Apparatus and method of data pipeline measurement and reporting

Abstract

A method of data pipeline measurement and reporting performed by a data pipeline coordinator includes transmitting a measurement configuration and reporting criteria to at least one data pipeline contributor, receiving, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria, and performing a data pipeline control action based on the measurement report.

Description

Atty. Dkt. No. 10085-01-0187-PCTAPPARATUS AND METHOD OF DATA PIPELINE MEASUREMENT ANDREPORTINGCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 63 / 728,089, entitled “METHOD AND APPARATUS FOR DATA PIPELINE CONTRIBUTOR MEASUREMENT AND REPORTING,” filed on December 4, 2024, and to U.S. Provisional Application No. 63 / 733,324, entitled “METHOD AND APPARATUS OF Al SERVICE FLOW CONTRIBUTOR SELECTION BASED ON QUALITY OF WIRELESS INTERFACE,” filed on December 12, 2024, the entire disclosures of which are hereby incorporated by reference in their entirety.TECHNICAL FIELD

[0002] The present disclosure relates to the field of communication systems, and more particularly, to apparatuses and methods of data pipeline measurement and reporting.BACKGROUND

[0003] In sixth generation (6G) communication systems, a data plane is introduced to enable trusted data collection, storage, access, and sharing across distributed network environments. To support these operations, a new network entity referred to as a data plane access controller (DPAC) has been proposed, functioning as a management or control unit between the 6G core network and the data plane infrastructure to handle tasks such as data collection, identity verification, processing, and interaction with data storage facilities. Within this framework, a data pipeline provides efficient and automated data flow among multiple network entities, including data sources, contributors, and receivers that cooperatively perform data acquisition, transformation, and delivery. However, during operation, some data pipeline nodes may become unavailable or experience degraded performance, requiring data pipeline measurement and reporting to dynamically reconfigure the pipeline by selecting alternative nodes or paths to ensure stability and service continuity.

[0004] In existing 3GPP systems, a DPAC may select data pipeline contributors (DPCs) based on computing power, latency, or data characteristics; yet, when a user equipment (UE) acts as a DPC, the current selection mechanisms fail to consider the air interface quality between the UE and the radio access network (RAN), potentially degrading data pipeline efficiency and reliability in data plane operations.

[0005] Therefore, there is a need for apparatuses and methods of data pipeline measurement and reporting.Atty. Dkt. No. 10085-01-0187-PCTSUMMARY

[0006] An object of the present disclosure is to propose apparatuses and methods of data pipeline measurement and reporting, which can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0007] In a first aspect of the present disclosure, a method of data pipeline measurement and reporting performed by a data pipeline coordinator includes transmitting a measurement configuration and reporting criteria to at least one data pipeline contributor, receiving, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria, and performing a data pipeline control action based on the measurement report.

[0008] In a second aspect of the present disclosure, a data pipeline coordinator includes a transceiver and an executor. The transceiver is configured to transmit a measurement configuration and reporting criteria to at least one data pipeline contributor and receive, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria, and the executor is configured to perform a data pipeline control action based on the measurement report.

[0009] In a third aspect of the present disclosure, a data pipeline coordinator includes a memory, a transceiver, and a processor coupled to the memory and the transceiver. The data pipeline coordinator is configured to perform the above method.

[0010] In a fourth aspect of the present disclosure, a method of data pipeline measurement and reporting performed by a data pipeline contributor includes receiving, from a data pipeline coordinator, a measurement configuration and reporting criteria, performing at least one measurement according to the measurement configuration, and transmitting a measurement report to the data pipeline coordinator when the reporting criteria are satisfied.

[0011] In a fifth aspect of the present disclosure, a data pipeline contributor includes a transceiver and an executor. The transceiver is configured to receive, from a data pipeline coordinator, a measurement configuration and reporting criteria, the executor is configured to perform at least one measurement according to the measurement configuration, and the transceiver is configured to transmit a measurement report to the data pipeline coordinator when the reporting criteria are satisfied.Atty. Dkt. No. 10085-01-0187-PCT

[0012] In a sixth aspect of the present disclosure, a data pipeline contributor includes a memory, a transceiver, and a processor coupled to the memory and the transceiver. The data pipeline contributor is configured to provide the above method.

[0013] In a seventh aspect of the present disclosure, a non-transitory machine-readable storage medium has stored thereon instructions that, when executed by a computer, cause the computer to perform the above method.

[0014] In an eighth aspect of the present disclosure, a chip includes a processor, configured to call and run a computer program stored in a memory, to cause a device in which the chip is installed to execute the above method.

[0015] In a ninth aspect of the present disclosure, a computer readable storage medium, in which a computer program is stored, causes a computer to execute the above method.

[0016] In a tenth aspect of the present disclosure, a computer program product includes a computer program, and the computer program causes a computer to execute the above method.

[0017] In an eleventh aspect of the present disclosure, a computer program causes a computer to execute the above method.BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to illustrate the embodiments of the present disclosure or related art more clearly, the following figures will be described in the embodiments are briefly introduced. It is obvious that the drawings are merely some embodiments of the present disclosure, a person having ordinary skill in this field can obtain other figures according to these figures without paying the premise.

[0019] FIG. l is a block diagram of an architecture of 6G data plane according to an embodiment of the present disclosure.

[0020] FIG. 2 is a block diagram of a data pipeline in 6G data plane according to an embodiment of the present disclosure.

[0021] FIG. 3 is a block diagram of a data plane architecture according to an embodiment of the present disclosure.

[0022] FIG. 4 is a diagram of data pipeline communication flows according to an embodiment of the present disclosure.

[0023] FIG. 5 is a block diagram of one or more data pipeline contributors and a data pipeline coordinator according to an embodiment of the present disclosure.

[0024] FIG. 6A is a block diagram of a data pipeline coordinator according to an embodiment of the present disclosure.

[0025] FIG. 6B is a block diagram of a data pipeline coordinator according to an embodiment of the present disclosure.Atty. Dkt. No. 10085-01-0187-PCT

[0026] FIG. 7 is a flowchart illustrating a method of data pipeline measurement and reporting performed by a data pipeline coordinator according to an embodiment of the present disclosure.

[0027] FIG. 8A is a block diagram of a data pipeline contributor according to an embodiment of the present disclosure.

[0028] FIG. 8B is a block diagram of a data pipeline contributor according to an embodiment of the present disclosure.

[0029] FIG. 9 is a flowchart illustrating a method of data pipeline measurement and reporting performed by a data pipeline contributor according to an embodiment of the present disclosure.

[0030] FIG. 10 is a block diagram of an example of data pipeline topology according to an embodiment of the present disclosure.

[0031] FIG. 11 is a flowchart illustrating a data pipeline contributor measurement and reporting according to an embodiment of the present disclosure.

[0032] FIG. 12 is a flowchart illustrating procedures that use UE’s wireless link to perform data pipeline contributor selection according to an embodiment of the present disclosure.

[0033] FIG. 13 is a block diagram of an example of a computing device according to an embodiment of the present disclosure.

[0034] FIG. 14 is a block diagram of a communication system according to an embodiment of the present disclosure.DETAILED DESCRIPTION OF EMBODIMENTS

[0035] Embodiments of the present disclosure are described in detail with the technical matters, structural features, achieved objects, and effects with reference to the accompanying drawings as follows. Specifically, the terminologies in the embodiments of the present disclosure are merely for describing the purpose of the certain embodiment, but not to limit the disclosure.

[0036] The technical solutions of the embodiments of the present disclosure can be applied to various communication systems, such as a global system of mobile communication (GSM) system, a code division multiple access (CDMA) system, a wideband code division multiple access (WCDMA) system, a general packet radio service (GPRS), a long term evolution (LTE) system, a LTE frequency division duplex (FDD) system, a LTE time division duplex (TDD) system, an advanced long term evolution (LTE-A) system, a new radio (NR) system, an evolution system of a NR system, a LTE-based access to unlicensed spectrum (LTE-U) system, a NR-based access to unlicensed spectrum (NR-U) system, an universal mobile telecommunication system (UMTS), a global interoperability for microwave access (WiMAX) communication system, wireless local area networks (WLAN), wireless fidelity (Wi-Fi), a 5th generation (5G) system (may also be called a new radio (NR) system), a 6th generation (6G) system, or other communication systems, etc.Atty. Dkt. No. 10085-01-0187-PCT

[0037] Optionally, a user equipment (UE) mentioned in the embodiments of the present application may refer to an access terminal, a subscriber unit, a subscriber station, a mobile station, a remote station, a remote terminal, a mobile device, a user terminal, a terminal, a wireless communication device, a user agent, or a user device. The access terminal may be a cellular radio telephone, a cordless telephone, a session initiation protocol (SIP) telephone, a wireless local loop (WLL) station, a personal digital assistant (PDA), a handheld device with wireless communication functions, a computing device, other processing devices coupled with a wireless modem, an in- vehicle device, a wearable device, a terminal device in a future 5G network, a terminal device in a future evolved public land mobile network (PLMN), etc.

[0038] Optionally, the communication system in the embodiment of the present application may be applied to an unlicensed spectrum, where the unlicensed spectrum may also be considered as a shared spectrum; or the communication system in the embodiment of the present application may also be applied to a licensed spectrum, where the licensed spectrum can also be considered an unshared spectrum.

[0039] 6G data plane and its associated data pipeline design have been proposed. An architecture of 6G data plane is illustrated in FIG. 1. To ensure the 6G data plane can support trusted data collection, storage, access, and sharing, a new network element called data plane access controller (DP AC) is proposed. It may also be referred to as the data plane management network element, data plane interface, data plane control network element, etc. The 6G data plane architecture introduces a new network element, the DP AC, to enable trusted data collection, storage, access, and sharing.

[0040] The functionalities supported by this network element can either be implemented by enhancing the existing data collection and coordination function (DCCF) or as a completely new network element. The DP AC will serve as the interface between the 6G network's data and the data plane infrastructure, with at least one of the following key functions: 1. Data collection. 2. Management and verification of data source and data consumer IDs. 3. Data processing and sharing. 4. Interaction with data plane storage facilities to store or retrieve data. For example, a data transaction request occurs when a data source or data consumer interacts with the DP AC for services such as data storage or retrieval. 5. Data tracking support. The DP AC functions as an interface between the 6G network and the data plane infrastructure, providing capabilities such as data collection, identity management, data processing and sharing, storage interaction, and data tracking.

[0041] When the core network’ s data plane collects data from a UE, the UE acts as the data source, engaging in a data transaction with the core network’s data plane. The UE sends a data transactionAtty. Dkt. No. 10085-01-0187-PCT request to the DP AC, carrying the data source ID, raw data, and metadata. Upon receiving the request, DP AC verifies the data source ID. If verification is successful, it forwards the data source ID, raw data, and metadata to the data plane storage facility. When a UE acts as a data source, the UE sends a data transaction request with its ID, raw data, and metadata to the DP AC, which verifies the ID and forwards the information to the data plane storage facility.

[0042] To enable flexible and efficient data management, the data plane adopts a distributed architecture. This allows data sources to connect to a data plane closer to them, thereby reducing data transmission latency.

[0043] FIG. 2 illustrates a data pipeline in 6G data plane. The data pipeline is a series of data processing steps combined to facilitate data flow. Data is collected from a source and sent to the next node for processing, where it is handled and then forwarded to the subsequent node, enabling on-the-fly data processing. FIG. 2 illustrates a 6G data pipeline that enables continuous data flow through sequential processing steps from source to subsequent nodes for real-time data handling.

[0044] FIG. 2 illustrates that an operation of the data pipeline is like an assembly line in manufacturing. It simplifies data management processes, improves data processing efficiency, and ensures data integrity. In the data pipeline, the output of one network entity’s data processing serves as the input for the next, allowing for a smooth and automated workflow throughout the pipeline. FIG. 2 illustrates that the 6G data pipeline operates like a manufacturing assembly line, simplifying data management, enhancing processing efficiency, and ensuring data integrity through an automated workflow between sequential network entities.

[0045] Components of the data pipeline may include at least one of the followings:

[0046] 1. Data sources: the starting point of the pipeline, responsible for collecting raw data. A single pipeline can include multiple data sources, enabling diverse data services.

[0047] 2. Pipeline contributors: these entities process the data provided by the sources. Examples of processing include compression, normalization, and Al-based data processing. The processed data is then passed to the next node in the pipeline.

[0048] 3. Data Receivers: the endpoint of the pipeline, where the fully processed data is received. No further processing is performed at this stage.

[0049] The data pipeline includes data sources that collect raw data, pipeline contributors that process the data, and data receivers that obtain the final processed output. The pipeline supports different types of data, such as continuous data, intermittent data, and batch data. All aspects of the pipeline, including node selection, pipeline establishment, allocation of data processing strategies, and data routing topology design, are managed by the DP AC as previously described. This structure ensures the efficient and systematic operation of the data pipeline. The DP ACAtty. Dkt. No. 10085-01-0187-PCT manages all aspects of the data pipeline, including node selection, establishment, processing strategy allocation, and routing design, to efficiently handle continuous, intermittent, and batch data in a systematic manner.

[0050] Once a data pipeline is established, data can flow seamlessly within it. However, during the pipeline's execution, data sources or contributors may become unavailable or fail to meet the pipeline's performance requirements. In such cases, the pipeline may dynamically select new data sources and contributors, a process referred to as data pipeline mobility management. A critical component of mobility management is the continuous monitoring and evaluation of existing data sources and contributors against predefined performance criteria. A monitoring mechanism that evaluates the data pipeline based on end-to-end delay and throughput has been proposed. However, it may be beneficial to individually monitor and measure the performance of each data source and contributor. It is therefore advantageous to perform individual performance measurement and reporting for each data source and contributor to enable more precise and efficient data pipeline management.

[0051] FIG. 3 illustrates a data plane architecture according to an embodiment of the present disclosure. FIG. 3 illustrates that, in some embodiments, a system architecture of data pipeline support in data plane has been specified. The data pipeline is defined as a composite chain of activities which may cross the mobile network functional domains when manipulating the metadata that are collected from one or more data sources for supporting a data plane service. The data pipeline is formed by a group of data pipeline contributors (DPCs) which support data plane functionalities such as data collection, data pre-processing, data labelling, model training, etc. The data pipeline in the data plane architecture comprises multiple data pipeline contributors that collaboratively perform various data-related functions across network domains to support data plane services. In the context of the 3GPP mobile system, a data pipeline contributor itself is a system functional entity that supports system operation by leveraging the metadata and model training model to navigate its local operation which is part of the data pipeline operation to support network service. In 3 GPP mobile systems, each data pipeline contributor functions as a system entity that utilizes metadata and trained models to optimize its local operations in support of overall network services.

[0052] FIG. 4 illustrates data pipeline communication flows according to an embodiment of the present disclosure. FIG. 4 illustrates that, in some embodiments, a mechanism to select data pipeline contributors has been proposed. For instance, the DP AC selects data pipeline contributors based on a list of criteria, for example computing power, pipeline’s end-to-end delay, data size, data consistency, Al service, etc. However, one important aspect is not considered: the UEs over the air interface quality. If UEs are selected for data pipeline operation, it is important to considerAtty. Dkt. No. 10085-01-0187-PCT the link quality between the UE and the RAN node. Accordingly, when UE participates as a data pipeline contributor, its air interface link quality with the RAN node can be considered to ensure reliable and efficient pipeline operation.

[0053] To overcome these and other challenges, some embodiments of the present disclosure provide a solution for more granular performance monitoring and management. In details, some embodiments of the present disclosure define how a DP AC orchestrates the discovery and selection of DPCs to participate in end-to-end data pipeline operations. Furthermore, some embodiments of the present disclosure propose a mechanism that enables the DP AC to consider the UE-RAN link quality as one of the criteria for selecting data pipeline contributors.

[0054] FIG. 5 illustrates that, in some embodiments, one or more data pipeline contributors 10 and a data pipeline coordinator 20 of communication in a communication network system 30 (e.g., 6G system) according to an embodiment of the present disclosure are provided. The communication network system 30 includes the one or more data pipeline contributors 10 and the data pipeline coordinator 20. The one or more data pipeline contributors 10 may include a memory 12, a transceiver 13, and a processor 11 coupled to the memory 12 and the transceiver 13. The data pipeline coordinator 20 may include a memory 22, a transceiver 23, and a processor 21 coupled to the memory 22 and the transceiver 23. The processor 11 or 21 may be configured to implement proposed functions, procedures and / or methods described in this description. Layers of radio interface protocol may be implemented in the processor 11 or 21. The memory 12 or 22 is operatively coupled with the processor 11 or 21 and stores a variety of information to operate the processor 11 or 21. The transceiver 13 or 23 is operatively coupled with the processor 11 or 21, and the transceiver 13 or 23 transmits and / or receives a radio signal.

[0055] The processor 11 or 21 may include application-specific integrated circuit (ASIC), other chipset, logic circuit and / or data processing device. The memory 12 or 22 may include read-only memory (ROM), random access memory (RAM), flash memory, memory card, storage medium and / or other storage device. The transceiver 13 or 23 may include baseband circuitry to process radio frequency signals. When the embodiments are implemented in software, the techniques described herein can be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The modules can be stored in the memory 12 or 22 and executed by the processor 11 or 21. The memory 12 or 22 can be implemented within the processor 11 or 21 or external to the processor 11 or 21 in which case those can be communicatively coupled to the processor 11 or 21 via various means as is known in the art.

[0056] In some embodiments, the transceiver 23 is configured to transmit a measurement configuration and reporting criteria to at least one data pipeline contributor 10 and receive, from the at least one data pipeline contributor 10, a measurement report according to the measurementAtty. Dkt. No. 10085-01-0187-PCT configuration and the reporting criteria, and the processor 21 is configured to perform a data pipeline control action based on the measurement report. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0057] In some embodiments, the transceiver 13 is configured to receive, from the data pipeline coordinator 20, a measurement configuration and reporting criteria, and the processor 11 is configured to perform at least one measurement according to the measurement configuration, and the transceiver 13 is configured to transmit a measurement report to the data pipeline coordinator 20 when the reporting criteria are satisfied. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0058] FIG. 6A illustrates an example of a data pipeline coordinator 600A according to an embodiment of the present application. The data pipeline coordinator 600A is configured to implement some embodiments of the disclosure. Some embodiments of the disclosure may be implemented into the data pipeline coordinator 600A using any suitably configured hardware and / or software. The data pipeline coordinator 600A includes a transceiver 601 A and an executor 602A. The transceiver 601 A is configured to transmit a measurement configuration and reporting criteria to at least one data pipeline contributor and receive, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria. The executor 602A is configured to perform a data pipeline control action based on the measurement report. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0059] FIG. 4B illustrates an example of a data pipeline coordinator 800B according to an embodiment of the present disclosure. The data pipeline coordinator 800B is configured to implement some embodiments of the disclosure. Some embodiments of the disclosure may be implemented into the data pipeline coordinator 800B using any suitably configured hardware and / or software. The data pipeline coordinator 800B may include a memory 80 IB, a transceiver 802B, and a processor 803B coupled to the memory 80 IB and the transceiver 802B. The processor 803B may be configured to implement proposed functions, procedures and / or methods described in this description. Layers of radio interface protocol may be implemented in the processor 803B. The memory 80 IB is operatively coupled with the processor 803B and stores a variety of information to operate the processor 803B. The transceiver 802B is operatively coupled with theAtty. Dkt. No. 10085-01-0187-PCT processor 803B, and the transceiver 802B transmits and / or receives a radio signal. The processor 803B may include application-specific integrated circuit (ASIC), other chipset, logic circuit and / or data processing device. The memory 80 IB may include read-only memory (ROM), random access memory (RAM), flash memory, memory card, storage medium and / or other storage device. The transceiver 802B may include baseband circuitry to process radio frequency signals. When the embodiments are implemented in software, the techniques described herein can be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The modules can be stored in the memory 80 IB and executed by the processor 803B. The memory 80 IB can be implemented within the processor 803B or external to the processor 803B in which case those can be communicatively coupled to the processor 803B via various means as is known in the art.

[0060] In some embodiments, the transceiver 802B is configured to transmit a measurement configuration and reporting criteria to at least one data pipeline contributor and receive, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria, and the processor 803B is configured to perform a data pipeline control action based on the measurement report. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0061] FIG. 7 is an example of a method 700 of data pipeline measurement and reporting performed by a data pipeline coordinator according to an embodiment of the present disclosure. The method 700 of data pipeline measurement and reporting performed by the data pipeline coordinator is configured to implement some embodiments of the disclosure. Some embodiments of the disclosure may be implemented into the method 700 of data pipeline measurement and reporting performed by the data pipeline coordinator using any suitably configured hardware and / or software. In some embodiments, the method 700 of data pipeline measurement and reporting performed by the data pipeline coordinator includes: an operation 702, transmitting a measurement configuration and reporting criteria to at least one data pipeline contributor; an operation 704, receiving, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria; and an operation 706, performing a data pipeline control action based on the measurement report. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0062] In some embodiments, the at least one data pipeline contributor includes at least one of a data source, a data contributor, or a data sink. In some embodiments, the data pipeline coordinator resides in a data pipeline access control (DP AC) function. In some embodiments, the measurement configuration and the reporting criteria are included in a data pipeline measurement controlAtty. Dkt. No. 10085-01-0187-PCT message. In some embodiments, the measurement report is included in a data pipeline measurement report message. In some embodiments, performing the data pipeline control action based on the measurement report includes selecting one or more data pipeline contributors for participation in a data pipeline operation based on the measurement report. In some embodiments, the data pipeline control action includes triggering a data pipeline establishment, a data pipeline modification, or a data pipeline termination. The DP AC coordinates data pipeline operations by configuring measurement and reporting procedures, collecting measurement reports from data sources, contributors, or sinks, and performing control actions such as establishing, modifying, or terminating data pipelines based on the reported results.

[0063] In some embodiments, the measurement configuration includes at least one parameter associated with a data pipeline operation requirement, including at least one of a data size, data burst characteristics, a jitter, a data rate, or a number of participating user equipments (UEs). In some embodiments, the reporting criteria include at least one triggering condition associated with a measured parameter. In some embodiments, the method further includes receiving a measurement result from at least one radio access network (RAN) node and selecting at least one corresponding UE for participation based on the measurement result. The measurement configuration defines parameters such as data size, burst characteristics, jitter, data rate, or the number of participating UEs, while the reporting criteria specify triggering conditions, and the DP AC may select UEs for participation based on measurement results received from RAN nodes.

[0064] FIG. 8A illustrates an example of a data pipeline contributor 800A according to an embodiment of the present application. The data pipeline contributor 800A is configured to implement some embodiments of the disclosure. Some embodiments of the disclosure may be implemented into the data pipeline contributor 800A using any suitably configured hardware and / or software. The data pipeline contributor 800A includes a transceiver 801 A and an executor 802A. The transceiver 801A is configured to receive, from a data pipeline coordinator, a measurement configuration and reporting criteria, the executor 802A is configured to perform at least one measurement according to the measurement configuration, and the transceiver 801A is configured to transmit a measurement report to the data pipeline coordinator when the reporting criteria are satisfied. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0065] FIG. 8B illustrates an example of a data pipeline contributor 800B according to an embodiment of the present disclosure. The data pipeline contributor 800B is configured to implement some embodiments of the disclosure. Some embodiments of the disclosure may be implemented into the data pipeline contributor 800B using any suitably configured hardware and / or software. The data pipeline contributor 800B may include a memory 80 IB, a transceiver 802B, and a processor 803B coupled to the memory 80 IB and the transceiver 802B. The processorAtty. Dkt. No. 10085-01-0187-PCT803B may be configured to implement proposed functions, procedures and / or methods described in this description. Layers of radio interface protocol may be implemented in the processor 803B. The memory 80 IB is operatively coupled with the processor 803B and stores a variety of information to operate the processor 803B. The transceiver 802B is operatively coupled with the processor 803B, and the transceiver 802B transmits and / or receives a radio signal. The processor 803B may include application-specific integrated circuit (ASIC), other chipset, logic circuit and / or data processing device. The memory 80 IB may include read-only memory (ROM), random access memory (RAM), flash memory, memory card, storage medium and / or other storage device. The transceiver 802B may include baseband circuitry to process radio frequency signals. When the embodiments are implemented in software, the techniques described herein can be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The modules can be stored in the memory 80 IB and executed by the processor 803B. The memory 80 IB can be implemented within the processor 803B or external to the processor 803B in which case those can be communicatively coupled to the processor 803B via various means as is known in the art.

[0066] In some embodiments, the transceiver 802B is configured to receive, from a data pipeline coordinator, a measurement configuration and reporting criteria, the processor 803B is configured to perform at least one measurement according to the measurement configuration, and the transceiver 802B is configured to transmit a measurement report to the data pipeline coordinator when the reporting criteria are satisfied. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.

[0067] FIG. 9 is an example of a method 900 of data pipeline measurement and reporting performed by a data pipeline contributor according to an embodiment of the present disclosure. The method 900 of data pipeline measurement and reporting performed by the data pipeline contributor is configured to implement some embodiments of the disclosure. Some embodiments of the disclosure may be implemented into the method 900 of data pipeline measurement and reporting performed by the data pipeline contributor using any suitably configured hardware and / or software. In some embodiments, the method 900 of data pipeline measurement and reporting performed by the data pipeline contributor includes: an operation 902, receiving, from a data pipeline coordinator, a measurement configuration and reporting criteria; an operation 904, performing at least one measurement according to the measurement configuration; and an operation 906, transmitting a measurement report to the data pipeline coordinator when the reporting criteria are satisfied. This can solve issues in the prior art and other issues, provide stable performance and continuity of data services, provide enhanced adaptability for dynamic pipeline reconfiguration, and / or improve overall data transmission efficiency and reliability in data plane operations.Atty. Dkt. No. 10085-01-0187-PCT

[0068] In some embodiments, the data pipeline contributor includes at least one of a data source, a data contributor, or a data sink participating in a data pipeline operation. In some embodiments, the measurement configuration and the reporting criteria are included in a data pipeline measurement control message. In some embodiments, the measurement report is included in a data pipeline measurement report message. In some embodiments, the at least one measurement includes at least one of: a data throughput measurement, a latency or jitter measurement, a packet error rate measurement, a computing resource utilization measurement, or a radio link quality measurement. In some embodiments, the reporting criteria include at least one triggering condition associated with a measured parameter. Each data pipeline contributor performs measurements such as throughput, latency jitter, packet error rate, computing resource utilization, or radio link quality based on configurations and criteria defined in a data pipeline measurement control message, and reports the results through a data pipeline measurement report message when triggering conditions are met.

[0069] In some embodiments, the data pipeline contributor transmits the measurement report to the data pipeline coordinator when the at least one triggering condition associated with the measured parameter is satisfied, including when the measured parameter exceeds or falls below a corresponding threshold value. In some embodiments, the method further includes receiving, from the data pipeline coordinator, an instruction to participate in a data pipeline establishment, a data pipeline modification, or a data pipeline termination based on the measurement report. In some embodiments, performing the at least one measurement includes using a configuration information associated with a data pipeline operation requirement including at least one of a data size, data burst characteristics, a jitter, a data rate, or a number of participating user equipments (UEs). In some embodiments, the data pipeline contributor performs the at least one measurement and transmits the measurement report in coordination with one or more other data pipeline contributors under a control of the data pipeline coordinator. The data pipeline contributor measures performance parameters such as data size, burst characteristics, jitter, or data rate, and reports results when triggering conditions are met, allowing the DP AC to coordinate contributors for pipeline establishment, modification, or termination based on the reported measurements.

[0070] Exemplary Technical Solutions:

[0071] FIG. 10 illustrates an example of data pipeline topology according to an embodiment of the present disclosure. FIG. 10 illustrates that, in some embodiments, the focus is on end-to-end KPIs and overall performance metrics, such as the end-to-end latency and throughput between data source A and data sink K. In some embodiments, however, the KPIs of individual nodes and links within the pipeline are emphasized. For example, the KPIs for data source A, data operations E and J, and data sink K, assuming the established data pipeline follows the sequence A->E->J-K may be separately evaluated. While end-to-end KPIs such as latency and throughput are important, the present disclosure also emphasizes evaluating the performance of individual nodes and links within the data pipeline for more granular performance analysis.Atty. Dkt. No. 10085-01-0187-PCT

[0072] KPI’s on a per node or per link purpose for a data pipeline are listed below.

[0073] Latency: The time it takes for data to travel from the last node to the current node.

[0074] Processing delay: the time it takes for data to be processed at the current node.

[0075] Total delay of the last hop: the sum of latency and process delay defined above.

[0076] Throughput: the volume of data that is transmitted across the previous hop in unit time.

[0077] Reliability: the ability of the path to consistently deliver data without errors or disruptions. This can be measured by packet delivery ratio (PDR): Percentage of successfully delivered packets and availability time of the nodes and the path.

[0078] Jitter: variability in packet delay times. This can be measured by variance in latency measurements over time.

[0079] Bandwidth utilization: the percentage of available bandwidth used for data transfer. This can be measured by real-time and average bandwidth utilization across nodes.

[0080] Scalability: the ability of the path to handle increasing data volume. This can be measured by performance metrics under increased load conditions.

[0081] Energy efficiency: the energy consumption associated with transferring data across the nodes. This can be measured by energy transferred per bit (e.g., Joules / bit).

[0082] Security: the protection of data from unauthorized access or tampering during transfer. This can be measured by the number of security breaches or incidents and compliance with encryption and authentication protocols.

[0083] Computing resources available: the available computing resources at the node to support the required data pipeline operation.

[0084] Dataset size: the size of the dataset reflects either the volume of raw data collected or the size of data output by each node. A larger dataset often indicates greater data richness.

[0085] Data completeness: refer to the attributes and features the data possesses. Datasets with richer features can train models with higher generalization ability.

[0086] Data bias: refer to overrepresentation of certain data attributes within the dataset, which could result in biased data.

[0087] Some embodiments define key performance indicators (KPIs) for evaluating data pipeline performance on a per-node or per-link basis, including latency, processing delay, total delay, throughput, reliability, jitter, bandwidth utilization, scalability, energy efficiency, security, computing resources, dataset size, data completeness, and data bias. These KPIs collectively measure transmission efficiency, processing capability, data quality, and system robustness, enabling precise assessment and optimization of data pipeline performance across all contributing nodes and links.

[0088] FIG. 11 illustrates a data pipeline contributor measurement and reporting according to an embodiment of the present disclosure. FIG. 11 illustrates that, in some embodiments, the data pipeline contributor measurement and reporting may include at least one of the following operations.Atty. Dkt. No. 10085-01-0187-PCT

[0089] 1. Data pipeline contributors include data sources, data contributors, and data sink. The data pipeline coordinator can trigger measurement and reporting on each individual contributor based on pre-defined policy and external trigger by data pipeline customer. The customer can be a network NF or an application server outside MNO. The data pipeline coordinator can reside in DP AC or other network functions.

[0090] 2. From operation 2 to operation 5, the data pipeline coordinator sends measurement configuration and reporting criteria to each data pipeline contributor.

[0091] a. Measurement configuration and reporting criteria are included in data pipeline measurement control message. It will be discussed in the next section.

[0092] 3. From operation 6 to 9, each data pipeline contributor performs data pipeline measurement based on the configuration.

[0093] 4. From operation 10 to operation 13, if the reporting criteria are triggered, the data pipeline contributor sends measured results to the data pipeline coordinator.

[0094] a. Measured results are included in the data pipeline measurement report message. It will be discussed in the following embodiments.

[0095] 5. At operation 14, the data pipeline coordinator may take necessary action based on the reported results.

[0096] Some embodiments describe a data pipeline measurement and reporting procedure in which the data pipeline coordinator, residing in a DP AC or another network function, configures, triggers, and collects measurement results from various data pipeline contributors such as data sources, contributors, and sinks. Based on predefined policies or external triggers from data pipeline customers, the coordinator sends measurement configurations and reporting criteria to each contributor, which then performs measurements and reports results through data pipeline measurement control and report messages. When the reporting conditions are met, contributors transmit results to the coordinator, which subsequently performs appropriate control actions to maintain optimal data pipeline performance.

[0097] In some embodiments, in the data pipeline measurement control message, the data pipeline coordinator may include at least one following information:

[0098] 1. Measurement ID: identify the configured measurement KPI’s and the reporting configuration.

[0099] 2. Measured KPI’s: indicate which measurement KPI’s should be measured. Details are in table 1 below.

[0100] 3. Measurement events: indicate which measurement events are configured. Details are in table 2 below.

[0101] 4. Measurement frequency: indicate how frequently the measurement should be performed.

[0102] 5. Measurement reporting criteria:Atty. Dkt. No. 10085-01-0187-PCT

[0103] a. One-time reporting: indicate the node should send a report once after receiving this message.

[0104] b. Periodic reporting and the periodicity: indicate the node should send a report periodically based on the configured periodicity.

[0105] c. Event-based reporting: indicate the node should send a report if the configured events are triggered.

[0106] The data pipeline coordinator can configure at least one of the following measurement quantities for a single data pipeline contributor.

[0107] Some embodiments define the structure of a data pipeline measurement control message, which includes key configuration elements such as a measurement ID, specified KPIs to be measured, measurement events, measurement frequency, and reporting criteria. The reporting criteria may include one-time, periodic, or event-based reporting modes, allowing the data pipeline coordinator to flexibly configure and manage measurement activities for each data pipeline contributor based on performance monitoring requirements.

[0108] Table 1 : Data pipeline measurement KPI.Atty. Dkt. No. 10085-01-0187-PCTComputing resources The available computing resources at the node to support the available required data pipeline operation.

[0109] Table 2: Data pipeline measurement event.Atty. Dkt. No. 10085-01-0187-PCT

[0110] In some embodiments, once the measurement report is triggered based on the reporting criteria included in the data pipeline measurement control message, the node sends a measurement report message with at least one following information:

[0111] 1. Measurement ID: the same ID included in the measurement control message. This is used to identify the report KPI’s and their quantities.

[0112] 2 For one-time reporting: include the measured KPI’s and the quantities in the message.Atty. Dkt. No. 10085-01-0187-PCT

[0113] 3 For periodic reporting: include the measured KPI’s and the quantities in the message.

[0114] 4. For event-triggered reporting: include the event (and event ID) that triggers the reporting and include the measured KPI’s and the quantities.

[0115] Some embodiments define the structure of a data pipeline measurement report message, which includes information such as a measurement ID corresponding to the control message, measured KPIs, and their quantities. Depending on the reporting type, one-time, periodic, or event- triggered, the report contains the relevant KPI data, and in the case of event-triggered reporting, it also includes the event ID that initiated the report.

[0116] In some embodiments, when the DP AC selects data pipeline contributors, the link quality between the UE and the RAN node is one important factor. Depending on the characteristics of the data pipeline operation, the link quality requirement can be different. For example, if the data pipeline operation only involves bursty-type of non-real time data, the link quality requirement can be relaxed. However, if the data pipeline operation requires the UE to keep sending small amounts of real time sensing data, the reliability of the wireless connection can be more important than the link’s throughput. On the other hand, when DP AC selects a RAN node as a data pipeline contributor, the RAN nodes that have enough contributing UEs with satisfying wireless connection quality can be selected. When the DP AC selects data pipeline contributors, it considers the UE- RAN link quality according to the pipeline’s operational requirements, prioritizing reliability for real-time sensing data and selecting RAN nodes with sufficient UEs maintaining good wireless connection quality.

[0117] Various proposals provided by some embodiments of the present disclosure may include:

[0118] 1. DP AC configures the link quality measurement and reporting settings for the candidate UEs based on the requirements of the data pipeline operation.

[0119] 2 The candidate UEs send their link quality measurements to DP AC for the selection of data pipeline contributors. DP AC selects UEs with satisfactory link quality as contributors to the data pipeline.

[0120] 3. DP AC configures the candidate RAN nodes with the link quality requirements. The RAN nodes, in turn, set up link quality measurements for the serving UEs. RAN nodes with an aggregated group of UEs that meet the required link quality criteria are selected as contributors to the data pipeline.

[0121] Some embodiments propose a mechanism in which the DP AC manages link quality -based selection of data pipeline contributors. Specifically, the DP AC first configures link quality measurement and reporting settings for candidate UEs according to pipeline requirements. The UEs then report their link quality to the DP AC, which selects those with satisfactory conditions as contributors. Additionally, the DP AC may configure RAN nodes with link quality thresholds, allowing them to monitor their serving UEs and identify nodes with groups of UEs that meet the required link quality for participation in the data pipeline.Atty. Dkt. No. 10085-01-0187-PCT

[0122] In some embodiments, a data pipeline contributor selection based on air interface quality is disclosed. The data pipeline contributor selection criteria may include pipeline end-to-end delay, per-hop delay, end-to-end throughput, per-hop throughput, data processing capability, data collection capability, data size, computing power, data path hop selection, Al model information, etc. However, in a cellular network, if UEs are selected as data pipeline contributors, the UE’s wireless link quality is an important factor. If the link quality is not good enough to support the data pipeline operation, this UE should not be selected as a contributor. Some embodiments introduce a data pipeline contributor selection method that, in addition to conventional criteria such as delay, throughput, and computing capability, also considers the UE’s wireless link quality to ensure only UEs with sufficient connectivity are chosen for data pipeline operations.

[0123] According to some embodiments, the following parameters are defined to evaluate the air interface quality.

[0124] 1. Signal strength:

[0125] a) Received signal strength indicator (RSSI): measure the power level of the received signal.

[0126] b) Reference signal received power (RSRP): indicate the strength of the reference signal.

[0127] 2. Signal quality:

[0128] a) Signal-to-noise ratio (SNR): ratio of signal power to noise power in the channel.

[0129] b) Reference signal received quality (RSRQ): measure signal quality combining power and interference.

[0130] 3. Bit error rate (BER): percentage of bits received incorrectly over the air interface.

[0131] 4. Neighbor cell quality: measure neighbor cells’ RSRP and RSSI.

[0132] 5. UE moving speed: measure the speed of the UE moving.

[0133] 6. UE moving trajectory: measure UE’s moving path.

[0134] 7. Call setup delay: measures serving cell load.

[0135] 8. round-trip-time (RTT): measure the time for signals to travel to the RAN node and back.

[0136] Some embodiments define multiple parameters for evaluating air interface quality in data pipeline contributor selection, including signal strength metrics such as RSSI and RSRP, signal quality indicators such as SNR and RSRQ, BER, and neighbor cell quality. Additional factors such as UE mobility characteristics (speed and trajectory), call setup delay reflecting cell load, and RTT between the UE and RAN node are also considered to comprehensively assess wireless link performance and ensure reliable contributor selection.

[0137] FIG. 12 illustrates procedures that use UE’s wireless link to perform data pipeline contributor selection according to an embodiment of the present disclosure. FIG. 12 illustrates that, in some embodiments, procedures that use UE’s wireless link to perform data pipeline contributor selection may include at least one of following operations.Atty. Dkt. No. 10085-01-0187-PCT

[0138] 1. DP AC sends radio link measurement request to the serving RAN node including the data pipeline’s information:

[0139] a) Data pipeline ID.

[0140] b) Data pipeline operation requirements on the radio link: data size, data bursty characteristics, jitter, data rate, number of required participating UEs.

[0141] 2 The RAN node sends data pipeline radio measurement message based on the data pipeline operation requirements to UEs. In the measurement message, one or more above- mentioned measurement parameters are included. The thresholds and reporting trigger of each parameter are also included. This message can be sent to multiple UEs depending on the number of required participating UEs.

[0142] 3. Upon receiving the measurement configuration message, the UE performs the measurement. When the reporting is triggered, the UE sends a data pipeline radio link measurement report to the RAN node.

[0143] 4. The RAN node sends the UE ID and the measured results to DP AC for data pipeline contributor selection. Multiple RAN nodes can send measurement results to DP AC.

[0144] 5. Based on the received measurement results, DP AC selects the participating UEs and participating RAN nodes for data pipeline operation.

[0145] Some embodiments describe a procedure for selecting data pipeline contributors based on UE wireless link quality. The DP AC sends a radio link measurement request to the serving RAN node, including the data pipeline ID and operation requirements such as data size, jitter, and the number of required UEs. The RAN node then transmits measurement configuration messages to UEs, specifying parameters, thresholds, and reporting triggers. Upon receiving this configuration, the UEs perform measurements and send radio link reports to the RAN node, which forwards the measurement results and UE IDs to the DP AC. Based on these results, the DP AC selects the appropriate UEs and RAN nodes to participate in the data pipeline operation.

[0146] Commercial interests for some embodiments are as follows. 1. Solve issues in the prior art and other issues. 2. Provide stable performance and continuity of data services. 3. Provide stable performance and continuity of data services. 4. Provide enhanced adaptability for dynamic pipeline reconfiguration. 5. Improve overall data transmission efficiency and reliability in data plane operations. 6. Provide a good communication performance. 7. Provide high reliability. Some embodiments of the present disclosure can be used in many applications. Some embodiments of the present disclosure are used by chipset vendors, video system development vendors, automakers including cars, trains, trucks, buses, bicycles, moto-bikes, helmets, and etc., drones (unmanned aerial vehicles), smartphone makers, communication devices for public safety use, AR / VR / MR device maker for example gaming, conference / seminar, education purposes. Some embodiments of the present disclosure are a combination of “techniques / processes” that can be adopted in video standards to create an end product. Some embodiments of the present disclosure propose technical mechanisms. The at least one proposed solution, method, system, and apparatus of someAtty. Dkt. No. 10085-01-0187-PCT embodiments of the present disclosure may be used for current and / or new / future standards regarding communication systems such as a UE, a base station, and / or a communication system. Compatible products follow at least one proposed solution, method, system, and apparatus of some embodiments of the present disclosure. The proposed solution, method, system, and apparatus are widely used in a UE, a base station, and / or a communication system. With the implementation of the at least one proposed solution, method, system, and apparatus of some embodiments of the present disclosure, at least one modification to methods and apparatus of wireless communication are considered for standardizing.

[0147] In some embodiments, a network function includes a memory, a transceiver, and a processor coupled to the memory and the transceiver. The network function is configured to perform the above method. In some embodiments, a core network element includes a memory, a transceiver, and a processor coupled to the memory and the transceiver. The core network element is configured to provide the above method. In some embodiments, a non-transitory machine- readable storage medium has stored thereon instructions that, when executed by a computer, cause the computer to perform the above method. In some embodiments, a chip includes a processor, configured to call and run a computer program stored in a memory, to cause a device in which the chip is installed to execute the above method. In some embodiments, a computer readable storage medium, in which a computer program is stored, causes a computer to execute the above method. In some embodiments, a computer program product includes a computer program, and the computer program causes a computer to execute the above method. In some embodiments, a computer program causes a computer to execute the above method.

[0148] In some embodiments, a network function or a core network element may be implemented using a computing platform such as the example computing device 1100 illustrated in FIG. 13 or the communication system 1200 illustrated in FIG. 14. As shown in FIG. 13, the computing device 1100 may include a processor 1112, memory 1114, and input / output (I / O) interfaces 1118 coupled via a bus 1116. The processor 1112 may execute program code stored in the memory 1114 to perform one or more methods described above with respect to FIG. 1 to FIG. 12. The memory 1114 may be a non-transitory computer-readable medium storing instructions that, when executed, enable NAS message handling, partial decoding, SRB-based routing, or collaboration with the AMF. In some cases, the program code may be stored on a separate computer-readable storage medium or integrated within the device as a computer program product. As shown in FIG. 14, the communication system 1200 may include RF circuitry 1210, baseband circuitry 1220, application circuitry 1230, and memory / storage 1240, among other components such as display 1250, camera 1260, sensor 1270, and I / O interface 1280. The application circuitry 1230 and baseband circuitry 1220 may be configured to execute program instructions and perform processing functions related to NAS signaling, including determining the destination core network function, managing signaling bearers, and communicating with the AMF. These components may be integrated into a mobile or edge device, supporting edge-cloud deployment as described in earlier embodiments.Atty. Dkt. No. 10085-01-0187-PCTThe hardware and software integration in such devices enables flexible and efficient execution of the NAS message distribution mechanisms disclosed herein.

[0149] FIG. 14 is an example of a computing device 1100 according to an embodiment of the present disclosure. Any suitable computing device can be used for performing the operations described herein. For example, FIG. 14 illustrates an example of the computing device 1100 that can implement some embodiments of FIG. 1 to FIG. 12 using any suitably configured hardware and / or software. In some embodiments, the computing device 1100 can include a processor 1112 that is communicatively coupled to a memory 1114 and that executes computer-executable program code and / or accesses information stored in the memory 1114. The processor 1112 may include a microprocessor, an application-specific integrated circuit (“ASIC”), a state machine, or other processing device. The processor 1112 can include any of a number of processing devices, including one. Such a processor can include or may be in communication with a computer-readable medium storing instructions that, when executed by the processor 1112, cause the processor to perform the operations described herein.

[0150] The memory 1114 can include any suitable non-transitory computer-readable medium. The computer-readable medium can include any electronic, optical, magnetic, or other storage device capable of providing a processor with computer-readable instructions or other program code. Non-limiting examples of a computer-readable medium include a magnetic disk, a memory chip, a read-only memory (ROM), a random access memory (RAM), an application specific integrated circuit (ASIC), a configured processor, optical storage, magnetic tape or other magnetic storage, or any other medium from which a computer processor can read instructions. The instructions may include processor-specific instructions generated by a compiler and / or an interpreter from code written in any suitable computer-programming language, including, for example, C, C++, C#, visual basic, java, python, perl, javascript, and actionscript.

[0151] The computing device 1100 can also include a bus 1116. The bus 1116 can communicatively couple one or more components of the computing device 1100. The computing device 1100 can also include a number of external or internal devices such as input or output devices. For example, the computing device 1100 is illustrated with an input / output (“VO”) interface 1118 that can receive input from one or more input devices 1120 or provide output to one or more output devices 1122. The one or more input devices 1120 and one or more output devices 1122 can be communicatively coupled to the I / O interface 1118. The communicative coupling can be implemented via any suitable manner (e.g., a connection via a printed circuit board, connection via a cable, communication via wireless transmissions, etc.). Non-limiting examples of input devices 1120 include a touch screen (e g., one or more cameras for imaging a touch area or pressure sensors for detecting pressure changes caused by a touch), a mouse, a keyboard, or any other device that can be used to generate input events in response to physical actions by a user of a computing device. Non-limiting examples of output devices 1122 include a liquid crystal displayAtty. Dkt. No. 10085-01-0187-PCT(LCD) screen, an external monitor, a speaker, or any other device that can be used to display or otherwise present outputs generated by a computing device.

[0152] The computing device 1100 can execute program code that configures the processor 1112 to perform one or more of the operations described above with respect to some embodiments of FIG. 1 to FIG. 12. The program code may be resident in the memory 1114 or any suitable computer-readable medium and may be executed by the processor 1112 or any other suitable processor.

[0153] The computing device 1100 can also include at least one network interface device 1124. The network interface device 1124 can include any device or group of devices suitable for establishing a wired or wireless data connection to one or more data networks 1128. Non limiting examples of the network interface device 1124 include an Ethernet network adapter, a modem, and / or the like. The computing device 1100 can transmit messages as electronic or optical signals via the network interface device 1124.

[0154] FIG. 14 is a block diagram of an example of a communication system 1200 according to an embodiment of the present disclosure. Embodiments described herein may be implemented into the communication system 1200 using any suitably configured hardware and / or software. FIG. 14 illustrates the communication system 1200 including a radio frequency (RF) circuitry 1210, a baseband circuitry 1220, an application circuitry 1230, a memory / storage 1240, a display 1250, a camera 1260, a sensor 1270, and an input / output (I / O) interface 1280, coupled with each other at least as illustrated.

[0155] The application circuitry 1230 may include a circuitry such as, but not limited to, one or more single-core or multi-core processors. The processors may include any combination of general-purpose processors and dedicated processors, such as graphics processors, application processors. The processors may be coupled with the memory / storage and configured to execute instructions stored in the memory / storage to enable various applications and / or operating systems running on the system. The communication system 1200 can execute program code that configures the application circuitry 1230 to perform one or more of the operations described above with respect to some embodiments of FIG. 1 to FIG. 12. The program code may be resident in the application circuitry 1230 or any suitable computer-readable medium and may be executed by the application circuitry 1230 or any other suitable processor.

[0156] The baseband circuitry 1220 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The processors may include a baseband processor. The baseband circuitry may handle various radio control functions that may enable communication with one or more radio networks via the RF circuitry. The radio control functions may include, but are not limited to, signal modulation, encoding, decoding, radio frequency shifting, etc. In some embodiments, the baseband circuitry may provide for communication compatible with one or more radio technologies. For example, in some embodiments, the baseband circuitry may support communication with an evolved universal terrestrial radio access network (EUTRAN) and / or otherAtty. Dkt. No. 10085-01-0187-PCT wireless metropolitan area networks (WMAN), a wireless local area network (WLAN), a wireless personal area network (WPAN). Embodiments in which the baseband circuitry is configured to support radio communications of more than one wireless protocol may be referred to as multimode baseband circuitry.

[0157] In various embodiments, the baseband circuitry 1220 may include circuitry to operate with signals that are not strictly considered as being in a baseband frequency. For example, in some embodiments, baseband circuitry may include circuitry to operate with signals having an intermediate frequency, which is between a baseband frequency and a radio frequency. The RF circuitry 1210 may enable communication with wireless networks using modulated electromagnetic radiation through a non-solid medium. In various embodiments, the RF circuitry may include switches, filters, amplifiers, etc. to facilitate the communication with the wireless network. In various embodiments, the RF circuitry 1210 may include circuitry to operate with signals that are not strictly considered as being in a radio frequency. For example, in some embodiments, RF circuitry may include circuitry to operate with signals having an intermediate frequency, which is between a baseband frequency and a radio frequency.

[0158] In various embodiments, the transmitter circuitry, control circuitry, or receiver circuitry discussed above with respect to some embodiments of FIG. 1 to FIG. 12 may be embodied in whole or in part in one or more of the RF circuitry, the baseband circuitry, and / or the application circuitry. As used herein, “circuitry” may refer to, be part of, or include an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group), and / or a memory (shared, dedicated, or group) that execute one or more software or firmware programs, a combinational logic circuit, and / or other suitable hardware components that provide the described functionality. In some embodiments, the electronic device circuitry may be implemented in, or functions associated with the circuitry may be implemented by, one or more software or firmware modules. In some embodiments, some or all of the constituent components of the baseband circuitry, the application circuitry, and / or the memory / storage may be implemented together on a system on a chip (SOC). The memory / storage 1240 may be used to load and store data and / or instructions, for example, for system. The memory / storage for one embodiment may include any combination of suitable volatile memory, such as dynamic random access memory (DRAM)), and / or non-volatile memory, such as flash memory.

[0159] In various embodiments, the I / O interface 1280 may include one or more user interfaces designed to enable user interaction with the system and / or peripheral component interfaces designed to enable peripheral component interaction with the system. User interfaces may include, but are not limited to a physical keyboard or keypad, a touchpad, a speaker, a microphone, etc. Peripheral component interfaces may include, but are not limited to, a non-volatile memory port, a universal serial bus (USB) port, an audio jack, and a power supply interface. In various embodiments, the sensor 1270 may include one or more sensing devices to determine environmental conditions and / or location information related to the system. In some embodiments,Atty. Dkt. No. 10085-01-0187-PCT the sensors may include, but are not limited to, a gyro sensor, an accelerometer, a proximity sensor, an ambient light sensor, and a positioning unit. The positioning unit may also be part of, or interact with, the baseband circuitry and / or RF circuitry to communicate with components of a positioning network, e.g., a global positioning system (GPS) satellite.

[0160] In various embodiments, the display 1250 may include a display, such as a liquid crystal display and a touch screen display. In various embodiments, the communication system 1200 may be a mobile computing device such as, but not limited to, a laptop computing device, a tablet computing device, a netbook, an ultrabook, a smartphone, an AR / VR glasses, etc. In various embodiments, system may have more or less components, and / or different architectures. Where appropriate, methods described herein may be implemented as a computer program. The computer program may be stored on a storage medium, such as a non-transitory storage medium.

[0161] A person having ordinary skill in the art understands that each of the units, algorithm, and operations described and disclosed in the embodiments of the present disclosure are realized using electronic hardware or combinations of software for computers and electronic hardware. Whether the functions run in hardware or software depends on the condition of application and design requirement for a technical plan. A person having ordinary skill in the art can use different ways to realize the function for each specific application while such realizations should not go beyond the scope of the present disclosure. It is understood by a person having ordinary skill in the art that he / she can refer to the working processes of the system, device, and unit in the above-mentioned embodiment since the working processes of the above-mentioned system, device, and unit are basically the same. For easy description and simplicity, these working processes will not be detailed.

[0162] It is understood that the disclosed system, device, and method in the embodiments of the present disclosure can be realized with other ways. The above-mentioned embodiments are exemplary only. The division of the units is merely based on logical functions while other divisions exist in realization. It is possible that a plurality of units or components are combined or integrated in another system. It is also possible that some characteristics are omitted or skipped. On the other hand, the displayed or discussed mutual coupling, direct coupling, or communicative coupling operate through some ports, devices, or units whether indirectly or communicatively by ways of electrical, mechanical, or other kinds of forms.

[0163] The units as separating components for explanation are or are not physically separated. The units for display are or are not physical units, that is, located in one place or distributed on a plurality of network units. Some or all of the units are used according to the purposes of the embodiments. Moreover, each of the functional units in each of the embodiments can be integrated in one processing unit, physically independent, or integrated in one processing unit with two or more than two units.

[0164] If the software function unit is realized and used and sold as a product, it can be stored in a readable storage medium in a computer. Based on this understanding, the technical plan proposedAtty. Dkt. No. 10085-01-0187-PCT by the present disclosure can be essentially or partially realized as the form of a software product. Or, one part of the technical plan beneficial to the conventional technology can be realized as the form of a software product. The software product in the computer is stored in a storage medium, including a plurality of commands for a computational device (such as a personal computer, a server, or a network device) to run all or some of the operations disclosed by the embodiments of the present disclosure. The storage medium includes a USB disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a floppy disk, or other kinds of media capable of storing program codes.

[0165] While the present disclosure has been described in connection with what is considered the most practical and preferred embodiments, it is understood that the present disclosure is not limited to the disclosed embodiments but is intended to cover various arrangements made without departing from the scope of the broadest interpretation of the appended claims.

Claims

Atty. Dkt. No. 10085-01-0187-PCTWhat is claimed is:

1. A method of data pipeline measurement and reporting performed by a data pipeline coordinator, comprising: transmitting a measurement configuration and reporting criteria to at least one data pipeline contributor; receiving, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria; and performing a data pipeline control action based on the measurement report.

2. The method of claim 1, wherein the at least one data pipeline contributor comprises at least one of a data source, a data contributor, or a data sink.

3. The method of claim 1, wherein the data pipeline coordinator resides in a data pipeline access control (DPAC) function.

4. The method of claim 1, wherein the measurement configuration and the reporting criteria are included in a data pipeline measurement control message.

5. The method of claim 1, wherein the measurement report is included in a data pipeline measurement report message.

6. The method of claim 1, wherein performing the data pipeline control action based on the measurement report comprises: selecting one or more data pipeline contributors for participation in a data pipeline operation based on the measurement report.

7. The method of claim 1, wherein the data pipeline control action comprises triggering a data pipeline establishment, a data pipeline modification, or a data pipeline termination.

8. The method of claim 1, wherein the measurement configuration comprises at least one parameter associated with a data pipeline operation requirement, comprising at least one of a data size, data burst characteristics, a jitter, a data rate, or a number of participating user equipments (UEs).

9. The method of claim 1, wherein the reporting criteria comprise at least one triggering condition associated with a measured parameter.

10. The method of claim 1, further comprising receiving a measurement result from at least one radio access network (RAN) node and selecting at least one corresponding UE for participation based on the measurement result.

11. A method of data pipeline measurement and reporting performed by a data pipeline contributor, comprising: receiving, from a data pipeline coordinator, a measurement configuration and reporting criteria; performing at least one measurement according to the measurement configuration; andAtty. Dkt. No. 10085-01-0187-PCT transmitting a measurement report to the data pipeline coordinator when the reporting criteria are satisfied.

12. The method of claim 11, wherein the data pipeline contributor comprises at least one of a data source, a data contributor, or a data sink participating in a data pipeline operation.

13. The method of claim 11, wherein the measurement configuration and the reporting criteria are included in a data pipeline measurement control message.

14. The method of claim 11, wherein the measurement report is included in a data pipeline measurement report message.

15. The method of claim 11, wherein the at least one measurement comprises at least one of a data throughput measurement, a latency or jitter measurement, a packet error rate measurement, a computing resource utilization measurement, or a radio link quality measurement.

16. The method of claim 11, wherein the reporting criteria comprise at least one triggering condition associated with a measured parameter.

17. The method of claim 16, wherein the data pipeline contributor transmits the measurement report to the data pipeline coordinator when the at least one triggering condition associated with the measured parameter is satisfied, comprising when the measured parameter exceeds or falls below a corresponding threshold value.

18. The method of claim 11, further comprising receiving, from the data pipeline coordinator, an instruction to participate in a data pipeline establishment, a data pipeline modification, or a data pipeline termination based on the measurement report.

19. The method of claim 11, wherein performing the at least one measurement comprises using a configuration information associated with a data pipeline operation requirement comprising at least one of a data size, data burst characteristics, a jitter, a data rate, or a number of participating user equipments (UEs).

20. The method of claim 11, wherein the data pipeline contributor performs the at least one measurement and transmits the measurement report in coordination with one or more other data pipeline contributors under a control of the data pipeline coordinator.

21. A data pipeline coordinator, comprising: a transceiver configured to transmit a measurement configuration and reporting criteria to at least one data pipeline contributor and receive, from the at least one data pipeline contributor, a measurement report according to the measurement configuration and the reporting criteria; and an executor configured to perform a data pipeline control action based on the measurement report.Atty. Dkt. No. 10085-01-0187-PCT22. A data pipeline coordinator, comprising: a memory; a transceiver; and a processor coupled to the memory and the transceiver; wherein the data pipeline coordinator is configured to perform the method of any one of claims 1 to 10.

23. A data pipeline contributor, comprising: a transceiver configured to receive, from a data pipeline coordinator, a measurement configuration and reporting criteria; and an executor configured to perform at least one measurement according to the measurement configuration, wherein the transceiver is configured to transmit a measurement report to the data pipeline coordinator when the reporting criteria are satisfied.

24. A data pipeline contributor, comprising: a memory; a transceiver; and a processor coupled to the memory and the transceiver; wherein the data pipeline contributor is configured to perform the method of any one of claims 11

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