Resource collaboration method and device, program product and electronic equipment

Abstract

The invention provides a resource collaboration method and device, a program product and electronic equipment, and relates to the technical field of computers and communication. The method comprises the following steps: determining whether resource co-processing is started for a first data center; under the condition that it is determined that resource co-processing is started for the first data center, deploying a function network manager executing resource co-processing for the first data center, so that the function network manager integrates co-processing resources provided by a second data center of a network element with the same function as the first data center to obtain a unique external identifier, the unique external identifier can be accessed by the first data center to obtain resources of the second data center. According to the method and the device, the resource which can be cooperatively used is integrated and the unique external identifier is obtained through the deployed function network management, so that the first data center does not need to obtain the resource based on the external identifiers of other data centers, and the problem that the resource cannot be coordinated across the data centers is solved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer and communication technology, and in particular to a resource collaboration method, device, program product and electronic device. Background Art

[0002] At present, with the existence of multiple services and multiple descriptors, there may be a phenomenon of deploying the same logical functional entity across data centers (DCs). For example, the user plane function (UPF) resources in DC1 are insufficient and need to be expanded, and DC2 also has some UPF resources. However, since DC1 and DC2 use physically isolated devices (such as firewalls and routers), or DC1 and DC2 use network address translation (NAT), virtual local area networks (VLAN) or different subnet masks, the network is isolated, resulting in the inability to coordinate UPF resources, that is, the UPF of DC2 cannot be coordinated for use by DC1.

[0003] However, how to achieve resource collaboration across data centers has become an urgent problem to be solved. Summary of the invention

[0004] The present disclosure provides a resource collaboration method, a resource collaboration device, a computer program product, and an electronic device, so as to realize the collaboration of resources across data centers to a certain extent.

[0005] According to a first aspect of the present disclosure, a resource collaboration method is provided, the method comprising:

[0006] Determining whether to initiate resource collaborative processing for the first data center;

[0007] When it is determined to start resource collaborative processing on the first data center, a functional network manager is deployed to perform resource collaborative processing on the first data center, so that the functional network manager integrates the collaborative resources provided by the second data center of the network elements having the same functions as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center.

[0008] In one embodiment, before determining whether to start resource collaborative processing for the first data center, the method further includes:

[0009] Determine whether network elements with the same functions are monitored in different data centers;

[0010] If it is monitored that the first data center and multiple data centers include network elements with the same functions, it is determined whether to start resource collaborative processing for the first data center.

[0011] In one implementation, determining whether to start resource collaborative processing for the first data center includes:

[0012] Determining service parameter information of the first data center;

[0013] Determine whether to start resource collaborative processing for the first data center according to the business parameter information.

[0014] In one implementation, the service parameter information includes at least one of service complexity, the number of services to be executed, and the number of new services.

[0015] In one implementation, determining whether to start resource collaborative processing for the first data center according to the service parameter information includes:

[0016] Determining whether to start resource collaborative processing for the first data center according to a matching result between the business parameter information and a preset range;

[0017] Or, based on a comparison result between the business parameter information and the business parameters of other data centers, it is determined whether to start resource collaborative processing for the first data center.

[0018] In one embodiment, the method further comprises:

[0019] Sending indication information of reporting collaborative resources to the second data center respectively;

[0020] Each of the second data centers converts its own internal identifier indicating a collaborative resource into an external identifier, so that the first data center searches for the corresponding collaborative resource based on the unique external identifier and the external identifier.

[0021] In one implementation, when it is determined to start resource collaborative processing on the first data center, deploying a functional network management for performing resource collaborative processing on the first data center includes:

[0022] Determine a first network manager that manages a first network element; the first network element is a network element having the same functions as the first data center and other data centers;

[0023] Determining whether the first network manager can perform resource collaborative processing;

[0024] When it is determined that the first network manager can perform resource collaborative processing, the first network manager is used as a functional network manager for performing resource collaborative processing on the first data center;

[0025] When it is determined that the first network manager cannot perform resource collaborative processing, a new network element network manager is established as a functional network manager that performs resource collaborative processing on the first data center.

[0026] According to a second aspect of the present disclosure, a resource collaboration device is provided, the device comprising:

[0027] A determination unit, used to determine whether to start resource collaborative processing for the first data center;

[0028] A collaboration unit is used to deploy a functional network manager that performs resource collaborative processing on the first data center when it is determined that resource collaborative processing is to be initiated on the first data center, so that the functional network manager integrates collaborative resources provided by a second data center having network elements with the same functions as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain resources of the second data center.

[0029] In one implementation, before determining whether to start resource collaborative processing for the first data center, the determining unit is further configured to:

[0030] Determine whether network elements with the same functions are monitored in different data centers;

[0031] If it is monitored that the first data center and multiple data centers include network elements with the same functions, it is determined whether to start resource collaborative processing for the first data center.

[0032] In one implementation, the determining unit is specifically configured to:

[0033] Determining service parameter information of the first data center;

[0034] Determine whether to start resource collaborative processing for the first data center according to the business parameter information.

[0035] In one implementation, the service parameter information includes at least one of service complexity, the number of services to be executed, and the number of new services.

[0036] In one implementation, the determining unit is specifically configured to:

[0037] Determining whether to start resource collaborative processing for the first data center according to a matching result between the business parameter information and a preset range;

[0038] Or, based on a comparison result between the business parameter information and the business parameters of other data centers, it is determined whether to start resource collaborative processing for the first data center.

[0039] In one embodiment, the device further includes a sending unit, configured to:

[0040] Sending indication information of reporting collaborative resources to the second data center respectively;

[0041] Each of the second data centers converts its own internal identifier indicating a collaborative resource into an external identifier, so that the first data center searches for the corresponding collaborative resource based on the unique external identifier and the external identifier.

[0042] In one embodiment, the collaboration unit is used to:

[0043] Determine a first network manager that manages a first network element; the first network element is a network element having the same functions as the first data center and other data centers;

[0044] Determining whether the first network manager can perform resource collaborative processing;

[0045] When it is determined that the first network manager can perform resource collaborative processing, the first network manager is used as a functional network manager for performing resource collaborative processing on the first data center;

[0046] When it is determined that the first network manager cannot perform resource collaborative processing, a new network element network manager is established as a functional network manager that performs resource collaborative processing on the first data center.

[0047] According to a third aspect of the present disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the method of the first aspect and possible implementations thereof are implemented.

[0048] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the method of the above-mentioned first aspect and its possible implementation methods by executing the executable instructions.

[0049] The technical solution disclosed in this disclosure has the following beneficial effects:

[0050] In the embodiment of the present disclosure, it can be determined whether to start resource collaborative processing for the first data center; in the case of determining to start resource collaborative processing for the first data center, a functional network manager that performs resource collaborative processing on the first data center is deployed, so that the functional network manager integrates the collaborative resources provided by the second data center of the network element having the same function as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center. It can be seen that the present disclosure integrates the resources that can be used collaboratively and obtains the unique external identifier through the deployed functional network manager, so that the first data center directly obtains the resources of other data centers based on the unique external identifier, thereby achieving the purpose of cross-data center data acquisition resources, which is conducive to improving resource utilization and the business service quality of the first data center, and enhancing the user experience.

[0051] Other features and advantages of the present disclosure will be described in the following description, and partly become apparent from the description, or be understood by practicing the present disclosure. The purpose and other advantages of the present disclosure can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for use in the embodiments of the present disclosure will be briefly introduced below. Obviously, the drawings introduced below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 A schematic diagram of data center classification in this exemplary embodiment is shown;

[0054] Figure 2 A schematic diagram of an application scenario in this exemplary embodiment is shown;

[0055] Figure 3 A flow chart showing a resource collaboration method in this exemplary embodiment;

[0056] Figure 4 A schematic diagram showing the structure of a resource coordination device in this exemplary embodiment is shown;

[0057] Figure 5 A schematic structural diagram of an electronic device in this exemplary embodiment is shown. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present disclosure. In the absence of conflict, the embodiments in the present disclosure and the features in the embodiments can be arbitrarily combined with each other. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0059] The term "comprising" and any variations thereof in the specification and claims of the present disclosure are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0060] In the embodiments of the present disclosure, one or more, "many" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or plural.

[0061] It should be noted that the terms "first", "second", "third", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order, sequence, size, and priority. For example, the first data center and the second data center in the embodiment of the present disclosure are only used to distinguish different data centers. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0062] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, which are schematic diagrams of the present disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the accompanying drawings may be functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in hardware modules or integrated circuits, or in networks, processors or microcontrollers. The implementation method can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein. The features, structures or characteristics described in the present disclosure may be combined in one or more implementations in any suitable manner. In the following description, many specific details are provided to provide a full description of the implementation methods of the present disclosure. However, those skilled in the art should be aware that one or more specific details may be omitted when implementing the technical solution of the present disclosure, or one or more specific details may be replaced by other methods, components, devices, steps, etc.

[0063] It should be noted that in the embodiments of the present disclosure, certain software, components, models and other existing solutions in the industry may be mentioned, which should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present disclosure, but it does not mean that the applicant has or will necessarily use the solution.

[0064] In the related technologies, virtual machines and containers have been widely used in the fifth-generation mobile communication technology (5G) network. Driven by new application scenarios and different workload requirements (such as video, cloud radio access network (Cloud RAN)), the new demand for deploying diversified heterogeneous hardware resources (such as different numbers of Pods, instances, or directly services) in the network function virtualization (NFV) system is becoming a reality. In order to meet the needs of various vertical industries and the diversification of services, a single resource of a single data center (DC) cannot meet the needs of regional business diversification, or a single DC resource load reaches the upper limit and still cannot meet business development, then cross-DC resource collaboration becomes inevitable. However, there is a problem of multiple logics for multiple loads, which makes network deployment more complicated.

[0065] Currently, operators generally adopt a hierarchical model to build networks, such as Figure 1 As shown, for example, it is divided into regional DC, provincial DC and municipal DC. Among them, regional DC and provincial DC, i.e., the upper two layers, are mainly interconnected at the signaling level, but the lowest layer of municipal DC is the isolation at the resource level, i.e., UPF.

[0066] In addition, the current specifications and operators have established intercommunication between UPF and the upper-layer central UPF, Session Management Function (SMF), virtual network management system (EMS), lower-layer base stations and virtual infrastructure management (VIM). However, there is no intercommunication between UPFs across DCs, mainly because different DCs have their own regional management / planning, and DCs form a natural barrier. But more importantly, the diversity of services also brings different functions of different UPFs. For example, some services require ordinary low-speed data transmission functions, while some services require a large number of fast computing functions. In addition, from the perspective of currently foreseeable virtualized resources, there are already virtualized network resource modules (Virtualised Network Function, VNF), and container-based container network file systems (Container Network FileSystem, CNFs). From the perspective of descriptors, there are NSD, AppD, VNFD, HelmChart and other possible new descriptors. But these virtualized resources cannot currently communicate with each other.

[0067] It can be seen that with the existence of multiple services and multiple descriptors, the same logical functional entity may be deployed across DCs. For example, the UPF resources in DC1 are insufficient and need to be expanded. DC2 also has some UPF resources, but because DC1 and DC2 use physically isolated devices (such as firewalls and routers), or DC1 and DC2 use network address translation (NAT), virtual local area networks (VLAN) or different subnet masks, they are isolated networks, resulting in the inability to coordinate UPF resources, that is, the UPF of DC2 cannot be coordinated for use by DC1.

[0068] However, how to achieve resource collaboration across data centers has become an urgent problem to be solved.

[0069] In view of one or more of the above problems, an exemplary embodiment of the present disclosure provides a resource collaboration method, through which it can be determined whether to start resource collaborative processing for the first data center; in the case of determining to start resource collaborative processing for the first data center, a functional network manager that performs resource collaborative processing on the first data center is deployed, so that the functional network manager integrates the collaborative resources provided by the second data center of the network element having the same function as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center. It can be seen that the present disclosure integrates the resources that can be used collaboratively and obtains the unique external identifier through the deployed functional network manager, so that the first data center directly obtains the resources of other data centers based on the unique external identifier, thereby achieving the purpose of cross-data center data acquisition resources, which is conducive to improving resource utilization and the business service quality of the first data center, and enhancing the user experience.

[0070] In order to better understand the technical solution provided by the embodiment of the present disclosure, the following is an introduction to the application scenarios to which the technical solution provided by the embodiment of the present disclosure is applicable. It should be noted that the application scenarios introduced below are only used to illustrate the embodiment of the present disclosure and are not limited. In specific implementation, the technical solution provided by the embodiment of the present disclosure can be flexibly applied according to actual needs.

[0071] In the embodiments of the present disclosure, the resource collaboration technology can be applied to various business scenarios that require cross-data center collaborative resource scheduling, which is not limited in the embodiments of the present disclosure.

[0072] See also Figure 2 As shown, Figure 2 An application scenario to which the technical solution of the embodiment of the present disclosure can be applied. In the scenario diagram, multiple data centers 101, a central network management 102 and multiple functional network managements 103 are included. Among them, data center 101-1, data center 101-2, ..., data center 101-n can be used at different levels, and n is a positive integer. In other words, resource collaboration can be performed on different data centers synchronously or asynchronously. For example, resource collaboration is performed on data center 1 first, and then on data center 2; for another example, resource collaboration is performed on data center 1 and data center 2 at the same time. Among them, functional network management 103-1, functional network management 103-2, ..., functional network management 103-m can be used to manage different network elements, and m is a positive integer.

[0073] In the embodiment of the present disclosure, the central network management 102 may be preset by the corresponding staff of the operator to set the collaborative strategy of resource collaboration, and the collaborative strategy is used to determine whether to start and execute resource collaborative processing. In addition, the central network management 102 may monitor whether there are network elements with the same functions or attributes in the target area. Among them, the target area can be understood as the area under jurisdiction. For example, if the central network management 102 is the network management corresponding to the provincial DC at the provincial level, the target area can be understood as the area under the jurisdiction of the province.

[0074] In the disclosed embodiment, the central network management 102 can determine whether it is necessary to start cross-DC resource collaboration. When the central network management determines to start cross-DC resource collaboration for the data center 101-1, it first checks whether the current functional network management 103 needs to meet the requirements after collaboration. Optionally, the functional network management 103 is, for example, EMS. If the current functional network management 103 does not meet the requirements after collaboration, it instructs the operator to build a new functional network management 103. After success, the Internet Protocol Address (IP address) and port number of the functional network management 103 are obtained.

[0075] In the embodiment of the present disclosure, after the central network management 102 determines the IP address and port number of the functional network management 103, it can notify the corresponding data center to report the collaborative resources, such as the external IP address or port number. The corresponding data center is a data center of a network element having the same function or attribute as the data center 101, for example, called a second data center, and the second data center can be one or more, which is not limited in the embodiment of the present disclosure.

[0076] In the disclosed embodiment, the functional network management 103 can process the external information of resources through its receiving / analysis module and address conversion module, and finally output the converted external identifiers of the corresponding VNFs or CNFs to the functional network management 103 through the output module.

[0077] In the disclosed embodiment, after receiving the corresponding external identification information, the functional network management 103 integrates all resources into an integrated external logical entity (software loading, internal interface configuration, etc.), such as a unique identification, such as an IP address, etc. In this way, when the first data center has a corresponding business demand and uses the functional demand, it only needs to access the above unique identification, and does not need to access the resource identification corresponding to the specific DC as before, thereby realizing cross-DC resource collaboration.

[0078] Of course, the method provided in the embodiment of the present disclosure is not limited to Figure 2 The application scenarios shown may also be used in other possible application scenarios, and the embodiments of the present disclosure are not limited thereto.

[0079] To further illustrate the technical solution provided by the embodiments of the present disclosure, this is described in detail below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiments of the present disclosure provide method operation steps as shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or no creative labor. In the steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided by the embodiments of the present disclosure. The method may be executed in the order of the method shown in the embodiments or drawings or in parallel during the actual processing process or when the device is executed.

[0080] See also Figure 3 , Figure 3 FIG. 1 is a flow chart of a resource collaboration method in an embodiment of the present disclosure. The flow of the method can be, for example, Figure 2 The central network management 102 in the embodiment is executed, and the specific implementation process of the method is as follows:

[0081] Step 301: Determine whether to start resource collaborative processing for the first data center.

[0082] In the embodiment of the present disclosure, before determining whether to start resource collaborative processing for the first data center, the central network management may also determine whether network elements with the same functions are monitored in different data centers; if it is monitored that the first data center and multiple data centers include network elements with the same functions, it is determined whether to start resource collaborative processing for the first data center.

[0083] For example, the target area monitored by the central network management includes four data centers, namely Data Center 1, Data Center 2, Data Center 3 and Data Center 4. When it is determined that Data Center 1, Data Center 3 and Data Center 4 all include UPF, the process of whether to start resource collaborative processing can be executed.

[0084] In other words, in the disclosed embodiment, the central network management needs to first determine whether there are resources that can be coordinated. When it is determined that there are resources that can be coordinated or scheduled, it determines which data center needs to schedule the resources and how to schedule them specifically.

[0085] In the embodiment of the present disclosure, when the central network management determines whether to start resource collaborative processing for the first data center, the following steps may be adopted but are not limited to:

[0086] Step A: Determine the service parameter information of the first data center.

[0087] In the embodiment of the present disclosure, the central network management may determine the service parameter information of the first data center. Optionally, the service parameter information includes at least one of service complexity, the number of services to be executed, and the number of new services.

[0088] Step B: Determine whether to start resource collaborative processing for the first data center based on the business parameter information.

[0089] In a possible implementation, the central network management may determine whether to start resource collaborative processing for the first data center based on a matching result between the service parameter information and a preset range.

[0090] In this exemplary embodiment, if the business parameter information of the first data center is business complexity, the preset range is a complexity range set according to the actual business complexity. For example, if the business complexity of the first data center is 75, and the preset range indicating the start of resource collaborative processing is greater than 70, it is determined that the regional business of the first data center is relatively complex, and thus it is determined that resource collaborative processing is started for the first data center.

[0091] In this exemplary embodiment, if the service parameter information of the first data center is the number of services to be executed, the preset range is a number range set according to the actual number of services to be executed. For example, if the number of services to be executed of the first data center is 300, and the preset range indicating the start of resource collaborative processing is greater than 270, it is determined that the number of regional services of the first data center is large, and thus it is determined that resource collaborative processing is started for the first data center.

[0092] In this exemplary embodiment, if the business parameter information of the first data center is the number of new businesses, the preset range is a number range set according to the actual number of new businesses. For example, if the number of new businesses of the first data center is 100, and the preset range indicating the start of resource collaborative processing is greater than 60, it is determined that the first data center corresponds to an emerging business area with a large number of young people, and thus it is determined that resource collaborative processing is started for the first data center.

[0093] In this exemplary embodiment, if the business parameter information of the first data center includes more than two parameter information, it can be comprehensively determined whether to start resource collaborative processing for the first data center based on the matching results corresponding to the respective parameter information.

[0094] For example, if the business parameter information of the first data center is business complexity and the number of new businesses, and the preset range includes a first sub-preset range and a second sub-preset range, and the first sub-preset range is a range corresponding to the business complexity, and the second sub-preset range is a range corresponding to the number of new businesses, it is possible to comprehensively determine whether to start resource collaborative processing for the first data center based on the first matching result of the business complexity and the first sub-preset range, and the second matching result of the number of new businesses and the second sub-preset range. Optionally, if any one of the first matching result and the second matching result indicates to start resource collaborative processing, then resource collaborative processing is started; or if both the first matching result and the second matching result indicate to start resource collaborative processing, then resource collaborative processing is started; or, a new matching degree value may be determined based on the first matching result and the second matching result, and whether to start resource collaborative processing is determined based on the matching degree value. This is not limited in the embodiments of the present disclosure.

[0095] In a possible implementation, the central network management may determine whether to start resource collaborative processing for the first data center based on a comparison result of the service parameter information with the service parameters of other data centers.

[0096] In this exemplary embodiment, if the service parameter information of the first data center includes single parameter information, it can be directly determined whether to start resource collaborative processing for the first data center according to the comparison result.

[0097] For example, if the business parameter information of the first data center is business complexity and is 65, the target area includes three network elements with the same functions as the first data center, namely the third data center, the fourth data center and the fifth data center, and the business complexity of the third data center is 10, the business complexity of the fourth data center is 17, and the business complexity of the fifth data center is 39. Obviously, it is determined that the business complexity of the first data center is the highest, that is, the regional business of the first data center is more complex, and thus it is determined to start resource collaborative processing for the first data center.

[0098] For another example, if the business parameter information of the first data center is the number of pending businesses and it is 280, the target area includes two network elements with the same functions as the first data center, namely the seventh data center and the eighth data center, and the number of pending businesses of the seventh data center is 140, and the number of pending businesses of the eighth data center is 69. Obviously, it is determined that the first data center has the largest number of pending businesses, and thus it is determined to start resource collaborative processing for the first data center.

[0099] For another example, if the business parameter information of the first data center is the number of new businesses and it is 61, the target area includes two network elements with the same functions as the first data center, namely the third data center and the ninth data center, and the number of new businesses of the third data center is 10, and the number of new businesses of the ninth data center is 6. Obviously, it is determined that the first data center has the largest number of new businesses, and it is determined that the first data center corresponds to an emerging business area with more young people, thereby determining to start resource collaborative processing for the first data center.

[0100] In this exemplary embodiment, if the business parameter information of the first data center includes more than two parameter information, it can be comprehensively determined whether to start resource collaborative processing for the first data center based on the comparison results corresponding to each parameter information.

[0101] For example, if the business parameter information of the first data center is: business complexity is 78, and the number of new services is 43, the target area includes 3 network elements with the same functions as the first data center, namely the third data center, the fourth data center and the fifth data center, and the business complexity of the third data center is 10, and the number of new services is 9; the business complexity of the fourth data center is 17, and the number of new services is 6; and the business complexity of the fifth data center is 39, and the number of new services is 43. Obviously, although the number of new services of the first data center is the same as that of the fifth data center, the regional business of the first data center is more complex. Therefore, based on comprehensive considerations, resource collaborative processing can be initiated for the first data center.

[0102] Step 302: When it is determined to start resource collaborative processing for the first data center, a functional network manager is deployed to perform resource collaborative processing on the first data center, so that the functional network manager integrates the collaborative resources provided by the second data center of the network element having the same functions as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center.

[0103] In the disclosed embodiment, if the central network manager determines to start resource collaborative processing for the first data center, the first network manager that manages the first network element is determined; the first network element is a network element that includes the same functions as the first data center and other data centers; it is determined whether the first network manager can perform resource collaborative processing; when it is determined that the first network manager can perform resource collaborative processing, the first network manager is used as the functional network manager that performs resource collaborative processing for the first data center; when it is determined that the first network manager cannot perform resource collaborative processing, a new network element network manager is built as the functional network manager that performs resource collaborative processing for the first data center. It can be seen that in the disclosed embodiment, the central network manager can instruct the operator that the functional network manager needs to be deployed in the center, and obtain the corresponding IP information and port number of the functional network manager.

[0104] In the disclosed embodiment, the central network management can simultaneously instruct the monitored data centers to report collaborative resources. That is, the central network management can send indication information for reporting collaborative resources to the second data centers respectively; wherein each second data center converts the internal identifier indicating the collaborative resource into an external identifier, so that the first data center can search for the corresponding collaborative resource based on the unique external identifier and the external identifier. Among them, the second data center can include a receiving / analysis module, an identifier conversion module and an output module. Among them, the receiving / analysis module is used for instructions from the central network management; the conversion module is used to convert the identifier of the internal resource into an external identifier when deciding to output the corresponding resource. Of course, the conversion module can also convert the external identifier of the resource into an internal identifier; the output module is used to send the converted resource identifier to the functional network management indicated by the central network management.

[0105] In the embodiment of the present disclosure, when any data center in the second data center needs resource coordination, the corresponding collaborative resources can also be found based on the unique external identifier, thereby realizing resource scheduling across data centers.

[0106] In the disclosed embodiment, the upper-level network management, i.e., the central network management, is used for monitoring. When network elements with the same attributes are found, it is further determined whether the functions of the network elements in the area under its jurisdiction need to be coordinated. If necessary, the relevant DC is instructed to report resources to the designated EMS. The EMS completes the software updates, IP and port allocation, etc. of the corresponding VNFs and CNFs. Then, the DC obtains the corresponding resources based on the unique external identifier corresponding to the EMS, thereby realizing resource coordination.

[0107] The exemplary embodiment of the present disclosure also provides a resource coordination device. Figure 4 As shown, the resource collaboration device 400 includes the following program modules:

[0108] A determination unit 401 is used to determine whether to start resource collaborative processing for the first data center;

[0109] The collaboration unit 402 is used to deploy a functional network manager that performs resource collaborative processing on the first data center when it is determined that resource collaborative processing is to be initiated on the first data center, so that the functional network manager integrates the collaborative resources provided by the second data center of the network element having the same function as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center.

[0110] In one implementation, before determining whether to start resource collaborative processing for the first data center, the determining unit 401 is further configured to:

[0111] Determine whether network elements with the same functions are monitored in different data centers;

[0112] If it is monitored that the first data center and multiple data centers include network elements with the same functions, it is determined whether to start resource collaborative processing for the first data center.

[0113] In one implementation, the determining unit 401 is specifically configured to:

[0114] Determining service parameter information of the first data center;

[0115] Determine whether to start resource collaborative processing for the first data center according to the business parameter information.

[0116] In one implementation, the service parameter information includes at least one of service complexity, the number of services to be executed, and the number of new services.

[0117] In one implementation, the determining unit 401 is specifically configured to:

[0118] Determining whether to start resource collaborative processing for the first data center according to a matching result between the business parameter information and a preset range;

[0119] Or, based on a comparison result between the business parameter information and the business parameters of other data centers, it is determined whether to start resource collaborative processing for the first data center.

[0120] In one embodiment, the device further includes a sending unit, configured to:

[0121] Sending indication information of reporting collaborative resources to the second data center respectively;

[0122] Each of the second data centers converts its own internal identifier indicating a collaborative resource into an external identifier, so that the first data center searches for the corresponding collaborative resource based on the unique external identifier and the external identifier.

[0123] In one implementation, the collaboration unit 402 is configured to:

[0124] Determine a first network manager that manages a first network element; the first network element is a network element having the same functions as the first data center and other data centers;

[0125] Determining whether the first network manager can perform resource collaborative processing;

[0126] When it is determined that the first network manager can perform resource collaborative processing, the first network manager is used as a functional network manager for performing resource collaborative processing on the first data center;

[0127] When it is determined that the first network manager cannot perform resource collaborative processing, a new network element network manager is established as a functional network manager that performs resource collaborative processing on the first data center.

[0128] The specific details of each part of the above-mentioned device have been described in detail in the implementation method of the method part. The undisclosed details can be found in the implementation method of the method part, so they will not be repeated here.

[0129] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the exemplary embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0130] The exemplary embodiments of the present disclosure also provide a computer program product, which includes a computer program, and when the computer program is executed by a processor, the resource coordination method is implemented.

[0131] In one embodiment, the computer program product may be a tangible product containing a computer program, such as a computer-readable storage medium storing a computer program. The readable storage medium may be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), mechanical hard disk (HDD), solid-state drive (SSD), and the like. Exemplarily, the computer program product may be implemented as a non-volatile storage medium storing a computer program, such as a read-only memory, a NAND flash memory, and the like.

[0132] In one embodiment, the computer program product may be an intangible product including a computer program. Exemplarily, the computer program product may be implemented as a virtual digital product, such as a digital file storing an executable file, an installation package, etc. of the computer program.

[0133] The code of the computer program can be written in one or more programming languages. Programming languages ​​such as C language, Java, C++, etc. The program code can be executed entirely on the user computing device, or partially on the user computing device, or as a separate software package, or partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (e.g., an Internet connection provided by an operator).

[0134] Computer programs can be carried or transmitted through electrical, magnetic, optical, electromagnetic, infrared and other signals. Electronic devices can convert signals carrying computer programs into digital signals to run computer programs. When a computer program runs on an electronic device, its code is used to enable the electronic device to execute (more specifically, it can enable the processor of the electronic device to execute) the method steps of various exemplary embodiments of the present disclosure, such as the above-mentioned resource collaboration method, which includes the following steps: Step 301: Determine whether to start resource collaborative processing for the first data center; Step 302: In the case of determining that resource collaborative processing is started for the first data center, deploy a functional network management that performs resource collaborative processing on the first data center, so that the functional network management integrates the collaborative resources provided by the second data center of the network element having the same function as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain resources of the second data center.

[0135] By implementing the above method steps through a computer program, it can be determined whether to start resource collaborative processing for the first data center; in the case of determining to start resource collaborative processing for the first data center, a functional network manager that performs resource collaborative processing on the first data center is deployed, so that the functional network manager integrates the collaborative resources provided by the second data center of the network element having the same function as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center. It can be seen that the present disclosure integrates the resources that can be used collaboratively and obtains a unique external identifier through the deployed functional network manager, so that the first data center directly obtains the resources of other data centers based on the unique external identifier, and achieves the purpose of cross-data center data acquisition resources, which is conducive to improving resource utilization and the business service quality of the first data center, and enhancing the user experience.

[0136] The exemplary embodiments of the present disclosure also provide an electronic device, which may include a processor and a memory. The memory stores executable instructions of the processor, such as a computer program. The processor executes the method steps of various exemplary embodiments of the present disclosure by executing the executable instructions.

[0137] Reference below Figure 5 , the electronic device is exemplarily described in the form of a general-purpose computing device. It should be understood that Figure 5 The electronic device 500 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0138] like Figure 5 As shown, the electronic device 500 may include: a processor 510 , a memory 520 , a bus 530 , an I / O (input / output) interface 540 , and a network adapter 550 .

[0139] The memory 520 may include a volatile memory, such as a RAM 521, a cache unit 522, and may also include a non-volatile memory, such as a ROM 523. The memory 520 may also include one or more program modules 524, such program modules 524 include but are not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or a combination thereof may include the implementation of a network environment. For example, the program module 524 may include each module in the above-mentioned device.

[0140] The processor 510 may include one or more processing units. For example, the processor 510 may include an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor and / or an NPU (Neural-Network Processing Unit), etc.

[0141] The processor 510 can be used to execute executable instructions stored in the memory 520, such as the above-mentioned resource collaboration method, which includes the following steps: Step 301: Determine whether to start resource collaborative processing for the first data center; Step 302: When it is determined that resource collaborative processing is started for the first data center, deploy a functional network manager that performs resource collaborative processing on the first data center, so that the functional network manager integrates the collaborative resources provided by the second data center of the network element having the same function as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain resources of the second data center.

[0142] By executing the above method steps through the processor 510, it can be determined whether to start resource collaborative processing for the first data center; in the case of determining to start resource collaborative processing for the first data center, a functional network management system that performs resource collaborative processing on the first data center is deployed, so that the functional network management system integrates the collaborative resources provided by the second data center of the network element having the same function as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center. It can be seen that the present disclosure integrates the resources that can be used collaboratively and obtains the unique external identifier through the deployed functional network management system, so that the first data center directly obtains the resources of other data centers based on the unique external identifier, thereby achieving the purpose of cross-data center data acquisition resources, which is conducive to improving resource utilization and the business service quality of the first data center, and enhancing the user experience.

[0143] The bus 530 is used to realize the connection between different components of the electronic device 500, and may include a data bus, an address bus, and a control bus.

[0144] The electronic device 500 can communicate with one or more external devices 600 (eg, a keyboard, a mouse, an external controller, etc.) through the I / O interface 540 .

[0145] The electronic device 500 can communicate with one or more networks through the network adapter 550. For example, the network adapter 850 can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless LAN, Bluetooth, near field communication, etc. The network adapter 550 can communicate with other modules of the electronic device 500 through the bus 530.

[0146] although Figure 5 Not shown, other hardware and / or software modules may also be provided in the electronic device 500, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0147] As can be seen from the above, the technical solution of the present disclosure can be implemented as a method, an apparatus, a system, a computer program product, a storage medium, an electronic device, etc. Those skilled in the art can understand that various aspects of the present disclosure can be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software, such as being respectively referred to as a "circuit", "module" or "system".

[0148] It should be understood that the present disclosure is not limited to the specific method steps or structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. Those skilled in the art will easily think of other embodiments based on the specific embodiments provided by the present disclosure. Therefore, the specific embodiments provided by the present disclosure are only exemplary, and the scope and spirit of the present disclosure are indicated by the claims, and any variations, uses or adaptive changes of the present disclosure should be covered, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the technical field that are not disclosed in the present disclosure.

Claims

1. A resource collaboration method, characterized in that: The method comprises: Determining whether to initiate resource collaborative processing for the first data center; When it is determined to start resource collaborative processing on the first data center, a functional network manager is deployed to perform resource collaborative processing on the first data center, so that the functional network manager integrates the collaborative resources provided by the second data center of the network elements having the same functions as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain the resources of the second data center.

2. The method according to claim 1, characterized in that Before determining whether to start resource collaborative processing for the first data center, the method further includes: Determine whether network elements with the same functions are monitored in different data centers; If it is monitored that the first data center and multiple data centers include network elements with the same functions, it is determined whether to start resource collaborative processing for the first data center.

3. The method according to claim 1, characterized in that Determining whether to start resource collaborative processing for the first data center includes: Determining service parameter information of the first data center; Determine whether to start resource collaborative processing for the first data center according to the business parameter information.

4. The method according to claim 3, characterized in that: The service parameter information includes at least one of service complexity, the number of services to be executed, and the number of new services.

5. The method according to claim 3, characterized in that: Determining whether to start resource collaborative processing for the first data center according to the business parameter information includes: Determining whether to start resource collaborative processing for the first data center according to a matching result between the business parameter information and a preset range; Or, based on the comparison result of the business parameter information with the business parameters of other data centers, it is determined whether to start resource collaborative processing for the first data center.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: Sending indication information of reporting collaborative resources to the second data center respectively; Each of the second data centers converts its own internal identifier indicating a collaborative resource into an external identifier, so that the first data center searches for the corresponding collaborative resource based on the unique external identifier and the external identifier.

7. The method according to any one of claims 1 to 5, characterized in that: In a case where it is determined to start resource collaborative processing for the first data center, deploying a functional network management for performing resource collaborative processing for the first data center includes: Determine a first network manager that manages a first network element; the first network element is a network element having the same functions as the first data center and other data centers; Determining whether the first network manager can perform resource collaborative processing; When it is determined that the first network manager can perform resource collaborative processing, the first network manager is used as a functional network manager for performing resource collaborative processing on the first data center; When it is determined that the first network manager cannot perform resource collaborative processing, a new network element network manager is established as a functional network manager that performs resource collaborative processing on the first data center.

8. A resource coordination device, characterized in that: The device comprises: A determination unit, used to determine whether to start resource collaborative processing for the first data center; A collaboration unit is used to deploy a functional network manager that performs resource collaborative processing on the first data center when it is determined that resource collaborative processing is to be initiated on the first data center, so that the functional network manager integrates collaborative resources provided by a second data center having network elements with the same functions as the first data center to obtain a unique external identifier, and the unique external identifier can be accessed by the first data center to obtain resources of the second data center.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: include: processor; A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

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