technical detail integration. Furthermore, one or more of the above components described above may be implemented as instructions stored on a computer-readable medium and executable by at least one processor (and / or may include at least one processor). A computer-readable medium may include a computer-readable non-transitory recording medium(s) having computer-readable program instructions thereon to cause a processor to perform operations.

[0094] A computer readable storage medium may be a tangible device capable of holding and storing instructions for use by an instruction execution device. A computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer readable storage media includes portable computer diskettes, hard disks, Random Access Memory (RAM), Read-Only Memory (ROM), Erasable Programmable Read-Only Memory (EPROM) or Flash memory, Static Random Access Memory (SRAM), portable Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disk (DVD), memory sticks, floppy disks, mechanically encoded devices such as punch cards or ridge structures in a groove on which instructions are recorded, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, should not be construed as being, per se, a transitory signal, such as an electric wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., light pulses passing through a fiber optic cable), or an electrical signal transmitted through a wire.

[0095] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to an individual computing / processing device or to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may comprise copper transmission cables, optical transmission fiber, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the individual computing / processing device.

[0096] The computer readable program code / instructions for performing the operations may be either source code or object code written in any combination of one or more programming languages, including assembler instructions, Instruction-Set-Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for an integrated circuit, or object-oriented programming languages ​​such as Smalltalk, C++, and procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuits, Field-Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry to perform an aspect or operation.

[0097] These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, whereby the instructions executing via the processor of the computer or other programmable data processing apparatus create means for implementing the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams. These computer readable program instructions may also be stored on a computer readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, whereby the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions that implement aspects of the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0098] The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device and cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to generate a computer-implemented process, whereby the instructions executing on the computer, other programmable apparatus, or other device implement the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0099] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer-readable media according to various embodiments. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or part of an instruction that comprises one or more executable instructions for implementing a specified logical function. The methods, computer systems, and computer-readable media may include more, fewer, different, or differently arranged blocks than those depicted in the figures. In some alternative implementations, the functions described in the blocks may occur in a different order than that described in the figures. For example, two blocks shown in succession may actually be executed simultaneously or substantially simultaneously, or the blocks may be executed in reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart diagrams, and combinations of blocks in the block diagrams and / or flowchart diagrams, may be implemented by a special-purpose hardware-based system that performs the specified functions or actions or performs a combination of special-purpose hardware and computer instructions.

[0100] It will be apparent that the systems and / or methods described herein may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and / or methods is not intended to limit the implementation. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code, and it will be understood that software and hardware can be designed to implement the systems and / or methods based on the description herein.

Claims

1. 1. A system for implementing an Open Cloud (O-Cloud) optimization policy by an application hosted on a near real-time Radio Access Network Intelligent Controller (nRT-RIC) of a telecommunications network, comprising: A memory for storing instructions; at least one processor configured to implement the nRT-RIC within an Open Radio Access Network (O-RAN) architecture; The at least one processor executes the instructions to: The system is configured to receive the O-Cloud optimization policy from a Non-Real-Time Radio Access Network Intelligent Controller (NRT-RIC) within a Service Management and Orchestration (SMO) framework of the telecommunications network, and to control implementation of the O-Cloud optimization policy in the O-Cloud computing environment within the O-RAN.

2. The at least one processor executes the instructions to: The system of claim 1 , configured to receive the O-Cloud optimization policy from the NRT-RIC in the SMO framework via an A1 interface.

3. The at least one processor executes the instructions to: The system of claim 2, configured to control implementation of the O-Cloud optimization policy in the O-Cloud computing environment in the O-RAN via an O2 interface.

4. The at least one processor executes the instructions to:

4. The system of claim 3, further configured to receive data comprising at least one of performance data and event data from at least one physical host in the O-Cloud computing environment in the O-RAN via the O2 interface.

5. The at least one processor executes the instructions to: The system of claim 4 , further configured to transmit and receive data of at least one O2 managed service in the O-Cloud computing environment via the O2 interface.

6. The at least one processor executes the instructions to: The system of claim 2 , further configured to control implementation of the O-Cloud optimization policy via at least one O2 management service in the O-Cloud computing environment via an O2 interface.

7. The system of claim 4 , wherein the performance data of the at least one physical host includes processor load, memory usage, and hard disk drive usage of the at least one physical host.

8. 1. A method for implementing an Open Cloud (O-Cloud) optimization policy by an application hosted in a near real-time Radio Access Network Intelligent Controller (nRT-RIC) of a telecommunications network, comprising: receiving, by the nRT-RIC, the O-Cloud optimization policy from a non-real-time radio access network intelligent controller (NRT-RIC) within a service management and orchestration (SMO) framework of the telecommunications network; Controlling, by the nRT-RIC, the implementation of the O-Cloud optimization policy in the O-Cloud computing environment in the O-RAN; A method comprising:

9. The method comprises: The method of claim 8, comprising receiving, by the nRT-RIC, the O-Cloud optimization policy from the NRT-RIC in the SMO framework via an A1 interface.

10. The method comprises: The method of claim 9, comprising controlling, by the nRT-RIC, to implement the O-Cloud optimization policy in the O-Cloud computing environment in the O-RAN via an O2 interface.

11. The method comprises:

11. The method of claim 10, comprising receiving, by the nRT-RIC, data comprising at least one of performance data and event data from at least one physical host in the O-Cloud computing environment in the O-RAN via the O2 interface.

12. The method comprises: The method of claim 11, comprising transmitting and receiving data of at least one O2 managed service in the O-Cloud computing environment via the O2 interface by the nRT-RIC.

13. The method comprises:

10. The method of claim 9, further comprising controlling, by the nRT-RIC, to implement the O-Cloud optimization policy via at least one O2 management service in the O-Cloud computing environment via an O2 interface.

14. The method of claim 11 , wherein the performance data of the at least one physical host includes processor load, memory usage, and hard disk drive usage of the at least one physical host.

15. 1. A non-transitory computer-readable storage medium having instructions executable by at least one processor recorded thereon, the non-transitory computer-readable storage medium being configured to perform a method for implementing a near real-time radio access network intelligent controller (nRT-RIC) in an open radio access network (O-RAN) architecture to implement an open cloud (O-Cloud) optimization policy by an application hosted on the nRT-RIC, the method comprising: receiving, by the nRT-RIC, the O-Cloud optimization policy from a non-real-time radio access network intelligent controller (NRT-RIC) within a service management and orchestration (SMO) framework of the telecommunications network; and controlling, by the nRT-RIC, to implement the O-Cloud optimization policy in the O-Cloud computing environment in the O-RAN.

16. The method comprises:

16. The non-transitory computer-readable medium of claim 15, comprising receiving, by the nRT-RIC, the O-Cloud optimization policy from the NRT-RIC in the SMO framework via an A1 interface.

17. The method comprises: The non-transitory computer-readable storage medium of claim 16, further comprising controlling, by the nRT-RIC, to implement the O-Cloud optimization policy in the O-Cloud computing environment in the O-RAN via an O2 interface.

18. The method comprises:

20. The non-transitory computer-readable storage medium of claim 17, further comprising receiving, by the nRT-RIC, data including at least one of performance data and event data from at least one physical host in the O-Cloud computing environment in the O-RAN via the O2 interface.

19. The method comprises:

20. The non-transitory computer-readable medium of claim 18, further comprising transmitting and receiving data of at least one O2 managed service in the O-Cloud computing environment via the O2 interface by the nRT-RIC.

20. The method comprises:

17. The non-transitory computer-readable storage medium of claim 16, further comprising controlling, by the nRT-RIC, to implement the O-Cloud optimization policy via at least one O2 management service in the O-Cloud computing environment via an O2 interface.

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