技术领域Technical field
本公开涉及通信技术领域，尤其涉及一种网元扩容方法、装置、电子设备及存储介质。The present disclosure relates to the field of communication technology, and in particular, to a network element expansion method, device, electronic equipment and storage medium.
背景技术Background technique
随着运营商的用户数据逐步增加，核心网设备间的信令链路负荷日渐增高，部分网元的信令处理能力有限，长期来看会造成网络安全隐患，当网元无法及时处理当前信令，可能会形成信令风暴，造成整个核心网的坍塌，同时网元有限的处理能力也是用户量增长的瓶颈。As operators' user data gradually increases, the load on the signaling links between core network devices is increasing day by day. Some network elements have limited signaling processing capabilities, which will cause network security risks in the long run. When network elements cannot process the current signaling in a timely manner, A signaling storm may occur, causing the entire core network to collapse. At the same time, the limited processing capabilities of network elements are also a bottleneck for user growth.
因此对核心网元进行扩容是亟待解决的技术问题。当前扩容方案具有延后性，网元出现告警后才会考虑扩容，当该网元无法及时处理信令，就有可能形成信令风暴，最终将会对整个核心网网络造成影响。Therefore, expanding the capacity of core network elements is an urgent technical issue that needs to be solved. The current expansion plan is delayed. Capacity expansion will only be considered after an alarm occurs on a network element. When the network element cannot process signaling in a timely manner, a signaling storm may occur, which will eventually affect the entire core network.
需要说明的是，在上述背景技术部分公开的信息仅用于加强对本公开的背景的理解，因此可以包括不构成对本领域普通技术人员已知的现有技术的信息。It should be noted that the information disclosed in the above background section is only used to enhance understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to those of ordinary skill in the art.
发明内容Contents of the invention
本公开提供一种网元扩容方法、装置、电子设备及存储介质，至少在一定程度上克服相关技术中网元扩容具有的延后性问题。The present disclosure provides a network element expansion method, device, electronic equipment and storage medium, which at least to a certain extent overcomes the delay problem of network element expansion in related technologies.
本公开的其他特性和优点将通过下面的详细描述变得显然，或部分地通过本公开的实践而习得。Additional features and advantages of the disclosure will be apparent from the following detailed description, or, in part, may be learned by practice of the disclosure.
根据本公开的一个方面，提供了一种网元扩容方法，包括：采集目标网元的业务指标数据和资源指标数据；将目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量；若目标网元的最大承载量超过预设阈值，则对目标网元进行扩容处理。According to one aspect of the present disclosure, a network element expansion method is provided, which includes: collecting business indicator data and resource indicator data of a target network element; inputting the business indicator data and resource indicator data of the target network element into a pre-trained In the network element carrying capacity prediction model, the maximum carrying capacity of the target network element when it meets the preset conditions is output; if the maximum carrying capacity of the target network element exceeds the preset threshold, the target network element is expanded.
在一些实施例中，在将目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量之前，方法还包括：获取构建网元承载量预测模型的样本数据，其中，样本数据包括来自一个或多个网元的业务指标数据和资源指标数据；将样本数据划分为训练数据集和测试数据集；根据训练数据集对网元承载量预测模型进行训练；根据测试数据集对训练后的网元承载量预测模型进行测试。In some embodiments, before inputting the service indicator data and resource indicator data of the target network element into the pre-trained network element carrying capacity prediction model and outputting the maximum carrying capacity of the target network element when it meets the preset conditions, the method It also includes: obtaining sample data for constructing a network element carrying capacity prediction model, where the sample data includes business indicator data and resource indicator data from one or more network elements; dividing the sample data into a training data set and a test data set; according to The training data set is used to train the network element carrying capacity prediction model; the trained network element carrying capacity prediction model is tested according to the test data set.
在一些实施例中，在获取构建网元承载量预测模型的样本数据之后，方法还包括：利用主成分分析PCA方法对样本数据进行降维处理；对降维后的样本数据进行降去噪处理，得到满足预设条件的样本数据。In some embodiments, after obtaining the sample data for constructing the network element carrying capacity prediction model, the method further includes: using principal component analysis (PCA) method to perform dimensionality reduction processing on the sample data; and performing dimensionality reduction and denoising processing on the sample data after dimensionality reduction. , get sample data that meets the preset conditions.
在一些实施例中，业务指标数据包括如下至少之一：4G/5G用户总数、长期演进语音承载VOLTE用户总数、VOLTE用户注册成功率、主叫接通率、主叫接通次数、被叫接通率、被叫接通次数。In some embodiments, the service indicator data includes at least one of the following: total number of 4G/5G users, total number of Long Term Evolution voice bearer VOLTE users, VOLTE user registration success rate, caller connection rate, caller connection times, called connection times The call rate and the number of calls connected.
在一些实施例中，资源指标数据包括如下至少之一：网元内存占用率、网元内存空闲总量，服务器占用率、网络连接数、带宽信息。In some embodiments, the resource indicator data includes at least one of the following: network element memory occupancy, total network element memory idleness, server occupancy, number of network connections, and bandwidth information.
在一些实施例中，上述目标网元为核心网网元。In some embodiments, the above target network element is a core network element.
根据本公开的另一个方面，还提供了一种网元扩容装置，包括：数据采集模块，用于采集目标网元的业务指标数据和资源指标数据；承载量预测模块，用于将目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量；网元扩容模块，用于当目标网元的最大承载量超过预设阈值，则对目标网元进行扩容处理。According to another aspect of the present disclosure, a network element expansion device is also provided, including: a data collection module for collecting service indicator data and resource indicator data of the target network element; a load capacity prediction module for The business indicator data and resource indicator data are input into the pre-trained network element carrying capacity prediction model to output the maximum carrying capacity of the target network element when it meets the preset conditions; the network element expansion module is used when the maximum capacity of the target network element is If the carrying capacity exceeds the preset threshold, the target network element will be expanded.
根据本公开的另一个方面，还提供了一种电子设备，该电子设备包括：处理器；以及存储器，用于存储所述处理器的可执行指令；其中，所述处理器配置为经由执行所述可执行指令来执行上述任意一项所述的网元扩容方法。According to another aspect of the present disclosure, an electronic device is also provided, the electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the The executable instructions are used to execute any one of the above network element expansion methods.
根据本公开的另一个方面，还提供了一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现上述任意一项所述的网元扩容方法。According to another aspect of the present disclosure, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, any one of the above network element expansion methods is implemented.
根据本公开的另一个方面，还提供了一种计算机程序产品，包括计算机程序，所述计算机程序被处理器执行时实现上述任意一项的网元扩容方法。According to another aspect of the present disclosure, a computer program product is also provided, including a computer program that implements any one of the above network element expansion methods when executed by a processor.
本公开的实施例中提供的网元扩容方法、装置、电子设备及存储介质，通过采集目标网元的业务指标数据和资源指标数据；并将采集目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量；当目标网元的最大承载量超过预设阈值，则对目标网元进行扩容处理。本公开实施例避免了人工监测数据再进行网元扩容导致的延后性问题，实现了网元的实时扩容，并使用网络承载量预测模型进行数据预测，通过实时监测和分析网元的业务指标数据和资源指标数据，将这些数据输入到预测模型中进行计算，可以及时获得目标网元满足预设条件时的最大承载量，提高了扩容决策的准确性和时效性。The network element expansion method, device, electronic equipment and storage medium provided in the embodiments of the present disclosure collect the business indicator data and resource indicator data of the target network element; and will collect the business indicator data and resource indicator data of the target network element, Input into the pre-trained network element carrying capacity prediction model, and output the maximum carrying capacity of the target network element when it meets the preset conditions; when the maximum carrying capacity of the target network element exceeds the preset threshold, the target network element is expanded. The disclosed embodiments avoid the delay problem caused by manual monitoring of data and then network element expansion, realize real-time expansion of network elements, and use the network carrying capacity prediction model for data prediction, through real-time monitoring and analysis of business indicators of network elements. Data and resource indicator data are input into the prediction model for calculation, and the maximum carrying capacity of the target network element when it meets the preset conditions can be obtained in a timely manner, which improves the accuracy and timeliness of capacity expansion decisions.
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本公开。It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only, and do not limit the present disclosure.
附图说明Description of the drawings
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本公开的实施例，并与说明书一起用于解释本公开的原理。显而易见地，下面描述中的附图仅仅是本公开的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting creative efforts.
图1示出本公开实施例中一种相关技术网元扩容的示意图；Figure 1 shows a schematic diagram of a related technology network element expansion in an embodiment of the present disclosure;
图2示出本公开实施例中一种应用实施例系统架构示意图；Figure 2 shows a schematic diagram of the system architecture of an application embodiment in the embodiment of the present disclosure;
图3示出本公开实施例中一种网元扩容方法流程图；Figure 3 shows a flow chart of a network element expansion method in an embodiment of the present disclosure;
图4示出本公开实施例中又一种网元扩容方法流程图；Figure 4 shows a flow chart of yet another network element expansion method in an embodiment of the present disclosure;
图5示出本公开实施例中又一种网元扩容方法流程图；Figure 5 shows a flow chart of yet another network element expansion method in an embodiment of the present disclosure;
图6示出本公开实施例中一种网元扩容系统示意图；Figure 6 shows a schematic diagram of a network element expansion system in an embodiment of the present disclosure;
图7示出本公开实施例中一种网元扩容具体流程图；Figure 7 shows a specific flow chart of network element expansion in an embodiment of the present disclosure;
图8示出本公开实施例中一种网元扩容装置示意图；Figure 8 shows a schematic diagram of a network element expansion device in an embodiment of the present disclosure;
图9示出本公开实施例中一种电子设备的结构框图；Figure 9 shows a structural block diagram of an electronic device in an embodiment of the present disclosure;
图10示出本公开实施例中一种计算机可读存储介质示意图。Figure 10 shows a schematic diagram of a computer-readable storage medium in an embodiment of the present disclosure.
具体实施方式Detailed ways
现在将参考附图更全面地描述示例实施方式。然而，示例实施方式能够以多种形式实施，且不应被理解为限于在此阐述的范例；相反，提供这些实施方式使得本公开将更加全面和完整，并将示例实施方式的构思全面地传达给本领域的技术人员。所描述的特征、结构或特性可以以任何合适的方式结合在一个或更多实施方式中。Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concepts of the example embodiments. To those skilled in the art. The described features, structures or characteristics may be combined in any suitable manner in one or more embodiments.
此外，附图仅为本公开的示意性图解，并非一定是按比例绘制。图中相同的附图标记表示相同或类似的部分，因而将省略对它们的重复描述。附图中所示的一些方框图是功能实体，不一定必须与物理或逻辑上独立的实体相对应。可以采用软件形式来实现这些功能实体，或在一个或多个硬件模块或集成电路中实现这些功能实体，或在不同网络和/或处理器装置和/或微控制器装置中实现这些功能实体。Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus their repeated description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and/or processor devices and/or microcontroller devices.
为便于理解，在介绍本公开实施例之前，首先对本公开实施例中涉及到的几个名词进行解释如下：To facilitate understanding, before introducing the embodiments of the present disclosure, several terms involved in the embodiments of the present disclosure are first explained as follows:
正如前述背景技术所提及的，随着运营商用户数据的增加，核心网设备之间的信令链路负荷的增加确实可能导致部分网元的处理能力有限，并可能引发一系列的问题，包括网络安全隐患和信令风暴等。对于这种情况，扩容核心网网元是一种必要的解决方案。通过增加网元的处理能力，可以更好地应对不断增长的用户数据和信令负荷。扩容的方式可以包括增加硬件资源、进行网络优化和调整以提高效率，或者采用更高性能的设备来替换现有的设备。图1示出了相关技术中对网元的扩容过程图，如图1所示，网元扩容需要在监控模块下，对各网元进行网管监控，对诸如CPU、内存、带宽、MO(Mobile Originated，终端发起)成功率、注册成功率等指标进行观测，当这些指标显示异常时，发起警告，当部署人员发现警告时，对网元人工部署，实现网元扩容。As mentioned in the background technology mentioned above, with the increase of operator user data, the increase in signaling link load between core network devices may indeed lead to limited processing capabilities of some network elements and may cause a series of problems. Including network security risks and signaling storms. For this situation, expanding the capacity of core network elements is a necessary solution. By increasing the processing capabilities of network elements, the growing user data and signaling loads can be better handled. Capacity expansion can include adding hardware resources, network optimization and adjustment to improve efficiency, or replacing existing equipment with higher-performance equipment. Figure 1 shows the expansion process of network elements in related technologies. As shown in Figure 1, network element expansion requires network management monitoring of each network element under the monitoring module, such as CPU, memory, bandwidth, MO (Mobile Originated (terminal initiated) success rate, registration success rate and other indicators are observed. When these indicators show abnormalities, a warning is initiated. When the deployment personnel find the warning, the network element is manually deployed to achieve network element expansion.
然而，当前的扩容方案具有延后性。通常情况下，网元出现告警或性能下降等问题后才会考虑扩容，这可能导致在信令风暴发生之前无法及时增加处理能力，从而对整个核心网网络造成危害。However, the current expansion plan has delays. Normally, capacity expansion will only be considered after network elements experience problems such as alarms or performance degradation. This may result in the inability to increase processing capacity in time before a signaling storm occurs, thus causing harm to the entire core network.
为了避免这种情况，本公开实施例提出一种网元扩容方法，下面结合附图，对本公开实施例的具体实施方式进行详细说明。In order to avoid this situation, an embodiment of the present disclosure proposes a network element expansion method. The specific implementation manner of the embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings.
图2示出了可以应用本公开实施例中网元扩容方法的示例性应用系统架构示意图。如图2所示，该系统架构可以包括终端设备201、网络202和服务器203。Figure 2 shows a schematic diagram of an exemplary application system architecture to which the network element expansion method in the embodiment of the present disclosure can be applied. As shown in Figure 2, the system architecture may include a terminal device 201, a network 202 and a server 203.
网络202用以在终端设备201和服务器203之间提供通信链路的介质，可以是有线网络，也可以是无线网络。The network 202 is a medium used to provide a communication link between the terminal device 201 and the server 203, and may be a wired network or a wireless network.
可选地，上述的无线网络或有线网络使用标准通信技术和/或协议。网络通常为因特网、但也可以是任何网络，包括但不限于局域网(Local Area Network，LAN)、城域网(Metropolitan Area Network，MAN)、广域网(Wide Area Network，WAN)、移动、有线或者无线网络、专用网络或者虚拟专用网络的任何组合)。在一些实施例中，使用包括超文本标记语言(Hyper Text Mark-up Language，HTML)、可扩展标记语言(ExtensibleMarkupLanguage，XML)等的技术和/或格式来代表通过网络交换的数据。此外还可以使用诸如安全套接字层(Secure Socket Layer，SSL)、传输层安全(Transport Layer Security，TLS)、虚拟专用网络(Virtual Private Network，VPN)、互联网安全协议(InternetProtocol Security，IPSec)等常规加密技术来加密所有或者一些链路。在另一些实施例中，还可以使用定制和/或专用数据通信技术取代或者补充上述数据通信技术。Optionally, the above-mentioned wireless network or wired network uses standard communication technologies and/or protocols. The network is usually the Internet, but can also be any network, including but not limited to Local Area Network (LAN), Metropolitan Area Network (MAN), Wide Area Network (WAN), mobile, wired or wireless network, private network, or virtual private network). In some embodiments, technologies and/or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data exchanged through the network. In addition, you can also use technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (Virtual Private Network, VPN), Internet Protocol Security (IPSec), etc. Conventional encryption techniques to encrypt all or some links. In other embodiments, customized and/or dedicated data communication technologies may also be used in place of or in addition to the above-described data communication technologies.
终端设备201可以是各种电子设备，包括但不限于智能手机、平板电脑、膝上型便携计算机、台式计算机、智能音箱、智能手表、可穿戴设备、增强现实设备、虚拟现实设备等。The terminal device 201 may be various electronic devices, including but not limited to smartphones, tablet computers, laptop computers, desktop computers, smart speakers, smart watches, wearable devices, augmented reality devices, virtual reality devices, etc.
可选地，不同的终端设备201中安装的应用程序的客户端是相同的，或基于不同操作系统的同一类型应用程序的客户端。基于终端平台的不同，该应用程序的客户端的具体形态也可以不同，比如，该应用程序客户端可以是手机客户端、PC客户端等。Optionally, the clients of the application programs installed in different terminal devices 201 are the same, or the clients of the same type of application programs based on different operating systems. Based on different terminal platforms, the specific form of the application client can also be different. For example, the application client can be a mobile phone client, a PC client, etc.
服务器203可以是提供各种服务的服务器，例如对用户利用终端设备101所进行操作的装置提供支持的后台管理服务器。后台管理服务器可以对接收到的请求等数据进行分析等处理，并将处理结果反馈给终端设备。The server 203 may be a server that provides various services, such as a background management server that provides support for devices operated by the user using the terminal device 101 . The background management server can analyze and process the received request and other data, and feed the processing results back to the terminal device.
可选地，服务器可以是独立的物理服务器，也可以是多个物理服务器构成的服务器集群或者分布式系统，还可以是提供云服务、云数据库、云计算、云函数、云存储、网络服务、云通信、中间件服务、域名服务、安全服务、CDN(Content Delivery Network，内容分发网络)、以及大数据和人工智能平台等基础云计算服务的云服务器。Optionally, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or it can provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, Cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network, content distribution network), and cloud servers for basic cloud computing services such as big data and artificial intelligence platforms.
本领域技术人员可以知晓，图1中的终端设备、网络和服务器的数量仅仅是示意性的，根据实际需要，可以具有任意数目的终端设备、网络和服务器。本公开实施例对此不作限定。Those skilled in the art will know that the number of terminal devices, networks and servers in Figure 1 is only illustrative, and there can be any number of terminal devices, networks and servers according to actual needs. The embodiments of the present disclosure do not limit this.
在上述系统架构下，本公开实施例中提供的一种网元扩容方法，该方法可以由任意具备计算处理能力的电子设备执行。Under the above system architecture, an embodiment of the present disclosure provides a network element expansion method, which can be executed by any electronic device with computing processing capabilities.
在一些实施例中，本公开实施例中提供的网元扩容方法可以由上述系统架构的终端设备执行；在另一些实施例中，本公开实施例中提供的网元扩容方法可以由上述系统架构中的服务器执行；在另一些实施例中，本公开实施例中提供的扩容方法可以由上述系统架构中的终端设备和服务器通过交互的方式来实现。In some embodiments, the network element expansion method provided in the embodiments of the present disclosure can be executed by the terminal device of the above system architecture; in other embodiments, the network element expansion method provided in the embodiments of the present disclosure can be executed by the above system architecture. The server in the system is executed; in other embodiments, the capacity expansion method provided in the embodiments of the present disclosure can be implemented interactively by the terminal device and the server in the above system architecture.
图3示出本公开实施例中一种网元扩容方法流程图，如图3所示，本公开实施例中提供的网元扩容方法包括如下步骤：Figure 3 shows a flow chart of a network element expansion method in an embodiment of the present disclosure. As shown in Figure 3, the network element expansion method provided in an embodiment of the present disclosure includes the following steps:
S302，采集目标网元的业务指标数据和资源指标数据。S302: Collect service indicator data and resource indicator data of the target network element.
需要说明的是目标网元可以是任意一种网元，在本公开实施例中，目标网元具体可以是但不限于AMF(Access and Mobility Management Function，接入和移动管理功能)网元、SMF(Session Management Function，会话管理功能)网元、MME(MobilityManagement Entity，移动性管理实体)网元等。It should be noted that the target network element can be any kind of network element. In the embodiment of the present disclosure, the target network element can be, but is not limited to, an AMF (Access and Mobility Management Function) network element, an SMF (Session Management Function, session management function) network element, MME (MobilityManagement Entity, mobility management entity) network element, etc.
在本公开的一些实施例中，目标网元可以为核心网网元，核心网是一个通信网络的关键组成部分，负责提供高速、可靠、安全的数据传输和路由服务。核心网的承载能力决定了整个网络的性能和能力。随着业务量的增加、用户数量的增长、新技术的引入等，核心网网元可能会面临承载能力不足的问题。通过针对核心网网元的扩容处理，可以提高核心网的承载能力和性能，确保网络的稳定运行和高质量的服务。这对于满足日益增长的通信需求和提供优质的用户体验非常关键。In some embodiments of the present disclosure, the target network element may be a core network element. The core network is a key component of a communication network and is responsible for providing high-speed, reliable, and secure data transmission and routing services. The carrying capacity of the core network determines the performance and capabilities of the entire network. With the increase in business volume, the growth in the number of users, the introduction of new technologies, etc., core network elements may face the problem of insufficient carrying capacity. Through the expansion processing of core network elements, the carrying capacity and performance of the core network can be improved to ensure stable operation of the network and high-quality services. This is critical to meeting growing communication demands and providing a quality user experience.
目标网元的业务指标数据是指用于评估目标网元当前业务的相关指标数据。在本公开实施例中业务指标数据可以包括但不限于以下内容：The service indicator data of the target network element refers to the relevant indicator data used to evaluate the current business of the target network element. In this embodiment of the present disclosure, business indicator data may include but is not limited to the following:
1.用户总数：表示连接到目标网元的移动用户的总数量。在一些实施例中，当目标网元为4G核心网的网元时，用户总数可以是连接至该目标网元的4G移动用户的总数量；在一些实施例中，当目标网元为5G核心网的网元时，用户总数可以是连接至该目标网元的5G移动用户的总数量。1. Total number of users: Indicates the total number of mobile users connected to the target network element. In some embodiments, when the target network element is a network element of the 4G core network, the total number of users may be the total number of 4G mobile users connected to the target network element; in some embodiments, when the target network element is a 5G core network element When the target network element is a network element, the total number of users may be the total number of 5G mobile users connected to the target network element.
2.长期演进语音承载(Voice over Long Term Evolution，VoLTE)用户总数：表示在目标网元上使用长期演进技术(LTE)进行语音通信的用户总数量。2. Total number of Voice over Long Term Evolution (VoLTE) users: Indicates the total number of users using Long Term Evolution (LTE) technology for voice communication on the target network element.
3.VOLTE用户注册成功率：衡量使用VOLTE技术进行语音通信的用户在注册过程中成功连接到目标网元的比例。3. VOLTE user registration success rate: Measures the proportion of users who use VOLTE technology for voice communication to successfully connect to the target network element during the registration process.
4.主叫接通率：表示连接到目标网元的用户发起主叫呼叫并成功建立连接的比例。4. Caller connection rate: Indicates the proportion of users connected to the target network element who initiate a calling call and successfully establish a connection.
5.主叫接通次数：表示连接到目标网元的用户成功建立的主叫呼叫次数。5. Caller connection times: Indicates the number of caller calls successfully established by users connected to the target network element.
6.被叫接通率：表示连接到目标网元的用户接收到呼叫请求并成功建立连接的比例。6. Called connection rate: Indicates the proportion of users connected to the target network element who receive call requests and successfully establish connections.
7.被叫接通次数：表示连接到目标网元的用户成功建立的被叫呼叫次数。7. Number of called connections: Indicates the number of successfully established called calls by users connected to the target network element.
目标网元的资源指标数据是指用于评估目标网元的资源的相关指标数据。资源指标数据可以包括但不限于以下内容：The resource indicator data of the target network element refers to the relevant indicator data used to evaluate the resources of the target network element. Resource indicator data can include but is not limited to the following:
1.网元内存占用率：表示目标网元当前内存使用的百分比，可用于评估目标网元内存的利用率以及潜在的内存压力。1. Network element memory usage: Indicates the percentage of the target network element’s current memory usage, which can be used to evaluate the target network element’s memory utilization and potential memory pressure.
2.网元内存空闲总量：表示目标网元当前可用的内存空间总量，可用于了解目标网元内存资源的剩余情况。2. Total free memory space of the network element: Indicates the total amount of memory space currently available on the target network element, which can be used to understand the remaining memory resources of the target network element.
3.服务器占用率：表示目标网元所在服务器CPU当前正在执行任务的比例。3. Server occupancy rate: Indicates the proportion of the CPU of the server where the target network element is located that is currently executing tasks.
4.网络连接数：表示目标网元当前活动的网络连接数量，可以用于监控目标网元的连接负载和连接状态，帮助评估网络性能和容量。4. Number of network connections: Indicates the number of currently active network connections of the target network element. It can be used to monitor the connection load and connection status of the target network element and help evaluate network performance and capacity.
5.带宽信息：表示目标网元所使用的网络带宽信息。5. Bandwidth information: Indicates the network bandwidth information used by the target network element.
S304，将目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量。S304: Input the service indicator data and resource indicator data of the target network element into the pre-trained network element carrying capacity prediction model, and output the maximum carrying capacity of the target network element when it meets the preset conditions.
需要说明的是，网元承载量预测模型可以是任意一种用于预测目标网元的承载能力的模型。网元承载量预测模型基于目标网元的业务指标数据和资源指标数据，通过建立关系和算法，对目标网元在满足一定条件下的最大承载量进行估计和预测。网元承载量预测模型可以通过监测和分析目标网元的历史数据来进行训练和构建。在模型训练过程中，通过对大量的业务指标数据和资源指标数据进行学习和分析，捕捉不同指标之间的相互影响和关联。It should be noted that the network element carrying capacity prediction model can be any model used to predict the carrying capacity of the target network element. The network element carrying capacity prediction model is based on the service indicator data and resource indicator data of the target network element, and estimates and predicts the maximum carrying capacity of the target network element under certain conditions by establishing relationships and algorithms. The network element carrying capacity prediction model can be trained and constructed by monitoring and analyzing the historical data of the target network element. During the model training process, a large amount of business indicator data and resource indicator data are learned and analyzed to capture the mutual influence and correlation between different indicators.
网元承载量预测模型完成训练后，通过分析输入的当前采集的业务指标数据和资源指标数据，网元承载量预测模型输出目标网元在满足预设条件时的最大承载量。After the network element carrying capacity prediction model completes training, by analyzing the input currently collected business indicator data and resource indicator data, the network element carrying capacity prediction model outputs the maximum carrying capacity of the target network element when it meets the preset conditions.
承载量是网元承载的容量，本公开实施例所需要满足的预设条件可以是保证注册成功率、接通率。其中，注册成功率指定了目标网元设定的注册成功率的预设条件，接通率指定了目标网元设定的接通率的预设条件。本公开在满足注册成功率、接通率的条件下输出目标网元的最大承载量，可以确保在用户激增的场景下网元能够及时扩容，降低了网元过载的概率，提升用户体验。Bearing capacity refers to the carrying capacity of a network element. The preset conditions that need to be met in the embodiment of the present disclosure may be to ensure the registration success rate and connection rate. Among them, the registration success rate specifies the preset condition of the registration success rate set by the target network element, and the connection rate specifies the preset condition of the connection rate set by the target network element. This disclosure outputs the maximum carrying capacity of the target network element under the condition that the registration success rate and connection rate are met, which can ensure that the network element can be expanded in time in a scenario where users surge, reducing the probability of network element overload and improving user experience.
S306，若目标网元的最大承载量超过预设阈值，则对目标网元进行扩容处理。S306: If the maximum carrying capacity of the target network element exceeds the preset threshold, expand the capacity of the target network element.
如果预测的最大承载量超过了预设阈值，这说明目标网元当前的配置已经达到或超过了预设的限制。在这种情况下，对目标网元进行扩容处理，以增加目标网元的承载能力，从而满足更高的业务需求。If the predicted maximum load capacity exceeds the preset threshold, it means that the current configuration of the target network element has reached or exceeded the preset limit. In this case, the target network element is expanded to increase the carrying capacity of the target network element to meet higher business requirements.
由上可知，本公开实施例提供的网元扩容方法，通过采集的目标网元的当前数据和目标网元承载量预测模型来估计目标网元的最大承载量，并根据预设的阈值来判断是否需要进行扩容处理，可以更准确地评估目标网元当前的承载能力情况，以此进行及时扩容，动态且及时的对网元进行了扩容，避免了网元扩容出现滞后情况的发生，根据资源负载情况，避免了网元超负荷运行，保证网络的稳定性和性能。同时，也可以帮助网络管理员更好地规划和管理网络资源，提前做好扩容准备，以适应未来业务增长的需求。It can be seen from the above that the network element expansion method provided by the embodiment of the present disclosure estimates the maximum carrying capacity of the target network element through the collected current data of the target network element and the target network element carrying capacity prediction model, and judges based on the preset threshold Whether expansion processing is needed can more accurately evaluate the current carrying capacity of the target network element, so as to expand the capacity in a timely manner. The network element is dynamically and timely expanded to avoid the occurrence of lag in network element expansion. According to the resources The load condition avoids overload operation of network elements and ensures the stability and performance of the network. At the same time, it can also help network administrators better plan and manage network resources and prepare for capacity expansion in advance to adapt to future business growth needs.
需要注意的是，本公开技术方案中对数据的获取、存储、使用、处理等均符合国家法律法规的相关规定，本公开实施例中获取的个人、客户和人群等相关的个人身份数据、操作数据、行为数据等多种类型的数据，均已获得授权。It should be noted that the acquisition, storage, use, and processing of data in the technical solution of this disclosure are all in compliance with the relevant provisions of national laws and regulations. The personal identity data and operations related to individuals, customers, and groups obtained in the embodiments of this disclosure are Various types of data, including data and behavioral data, have been authorized.
在本公开的一些实施例中，如图4所示，在将目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量之前，还包括如下步骤：In some embodiments of the present disclosure, as shown in Figure 4, after inputting the service indicator data and resource indicator data of the target network element into the pre-trained network element carrying capacity prediction model, the output target network element satisfies the preset Before determining the maximum load capacity under the conditions, the following steps are also included:
S402，获取构建网元承载量预测模型的样本数据，其中，样本数据包括来自一个或多个网元的业务指标数据和资源指标数据；S402: Obtain sample data for constructing a network element carrying capacity prediction model, where the sample data includes business indicator data and resource indicator data from one or more network elements;
S404，将样本数据划分为训练数据集和测试数据集；S404, divide the sample data into a training data set and a test data set;
S406，根据训练数据集对网元承载量预测模型进行训练；S406, train the network element carrying capacity prediction model according to the training data set;
S408，根据测试数据集对训练后的网元承载量预测模型进行测试。S408: Test the trained network element carrying capacity prediction model based on the test data set.
需要说明的是，样本数据是用于构建网元承载量预测模型的数据集，具体构建过程分为训练过程和测试验证过程，因此获取的样本数据对应分为训练数据集和测试数据集，其中训练数据集用于对网元承载量预测模型进行训练，测试数据集用于对训练后的网元承载量预测模型进行测试验证，以使网元承载量预测模型输出的最大承载量更为准确。It should be noted that the sample data is a data set used to construct the network element carrying capacity prediction model. The specific construction process is divided into a training process and a test verification process. Therefore, the obtained sample data is divided into a training data set and a test data set, where The training data set is used to train the network element carrying capacity prediction model, and the test data set is used to test and verify the trained network element carrying capacity prediction model, so that the maximum carrying capacity output by the network element carrying capacity prediction model is more accurate. .
还需要说明的是，样本数据来自于一个或多个网元的业务指标数据和资源指标数据，需要理解的是，这些业务指标数据和资源指标数据是对应网元的历史数据，根据这些历史数据对神经网络模型进行模型训练得到网元承载量预测模型可以更好地适应实际数据的特征和变化，从而提高预测的准确性和精确度。It should also be noted that the sample data comes from the business indicator data and resource indicator data of one or more network elements. It should be understood that these business indicator data and resource indicator data are historical data of the corresponding network elements. According to these historical data The network element carrying capacity prediction model obtained by training the neural network model can better adapt to the characteristics and changes of the actual data, thereby improving the accuracy and precision of the prediction.
在本公开的一些实施例中，网元承载量预测模型是根据支持向量回归(SupportVector Regression,SVR)模型训练得到的。支持向量回归是一种基于支持向量机(SupportVector Machine,SVM)算法的回归方法，通过寻找一个最优超平面来拟合数据，并根据超平面上离散样本点与该超平面的距离进行预测。SVR适用于非线性关系并且能够处理高维数据。In some embodiments of the present disclosure, the network element carrying capacity prediction model is trained according to a Support Vector Regression (SVR) model. Support vector regression is a regression method based on the Support Vector Machine (SVM) algorithm, which fits the data by finding an optimal hyperplane and makes predictions based on the distance between the discrete sample points on the hyperplane and the hyperplane. SVR is suitable for non-linear relationships and can handle high-dimensional data.
通过使用支持向量回归SVR模型进行训练，可以借助模型的特性和强大的拟合能力，更准确地预测网元的承载量。训练过程中，模型将根据历史的业务指标数据和资源指标数据，学习出一个能够对目标网元的承载量进行回归预测的模型。By using the support vector regression SVR model for training, you can use the model's characteristics and powerful fitting capabilities to more accurately predict the carrying capacity of network elements. During the training process, the model will learn a model that can perform regression predictions on the target network element's carrying capacity based on historical business indicator data and resource indicator data.
在本公开的一些实施例中，如图5所示，在获取构建网元承载量预测模型的样本数据之后，还包括如下步骤：In some embodiments of the present disclosure, as shown in Figure 5, after obtaining the sample data for constructing the network element carrying capacity prediction model, the following steps are also included:
S502，利用主成分分析(Principal Component Analysis,PCA)方法对样本数据进行降维处理；S502, use the principal component analysis (Principal Component Analysis, PCA) method to perform dimensionality reduction processing on the sample data;
S504，对降维后的样本数据进行降去噪处理，得到满足预设条件的样本数据。S504: Perform denoising processing on the dimensionally reduced sample data to obtain sample data that meets preset conditions.
需要说明的是，主成分分析(Principal Component Analysis,PCA)是一种降维方法，它通过寻找原始数据中的主要特征，并将其转换成一组较低维度的主成分，从而减少数据的维度。通过降低数据的维度，可以去除冗余的特征信息，同时保留对数据变化具有较大贡献的主要特征，从而减少数据集的复杂度。It should be noted that Principal Component Analysis (PCA) is a dimensionality reduction method that reduces the dimensionality of the data by finding the main features in the original data and converting them into a set of lower-dimensional principal components. . By reducing the dimensionality of the data, redundant feature information can be removed while retaining the main features that contribute significantly to data changes, thereby reducing the complexity of the data set.
在本公开实施例提供的网元扩容方法中，使用PCA方法对样本数据进行降维处理的目的是减少计算复杂度，并提高模型训练和预测的效率。通过选择适当的主成分数量，可以在保持数据主要特征的同时，减少样本的维度。In the network element expansion method provided by the embodiments of the present disclosure, the purpose of using the PCA method to perform dimensionality reduction processing on sample data is to reduce computational complexity and improve the efficiency of model training and prediction. By choosing an appropriate number of principal components, the dimensionality of the sample can be reduced while maintaining the main characteristics of the data.
此外，在降维后的样本数据中，可能存在一些噪声或异常值，这可能会对模型的性能产生不良影响。因此，对降维后的样本数据进行降噪处理可以进一步提高模型预测的准确性和稳定性。In addition, there may be some noise or outliers in the sample data after dimensionality reduction, which may have a negative impact on the performance of the model. Therefore, denoising the dimensionally reduced sample data can further improve the accuracy and stability of model predictions.
在本公开的一些实施例中，以图6公开的网元扩容系统图和图7公开的网元扩容具体流程图为例，对本公开实施例的实施方式做一个具体示例性解释：In some embodiments of the present disclosure, taking the network element expansion system diagram disclosed in Figure 6 and the specific flow chart of network element expansion disclosed in Figure 7 as examples, a specific exemplary explanation of the implementation of the embodiments of the present disclosure is given:
如图6所示，网元扩容系统包括：监控模块601、计算模块602、部署模块603三个部分。As shown in Figure 6, the network element expansion system includes three parts: a monitoring module 601, a computing module 602, and a deployment module 603.
各模块实现的功能包括如下：The functions implemented by each module include the following:
监控模块601主要是监控核心网元的业务指标数据、系统资源指标数据。其中系统资源指标包括服务器内存、CPU、带宽信息。The monitoring module 601 mainly monitors the business indicator data and system resource indicator data of core network elements. The system resource indicators include server memory, CPU, and bandwidth information.
计算模块602主要是通过各个网元的历史数据，构建基于SVR算法的网元承载量预测模型，在核心网元正常运行的前提下，通过该网元承载量预测模型计算网元的最大承载量。The calculation module 602 mainly constructs a network element carrying capacity prediction model based on the SVR algorithm through the historical data of each network element. Under the premise that the core network element is operating normally, the network element carrying capacity prediction model is used to calculate the maximum carrying capacity of the network element. .
部署模块603：监控模块601实时发送网元的承载量给部署模块603，部署模块603根据计算模块602推算出阈值判断该网元是否过载，如果过载，则部署网元，实现该目标网元的扩容。Deployment module 603: The monitoring module 601 sends the carrying capacity of the network element to the deployment module 603 in real time. The deployment module 603 determines whether the network element is overloaded based on the threshold calculated by the calculation module 602. If it is overloaded, the network element is deployed to achieve the target network element. Expansion.
具体的实现流程图如图7所示，监控模块601主要包括两部分：监控业务指标、监控资源指标；The specific implementation flow chart is shown in Figure 7. The monitoring module 601 mainly includes two parts: monitoring business indicators and monitoring resource indicators;
监控业务指标：4G/5G用户总数、volte用户总数、volte用户注册成功率、主叫接通率、主叫接通次数、被叫接通率、被叫接通次数等；Monitoring business indicators: total number of 4G/5G users, total number of volte users, volte user registration success rate, caller connection rate, caller connection times, called connection rate, called connection times, etc.;
监控资源指标：各网元内存占用率、内存空闲总量，目标服务器CPU占用率、网络连接数等；Monitor resource indicators: memory usage of each network element, total amount of free memory, target server CPU usage, number of network connections, etc.;
对于收集到的历史数据，采用PCA(主成分分析)对数据进行降维，将高维度的数据保留下最重要的一些特征，去除噪声和不重要的特征，从而实现提升数据处理速度的目的。For the collected historical data, PCA (Principal Component Analysis) is used to reduce the dimensionality of the data, retain the most important features of high-dimensional data, and remove noise and unimportant features, thereby achieving the purpose of improving data processing speed.
按照7:3将处理后的数据分为训练数据集和测试数据集，构建支持向量回归模型SVR(Support Vector Regression)，选择高斯核函数作为SVR的核函数。Divide the processed data into training data sets and test data sets according to 7:3, build the support vector regression model SVR (Support Vector Regression), and select the Gaussian kernel function as the kernel function of SVR.
利用训练数据集训练网络模型，训练出适用于预测网元最大承载量的网元承载量预测模型，通过网元承载量预测模型计算网元在确保注册成功率、接通率的前提下的最大承载量，计算该网元阈值并推送给部署模块。Use the training data set to train the network model and train a network element carrying capacity prediction model suitable for predicting the maximum carrying capacity of the network element. Use the network element carrying capacity prediction model to calculate the maximum load capacity of the network element while ensuring the registration success rate and connection rate. Carrying capacity, calculate the network element threshold and push it to the deployment module.
监控模块实时采集数据并发送到部署模块，部署模块通过阈值判断该网元是否需要扩容。The monitoring module collects data in real time and sends it to the deployment module, which determines whether the network element needs to be expanded through the threshold.
本公开实施例根据各网元采集的历史数据指标，在保证注册成功率、接通率的前提下，利用SVM模型计算出该网元的最大承载量，从而确保在用户激增的场景下网元能及时扩容，降低现网上出现网元过载的概率，提升用户体验。According to the historical data indicators collected by each network element, this disclosed embodiment uses the SVM model to calculate the maximum carrying capacity of the network element on the premise of ensuring the registration success rate and connection rate, thereby ensuring that the network element can handle the surge in users. It can expand capacity in a timely manner, reduce the probability of network element overload on the existing network, and improve user experience.
基于同一发明构思，本公开实施例中还提供了一种网元扩容装置，如下面的实施例所述。由于该装置实施例解决问题的原理与上述方法实施例相似，因此该装置实施例的实施可以参见上述方法实施例的实施，重复之处不再赘述。Based on the same inventive concept, embodiments of the present disclosure also provide a network element expansion device, as described in the following embodiments. Since the problem-solving principle of this device embodiment is similar to that of the above-mentioned method embodiment, the implementation of this device embodiment can refer to the implementation of the above-mentioned method embodiment, and repeated details will not be repeated.
图8示出本公开实施例中一种网元扩容装置示意图，如图8所示，该装置包括：Figure 8 shows a schematic diagram of a network element expansion device in an embodiment of the present disclosure. As shown in Figure 8, the device includes:
数据采集模块801，用于采集目标网元的业务指标数据和资源指标数据；The data collection module 801 is used to collect business indicator data and resource indicator data of the target network element;
承载量预测模块802，用于将目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量；The carrying capacity prediction module 802 is used to input the service indicator data and resource indicator data of the target network element into the pre-trained network element carrying capacity prediction model, and output the maximum carrying capacity of the target network element when it meets the preset conditions;
网元扩容模块803，用于当目标网元的最大承载量超过预设阈值，则对目标网元进行扩容处理。The network element expansion module 803 is used to expand the capacity of the target network element when the maximum carrying capacity of the target network element exceeds a preset threshold.
在本公开的一些实施例中，上述承载量预测模块802，还用于获取构建网元承载量预测模型的样本数据，其中，样本数据包括来自一个或多个网元的业务指标数据和资源指标数据；将样本数据划分为训练数据集和测试数据集；根据训练数据集对网元承载量预测模型进行训练；根据测试数据集对训练后的网元承载量预测模型进行测试。In some embodiments of the present disclosure, the above-mentioned load capacity prediction module 802 is also used to obtain sample data for constructing a network element load capacity prediction model, where the sample data includes business indicator data and resource indicators from one or more network elements. data; divide the sample data into a training data set and a test data set; train the network element capacity prediction model based on the training data set; test the trained network element capacity prediction model based on the test data set.
在本公开的一些实施例中，上述承载量预测模块802，还用于利用主成分分析PCA方法对样本数据进行降维处理；对降维后的样本数据进行降去噪处理，得到满足预设条件的样本数据。In some embodiments of the present disclosure, the above-mentioned carrying capacity prediction module 802 is also used to perform dimensionality reduction processing on the sample data using the principal component analysis PCA method; and performs denoising processing on the dimensionally reduced sample data to obtain a result that satisfies the preset Conditional sample data.
此处需要说明的是，上述模块与对应的步骤所实现的示例和应用场景相同，但不限于上述方法实施例所公开的内容。需要说明的是，上述模块作为装置的一部分可以在诸如一组计算机可执行指令的计算机系统中执行。It should be noted here that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above method embodiments. It should be noted that the above-mentioned modules, as part of the device, can be executed in a computer system such as a set of computer-executable instructions.
所属技术领域的技术人员能够理解，本公开的各个方面可以实现为系统、方法或程序产品。因此，本公开的各个方面可以具体实现为以下形式，即：完全的硬件实施方式、完全的软件实施方式(包括固件、微代码等)，或硬件和软件方面结合的实施方式，这里可以统称为“电路”、“模块”或“系统”。Those skilled in the art will understand that various aspects of the present disclosure may be implemented as systems, methods, or program products. Therefore, various aspects of the present disclosure may be embodied in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which may be collectively referred to herein as "Circuit", "Module" or "System".
下面参照图9来描述根据本公开的这种实施方式的电子设备900。图9显示的电子设备900仅仅是一个示例，不应对本公开实施例的功能和使用范围带来任何限制。An electronic device 900 according to this embodiment of the present disclosure is described below with reference to FIG. 9 . The electronic device 900 shown in FIG. 9 is only an example and should not impose any limitations on the functions and scope of use of the embodiments of the present disclosure.
如图9所示，电子设备900以通用计算设备的形式表现。电子设备900的组件可以包括但不限于：上述至少一个处理单元910、上述至少一个存储单元920、连接不同系统组件(包括存储单元920和处理单元910)的总线930。As shown in Figure 9, electronic device 900 is embodied in the form of a general computing device. The components of the electronic device 900 may include, but are not limited to: the above-mentioned at least one processing unit 910, the above-mentioned at least one storage unit 920, and a bus 930 connecting different system components (including the storage unit 920 and the processing unit 910).
其中，所述存储单元存储有程序代码，所述程序代码可以被所述处理单元910执行，使得所述处理单元910执行本说明书上述“示例性方法”部分中描述的根据本公开各种示例性实施方式的步骤。例如，处理单元910可以执行上述方法实施例的如下步骤：采集目标网元的业务指标数据和资源指标数据；将目标网元的业务指标数据和资源指标数据，输入至预先训练好的网元承载量预测模型中，输出目标网元满足预设条件时的最大承载量；若目标网元的最大承载量超过预设阈值，则对目标网元进行扩容处理。Wherein, the storage unit stores program code, and the program code can be executed by the processing unit 910, so that the processing unit 910 performs various exemplary methods according to the present disclosure described in the "Example Method" section of this specification. Implementation steps. For example, the processing unit 910 can perform the following steps of the above method embodiment: collect the service indicator data and resource indicator data of the target network element; input the service indicator data and resource indicator data of the target network element to the pre-trained network element bearer In the capacity prediction model, the maximum carrying capacity of the target network element when it meets the preset conditions is output; if the maximum carrying capacity of the target network element exceeds the preset threshold, the target network element is expanded.
存储单元920可以包括易失性存储单元形式的可读介质，例如随机存取存储单元(RAM)9201和/或高速缓存存储单元9202，还可以进一步包括只读存储单元(ROM)9203。The storage unit 920 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 9201 and/or a cache storage unit 9202, and may further include a read-only storage unit (ROM) 9203.
存储单元920还可以包括具有一组(至少一个)程序模块9205的程序/实用工具9204，这样的程序模块9205包括但不限于：操作系统、一个或者多个应用程序、其它程序模块以及程序数据，这些示例中的每一个或某种组合中可能包括网络环境的实现。Storage unit 920 may also include a program/utility 9204 having a set of (at least one) program modules 9205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, Each of these examples, or some combination, may include the implementation of a network environment.
总线930可以为表示几类总线结构中的一种或多种，包括存储单元总线或者存储单元控制器、外围总线、图形加速端口、处理单元或者使用多种总线结构中的任意总线结构的局域总线。Bus 930 may be a local area representing one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, a graphics acceleration port, a processing unit, or using any of a variety of bus structures. bus.
电子设备900也可以与一个或多个外部设备940(例如键盘、指向设备、蓝牙设备等)通信，还可与一个或者多个使得用户能与该电子设备900交互的设备通信，和/或与使得该电子设备900能与一个或多个其它计算设备进行通信的任何设备(例如路由器、调制解调器等等)通信。这种通信可以通过输入/输出(I/O)接口950进行。并且，电子设备900还可以通过网络适配器960与一个或者多个网络(例如局域网(LAN)，广域网(WAN)和/或公共网络，例如因特网)通信。如图所示，网络适配器960通过总线930与电子设备900的其它模块通信。应当明白，尽管图中未示出，可以结合电子设备900使用其它硬件和/或软件模块，包括但不限于：微代码、设备驱动器、冗余处理单元、外部磁盘驱动阵列、RAID系统、磁带驱动器以及数据备份存储系统等。Electronic device 900 may also communicate with one or more external devices 940 (e.g., keyboard, pointing device, Bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with electronic device 900, and/or with Any device that enables the electronic device 900 to communicate with one or more other computing devices (eg, router, modem, etc.). This communication may occur through an input/output (I/O) interface 950. Furthermore, the electronic device 900 may also communicate with one or more networks (eg, a local area network (LAN), a wide area network (WAN), and/or a public network, such as the Internet) through the network adapter 960. As shown, network adapter 960 communicates with other modules of electronic device 900 via bus 930. It should be understood that, although not shown in the figures, other hardware and/or software modules may be used in conjunction with electronic device 900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives And data backup storage system, etc.
通过以上的实施方式的描述，本领域的技术人员易于理解，这里描述的示例实施方式可以通过软件实现，也可以通过软件结合必要的硬件的方式来实现。因此，根据本公开实施方式的技术方案可以以软件产品的形式体现出来，该软件产品可以存储在一个非易失性存储介质(可以是CD-ROM，U盘，移动硬盘等)中或网络上，包括若干指令以使得一台计算设备(可以是个人计算机、服务器、终端装置、或者网络设备等)执行根据本公开实施方式的方法。Through the above description of the embodiments, those skilled in the art can easily understand that the example embodiments described here can be implemented by software, or can be implemented by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to cause a computing device (which may be a personal computer, a server, a terminal device, a network device, etc.) to execute a method according to an embodiment of the present disclosure.
特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机程序产品，该计算机程序产品包括：计算机程序，所述计算机程序被处理器执行时实现上述网元扩容方法。In particular, according to embodiments of the present disclosure, the process described above with reference to the flow chart can be implemented as a computer program product. The computer program product includes: a computer program that implements the above network element expansion method when executed by a processor. .
在本公开的示例性实施例中，还提供了一种计算机可读存储介质，该计算机可读存储介质可以是可读信号介质或者可读存储介质。图10示出本公开实施例中一种计算机可读存储介质示意图，如图10所示，该算机可读存储介质1000上存储有能够实现本公开上述方法的程序产品。在一些可能的实施方式中，本公开的各个方面还可以实现为一种程序产品的形式，其包括程序代码，当所述程序产品在终端设备上运行时，所述程序代码用于使所述终端设备执行本说明书上述“示例性方法”部分中描述的根据本公开各种示例性实施方式的步骤。In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, and the computer-readable storage medium may be a readable signal medium or a readable storage medium. Figure 10 shows a schematic diagram of a computer-readable storage medium in an embodiment of the disclosure. As shown in Figure 10, the computer-readable storage medium 1000 stores a program product capable of implementing the above method of the disclosure. In some possible implementations, various aspects of the present disclosure can also be implemented in the form of a program product, which includes program code. When the program product is run on a terminal device, the program code is used to cause the The terminal device performs the steps according to various exemplary embodiments of the present disclosure described in the above "Example Method" section of this specification.
本公开中的计算机可读存储介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。More specific examples of computer-readable storage media in this disclosure may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard drives, random access memory (RAM), read only memory (ROM), Erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
在本公开中，计算机可读存储介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了可读程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。可读信号介质还可以是可读存储介质以外的任何可读介质，该可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。In this disclosure, a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave carrying readable program code therein. Such propagated data signals may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A readable signal medium may also be any readable medium other than a readable storage medium that can send, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or device.
可选地，计算机可读存储介质上包含的程序代码可以用任何适当的介质传输，包括但不限于无线、有线、光缆、RF等等，或者上述的任意合适的组合。Alternatively, program code embodied on a computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.
在具体实施时，可以以一种或多种程序设计语言的任意组合来编写用于执行本公开操作的程序代码，所述程序设计语言包括面向对象的程序设计语言—诸如Java、C++等，还包括常规的过程式程序设计语言—诸如“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算设备上执行、部分地在用户设备上执行、作为一个独立的软件包执行、部分在用户计算设备上部分在远程计算设备上执行、或者完全在远程计算设备或服务器上执行。在涉及远程计算设备的情形中，远程计算设备可以通过任意种类的网络，包括局域网(LAN)或广域网(WAN)，连接到用户计算设备，或者，可以连接到外部计算设备(例如利用因特网服务提供商来通过因特网连接)。When implemented, program code for performing operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and Includes conventional procedural programming languages—such as "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server execute on. In situations involving remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device, such as provided by an Internet service. (business comes via Internet connection).
应当注意，尽管在上文详细描述中提及了用于动作执行的设备的若干模块或者单元，但是这种划分并非强制性的。实际上，根据本公开的实施方式，上文描述的两个或更多模块或者单元的特征和功能可以在一个模块或者单元中具体化。反之，上文描述的一个模块或者单元的特征和功能可以进一步划分为由多个模块或者单元来具体化。It should be noted that although several modules or units of equipment for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to embodiments of the present disclosure, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of one module or unit described above may be further divided into being embodied by multiple modules or units.
此外，尽管在附图中以特定顺序描述了本公开中方法的各个步骤，但是，这并非要求或者暗示必须按照该特定顺序来执行这些步骤，或是必须执行全部所示的步骤才能实现期望的结果。附加的或备选的，可以省略某些步骤，将多个步骤合并为一个步骤执行，以及/或者将一个步骤分解为多个步骤执行等。Furthermore, although various steps of the methods of the present disclosure are depicted in the drawings in a specific order, this does not require or imply that the steps must be performed in that specific order, or that all of the illustrated steps must be performed to achieve the desired results. result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution, etc.
通过以上实施方式的描述，本领域的技术人员易于理解，这里描述的示例实施方式可以通过软件实现，也可以通过软件结合必要的硬件的方式来实现。因此，根据本公开实施方式的技术方案可以以软件产品的形式体现出来，该软件产品可以存储在一个非易失性存储介质(可以是CD-ROM，U盘，移动硬盘等)中或网络上，包括若干指令以使得一台计算设备(可以是个人计算机、服务器、移动终端、或者网络设备等)执行根据本公开实施方式的方法。Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described here can be implemented by software, or can be implemented by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to cause a computing device (which may be a personal computer, a server, a mobile terminal, a network device, etc.) to execute a method according to an embodiment of the present disclosure.
本领域技术人员在考虑说明书及实践这里公开的发明后，将容易想到本公开的其它实施方案。本公开旨在涵盖本公开的任何变型、用途或者适应性变化，这些变型、用途或者适应性变化遵循本公开的一般性原理并包括本公开未公开的本技术领域中的公知常识或惯用技术手段。说明书和实施例仅被视为示例性的，本公开的真正范围和精神由所附的权利要求指出。Other embodiments of the disclosure will be readily apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. The present disclosure is intended to cover any variations, uses, or adaptations of the disclosure that follow the general principles of the disclosure and include common common sense or customary technical means in the technical field that are not disclosed in the disclosure. . It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
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