Method and system for managing a network function

Abstract

The present disclosure relates to a method and a system for managing a network function The present disclosure encompasses receiving a resource threshold event associated with at least one network function from an event routing manager (ERM) module [316], wherein the resource threshold event at least comprises resource load information; retrieving, from a database, a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules; computing a hysteresis evaluation based on the received resource load information and the predefined scaling policy; determining, whether the computed hysteresis evaluation breaches the set of threshold parameters; and transmitting a scaling request to a policy execution engine (PEEGN) module to mitigate breach of the computed hysteresis evaluation.

Description

METHOD AND SYSTEM FOR MANAGING A NETWORK FUNCTIONFIELD OF INVENTION

[0001] The present disclosure generally relates to network performance management systems. More particularly, embodiments of the present disclosure relate to methods and systems for managing a network function.BACKGROUND

[0002] The following description of the related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.

[0003] Wireless communication technology has rapidly evolved over the past few decades, with each generation bringing significant improvements and advancements. The first generation of wireless communication technology was based on analog technology and offered only voice services. However, with the advent of the second-generation (2G) technology, digital communication and data services became possible, and text messaging was introduced. 3G technology marked the introduction of high-speed internet access, mobile video calling, and location-based services. The fourth generation (4G) technology revolutionized wireless communication with faster data speeds, better network coverage, and improved security. Currently, the fifth generation (5G) technology is being deployed, promising even faster data speeds, low latency, and the ability to connect multiple devices simultaneously. With each generation, wireless communication technology has become more advanced, sophisticated, and capable of delivering more services to its users.

[0004] Virtual Network Functions (VNFs) and Cloud Network Functions (CNFs) play a critical role in modern networking infrastructure, enabling dynamic and scalable network services. To efficiently manage VNFs / Virtual Network Function Components (VNFCs) and CNFs / Cloud Network Function Components (CNFCs), it is essential to have a mechanism for auto-scaling that responds to changes in resource utilization in real-time. The Network Platform Decision Analytics(NPDA) micro-service offers an innovative solution by providing auto-scaling capabilities through seamless interaction with the Capacity Management Platform (CMP) microservice.

[0005] In traditional networking systems, there is a lack of real-time management for VNFs / VNFCs and CNFs / CNFCs, making it challenging to respond to resource utilization changes promptly. The CMP microservice not only tracks the resource details of these network functions but also serves as the conduit for initiating communication with the NPDA micro-service. This interaction is crucial for enabling dynamic auto-scaling.

[0006] Further, over the period of time various solutions have been developed to address resource management operations in microservices architecture. However, there are certain challenges with the existing solutions. For example, the existing solutions do not perform in real-time.

[0007] Thus, there exists an imperative need in the art to provide a method and system for managing a network function that addresses the challenges associated with resource management in microservices architecture, which the present disclosure aims to address.SUMMARY

[0008] This section is provided to introduce certain aspects of the present disclosure in a simplified form that are further described below in the detailed description. This summary is not intended to identify the key features or the scope of the claimed subject matter.

[0009] An aspect of the present disclosure may relate to a method for managing a network function. The method includes receiving, by a transceiver unit at a network function virtualization platform decision and analytics (NPDA) module, a resource threshold event associated with at least one network function from an event routing manager (ERM) module, wherein the resource threshold event at least comprises resource load information. The method further includes retrieving, by a retrieving unit at the NPDA module, from a database, a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules. The method further includes computing, by a processing unit at the NPDA module, a hysteresis evaluation based on the received resource load information and the predefined scaling policy. The method further includes determining, by a determining unit at the NPDAmodule, whether the computed hysteresis evaluation breaches the set of threshold parameters. Finally, the method includes transmitting, bythe transceiver unit at the NPDA module, a scaling request to a policy execution engine (PEEGN) module to mitigate breach of the computed hysteresis evaluation.

[0010] In an exemplary aspect of the present disclosure, the method further comprises executing, by the processing unit at the PEEGN module, a scaling action on the at least one network function, based on the scaling request.

[0011] In an exemplary aspect of the present disclosure, the scaling action comprises at least one of an auto-scale up, and an auto-scale down of the at least one network function.

[0012] In an exemplary aspect of the present disclosure, at least the network function is selected from a group consisting of Virtual Network Functions (VNFs), Virtual Network Function Components (VNFCs), Container Network functions (CNFs), and Container Network Function Components (CNFCs).

[0013] In an exemplary aspect of the present disclosure, the hysteresis evaluation comprises comparing, by a comparing unit, the resource load information with historical resource usage data to prevent frequent scaling operations.

[0014] In an exemplary aspect of the present disclosure, the resource threshold event is received at the ERM module from a capacity monitoring manager (CMM) microservice.

[0015] Another aspect of the present disclosure may relate to a system for managing a network function. The system comprises a network function virtualization platform decision and analytics (NPDA) module. The NPDA module comprises a transceiver unit configured to receive a resource threshold event associated with at least one network function from an event routing manager (ERM) module, wherein the resource threshold event includes resource load information. The NPDA module further comprises a retrieving unit configured to retrieve, from a database, a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules. The NPDA module further comprises a processing unit configured to compute a hysteresis evaluation based on the received resource load information and the predefined scaling policy. The NPDA module further comprises a determining unit configured to determine whether the computed hysteresis evaluation breaches the set of threshold parameters. The transceiver unit isfurther configured to transmit a scaling request to a policy execution engine (PEEGN) module to mitigate breach of the computed hysteresis.

[0016] Yet another aspect of the present disclosure may relate to a non-transitory computer readable storage medium storing instructions for managing a network function, the instructions include executable code which, when executed by one or more units of a system, causes a transceiver unit of the system to receive a resource threshold event associated with at least one network function from an event routing manager (ERM) module, wherein the resource threshold event includes resource load information. The instructions when executed further causes a retrieving unit of the system to retrieve, from a database, a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules. The instructions when executed further causes a processing unit of the system to compute a hysteresis evaluation based on the received resource load information and the predefined scaling policy. The instructions when executed further causes a determining unit of the system to determine whether the computed hysteresis evaluation breaches the set of threshold parameters. The instructions when executed further causes the transceiver unit of the system to transmit a scaling request to a policy execution engine (PEEGN) module to mitigate breach of the computed hysteresis.OBJECTS OF THE DISCLOSURE

[0017] Some of the objects of the present disclosure, which at least one embodiment disclosed herein satisfies are listed herein below.

[0018] It is an object of the present disclosure to provide a system and a method for managing a network function.

[0019] It is an object of the present disclosure to provide a system and a method to define a trigger point for evaluating a threshold breach based on pre-defined policies for a VNF / VNFC or CNF / CNFC.

[0020] It is another object of the present disclosure to provide a solution to keep track of the VNF / VNFC or CNF / CNFC load and informing the same to NPDA micro service in real-time.BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated herein, and constitute a part of this disclosure, illustrate exemplary embodiments of the disclosed methods and systems in which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Also, the embodiments shown in the figures are not to be construed as limiting the disclosure, but the possible variants of the method and system according to the disclosure are illustrated herein to highlight the advantages of the disclosure. It will be appreciated by those skilled in the art that disclosure of such drawings includes disclosure of electrical components or circuitry commonly used to implement such components.

[0022] FIG. 1 illustrates an exemplary block diagram representation of a management and orchestration (MANO) architecture

[0100] , in accordance with exemplary implementation of the present disclosure.

[0023] FIG. 2 illustrates an exemplary block diagram of a computing device upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure.

[0024] FIG. 3 illustrates an exemplary block diagram of a system for managing a network function, in accordance with exemplary implementations of the present disclosure.

[0025] FIG. 4 illustrates a method flow diagram for managing a network function in accordance with exemplary implementations of the present disclosure.

[0026] FIG. 5 illustrates a process flow diagram for managing a network function in accordance with exemplary implementations of the present disclosure.

[0027] The foregoing shall be more apparent from the following more detailed description of the disclosure.DETAILED DESCRIPTION

[0028] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure.It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter may each be used independently of one another or with any combination of other features. An individual feature may not address any of the problems discussed above or might address only some of the problems discussed above.

[0029] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosure as set forth.

[0030] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail.

[0031] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations may be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure.

[0032] The word “exemplary” and / or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and / or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive — in a manner similar to the term “comprising” as an open transition word — without precluding any additional or other elements.

[0033] As used herein, a “processing unit” or “processor” or “operating processor” includes one or more processors, wherein processor refers to any logic circuitry for processing instructions. A processor may be a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor, a plurality of microprocessors, one or more microprocessors in association with a Digital Signal Processing (DSP) core, a controller, a microcontroller, Application Specific Integrated Circuits, Field Programmable Gate Array circuits, any other type of integrated circuits, etc. The processor may perform signal coding data processing, input / output processing, and / or any other functionality that enables the working of the system according to the present disclosure. More specifically, the processor or processing unit is a hardware processor.

[0034] As used herein, “a user equipment”, “a user device”, “a smart-user-device”, “a smartdevice”, “an electronic device”, “a mobile device”, “a handheld device”, “a wireless communication device”, “a mobile communication device”, “a communication device” may be any electrical, electronic and / or computing device or equipment, capable of implementing the features of the present disclosure. The user equipment / device may include, but is not limited to, a mobile phone, smart phone, laptop, a general-purpose computer, desktop, personal digital assistant, tablet computer, wearable device or any other computing device which is capable of implementing the features of the present disclosure. Also, the user device may contain at least one input means configured to receive an input from unit(s) which are required to implement the features of the present disclosure.

[0035] As used herein, “storage unit” or “memory unit” refers to a machine or computer-readable medium including any mechanism for storing information in a form readable by a computer or similar machine. For example, a computer-readable medium includes read-only memory (“ROM”), random access memory (“RAM”), magnetic disk storage media, optical storage media, flash memory devices or other types of machine-accessible storage media. The storage unit stores at least the data that may be required by one or more units of the system to perform their respective functions.

[0036] As used herein “interface” or “user interface” refers to a shared boundary across which two or more separate components of a system exchange information or data. The interface may also be referred to a set of rules or protocols that define communication or interaction of one or more modules or one or more units with each other, which also includes the methods, functions, or procedures that may be called.

[0037] All modules, units, components used herein, unless explicitly excluded herein, may be software modules or hardware processors, the processors being a general-purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASIC), Field Programmable Gate Array circuits (FPGA), any other type of integrated circuits, etc.

[0038] As used herein the transceiver unit include at least one receiver and at least one transmitter configured respectively for receiving and transmitting data, signals, information, or a combination thereof between units / components within the system and / or connected with the system.

[0039] As used herein, a hysteresis evaluation refers to a process used in decision-making systems where actions are triggered based on certain threshold conditions, but with a delay or "buffer" to avoid rapid fluctuations between two states.

[0040] As discussed in the background section, the current known solutions have several shortcomings. The present disclosure aims to overcome the above-mentioned and other existing problems in this field of technology by providing method and system for managing a network function.

[0041] FIG. 1 illustrates an exemplary block diagram representation of a management and orchestration (MANO) architecture

[0100] , in accordance with exemplary implementation of the present disclosure. The MANO architecture

[0100] is developed for managing telecom cloud infrastructure automatically, managing design or deployment design, managing instantiation of a network node(s) etc. The MANO architecture

[0100] deploys the network node(s) in the form of Virtual Network Function (VNF) and Cloud-native / Container Network Function (CNF). The system may comprise one or more components of the MANO architecture. The MANO architecture

[0100] is used to auto-instantiate the VNFs into the corresponding environment of the present disclosure so that it could help in onboarding other vendor(s) CNFs and VNFs to the platform. In an implementation, the system comprises a NFV Platform Decision Analytics (NPDA) module

[1096] component.

[0042] As shown in FIG. 1, the MANO architecture

[0100] comprises a user interface layer, a network function virtualization (NFV) and software defined network (SDN) design function module

[0104] ; a platforms foundation services module

[0106] , a platform core services module

[0108] and a platform resource adapters and utilities module

[0112] , wherein all the components are assumed to be connected to each other in a manner as obvious to the person skilled in the art for implementing features of the present disclosure.

[0043] The NFV and SDN design function module

[0104] further comprises a VNF lifecycle manager (compute)

[1042] ; a VNF catalogue

[1044] ; a network services catalogue

[1046] ; a network slicing and service chaining manager

[1048] ; a physical and virtual resource manager

[1050] and a CNF lifecycle manager

[1052] , The VNF lifecycle manager (compute)

[1042] is responsible for on which server of the communication network the microservice will be instantiated. The VNF lifecycle manager (compute)

[1042] will manage the overall flow of incoming / outgoing requests during interaction with the user. The VNF lifecycle manager (compute)

[1042] is responsible for determining which sequence to be followed for executing the process. For example, in an AMF network function of the communication network (such as a 5G network), sequence for execution of processes Pl and P2 etc. The VNF catalogue

[1044] stores the metadata of all the VNFs (also CNFs in some cases). The network services catalogue

[1046] stores the information of the services that need to be run. The network slicing and service chaining manager

[1048] manages the slicing (an ordered and connected sequence of network service / network functions (NFs)) that must be applied to a specific networked data packet. The physical and virtual resource manager

[1050] stores the logical and physical inventory of the VNFs. Just like the VNF lifecycle manager (compute)

[1042] , the CNF lifecycle manager

[1052] is similarly used for the CNFs lifecycle management.

[0044] The platforms foundation services module

[0106] further comprises a microservices elastic load balancer

[1062] ; an identify & access manager

[1064] ; a command line interface (CLI)

[1066] ; a central logging manager

[1068] ; and an event routing manager

[1070] , The microservices elastic load balancer

[1062] is used for maintaining the load balancing of the request for the services. The identify & access manager

[1064] is used for logging purposes. The command line interface (CLI)

[1066] is used to provide commands to execute certain processes which requires changes during the run time. The central logging manager

[1068] is responsible for keeping the logs of every service. These logs are generated by the MANO architecture

[0100] , These logs are used for debugging purposes. The event routing manager

[1070] is responsible for routing the events i.e., the application programming interface (API) hits to the corresponding service.

[0045] The platforms core service module

[0108] further comprises NFV infrastructure monitoring manager

[1082] ; an assure manager

[1084] ; a performance manager

[1086] ; the PEEGN module

[1088] ; a capacity monitoring manager (CMM) microservice

[1090] (alternatively referred to as CP microservice

[1090] , and capacity management platform (CMP) microservice

[1090] ); a release management (mgmt.) repository (RMR)

[1092] ; a configuration manager & (GCT)

[1094] ; an NFV platform decision analytics (NPDA)

[1096] ; a platform NoSQL DB

[1098] ; a platform schedulers and cron jobs

[1100] ; a VNF backup & upgrade manager

[1102] ; a micro service auditor

[1104] ; and a platform operations, administration and maintenance manager

[1106] , The NFV infrastructure monitoring manager

[1082] monitors the infrastructure part of the NFs. For e.g., any metrics such as CPU utilization by the VNF. The assure manager

[1084] is responsible for supervising the alarms the vendor is generating. The performance manager

[1086] is responsible for manging the performance counters. The PEEGN module

[1088] is responsible for all the managing the policies. The CMM) microservice

[1090] is responsible for sending the request to the PEEGN module

[1088] , The release management (mgmt.) repository (RMR)

[1092] is responsible for managing the releases and the images of all the vendor network node. The configuration manager & (GCT)

[1094] manages the configuration and GCT of all the vendors. The NFV platform decision analytics (NPDA)

[1096] helps in deciding the priority of using the network resources. It is further noted that the PEEGN module

[1088] , the configuration manager & (GCT)

[1094] and the (NPDA)

[1096] work together. The platform NoSQL DB

[1098] is a database for storing all the inventory (both physical and logical) as well as the metadata of the VNFs and CNF. The platform schedulers and cron jobs

[1100] schedules the task such as but not limited to triggering of an event, traverse the network graph etc. The VNF backup & upgrade manager

[1102] takes backup of the images, binaries of the VNFs and the CNFs and produces those backups on demand in case of server failure. The micro service auditor

[1104] audits the microservices. For e.g., in a hypothetical case, instances not being instantiated by the MANO architecture

[0100] using the network resources then the micro service auditor

[1104] audits and informs the same so that resources can be released for services running in the MANO architecture

[0100] , thereby assuring the services only run on the MANO architecture

[0100] , The platform operations, administration, and maintenance manager

[1106] is used for newer instances that are spawning.

[0046] The platform resource adapters and utilities module

[0112] further comprises a platform external API adaptor and gateway

[1122] ; a generic decoder and indexer (XML, CSV, JSON)

[1124] ; a docker service adaptor

[1126] ; an API adapter

[1128] ; and a NFV gateway

[1130] , The platform external API adaptor and gateway

[1122] is responsible for handling the external services (to the MANO architecture

[0100] ) that requires the network resources. The generic decoder and indexer (XML, CSV, JSON)

[1124] directly gets the data of the vendor system in the XML, CSV,JSON format. The docker service adaptor

[1126] is the interface provided between the telecom cloud and the MANO architecture

[0100] for communication. The API adapter

[1128] ; is used to connect with the virtual machines (VMs). The NFV gateway

[1130] is responsible for providing the path to each service going to / incoming from the MANO architecture

[0100] ,

[0047] FIG. 2 illustrates an exemplary block diagram of a computing device

[0200] upon which the features of the present disclosure may be implemented in accordance with exemplary implementation of the present disclosure. In an implementation, the computing device

[0200] may also implement a method for managing a network function utilising the system

[0300] , In another implementation, the computing device

[0200] itself implements the method for managing a network function using one or more units configured within the computing device

[0200] , wherein said one or more units are capable of implementing the features as disclosed in the present disclosure.

[0048] The computing device

[0200] may include a bus

[0202] or other communication mechanism for communicating information, and a processor

[0204] coupled with bus

[0202] for processing information. The processor

[0204] may be, for example, a general-purpose microprocessor. The computing device

[0200] may also include a main memory

[0206] , such as a random-access memory (RAM), or other dynamic storage device, coupled to the bus

[0202] for storing information and instructions to be executed by the processor

[0204] , The main memory

[0206] also may be used for storing temporary variables or other intermediate information during execution of the instructions to be executed by the processor

[0204] , Such instructions, when stored in non-transitory storage media accessible to the processor

[0204] , render the computing device

[0200] into a special-purpose machine that is customized to perform the operations specified in the instructions. The computing device

[0200] further includes a read only memory (ROM)

[0208] or other static storage device coupled to the bus

[0202] for storing static information and instructions for the processor

[0204] ,

[0049] A storage device

[0210] , such as a magnetic disk, optical disk, or solid-state drive is provided and coupled to the bus

[0202] for storing information and instructions. The computing device

[0200] may be coupled via the bus

[0202] to a display

[0212] , such as a cathode ray tube (CRT), Liquid crystal Display (LCD), Light Emitting Diode (LED) display, Organic LED (OLED) display, etc. for displaying information to a computer user. An input device

[0214] , including alphanumeric and other keys, touch screen input means, etc. may be coupled to the bus

[0202] for communicating information and command selections to the processor

[0204] , Another type of user input device may be a cursor controller

[0216] , such as a mouse, a trackball, or cursor direction keys, for communicating direction information and command selections to the processor

[0204] , and forcontrolling cursor movement on the display

[0212] , The input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allow the device to specify positions in a plane.

[0050] The computing device

[0200] may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware, and / or program logic which in combination with the computing device

[0200] causes or programs the computing device

[0200] to be a special-purpose machine. According to one implementation, the techniques herein are performed by the computing device

[0200] in response to the processor

[0204] executing one or more sequences of one or more instructions contained in the main memory

[0206] , Such instructions may be read into the main memory

[0206] from another storage medium, such as the storage device

[0210] , Execution of the sequences of instructions contained in the main memory

[0206] causes the processor

[0204] to perform the process steps described herein. In alternative implementations of the present disclosure, hard-wired circuitry may be used in place of or in combination with software instructions.

[0051] The computing device

[0200] also may include a communication interface

[0218] coupled to the bus

[0202] , The communication interface

[0218] provides a two-way data communication coupling to a network link

[0220] that is connected to a local network

[0222] , For example, the communication interface

[0218] may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the communication interface

[0218] may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, the communication interface

[0218] sends and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

[0052] The computing device

[0200] can send messages and receive data, including program code, through the network(s), the network link

[0220] and the communication interface

[0218] , In the Internet example, a server

[0230] might transmit a requested code for an application program through the Internet

[0228] , the ISP

[0226] , the local network

[0222] , a host

[0224] and the communication interface

[0218] , The received code may be executed by the processor

[0204] as it is received, and / or stored in the storage device

[0210] , or other non-volatile storage for later execution.

[0053] The computing device

[0200] encompasses a wide range of electronic devices capable of processing data and performing computations. Examples of computing device

[0200] include, but are not limited only to, personal computers, laptops, tablets, smartphones, servers, and embedded systems. The devices may operate independently or as part of a network and can perform a variety of tasks such as data storage, retrieval, and analysis. Additionally, computing device

[0200] may include peripheral devices, such as monitors, keyboards, and printers, as well as integrated components within larger electronic systems, showcasing their versatility in various technological applications.

[0054] Referring to FIG. 3, an exemplary block diagram of a system

[0300] for managing a network function, is shown, in accordance with the exemplary implementations of the present disclosure. The system

[0300] comprises, at least one network function virtualization platform decision and analytics (NPDA) module

[1096] , The NPDA module

[1096] comprises at least one transceiver unit

[0302] , at least one retrieving unit

[0304] , at least one database

[0306] , at least one processing unit

[0308] , at least one a determining unit

[0310] and at least one policy execution engine (PEEGN) module

[1088] , at least one comparing unit

[0314] , and at least one event routing manager (ERM) module

[0316] , Also, all of the components / units of the system

[0300] are assumed to be connected to each other unless otherwise indicated below. As shown in the figures all units shown within the system

[0300] should also be assumed to be connected to each other. Also, in FIG. 3 only a few units are shown, however, the system

[0300] may comprise multiple such units or the system

[0300] may comprise any such numbers of said units, as required to implement the features of the present disclosure. Further, in an implementation, the system

[0300] may be present in a user device / user equipment to implement the features of the present disclosure. The system

[0300] may be a part of the user device or may be independent of but in communication with the user device (may also referred herein as a UE). In another implementation, the system

[0300] may reside in a server or a network entity. In yet another implementation, the system

[0300] may reside partly in the server / network entity and partly in the user device.

[0055] The system

[0300] is configured for managing a network function, with the help of the interconnection between the components / units of the system

[0300] ,

[0056] The system

[0300] comprises a network function virtualization platform decision and analytics (NPDA) module

[1096] , The NPDA module

[1096] further comprises a transceiver unit

[0302] which is configured to receive a resource threshold event associated with at least one networkfunction from an event routing manager (ERM) module

[0316] , wherein the resource threshold event includes resource load information.

[0057] The transceiver unit

[0302] receives from the event routing manager (ERM) module

[0316] , the resource threshold event associated with at least one network function that includes resource load information about the load capacity of various resources such as, but not limited only to CPU, RAM, storage, etc., in at least one network function. The resource threshold event determines whether the one or more resources has exceeded its load capacity which further helps the system in allocating additional resources thereby maintaining optimal system performance and preventing potential failures.

[0058] For example, if CPU usage exceeds its specified resource threshold event, additional virtual machines or containers might be provisioned. Similarly, if usage drops significantly, resources might be scaled back to avoid over-provisioning.

[0059] In an exemplary aspect, the network function is selected from a group consisting of Virtual Network Functions (VNFs), Virtual Network Function Components (VNFCs), Container Network functions (CNFs), and Container Network Function Components (CNFCs).

[0060] In an exemplary aspect, the virtual network function (VNF) refers to a network function module that operates in virtualized environments such as virtual machines or containers. This virtualization allows for dynamic scaling and rapid adaptation to changing network conditions, improving reducing hardware requirement.

[0061] In an exemplary aspect, the virtual network function component (VNFC) refers to a subcomponent within a virtual network function (VNF) that performs a specific task or set of tasks related to the overall network function. VNFCs reduces VNFs into smaller units, each responsible for unique functions, such as packet inspection, policy enforcement, etc.

[0062] In an exemplary aspect, the containerized network function (CNF) refers to a network function that act as portable container, which include all necessary configurations. CNFs offer increased portability, and scalability compared to traditional network functions.

[0063] In an exemplary aspect, the Containerized Network Function Component (CNFC) refers to a subcomponent of a Containerized Network Function (CNF) that performs a specific task orset of tasks within the broader network function. CNFCs are deployed in containers, having same advantages as CNFs, which includes efficient resource management.

[0064] In an exemplary aspect, the resource threshold event is received at the ERM module

[0316] from a capacity monitoring manager (CMP) microservice

[1090] ,

[0065] In an exemplary aspect, the resource threshold event is received using the event routing manager (ERM) module

[0316] which is responsible for routing the events i.e., an application programming interface (API) hit to the CMP microservice

[1090] ,

[0066] The NPDA module

[1096] further comprises a retrieving unit

[0304] configured to retrieve, from a database

[0306] , a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules.

[0067] The retrieving unit

[0304] retrieves predefined scaling policy associated with the at least one network function, from a database

[0306] , In an exemplary aspect the predefined scaling policy includes specific guidelines that instruct how to scale network resources in response to changes in load or utilization.

[0068] The predefined scaling policy includes at least one of a set of threshold parameters which are specific parameters defined by the network administrator within a system that initiates certain responses when they are exceeded. In an exemplary aspect, threshold parameters are used to determine whether to add resources or removes resources based on resource load information. For example, the network administrator sets the threshold parameter at 90% CPU utilization, if CPU utilization exceed this set threshold parameter of 90% then the system

[0300] may allocate additional resources maintaining optimal system performance and preventing potential failures.

[0069] The predefined scaling policy further includes at least one of a set of hysteresis rules. The set of hysteresis rules are rules for adjusting resource allocation parameters in real-time to manage system resources effectively so that to maintain system stability and performance.

[0070] The NPDA module

[1096] further comprises a processing unit

[0308] which is configured to compute a hysteresis evaluation based on the received resource load information and the predefined scaling policy.

[0071] The processing unit

[0308] computes the hysteresis evaluation based on the received resource load information and predefined scaling policy. In an exemplary aspect, hysteresis evaluation is analysed and evaluated based on the received resource load information which states how much resources are utilized which helps in avoiding frequent scaling actions that could put unnecessary load on the overall performance of the system.

[0072] Furthermore, the processing unit

[0308] computes the hysteresis evaluation based on predefined scaling policy by adjusting resource allocation parameters in real-time to manage system resources effectively so that to maintain system stability and performance.

[0073] In an exemplary aspect, for the hysteresis evaluation the system

[0300] further comprises a comparing unit

[0314] configured to compare the resource load information with historical resource usage data to prevent frequent scaling operations.

[0074] In order to compute the hysteresis evaluation, the comparing unit

[0314] compares the resource load information with the historical resource usage data to prevent frequent scaling operations. In an implementation, the trained model is trained on a historical resource usage data. This comparison, by the comparing unit

[0314] , determines whether the current load is a temporary load fluctuation or a significant trend, thereby preventing frequent and unnecessary scaling operations. By comparing trained historical data with the resource load information, the system

[0300] ensures that scaling actions are based on long term reoccurring trends and patterns rather than short-term changes, leading to more stable and efficient resource management.

[0075] The system

[0300] further comprises a determining unit

[0310] configured to determine whether the computed hysteresis evaluation breaches the set of threshold parameters.

[0076] The determining unit

[0310] determines whether the computed hysteresis evaluation breaches the set of threshold parameters which are specific parameters defined by the network administrator within the system

[0300] that initiates certain responses when they are exceeded or breached.

[0077] In an exemplary aspect, the set of threshold parameters are breached when there is an anomaly or fault in the reported load at the NPDAmodule

[1096] , For e.g., once the alarm is raised, the NPDA module

[1096] fetches the set of alarm restoration data defined against the providednetwork function from the database

[0306] , For example, an administrator may define the alarm restoration data for raising an alarm to determine that the network function requires recovery in a network. When the determination is made that the network function requires healing, the alarms are raised or triggered. The raising of alarm signifies that a particular network function requires healing.

[0078] The transceiver unit

[0302] is further configured to transmit a scaling request to the PEEGN module

[1088] to mitigate breach of the computed hysteresis evaluation.

[0079] The transceiver unit

[0302] transmits the scaling request in the form of instructions in order to mitigate breach of the computed hysteresis to the PEEGN module

[1088] by performing auto scale operations.

[0080] The processing unit

[0308] is further configured to execute a scaling action on the at least one network function, based on the scaling request.

[0081] The processing unit

[0308] executes the scaling action on the at least one network function, based on the scaling request. In an exemplary aspect, the scaling action on the at least one network function, is performed in order to manage the network resources when they are exceeded or breached leading to more stable and efficient resource management. In an implementation, the request may include the kind of scaling action that needs to be performed based on the current load of the network resources, which may further include scale in action, scale out action, scale up action, scale down action.

[0082] In an exemplary aspect, the scaling action comprises at least one of an auto-scale up, and an auto-scale down for the at least one network function.

[0083] In an exemplary aspect, the scaling action includes auto-scale up actions which automatically allocates more resources to the overloaded resources, such as CPU, memory, or storage, to meet increased demands. Similarly, the scaling action includes auto-scale down actions which automatically reduces the number of resources when the overall load on the system

[0300] decreases. The auto scale-up / auto scale down actions are significant as it allow the system

[0300] to optimize resource utilization, and efficiently manage predictable or variable workloads without the complexity of adding or removing more resources.

[0084] Referring to FIG. 4, an exemplary method flow diagram

[0400] for managing a network function, in accordance with exemplary implementations of the present disclosure is shown. In an implementation the method

[0400] is performed by the system

[0300] , Further, in an implementation, the system

[0300] may be present in a server device to implement the features of the present disclosure. Also, as shown in FIG. 4, the method

[0400] starts at step

[0402] ,

[0085] At step 404, the method

[0400] comprises receiving, by a transceiver unit

[0302] at a network function virtualization platform decision and analytics (NPDA) module

[1096] , a resource threshold event associated with at least one network function from an event routing manager (ERM) module

[0316] , wherein the resource threshold event at least comprises resource load information.

[0086] The transceiver unit

[0302] receives from an event routing manager (ERM) module

[0316] , the resource threshold event associated with at least one network function that includes resource load information about the load capacity of various resources such as, but not limited only to CPU, RAM, storage, etc., in at least one network function. The resource threshold event determines whether the one or more resources has exceeded its load capacity which further helps the system in allocating additional resources thereby maintaining optimal system performance and preventing potential failures.

[0087] For example, if CPU usage exceeds its specified resource threshold event, additional virtual machines or containers might be provisioned. Similarly, if usage drops significantly, resources might be scaled back to avoid over-provisioning.

[0088] In an exemplary aspect, the network function is selected from a group consisting of Virtual Network Functions (VNFs), Virtual Network Function Components (VNFCs), Container Network functions (CNFs), and Container Network Function Components (CNFCs).

[0089] In an exemplary aspect, the virtual network function (VNF) refers to a network function module that operates in virtualized environments such as virtual machines or containers. This virtualization allows for dynamic scaling and rapid adaptation to changing network conditions, improving reducing hardware requirement.

[0090] In an exemplary aspect, the virtual network function component (VNFC) refers to a subcomponent within a virtual network function (VNF) that performs a specific task or set of tasksrelated to the overall network function. VNFCs reduces VNFs into smaller units, each responsible for unique functions, such as packet inspection, policy enforcement, etc.

[0091] In an exemplary aspect, the containerized network function (CNF) refers to a network function that act as portable container, which include all necessary configurations. CNFs offer increased portability, and scalability compared to traditional network functions.

[0092] In an exemplary aspect, the Containerized Network Function Component (CNFC) refers to a subcomponent of a Containerized Network Function (CNF) that performs a specific task or set of tasks within the broader network function. CNFCs are deployed in containers, having same advantages as CNFs, which includes efficient resource management.

[0093] In an exemplary aspect, the resource threshold event is received at the ERM module

[0316] from the CMP microservice

[1090] ,

[0094] In an exemplary aspect, the resource threshold event is received using the event routing manager (ERM) module

[0316] which is responsible for routing the events i.e., an application programming interface (API) hit to the CMP microservice

[1090] ,

[0095] At step 406, the method

[0400] further comprises retrieving, by a retrieving unit

[0304] at the NPDA module

[1096] , from a database

[0306] , a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules.

[0096] The retrieving unit

[0304] retrieves predefined scaling policy associated with the at least one network function, from a database

[0306] , In an exemplary aspect the predefined scaling policy includes specific guidelines that instruct how to scale network resources in response to changes in load or utilization.

[0097] The predefined scaling policy includes at least one of a set of threshold parameters which are specific parameters defined by the network administrator within a system that initiates certain responses when they are exceeded. In an exemplary aspect, threshold parameters are used to determine whether to add resources or removes resources based on resource load information. For example, the network administrator sets the threshold parameter at 90% CPU utilization, if CPUutilization exceed this set threshold parameter of 90% then the system

[0300] may allocate additional resources maintaining optimal system performance and preventing potential failures.

[0098] The predefined scaling policy further includes at least one of a set of hysteresis rules. The set of hysteresis rules are rules for adjusting resource allocation parameters in real-time to manage system resources effectively so that to maintain system stability and performance.

[0099] At step 408, the method

[0400] further comprises computing, by a processing unit

[0308] at the NPD A module

[1096] , a hysteresis evaluation based on the received resource load information and the predefined scaling policy.

[0100] The processing unit

[0308] computes the hysteresis evaluation based on the received resource load information and predefined scaling policy. In an exemplary aspect, hysteresis evaluation is analysed and evaluated based on the received resource load information which states how much resources are utilized which helps in avoiding frequent scaling actions that could put unnecessary load on the overall performance of the system.

[0101] Furthermore, the processing unit

[0308] computes the hysteresis evaluation based on predefined scaling policy by adjusting resource allocation parameters in real-time to manage system resources effectively so that to maintain system stability and performance.

[0102] The method

[0400] further comprises the hysteresis evaluation comprises comparing, by a comparing unit

[0314] , the resource load information with historical resource usage data to prevent frequent scaling operations.

[0103] In order to compute the hysteresis evaluation, the comparing unit

[0314] compares the resource load information with the historical resource usage data to prevent frequent scaling operations. In an implementation, the trained model is trained on a historical resource usage data. This comparison, by the comparing unit

[0314] , determines whether the current load is a temporary load fluctuation or a significant trend, thereby preventing frequent and unnecessary scaling operations. By comparing trained historical data with the resource load information, the system

[0300] ensures that scaling actions are based on long term reoccurring trends and patterns rather than short-term changes, leading to more stable and efficient resource management.

[0104] At step 410, the method

[0400] further comprises determining, by a determining unit

[0310] at the NPDA module

[1096] , whether the computed hysteresis evaluation breaches the set of threshold parameters.

[0105] The determining unit

[0310] determines whether the computed hysteresis evaluation breaches the set of threshold parameters which are specific parameters defined by the network administrator within the system

[0300] that initiates certain responses when they are exceeded or breached.

[0106] At step 412, the method

[0400] further comprises transmitting, by the transceiver unit

[0302] at the NPDA module

[1096] , a scaling request to the PEEGN module

[1088] to mitigate breach of the computed hysteresis evaluation.

[0107] The transceiver unit

[0302] transmits the scaling request in the form of instructions in order to mitigate breach of the computed hysteresis to the PEEGN module

[1088] by performing auto scale operations.

[0108] The method

[0400] further comprises executing, by the processing unit

[0308] at the PEEGN module

[1088] , a scaling action on the at least one network function, based on the scaling request.

[0109] The processing unit

[0308] executes the scaling action on the at least one network function, based on the scaling request. In an exemplary aspect, the scaling action on the at least one network function, is performed in order to manage the network resources when they are exceeded or breached leading to more stable and efficient resource management. In an implementation, the request may include the kind of scaling action that needs to be performed based on the current load of the network resources, which may further include scale in action, scale out action, scale up action, scale down action.

[0110] In an exemplary aspect, the scaling action comprises at least one of an auto-scale up, and an auto-scale down for the at least one network function.[OHl] In an exemplary aspect, the scaling action includes auto-scale up actions which automatically allocates more resources to the overloaded resources, such as CPU, memory, or storage, to meet increased demands. Similarly, the scaling action includes auto-scale down actions which automatically reduces the number of resources when the overall load on the system

[0300] decreases. The auto scale-up / auto scale down actions are significant as it allow the system

[0300] to optimize resource utilization, and efficiently manage predictable or variable workloads without the complexity of adding or removing more resources.

[0112] Thereafter, at step

[0414] , the method

[0400] is terminated.

[0113] Referring to FIG. 5, an exemplary process

[0500] flow diagram for managing a network function, in accordance with exemplary implementations of the present disclosure is shown. The process

[0500] starts at step

[0502] ,

[0114] At step 504, the process

[0500] comprises transmitting, by the CMP microservice

[1090] , a resource threshold event associated with at least one network function to the event routing manager (ERM) module

[0316] , In an exemplary aspect, the network function is selected from a group consisting of Virtual Network Functions (VNFs), Virtual Network Function Components (VNFCs), Container Network functions (CNFs), and Container Network Function Components (CNFCs).

[0115] At step 506, the process

[0500] comprises receiving, at the ERM module

[0316] , a resource threshold event associated with at least one network function, wherein the resource threshold event includes resource load information. In an exemplary aspect, the resource threshold event is received using the event routing manager (ERM) module

[0316] which is responsible for routing the events i.e., an application programming interface (API) hit to the CMP microservice

[1090] , In an exemplary aspect, the received resource threshold event is further transmitted from the ERM module

[0316] to the NPDA module

[1096] ,

[0116] At step 508, the process

[0500] comprises providing, to the NPDA module

[1096] , resource load details / information raised by the CMP microservice

[1090] , In an exemplary aspect, the NPDA module

[1096] computes the hysteresis evaluation based on the received resource load information and predefined scaling policy. In an exemplary aspect, hysteresis evaluation is analysed and evaluated based on the received resource load information which states how much resources are utilized which helps in avoiding frequent scaling actions that could put unnecessary load on the overall performance of the system.

[0117] At step 510, the process

[0500] comprises receiving, at the policy evaluation module from the NPDA module, the hysteresis evaluation based on the received resource loadinformation / details and the predefined scaling policy and transmitting the same to the policy evaluation module. In an exemplary aspect, the policy evaluation module

[1096] determines whether the computed hysteresis evaluation breaches the set of threshold parameters which are specific parameters defined by the network administrator within the system

[0300] that initiates certain responses when they are exceeded or breached. In an exemplary aspect, if the computed hysteresis evaluation does not breach the set of threshold parameters, the process ends in the next step.

[0118] At step 512, if the computed hysteresis evaluation breaches the set of threshold parameters, the process

[0500] comprises performing, at the PEEGN module

[1088] , closed loop report to adjacent system regarding scaling (in / out) or scale up / scale out decisions based on evaluated CNFC / VNFC policy. In an exemplary aspect, the scaling action includes auto-scale up actions which automatically allocates more resources to the overloaded resources, such as CPU, memory, or storage, to meet increased demands. Similarly, the scaling action includes auto-scale down actions which automatically reduces the number of resources when the overall load on the system

[0300] decreases. The auto scale-up / auto scale down actions is significant as it allows the system

[0300] to optimize resource utilization, and efficiently manage predictable or variable workloads without the complexity of adding or removing more resources. In an exemplary aspect, the scaling request in the form of instructions are performed in order to mitigate breach of the computed hysteresis at the PEEGN module

[1088] by performing auto scale operations. Thereafter, the process

[0500] , ends in the next step.

[0119] At step 514, the process steps

[0510] and

[0512] ends.

[0120] The present disclosure further discloses a non-transitory computer readable storage medium storing instructions for managing a network function, the instructions include executable code which, when executed by one or more units of a system, causes a transceiver unit

[0302] of the system to receive a resource threshold event associated with at least one network function from an event routing manager (ERM) module

[0316] , wherein the resource threshold event includes resource load information. The instructions when executed further causes a retrieving unit

[0304] to retrieve, from a database

[0306] , a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules. The instructions when executed further causes a processing unit

[0308] configured to compute a hysteresis evaluation based on the received resource load information and the predefined scaling policy. The instructions when executed further causes adetermining unit

[0310] to determine whether the computed hysteresis evaluation breaches the set of threshold parameters. The instructions when executed further causes the transceiver unit

[0302] to transmit a scaling request to the PEEGN module

[1088] to mitigate breach of the computed hysteresis evaluation.

[0121] As is evident from the above, the present disclosure provides a technically advanced solution for managing a network function that adapts to changing workloads and resource demands in microservices architecture, ensuring optimal system performance while preventing overload.

[0122] While considerable emphasis has been placed herein on the disclosed implementations, it will be appreciated that many implementations can be made and that many changes can be made to the implementations without departing from the principles of the present disclosure. These and other changes in the implementations of the present disclosure will be apparent to those skilled in the art, whereby it is to be understood that the foregoing descriptive matter to be implemented is illustrative and non-limiting.

[0123] Further, in accordance with the present disclosure, it is to be acknowledged that the functionality described for the various components / units can be implemented interchangeably. While specific embodiments may disclose a particular functionality of these units for clarity, it is recognized that various configurations and combinations thereof are within the scope of the disclosure. The functionality of specific units as disclosed in the disclosure should not be construed as limiting the scope of the present disclosure. Consequently, alternative arrangements and substitutions of units, provided they achieve the intended functionality described herein, are considered to be encompassed within the scope of the present disclosure.

Claims

We Claim:

1. A method for managing a network function, the method comprising: receiving, by a transceiver unit [302] at a network function virtualization platform decision and analytics (NPDA) module [1096], a resource threshold event associated with at least one network function from an event routing manager (ERM) module [316], wherein the resource threshold event at least comprises resource load information; retrieving, by a retrieving unit [304] at the NPDA module [1096], from a database [306], a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules; computing, by a processing unit [308] at the NPDA module [1096], a hysteresis evaluation based on the resource load information and the predefined scaling policy; determining, by a determining unit [310] at the NPDA module [1096], whether the computed hysteresis evaluation breaches the set of threshold parameters; and transmitting, by the transceiver unit [302] at the NPDA module [1096], a scaling request to a policy execution engine (PEEGN) module [1088] to mitigate breach of the computed hysteresis evaluation.

2. The method as claimed in claim 1, wherein the method comprises executing, by the processing unit [308] at the PEEGN module [1088], a scaling action on the at least one network function, based on the scaling request.

3. The method as claimed in claim 2, wherein the scaling action comprises at least one of an auto-scale up, and an auto-scale down of the at least one network function.

4. The method as claimed in claim 1, wherein at least the network function is selected from a group consisting of Virtual Network Functions (VNFs), Virtual Network Function Components (VNFCs), Container Network functions (CNFs), and Container Network Function Components (CNFCs).

5. The method as claimed in claim 1, wherein the hysteresis evaluation comprises comparing, by a comparing unit [314], the resource load information with historical resource usage data to prevent frequent scaling operations.

6. The method as claimed in claim 1, wherein the resource threshold event is received at the ERM module [316] from a capacity monitoring manager (CMM) microservice [1090],7. A system for managing a network function, the system comprising:- a network function virtualization platform decision and analytics (NPDA) module [1096] comprising:- a transceiver unit [302] configured to receive a resource threshold event associated with at least one network function from an event routing manager (ERM) module [316], wherein the resource threshold event includes resource load information;- a retrieving unit [304] configured to retrieve, from a database [306], a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules;- a processing unit [308] configured to compute a hysteresis evaluation based on the resource load information and the predefined scaling policy;- a determining unit [310] configured to determine whether the computed hysteresis evaluation breaches the set of threshold parameters; and- the transceiver unit [302] configured to transmit a scaling request to a policy execution engine (PEEGN) module [1088] to mitigate breach of the computed hysteresis.

8. The system as claimed in claim 7, wherein the processing unit [308] is configured to execute a scaling action on the at least one network function, based on the scaling request.

9. The system as claimed in claim 8, wherein the scaling action comprises at least one of an auto-scale up, and an auto-scale down for the at least one network function.

10. The system as claimed in claim 7, wherein at least the network function is selected from a group consisting of Virtual Network Functions (VNFs), Virtual Network Function Components (VNFCs), Container Network functions (CNFs), and Container Network Function Components (CNFCs).

11. The system as claimed in claim 7, wherein for the hysteresis evaluation the system further comprises a comparing unit [314] configured to compare the resource load information with historical resource usage data to prevent frequent scaling operations.

12. The system as claimed in claim 7, wherein the resource threshold event is received at the ERM module [316] from a capacity monitoring manager (CMM) microservice [1090],13. A non-transitory computer-readable storage medium storing instruction for managing a network function the storage medium comprising executable code which, when executed by one or more units of a system, causes:- a transceiver unit [302] to receive a resource threshold event associated with at least one network function from an event routing manager (ERM) module [316], wherein the resource threshold event includes resource load information;- a retrieving unit [304] to retrieve, from a database [306], a predefined scaling policy associated with the at least one network function, wherein the predefined scaling policy comprises at least one of a set of threshold parameters and a set of hysteresis rules;- a processing unit [308] to compute a hysteresis evaluation based on the resource load information and the predefined scaling policy;- a determining unit [310] to determine whether the computed hysteresis evaluation breaches the set of threshold parameters; and- the transceiver unit [302] to transmit a scaling request to a policy execution engine (PEEGN) module [1088] to mitigate breach of the computed hysteresis.

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