DYNAMIC FILTERING OF TELECOMMUNICATION NETWORK AGENTS

Abstract

Telecommunications network hardware unit comprising a processor connected to a computer-readable memory unit, the memory unit containing instructions which, when executed by the processor, implement a method for dynamically filtering telecommunications network agents, the method comprising: Retrieval, by the processor executing software code with respect to a virtual network function (VNF) and a physical network function (PNF) of the telecommunications network hardware unit, of peripheral data associated with a user device (UE) that is enabled with respect to a telecommunications network associated with the telecommunications network hardware unit; Assigning peripheral data to a predefined filter selection model by the processor; Selecting, by the processor executing the predefined filter selection model, and in response to the results of mapping, a filtering agent model from a pool of model resources; Selecting, by the processor in response to the execution of the filtering agent model, filtering agents from the VNF and in connection with noise and distortion reduction, which is related to the UE in relation to the telecommunications network; Retrieval, by the processor using a plurality of sensors of a global positioning system (GPS sensors), of environmental properties related to the telecommunications network; Identify, by the processor based on the environmental characteristics, a specified location of the UE that is enabled in relation to the telecommunications network; Sending the filtering agents to the UE via push, through the processor, with the filtering agents being stored within a temporary memory area of ​​an operating system of the UE; Generating, by the processor, network instructions related to the execution of the filtering agents; Execution, by the processor in response to the activation of the network instructions, of the filtering agents with respect to the UE, wherein the execution activates the filtering agents with respect to the UE for a specified time frame; and Reduce, by the processor in response to the results of execution, noise and distortion that occur during the operation of the UE in relation to the telecommunications network.

Description

BACKGROUND

[0001] The present invention relates generally to a method for filtering noise and distortion occurring within a telecommunications network, and in particular to a method and an associated system for improving telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying the location of a user device, activating the filtering agents, and reducing noise and distortion occurring during the operation of the user device in relation to a telecommunications network.

[0002] In this context, there are already published documents. Document US 2021 / 0029042A1 describes 5G filters for virtual network functions. Security filters can protect direct communication and data exchanged between programs within a container system. In particular, an orchestration system can address the creation and behavior of security filters to manage the behavior of virtual network functions in containers.

[0003] Document US 11,178,041 B1 describes service chaining with physical network functions and updated network functions. It describes techniques related to centralized control, such as software-defined network (SDN) control. The control can create inter-network service chaining to establish traffic between a bare metal server (BMS) and a virtual execution element through inter-network service chaining, utilizing VXLAN as an underlying transport technology. Furthermore, document US 2019 / 0149434 A1 describes the management of physical network functions within a network service instance. This includes adding a physical function (PNF) instance to a network service (NS), modifying the PNF instance within the NS, and finally removing the PNF instance from the NS.Finally, document US 2014 / 0331221A1 describes a cooperative approach to network packet filtering. This involves a network controller that has a virtual function associated with a virtual machine running on a computer system. The network controller includes a simple filter agent associated with the first virtual function. This simple filter agent enforces basic filter rules on received network packets and can also block received network packets. Additional filtering functions are also implemented. SUMMARY

[0004] A first aspect of the invention provides a telecommunications network hardware unit comprising a processor connected to a computer-readable memory unit, the memory unit comprising instructions which, when executed by the processor, implement a method for dynamically filtering telecommunications network agents, the method comprising: retrieving, by the processor executing software code with respect to a virtual network function (VNF) and a physical network function (PNF) of the telecommunications network hardware unit, peripheral data associated with a user equipment (UE) activated with respect to a telecommunications network associated with the telecommunications network hardware unit; and assigning, by the processor, peripheral data to a predefined filter selection model.Selecting from a pool of model resources, by the processor executing the predefined filter selection model, and in response to the results of mapping a filtering agent model; selecting, by the processor in response to the execution of the filtering agent model, filtering agents from the VNF and related to noise and distortion reduction associated with the UE in relation to the telecommunications network; retrieving, by the processor from a plurality of sensors of a global positioning system (GPS sensors), environmental properties related to the telecommunications network; identifying, by the processor based on the environmental properties, a specified location of the UE that is enabled in relation to the telecommunications network;Pushing, by the processor, the filtering agents to the UE, wherein the filtering agents are stored within a temporary memory area of ​​an operating system of the UE; generating, by the processor, network instructions related to the execution of the filtering agents; executing, by the processor in response to the activation of the network instructions, the filtering agents with respect to the UE, wherein the execution activates the filtering agents with respect to the UE for a specified time frame; and reducing, by the processor in response to the results of the execution, noise and distortion that occur during the operation of the UE with respect to the telecommunications network.

[0005] A second aspect of the invention provides a method for dynamically filtering telecommunications network agents, the method comprising: retrieving, by a processor of a telecommunications network hardware unit executing software code with respect to a virtual network function (VNF) and a physical network function (PNF) of the telecommunications network hardware unit, peripheral data associated with a user device (UE) activated with respect to a telecommunications network associated with the telecommunications network hardware unit; mapping, by the processor, peripheral data to a predefined filter selection model; and selecting, by the processor executing the predefined filter selection model, from a pool of model resources in response to the results of the mapping, a filtering agent model.Selecting, by the processor in response to the execution of the filtering agent model, filtering agents from the VNF and related to noise and distortion reduction associated with the UE in relation to the telecommunications network; retrieving, by the processor from a plurality of sensors of a global positioning system (GPS sensors), environmental properties related to the telecommunications network; identifying, by the processor based on the environmental properties, a specified location of the UE that is enabled in relation to the telecommunications network; pushing, by the processor, the filtering agents to the UE, the filtering agents being stored within a temporary memory area of ​​an operating system of the UE; generating, by the processor, network instructions related to the execution of the filtering agents;Execution, by the processor in response to the activation of network instructions, of the filtering agents with respect to the UE, wherein the execution activates the filtering agents with respect to the UE for a specified time frame; and reduction, by the processor in response to the results of the execution, of noise and distortion that occur during the operation of the UE with respect to the telecommunications network.

[0006] A third aspect of the invention provides a computer program product comprising a computer-readable hardware storage unit on which computer-readable program code is stored, wherein the computer-readable program code comprises an algorithm which, when executed by a processor of a telecommunications network hardware unit, implements a method for dynamically filtering telecommunications network agents, the method comprising: retrieving, by the processor executing software code with respect to a virtual network function (VNF) and a physical network function (PNF) of the telecommunications network hardware unit, peripheral data relating to a user device (UE) that is activated with respect to a telecommunications network associated with the telecommunications network hardware unit;Mapping, by the processor, peripheral data to a predefined filter selection model; selecting from a pool of model resources, by the processor executing the predefined filter selection model and in response to the mapping results, a filtering agent model; selecting, by the processor in response to the execution of the filtering agent model, filtering agents from the VNF and in connection with noise and distortion reduction associated with the UE in relation to the telecommunications network; retrieving, by the processor from a plurality of sensors of a global positioning system (GPS sensors), environmental properties associated with the telecommunications network; identifying, by the processor based on the environmental properties, a specified location of the UE that is enabled in relation to the telecommunications network;Pushing, by the processor, the filtering agents to the UE, wherein the filtering agents are stored within a temporary memory area of ​​an operating system of the UE; generating, by the processor, network instructions related to the execution of the filtering agents; executing, by the processor in response to the activation of the network instructions, the filtering agents with respect to the UE, wherein the execution activates the filtering agents with respect to the UE for a specified time frame; and reducing, by the processor in response to the results of the execution, noise and distortion that occur during the operation of the UE with respect to the telecommunications network.

[0007] The present invention advantageously provides a simple method and an associated system capable of filtering noise and distortion occurring within a telecommunications network. BRIEF DESCRIPTION OF THE DRAWINGS Fig. Figure 1 illustrates, according to embodiments of the present invention, a system for implementing an automated process for improving telecommunications network technology, which is related to selecting a filtering agent model and filtering agents, identifying a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device with respect to a telecommunications network. Fig. Figure 2 illustrates, according to embodiments of the present invention, an algorithm that performs a task performed by the system of Fig. 1. Describes in detail the activated process flow for realizing an automated process to improve telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying the location of a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device in relation to a telecommunications network. Fig. Figure 3 illustrates a view of the internal structure of the software / hardware of Fig. 1 according to embodiments of the present invention. Fig. Figure 4 illustrates a data transmission system according to embodiments of the present invention, which enables data transmissions between a VNF and PNFs that are connected via the system of Fig. 1 were activated. Fig. Figure 5 illustrates an algorithm according to embodiments of the present invention which describes in detail a process flow for retrieving environmental properties and creating a noise profile. The Fig. 6A and Fig. Figure 6B illustrates embodiments of a system that includes requirements which are evaluated with a predefined query frequency over a service operating within a radio access network (i.e., a VNF). Fig. Figure 7 illustrates a computer system according to embodiments of the present invention, which is defined by the system of Fig. 1 is used to implement an automated process for improving telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying the location of a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device in relation to a telecommunications network. Fig. Figure 8 illustrates a cloud computing environment according to embodiments of the present invention. Fig. Figure 9 illustrates a set of functional abstraction layers provided by a cloud computing environment according to embodiments of the present invention. DETAILED DESCRIPTION

[0008] The system of Fig. Figure 1 illustrates, according to embodiments of the present invention, a system 100 for improving telecommunications network technology. This system is related to selecting a filtering agent model and filtering agents 138, identifying a user device 133, activating the filtering agents 138, and reducing noise and distortion that occur during the operation of the user device 133 with respect to a telecommunications network 153. Typical fifth-generation (5G) networks are configured to activate logical channeling processes that involve dividing a frequency spectrum into categories for associated applications. Each category is further subdivided into a number of logical channels based on a dynamic propagation delay configuration via a radio interface.The aforementioned internal segmentation process can result in a radio interface belonging to multiple subdivided, independent units that transport packet traffic from a user device (UE) to an eNodeB (e.g., an element of an LTE radio access network) via a new-radio interface, which is multiplexed before transmission to an S1 carrier (e.g., a connectivity provider). Logical channeling processes can introduce distortion and interference (e.g., noise) into a 5G network. Furthermore, if a user is detected to have exceeded the distance limits of a particular connectivity class (due to small cell architectures), distortion within the network traffic can increase, potentially leading to a greater need for retransmissions.The aforementioned increased distortions may not be eliminated due to requirements related to base carriers. Another cause of distortion (within the 5G network) can be natural phenomena such as rain, fog, or the presence of CO2 in the air. Distortion can be introduced into a 5G network within different channels associated with 5G radio operations. Alternatively, distortion can be introduced within a UE device if a user is located in a noisy environment. Similarly, background noise can be introduced into a 5G network, requiring additional processing at an eNodeB. The resulting interference data is then packaged into packets and shared via a New Radio Interface (NR interface), thereby increasing network traffic.Typical noise filtering techniques are unable to provide a unified process to prevent different types of noise from coming from UE units, and therefore the filtering process must be shifted to an eNodeB, so that eNodeB filters are used to reduce network traffic demands.

[0009] The filtering problems mentioned above may not be resolved using simple data filtering techniques, as filtering requirements can differ depending on the type of interference and distortion introduced into a 5G network. Similarly, a range of filtering techniques at an eNodeB and a UE device may be limited, potentially only enabling basic processing capabilities at a 5G core and an edge cloud processor. Furthermore, a significant portion of the noise and distortion processing at transport endpoints may be unable to handle the various types of errors introduced across different layers at NR and UE endpoints.Therefore, the System 100 is able to execute a process within a virtual network function (VNF) of a 5G telecommunications network, which interacts with a single physical network function to retrieve required information to build a multidimensional training model for filtering agents.

[0010] The System 100 from Fig. 1 comprises a telecommunications network hardware unit 139, a user device (UE) 133, a VNF 119, a PNF 122, peripheral data 122, filter selection models 135, and filtering agent models / filtering agents 138, all interconnected via a telecommunications network (telecomm. network) 153. The telecommunications network hardware unit 139 comprises sensors 112, circuit arrangements 127, and software / hardware 121. The UE 133 can comprise any type of data transmission unit, including a mobile unit, tablet computer, laptop computer, smart unit, etc. Peripheral data can comprise any type of data related to the UE 133. The telecommunications network hardware unit 139 and the UE 133 can each comprise embedded unit(s).For the purposes of this definition, an embedded unit is a purpose-built unit or computer comprising a combination of computer hardware and software (with fixed capability or programmable) specifically designed to perform a specialized function. Programmable embedded computers or units may have specialized programming interfaces. In one embodiment, the telecommunications network hardware unit 139 and the UE 133 may each comprise a specialized hardware unit comprising specialized (specific) hardware and circuit arrangements (i.e., specialized, discrete, specific analog, digital, and logic-based circuit arrangements) to perform (independently or in combination) a process that, with respect to the Fig. 1 to 6. Specialized, discrete specific analog, digital, and logic-based circuit arrangements (e.g., sensors 112, circuit arrangements / logic 127, software / hardware 121, etc.) may include proprietary, specially designed components (e.g., a specialized integrated circuit such as an application-specific integrated circuit (ASIC)) designed solely for the execution of an automated process for improving telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device with respect to a telecommunications network.The sensors 112 can include any type of internal or external sensors, including GPS sensors, Bluetooth beaconing sensors, mobile phone detection sensors, WLAN location detection sensors, triangulation detection sensors, activity tracking sensors, a temperature sensor, an ultrasonic sensor, an optical sensor, a video retrieval device, humidity sensors, voltage sensors, network traffic sensors, etc. The telecommunications network 117 can include any type of data transmission network, including a mobile network, a local area network (LAN), a wide area network (WAN), the internet, a wireless network, etc.

[0011] System 100 is configured to collect weather-related information and location-based data to build a location profile for specified objects served within the respective PNF 122. System 100 is also configured to feed information to VNF 119. Furthermore, System 100 is configured to collect all location-based requirements for filtering noise and distortion. These location-based requirements are used to build the filter selection model 135, which is implemented as a training corpus.

[0012] System 100 enables platforms for the dynamic delivery of insights into content to interact with each other to retrieve location-specific, real-time information from the PNF 122. This location-specific, real-time information can include, among other things, weather-related data and real-time environmental monitoring data, such as the presence of fog, CO2 levels in the air, etc. Accordingly, filtering agent requests are updated in the VNF 119. Proactive data retrieved from internet-based resources is used to retrieve the PNF, which provides data such as rainfall information, operational load and sewer balancing information from a respective eNodeB within the PNF 122, etc.

[0013] After receiving the aforementioned information and data, the filtering selection models 135 are invoked with attributes received from various resources. Filtering selection models 135 are activated via functions of the VNF 119. Activated filtering selection models 135 are configured to recognize a request for a filtering algorithm and the respective agents based on a situational need (noise reduction).

[0014] When heavy rain is detected within a region served by a PNF, distortion filters are selected with defined input parameters. A selected filter can then be pushed to an edged entity based on the nature of the event. If distortion filters are selected, they can be pushed to the eNodeB, and associated execution instructions can be transmitted to the eNodeB via an S1 carrier.

[0015] Similarly, if noise or speech interference filters are required, these are pushed to the eNodeB and executed via instructions from a common control channel (CCCH instructions) using S1 carriers and radio carriers to activate a signal. An associated query agent is configured to continuously check request validity and resolve a filter with a feedback loop when a request is completed. The feedback loop can be imposed with respect to a multidimensional model to improve related results.

[0016] Fig. Figure 2 illustrates, according to embodiments of the present invention, an algorithm that is performed by the system 100 of Fig. 1. Describes in detail the activated process flow for implementing an automated process to improve telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying the location of a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device with respect to a telecommunications network. Each of the steps in the algorithm of Fig. 2 can be activated and executed in any order by a computer processor (or processors) that execute the computer code. Furthermore, each of the steps in the algorithm of Fig. 2 by the telecommunications network hardware unit 139 and the UE 133 of Fig. Step 1 is activated and executed in combination. In step 200, peripheral data is retrieved by a telecommunications network hardware unit, which executes software code with respect to a VNF and a PNF of the telecommunications network hardware unit. The peripheral data is associated with a UE that is activated with respect to a telecommunications network associated with the telecommunications network hardware unit. In step 202, the peripheral data is mapped to a predefined filter selection model. In step 204, the filtering agent model is selected from a pool of model resources by executing the predefined filter selection model and in response to the results of the mapping in step 202. The selection of the filtering agent model can be performed with respect to a VNF and a service orchestration layer of a 5G network.

[0017] In step 208, filtering agents are selected from the VNF (via execution of the filtering agent model). The filtering agents are related to noise and distortion reduction, which is associated with the UE in relation to the telecommunications network. Selecting the filtering agents may involve executing a multidimensional VNF machine learning model based on features and attributes of entities at multiple levels.

[0018] In step 210, environmental properties related to the telecommunications network are retrieved via a plurality of sensors from a global positioning system (GPS sensors). The bypass properties may be related to resources that affect triggered PNF functions.

[0019] In step 212, a specified location of the UE, which is enabled with respect to the telecommunications network, is identified based on its environmental properties. In step 214, the filtering agents are pushed to the UE. The filtering agents are stored within a temporary memory area of ​​the UE's operating system. Pushing the filtering agents to the UE can include: 1. Transferring the activation interaction code to the UE 2. Activating (in response to the execution of the activation interaction code) the filtering agents to perform noise and distortion reduction.

[0020] In step 216, network commands related to the execution of the filtering agents are generated. In step 218, in response to the activation of the network commands, the filtering agents are executed with respect to the UE, thereby activating the filtering agents with respect to the UE for a specified time frame. In step 220, noise and distortion occurring during the operation of the UI with respect to the telecommunications network are reduced in response to the execution of step 218. Noise and distortion reduction may include: 1. Evaluating filter agent requests with respect to a predefined query frequency associated with a service running within the VNF. 2. Providing a respective filtering agent (or filtering agents) for a malfunctioning unit of the UE to perform noise and distortion reduction.

[0021] In step 224 (after the execution of step 220 has finished), the filtering agents are removed from the UE.

[0022] Fig. Figure 3 illustrates a view of the internal structure of software / hardware 121 of Fig. 1 according to embodiments of the present invention. The hardware / software 121 includes an assignment module 304, a selection module 305, an execution module 308, a noise and distortion reduction module 314, and data transmission control units 312. The assignment module 304 comprises specialized hardware and software for controlling all functions that perform the assignment steps of Fig. 2. The selection module 305 has specialized hardware and software for controlling all the functionality relating to the filter selection steps, which are related to the algorithm of Fig. 2 are described. The execution module 308 has specialized hardware and software for controlling all functions that define the filter agent execution steps of Fig. 2. The noise and distortion reduction module 314 features specialized hardware and software for controlling all functions that perform the noise and distortion reduction steps of the algorithm of Fig. 2. The data transmission control units 312 are activated to control all data transmissions between the assignment module 304, the selection module 305, the execution module 308 and the noise and distortion reduction module 314.

[0023] Fig. Figure 4 illustrates, according to embodiments of the present invention, a data transmission system 400 that enables data transmissions between a VNF 402 and PNFs 404a and 404b (which are related to peripheral information 408a and 408b and data transmissions 410a and 410b) via the system 100 of Fig. 1. The data transmission system 400 enables a process running within the VNF 402 to collect peripheral information 408a and 408b, such as details relating to ambient noise and details relating to noise at a UE endpoint, for mapping to a predefined filter selection model. Peripheral information 408a and 408b can be associated with various levels of data at the VNF 402. Peripheral information 408a and 408b can be activated through the use of VNF-PNF integrator services, which makes it possible to select a model from an available pool of resources. Likewise, selected filtering agents (at the VNF 402) are pushed to selected target endpoints (which are, for example, associated with PNF 404a and 404b), and associated activation interactions are made to an endpoint (e.g., UE 133 of VNF 402). Fig. 1) transmitted to activate a filter for noise and distortion reduction.

[0024] Fig. Figure 5 illustrates, according to embodiments of the present invention, an algorithm 500 that describes in detail a process flow for retrieving environmental properties and creating a noise profile. In steps 502 and 504, environmental properties are retrieved from GPS-based data resources of respective PNF functions. For example, data stream-based data collectors can be activated to retrieve a GPS identity of a PNF boundary region. Similarly, a selected noise and distortion cancellation filter from a 5G core network infrastructure is activated by executing protocols based on in-band MAC.In step 508, a filtering agent selection process is performed at a VNF function and on a 5G service orchestration layer. This process distributes filtering agents to be pushed to the PNF and a logical endpoint based on the nature of a noise / distortion event (in step 510). Similarly, the filter is pushed to UE units (in step 510) that are subject to noise on voice calls due to a noisy background. In steps 512 and 514, a location is flagged (within a time frame) to create a noise profile. In response, noise-based filters are dynamically deployed when a UE location is detected within a defined boundary region (in step 518). For example, if a crowded retail establishment is detected as the location, a noise cancellation filter will be deployed during the initiation of a voice call.Similarly, a noise suppression filter can be provided for events that trigger natural noise. For example, CO2-based distortion filtering agents are required on an eNodeB (in relation to detected heavy rain or CO2 levels in the air) to achieve correct decoding of packet data.

[0025] The Fig. 6A and Fig. Figure 6B (in combination) illustrates, according to embodiments, a system 600 comprising requirements 602, which are evaluated with a predefined query frequency 604 over a service operating within a radio access network 608 (i.e., a VNF). The system 600 is configured to provide a filtering agent to a degraded unit to optimize network utilization and avoid errors related to repeated packet transmissions. Interfaces are used to transmit different types of network traffic, so filtering agent selection is performed at the radio access network 608. Similarly, filters are selected using a multidimensional machine learning model of a VNF with respect to features and attributes at multiple levels within a common filter repository. Furthermore, input data attributes (i.e.,, which are related to weather, location, and other unit-specific properties) are applied to associated datasets. Selected filtering agents are then pushed to a unit located at the network edge as follows: 1. Suitable filters are detected in the 608 wireless access network based on a noise / distortion situation requirement. 2. Logical channels are created to transfer the machine learning model to a location at the edge. 3. A location at the edge of the network is detected based on a filter type. For example, a distortion filter has a loc=eNodeB at the edge of the network.

[0026] Furthermore, network commands are generated to execute a selected filter at a destination location, causing CCCH data packets to be formed over a radio interface and transmitted via a network repeater (NR). A destination unit is then configured to listen on an NR interface and receive an incoming filter in a temporary area of ​​the unit's operating system. The incoming filter is executed, and a selected filtering agent is activated for a specified timeframe, thus reducing computational overhead at the destination location and conserving processing power at the endpoint unit. All further packet data transmission processes are performed after filter processing. A query thread for a validation manager is enabled at a PNF and configured to check for event validity. Similarly, an event manager raises a signal when a current request is complete.The incoming filter is then dissolved (i.e., deleted).

[0027] Fig. Figure 7 illustrates a computer system 90 (e.g., the telecommunications network hardware unit 139 and the UE 133 of Fig. 1), which is achieved through the system 100 of Fig. 1. are used or comprised of this system to improve telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying the location of a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device in relation to a telecommunications network.

[0028] Aspects of the present invention may take the form of an embodiment fully realized in hardware, an embodiment fully realized in software (including, but not limited to, firmware, resident software, microcode, etc.), or an embodiment that combines software and hardware aspects, which are herein generally referred to as a “circuit”, “module”, or “system”.

[0029] The present invention may be a system, a method, and / or a computer program product. The computer program product may include a computer-readable storage medium (or media) on which computer-readable program instructions are stored to cause a processor to execute aspects of the present invention.

[0030] The computer-readable storage medium can be a physical unit on which instructions for use by a unit for executing instructions can be stored and retained. The computer-readable storage medium can be, for example, but is not limited to, an electronic storage unit, a magnetic storage unit, an optical storage unit, an electromagnetic storage unit, a semiconductor storage unit, or any suitable combination thereof.A non-exhaustive list of more precise examples of computer-readable storage media includes the following: a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable read-only memory in the form of a compact disc (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically coded unit such as punched cards or raised structures in a groove with instructions recorded on them, or any suitable combination of the foregoing.A computer-readable storage medium, as used herein, is not to be interpreted as consisting of volatile signals per se, such as radio waves or freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through an optical fiber cable), or electrical signals transmitted via a cable.

[0031] The computer-readable program instructions described herein can be downloaded over a network, such as the internet, a local area network, a wide area network, and / or a wireless network, from a computer-readable storage medium to the relevant data processing units or to an external computer or storage device. The network may include copper transmission cables, fiber optic transmission lines, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in the data processing unit receives computer-readable program instructions from the network and forwards them for storage on a computer-readable storage medium within the respective data processing unit.

[0032] Computer-readable program instructions for performing operations of the present invention may be assembly instructions, ISA instructions (ISA = Instruction Set Architecture), machine instructions, machine-dependent instructions, microcode, firmware instructions, data for setting states, or either source code or object code written in any combination of one or more programming languages, including an object-oriented programming language such as Smalltalk, C++, Spark, the R language or similar, and conventional procedural programming languages ​​such as the "C" programming language or similar programming languages.The computer-readable program instructions can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be to an external computer (for example, via the internet using an internet service provider).In some embodiments, electronic circuit arrangements, including, for example, programmable logic circuit arrangements, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), can execute computer-readable program instructions by using state information from the computer-readable program instructions to personalize the electronic circuit arrangement, thus implementing aspects of the present invention.

[0033] Aspects of the present invention are described herein with reference to flowchart representations and / or block diagrams of processes, units (systems), and computer program products according to embodiments of the invention. It will be clear that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented using computer-readable program instructions.

[0034] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a specialized computer, or other programmable data processing units to create a machine, such that the instructions executed via the processor of the computer or other programmable data processing units provide the means to realize the functions / actions specified in a block or blocks of the flowchart(s) and / or block scheme(s).These computer-readable program instructions may also be stored in a computer-readable medium that can instruct a computer, a programmable data processing unit and / or other units to function in a certain manner, such that the computer-readable medium with instructions stored on it constitutes a manufacturing item containing instructions that implement the function / action specified in a block or blocks of the flowcharts and / or block diagrams.

[0035] The computer-readable program instructions can also be loaded into a computer, another programmable data processing unit, or another unit to cause a series of operations to be performed on the computer, on the other programmable unit, or on the other unit to create a computer-realized process, such that the instructions executed on the computer, on the other programmable unit, or on the other unit realize the functions / actions specified in a block or blocks of the flowcharts and / or block diagrams.

[0036] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, processes, and computer program products according to various embodiments of the present invention. In this context, each block in the flowcharts or block diagrams can represent a module, segment, or section of instructions that includes one or more executable instructions for implementing the specified logic function(s). In some alternative implementations, the functions specified in the block can be executed in a different order than that shown in the figures.For example, two blocks shown consecutively can actually be executed as one step, simultaneously, essentially concurrently, in a partially or fully overlapping manner, or the blocks can sometimes be executed in reverse order, depending on the functionality associated with them. Furthermore, it should be noted that each block in the block diagrams and / or flowchart representations, as well as combinations of blocks in the block diagrams and / or flowchart representations, can be implemented using dedicated hardware systems to perform the specified functions or actions, or using combinations of dedicated hardware and dedicated computer instructions.

[0037] The in Fig. Figure 7 illustrates computer system 90, which comprises a processor 91, an input unit 92 connected to the processor 91, an output unit 93 connected to the processor 91, and memory units 94 and 95, each connected to the processor 91. The input unit 92 can be, among other things, a keyboard, a mouse, a camera, a touchscreen, etc. The output unit 93 can be, among other things, a printer, a plotter, a computer monitor, a magnetic tape, a removable hard disk, a floppy disk, etc. The memory units 94 and 95 can be, among other things, a hard disk, a floppy disk, a magnetic tape, an optical storage medium such as a compact disc (CD), a digital video disc (DVD), dynamic random access memory (DRAM), read-only memory (ROM), etc. The memory unit 95 contains a computer code 97.The computer code 97 includes algorithms (e.g., the algorithms of . Fig. 2) for improving telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device with respect to a telecommunications network. The processor 91 executes the computer code 97. The memory unit 94 contains input data 96. The input data 96 includes inputs required by the computer code 97. The output unit 93 displays outputs from the computer code 97. One or both memory units 94 and 95 (or one or more additional memory units, such as the read-only memory unit 85) can hold algorithms (e.g., the algorithms of Fig. 2) and may be used as a computer-usable medium (or as a computer-readable medium or as a program storage unit) that contains a computer-readable program code embodied therein and / or contains other data stored therein, the computer-readable program code comprising the computer code 97. In general terms, a computer program product (or alternatively a manufactured article) of the computer system 90 may comprise the computer-usable medium (or the program storage unit).

[0038] Unlike storing on and accessing from a hard disk, optical disk, or other writable, rewritable, or removable hardware storage unit 95, in some embodiments the stored computer program code 84 (which includes, for example, algorithms) may be stored on a static, non-removable, read-only storage medium, such as a read-only storage unit (ROM unit) 85, or the processor 91 may access it directly from such a static, non-removable, read-only storage medium. Similarly, in some embodiments the stored computer program code 97 may be stored as computer-readable firmware 85, or the processor 91 may access it directly from such firmware 85 instead of one or more dynamic or removable hardware data storage units 95, such as a hard disk or optical disk.

[0039] Furthermore, any of the components of the present invention could be created, integrated, hosted, maintained, deployed, managed, serviced, etc., by a service provider offering improvements to network technology related to selecting a filtering agent model and filtering agents, identifying a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device in relation to a telecommunications network.Thus, the present invention discloses a process for deploying, creating, integrating, hosting, maintaining, and / or integrating computer infrastructure, including integrating computer-readable code into the computer system 90, wherein the code, in combination with the computer system 90, is capable of enabling a process for improving telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device with respect to a telecommunications network. In a further embodiment, the invention provides a business-related method that performs the process steps of the invention on a subscription, advertising, and / or fee basis.Thus, a service provider, such as a solution integrator, could offer to enable a process for improving telecommunications network technology. This process involves selecting a filtering agent model and filtering agents, identifying a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device on a telecommunications network. In this case, the service provider can create, maintain, support, etc., a computer infrastructure that performs the process steps of the invention for one or more customers. In return, the service provider can receive payments from the customers under a subscription and / or fee agreement, and / or the service provider can receive payments from the sale of advertising content to one or more third parties.

[0040] Although it shows Fig. 7 a computer system 90 as a specific combination of hardware and software, however any configuration of hardware and software known to a person skilled in the art may be used for the aforementioned purposes in conjunction with the specific computer system 90. Fig. 7 can be used. For example, memory units 94 and 95 can be sections of a single memory unit instead of separate memory units. Cloud computing environment

[0041] It is understood that while this disclosure contains a detailed description of cloud computing, the implementation of the teachings presented herein is not limited to a cloud computing environment. Rather, embodiments of the present invention can be implemented in conjunction with any other type of data processing environment currently known or developed in the future.

[0042] Cloud computing is a service delivery model that provides convenient and on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing power, main memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management overhead or interaction with a service provider. This cloud model can include at least five characteristics, at least three service models, and at least four deployment models.

[0043] The properties are as follows:

[0044] On-demand Self Service: A cloud customer can unilaterally and automatically provision data processing functions such as server time and network storage as needed, without requiring any human interaction with the service provider.

[0045] Broad Network Access: Functions are available over a network, accessible via standard mechanisms that support use by heterogeneous platforms, thin or thick client platforms (e.g., mobile phones, notebook computers, and PDAs).

[0046] Resource pooling: The provider's data processing resources are pooled to serve multiple customers using a multi-user model with diverse physical and virtual resources that are dynamically allocated and reassigned according to demand. There is a perceived location independence in that the customer generally has no control over or knowledge of the exact location of the provided resources, but may be able to specify the location at a higher level of abstraction (e.g., country, state, or data center).

[0047] Rapid elasticity: Features can be deployed quickly and elastically, in some cases automatically, to rapidly scale up functionality, and released quickly to rapidly scale down functionality. This often gives customers the impression that the available features are unlimited and can be purchased in any quantity at any time.

[0048] Measured Service: Cloud systems automatically control and optimize resource usage by employing a metering function at a specific level of abstraction appropriate for the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the service provider and the customer.

[0049] The service models are as follows:

[0050] Software as a Service (SaaS): The functionality provided to the customer consists of using the provider's applications running on a cloud infrastructure. These applications can be accessed from various client devices via a thin-client interface, such as a web browser (e.g., web-based email). The customer does not manage or control the underlying cloud infrastructure, including networks, servers, operating systems, storage space, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.

[0051] Platform as a Service (PaaS): The functionality provided to the customer is to deploy customer-created or purchased applications on the cloud infrastructure, using programming languages ​​and tools supported by the provider. The customer does not manage or control the underlying cloud infrastructure, including networks, servers, operating systems, or storage space, but has control over the deployed applications and potentially over configurations of the applications' hosting environment.

[0052] Infrastructure as a Service (IaaS): The functionality provided to the customer consists of supplying processing, storage, networking, and other basic data processing resources, allowing the customer to deploy and run any software, including operating systems and applications. The customer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, and deployed applications, and potentially limited control over selected networking components (e.g., host firewalls).

[0053] The following are the deployment models:

[0054] Private Cloud: The cloud infrastructure is operated exclusively for one organization. It can be managed by the organization or a third party and can be located on the organization's premises or off-site.

[0055] Community Cloud: This cloud infrastructure is used by multiple organizations and supports a specific user community with shared interests (e.g., aspects related to a task, security requirements, policies, and compliance with laws and regulations). It can be managed by the organizations or a third party and may be located on or off-site.

[0056] Public Cloud: The cloud infrastructure is made available to the general public or a large group within an industry and is owned by an organization that sells cloud services.

[0057] Hybrid cloud: The cloud infrastructure is a mixture of two or more clouds (private cloud, community cloud or public cloud) that remain independent entities but are connected via a standardized or proprietary technology that enables the portability of data and applications (e.g. cloud bursting for load balancing between clouds).

[0058] A cloud computing environment is service-oriented, emphasizing statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure comprising a network of interconnected nodes.

[0059] Now with reference to Fig. Figure 8 shows an illustrative cloud computing environment 50. As shown, the cloud computing environment 50 comprises one or more cloud computing nodes 10 with which local data processing units used by cloud customers, such as a personal digital assistant (PDA) or mobile phone 54A, a desktop computer 54B, a laptop computer 54C, and / or an automotive computer system 54N, can exchange data. The nodes 10 can exchange data with each other. They can be grouped physically or virtually in one or more networks, such as a private cloud, community cloud, public cloud, or hybrid cloud, as described above, or in a combination thereof (not shown). This enables the cloud computing environment 50 to provide infrastructure, platforms, and / or software as services, for which a cloud customer does not need to manage resources on a local data processing unit.It goes without saying that the types of in . Fig. The data processing units 54A, 54B, 54C and 54N shown in Figure 12 are for illustrative purposes only, and the data processing nodes 10 and the cloud computing environment 50 can exchange data with any type of computer unit via any type of network and / or any type of connection that can be accessed via a network (e.g. using a web browser).

[0060] Now with reference to Fig. Figure 9 shows a set of functional abstraction layers that are used in the cloud computing environment 50 (see Fig. 8) be provided. It should be clear from the outset that the in Fig.The components, layers, and functions shown in Figure 9 are intended for illustrative purposes only, and embodiments of the invention are not limited to them. As illustrated, the following layers and corresponding functions are provided:

[0061] A hardware and software layer 60 comprises hardware and software components. Examples of hardware components include: Mainframe computers 61; servers 62 based on the RISC architecture (RISC = Reduced Instruction Set Computer); servers 63; blade servers 64; storage units 65; and networks and networking components 66. In some embodiments, software components include network application server software 67 and database software 68.

[0062] A virtualization layer 70 provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers 71; virtual storage 72; virtual networks 73, including virtual private networks; virtual applications and operating systems 74; and virtual clients 75.

[0063] In one example, an administration layer 80 can provide the functions described below. A resource provisioning layer 81 provides the dynamic procurement of data processing resources and other resources used to perform tasks within the cloud computing environment. A charge tracking and pricing layer 82 provides cost tracking while resources are used within the cloud computing environment, as well as billing and invoicing for the use of these resources. In one example, these resources could include application software licenses. A security layer provides identity verification for cloud customers and tasks, as well as protection for data and other resources. A user portal 83 provides customers and system administrators with access to the cloud computing environment.Service Level Management (SLM) 87 provides the allocation and management of cloud computing resources to ensure that the required level of service is achieved. Service Level Agreement (SLA) planning and fulfillment 88 provides the advance planning and procurement of cloud computing resources for which future requirements are anticipated based on an SLA.

[0064] An operational load layer 101 provides examples of functionalities for which the cloud computing environment can be used.Examples of operational loads and functions that can be provided from this layer include: mapping and navigation 102; software development and management 103 during the lifecycle; delivery 133 of training in virtual training rooms; processing 134 of data analytics; transaction processing 106; and improving network switching technology related to detecting operational states for ports, generating actions related to the operational states with respect to data packets arriving at the ports, and improving telecommunications network technology related to selecting a filtering agent model and filtering agents, identifying the location of a user device, activating the filtering agents, and reducing noise and distortion that occur during the operation of the user device with respect to a telecommunications network 107.

[0065] Although embodiments of the present invention have been described for illustrative purposes, many modifications and changes are clear to those skilled in the art. Accordingly, the appended claims and all such modifications and changes shall be deemed to fall within the scope of protection of this invention.

Claims

[1] Telecommunications network hardware unit comprising a processor connected to a computer-readable memory unit, the memory unit comprising instructions which, when executed by the processor, implement a method for dynamically filtering telecommunications network agents, the method comprising: Retrieval, by the processor executing software code with respect to a virtual network function (VNF) and a physical network function (PNF) of the telecommunications network hardware unit, of peripheral data associated with a user device (UE) that is enabled with respect to a telecommunications network associated with the telecommunications network hardware unit; Assigning peripheral data to a predefined filter selection model by the processor; Selecting, by the processor executing the predefined filter selection model, and in response to the results of mapping, a filtering agent model from a pool of model resources; Selecting, by the processor in response to the execution of the filtering agent model, filtering agents from the VNF and in connection with noise and distortion reduction, which is related to the UE in relation to the telecommunications network; Retrieval, by the processor using a plurality of sensors of a global positioning system (GPS sensors), of environmental properties related to the telecommunications network; Identify, by the processor based on the environmental characteristics, a specified location of the UE that is enabled in relation to the telecommunications network; Sending the filtering agents to the UE via push, through the processor, with the filtering agents being stored within a temporary memory area of ​​an operating system of the UE; Generating, by the processor, network instructions related to the execution of the filtering agents; Execution, by the processor in response to the activation of the network instructions, of the filtering agents with respect to the UE, wherein the execution activates the filtering agents with respect to the UE for a specified time frame; and Reduce, by the processor in response to the results of execution, noise and distortion that occur during the operation of the UE in relation to the telecommunications network. [2] Telecommunications network hardware unit according to claim 1, wherein the method further comprises: After the reduction process is complete, the processor removes the filtering agent from the user device. [3] Telecommunications network hardware unit according to claim 1, wherein the sending of the filtering agents via push to the UE comprises: Transfer of activation interaction codes to the UE; and Activate, in response to the execution of the activation interaction code, the filtering agents to perform noise and distortion reduction. [4] Telecommunications network hardware unit according to claim 1, wherein the environmental properties are related to resources that affect triggered PNF functions. [5] Telecommunications network hardware unit according to claim 1, wherein the selection of the filtering agent model is performed with respect to a VNF and a service orchestration layer of a 5G network. [6] Telecommunications network hardware unit according to claim 1, wherein the method further comprises: Evaluate, by the processor, requests from filtering agents with respect to a predefined query frequency associated with a service running within the VNF; and Providing, by the processor, a respective filtering agent of the filtering agents for a malfunctioning unit of the UE to perform the reduction. [7] Telecommunications network hardware unit according to claim 1, comprising the selection of the filtering agents: Executing a multidimensional VNF machine learning model based on features and attributes of units at multiple levels. [8] Method for dynamically filtering telecommunications network agents, which features: Retrieval, by a processor of a telecommunications network hardware unit executing software code with respect to a virtual network function (VNF) and a physical network function (PNF) of the telecommunications network hardware unit, of peripheral data associated with a user device (UE) that is enabled with respect to a telecommunications network associated with the telecommunications network hardware unit; Assigning peripheral data to a predefined filter selection model by the processor; Selecting, by the processor executing the predefined filter selection model, and in response to the results of mapping, a filtering agent model from a pool of model resources; Selecting, by the processor in response to the execution of the filtering agent model, filtering agents from the VNF and in connection with noise and distortion reduction, which is related to the UE in relation to the telecommunications network; Retrieval, by the processor using a plurality of sensors of a global positioning system (GPS sensors), of environmental properties related to the telecommunications network; Identify, by the processor based on the environmental characteristics, a specified location of the UE that is enabled in relation to the telecommunications network; Sending the filtering agents to the UE via push, through the processor, with the filtering agents being stored within a temporary memory area of ​​an operating system of the UE; Generating, by the processor, network instructions related to the execution of the filtering agents; Execution, by the processor in response to the activation of the network instructions, of the filtering agents with respect to the UE, wherein the execution activates the filtering agents with respect to the UE for a specified time frame; and Reduce, by the processor in response to the results of execution, noise and distortion that occur during the operation of the UE in relation to the telecommunications network. [9] The method of claim 8, further comprising: After the reduction process is complete, the processor removes the filtering agent from the user device. [10] Method according to claim 8, wherein the sending of the filtering agents to the UE via push: Transfer of activation interaction codes to the UE; and Activate, in response to the execution of the activation interaction code, the filtering agents to perform noise and distortion reduction. [11] Method according to claim 8, wherein the environmental properties are related to resources that affect triggered PNF functions. [12] Method according to claim 8, wherein the selection of the filtering agent model is performed with respect to a VNF and a service orchestration layer of a 5G network. [13] The method of claim 8, further comprising: Evaluate, by the processor, requests from filtering agents with respect to a predefined query frequency associated with a service running within the VNF; and Providing, by the processor, a respective filtering agent of the filtering agents for a malfunctioning unit of the UE to perform the reduction. [14] Method according to claim 8, wherein the selection of the filtering agents comprises: Executing a multidimensional VNF machine learning model based on features and attributes of units at multiple levels. [15] The method of claim 8, further comprising: Providing at least one support service for at least one of creating, integrating, hosting, maintaining or deploying computer-readable code in the telecommunications network hardware unit, wherein the code is executed by the processor to accomplish: retrieving peripheral data, mapping, selecting the filtering agent model, selecting the filtering agents, retrieving environment properties, tagging, pushing, generating, executing and decimating. [16] Computer program product comprising a computer-readable hardware storage unit which stores computer-readable program code, wherein the computer-readable program code comprises an algorithm which, when executed by a processor of a telecommunications network hardware unit, implements a method for dynamically filtering telecommunications network agents, wherein the method comprises: Retrieval, by the processor executing software code with respect to a virtual network function (VNF) and a physical network function (PNF) of the telecommunications network hardware unit, of peripheral data associated with a user device (UE) that is enabled with respect to a telecommunications network associated with the telecommunications network hardware unit; Assigning peripheral data to a predefined filter selection model by the processor; Selecting, by the processor executing the predefined filter selection model, and in response to the results of mapping, a filtering agent model from a pool of model resources; Selecting, by the processor in response to the execution of the filtering agent model, filtering agents from the VNF and in connection with noise and distortion reduction, which is related to the UE in relation to the telecommunications network; Retrieval, by the processor using a plurality of sensors of a global positioning system (GPS sensors), of environmental properties related to the telecommunications network; Identify, by the processor based on the environmental characteristics, a specified location of the UE that is enabled in relation to the telecommunications network; Sending the filtering agents to the UE via push, through the processor, with the filtering agents being stored within a temporary memory area of ​​an operating system of the UE; Generating, by the processor, network instructions related to the execution of the filtering agents; Execution, by the processor in response to the activation of the network instructions, of the filtering agents with respect to the UE, wherein the execution activates the filtering agents with respect to the UE for a specified time frame; and Reduce, by the processor in response to the results of execution, noise and distortion that occur during the operation of the UE in relation to the telecommunications network. [17] Computer program product according to claim 16, wherein the method further comprises: After the reduction process is complete, the processor removes the filtering agent from the user device. [18] Computer program product according to claim 16, wherein the sending of the filtering agents via push to the UE comprises: Transfer of activation interaction codes to the UE; and Activate, in response to the execution of the activation interaction code, the filtering agents to perform noise and distortion reduction. [19] Computer program product according to claim 16, wherein the environment properties are related to resources that affect triggered PNF functions. [20] Computer program product according to claim 16, wherein the selection of the filtering agent model is performed with respect to a VNF and a service orchestration layer of a 5G network.

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