Methods, devices, electronic equipment and storage media for collaborative activation of computing resources

Abstract

This application proposes a method, apparatus, electronic device, and storage medium for the collaborative activation of computing resources. The method includes: obtaining the computing-network converged product selected by the target object on the ordering page, the business requirements set by the target object, and the attribute information of the target object; determining the target computing power requirement for each service corresponding to the computing-network converged product based on the business requirements, and determining the business preferences and configuration information of each service; matching the target computing power requirement with the status data of each available resource pool to determine candidate resource pools and the target network paths corresponding to the candidate resource pools, and determining the target resource pool from the candidate resource pools based on the configuration information and business preferences; activating the computing-network converged product in the target resource pool based on the configuration information of each service and the correlation between each service, and establishing a connection between the target object and the target resource pool through the target network path corresponding to the target resource pool. This improves the efficiency and accuracy of collaborative activation of computing resources.

Description

Technical Field

[0001] This application relates to the field of cloud computing technology, and in particular to a method, apparatus, electronic device and storage medium for the collaborative activation of computing resources. Background Technology

[0002] When a converged computing network service requires the activation of multiple computing resources to support its normal operation, the activation of each computing resource is usually done independently. Furthermore, when multiple computing resources involve common parameters, manual configuration and synchronization are required on the management platform corresponding to each resource. This results in fragmented processes, low automation, high manual activation costs, long activation cycles, and poor customer experience.

[0003] Therefore, there is an urgent need for a highly efficient method for the collaborative activation of computing network resources. Summary of the Invention

[0004] This application aims to at least partially address one of the technical problems in the related art.

[0005] Therefore, the first objective of this application is to propose a collaborative method for the activation of computing resources in order to improve the efficiency of network resource activation.

[0006] The second objective of this application is to propose a collaborative activation device for computing resources.

[0007] The third objective of this application is to propose an electronic device.

[0008] The fourth objective of this application is to provide a computer-readable storage medium.

[0009] The fifth objective of this application is to provide a computer program product.

[0010] To achieve the above objectives, the first aspect of this application proposes a method for the collaborative activation of computing resources, comprising:

[0011] The ordering page is displayed on the screen to obtain the computing network convergence product selected by the target object on the ordering page and the business requirements set by the target object, and at the same time obtain the attribute information of the target object;

[0012] Based on business needs, determine the target computing power requirement for each service corresponding to the computing-network convergence product;

[0013] Based on attribute information and / or business requirements, determine business preferences, and then determine the configuration information for each service based on these preferences.

[0014] The target computing power requirement is matched with the status data of each available resource pool to determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools. Based on the configuration information and business preferences, the target resource pool is determined from the candidate resource pools.

[0015] Based on the configuration information of each service and the relationship between each service, the computing network convergence product is activated for the target object in the target resource pool, and the connection between the target object and the target resource pool is established through the target network path corresponding to the target resource pool.

[0016] To achieve the above objectives, a second aspect of this application provides a collaborative activation device for computing resources, comprising:

[0017] The acquisition module is used to display the ordering page on the display interface to obtain the computing network convergence product selected by the target object on the ordering page and the business requirements set by the target object, and at the same time obtain the attribute information of the target object;

[0018] The first determination module is used to determine the target computing power requirement for each service corresponding to the computing network convergence product based on business needs.

[0019] The second determining module is used to determine business preferences based on attribute information and / or business requirements, so as to determine the configuration information of each service based on the business preferences;

[0020] The third determination module is used to match the target computing power requirement with the status data of each available resource pool, determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools, and determine the target resource pool from the candidate resource pools according to the configuration information and business preferences.

[0021] The activation module is used to activate the computing and network converged product for the target object in the target resource pool based on the configuration information of each service and the relationship between each service, and to establish a connection between the target object and the target resource pool through the target network path corresponding to the target resource pool.

[0022] To achieve the above objectives, a third aspect of this application provides an electronic device comprising:

[0023] At least one processor; and

[0024] A memory that is communicatively connected to at least one processor; wherein,

[0025] The memory stores instructions that can be executed by at least one processor, which enables the at least one processor to perform the methods of the above embodiments.

[0026] To achieve the above objectives, a fourth aspect of this application provides a computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to perform the method according to the above embodiments.

[0027] To achieve the above objectives, a fifth aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the methods of the above embodiments.

[0028] The collaborative activation method, apparatus, electronic device, and storage medium for computing resources provided in this application display an ordering page on a screen to obtain the computing-network converged product selected by the target object and the business requirements set by the target object. Simultaneously, after obtaining the target object's attribute information, the target computing power requirement for each service corresponding to the computing-network converged product is determined based on the business requirements. Furthermore, business preferences are determined based on the attribute information and / or business requirements, and configuration information for each service is determined accordingly. Then, the target computing power requirement is matched with the status data of each available resource pool to determine candidate resource pools and their corresponding target network paths. Based on the configuration information and business preferences, a target resource pool is determined from the candidate pools. Finally, based on the configuration information of each service and the relationships between services, the computing-network converged product is activated for the target object in the target resource pool, and a connection is established between the target object and the target resource pool through the target network path corresponding to the target resource pool. This achieves one-stop ordering and automated activation of multiple computing resources while adapting the target object's computing power resource requirements to a matching resource pool. This improves the efficiency and accuracy of collaborative activation of computing resources.

[0029] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0030] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0031] Figure 1 A flowchart illustrating a collaborative activation method for computing resources provided in an embodiment of this application;

[0032] Figure 2 A flowchart illustrating another method for collaboratively enabling computing resources provided in an embodiment of this application;

[0033] Figure 3 This is a schematic diagram of another collaborative activation device for computing resources provided in an embodiment of this application. Detailed Implementation

[0034] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0035] The following describes a method and apparatus for collaboratively enabling computing resources according to embodiments of this application, with reference to the accompanying drawings.

[0036] The collaborative activation method for computing resources in this application embodiment is executed by the collaborative activation device for computing resources (hereinafter referred to as the activation device) provided in this application embodiment. The device can be configured in computer equipment or terminal equipment to improve the efficiency of activation of computing network resources.

[0037] Figure 1 This is a flowchart illustrating a collaborative activation method for computing resources provided in an embodiment of this application.

[0038] like Figure 1 As shown, the collaborative activation method for this computing resource includes the following steps:

[0039] Step 101: Display the order page on the display interface to obtain the computing network convergence product selected by the target object on the order page and the business requirements set by the target object, and at the same time obtain the attribute information of the target object.

[0040] In this application, after the target user successfully logs in to the client corresponding to the activation device (used for user interaction and providing activation services for converged computing and network products), the client displays an ordering page on the interface. This ordering page includes available converged computing and network products for ordering. The target user can select a specific converged computing and network product and enter their business requirements for ordering that product in a preset input box on the ordering interface. After the target user clicks the order confirmation control, the client confirms the selected converged computing and network product and obtains the business requirements. Then, it sends the selected product and business requirements to the activation device. Thus, the activation device can obtain the selected product and the set business requirements from the target user.

[0041] Furthermore, the target object's attribute information can be set by the client and sent to the activation device. Alternatively, the target object's attribute information can be pre-set in the system, and then retrieved from the system.

[0042] The target object's attribute information can include customer classification (e.g., large state-owned enterprises, large private enterprises, small and medium-sized enterprises, individual businesses, etc.) and industry (e.g., finance, healthcare, power, energy, chemical industry, communications, electronics, software, information products, education, construction, food, etc.). Business requirements can include application scenarios (e.g., smart parks, smart property management, smart scenic spots, smart ports, smart factories, smart parking lots, etc.), demand (e.g., number of video surveillance points (i.e., number of video streams)), and data storage cycle. Network-compute convergence products deeply integrate technologies such as cloud computing, big data, the Internet of Things, and artificial intelligence with the network to provide more intelligent services. Examples include converged communication products and intelligent video products. Converged communication products include cloud call centers, cloud video conferencing, and cloud telephony. These products combine traditional communication technologies with cloud computing, big data, and artificial intelligence to provide more intelligent, flexible, and efficient communication services. Intelligent video products combine traditional video surveillance technologies with cloud computing, big data, and artificial intelligence to provide more intelligent, flexible, and efficient video surveillance services.

[0043] Step 102: Based on business needs, determine the target computing power requirement for each service corresponding to the computing network convergence product.

[0044] In this application, when the converged computing and network product is an intelligent video product, the intelligent video product includes video access services, video storage services, video processing services, and network transmission services. Video access, video storage, video processing, and network transmission services all require computing resources. Therefore, based on business needs, the target computing power requirement for each service corresponding to the converged computing and network product is determined, including: determining the target computing power requirement for the video access service based on the number of video streams and the bitrate corresponding to the video resolution in the business requirements; determining the target computing power requirement for the video storage service based on the number of video streams, storage period, and bitrate in the business requirements; determining the target computing power requirement for the video processing service; and determining the target computing power requirement for the network transmission service based on the number of video streams, storage period, and bitrate in the business requirements.

[0045] The process of determining the target computing power requirement for video access services based on the number of video streams and the bitrate corresponding to the video resolution in the business requirements is illustrated in the following formula:

[0046]

[0047] Where baseline is the bitrate that a single vCPU can process, rate[i] is the bitrate of the i-th video stream, and channels is the number of video streams. The bitrate that a single vCPU can process can be preset in the system.

[0048] The process of determining the target computing power requirement for video storage services based on the number of video streams, storage period, and bitrate in business needs is illustrated in the following formula:

[0049]

[0050] Where rate[i] is the bitrate of the i-th video (in kbps), channels is the number of video channels, and T is the storage period.

[0051] The process of determining the target computing power requirement for video processing services based on the number of video streams is illustrated in the following formula:

[0052]

[0053] Where P[i] is the maximum concurrency of the i-th video processing algorithm, RT[i] is the preset average response time of the i-th video processing algorithm, Benchmark[i] is the preset benchmark computing power requirement (measurable in FLOPS) for the i-th video processing algorithm, and channels is the number of algorithm channels. The video processing algorithm can be an AI algorithm.

[0054] The process of determining the target computing power requirement for network transmission based on the number of video streams, storage period, and bitrate in business needs is illustrated in the following formula:

[0055]

[0056] Where rate[i] is the bitrate of the i-th video stream (in kbps), and channels is the number of video streams. The target computing power requirement for network transmission is the total network bandwidth.

[0057] In addition, the target computing power requirement also includes the performance requirements for computing and network resources (such as initial response time and latency), which constrain the performance of the converged computing and network products. Different target computing power requirements corresponding to different attribute information can be pre-set in the system. Then, the target computing power requirement corresponding to the attribute information of the target object can be queried and determined.

[0058] Optionally, the process for determining the target computing power requirement in terms of performance can refer to the following procedure:

[0059] a) If a certain performance indicator is too high, it will not meet the needs of the target object; if it is too low, the performance process may lead to excessive costs for the target object. In this case, the target computing power requirement for that performance indicator is a specific value. This specific value can be set by the target object or pre-associated with the target object's attribute information in the system. For example, network latency, jitter, packet loss rate, etc. Assuming the target object requires a latency of 5ms, if the actual latency exceeds 5ms, it does not meet the target object's latency requirement; if the actual latency is less than 5ms, the performance is excessive for the target object. Therefore, the target computing power requirement corresponding to the latency can be determined as 5.

[0060] b. If the target resource prefers to schedule the most idle computing resources, then the target computing power requirement for performance metrics indicating idle status can be set to 0. For example, bandwidth utilization and current load can be used to determine the target computing power requirement corresponding to bandwidth utilization and current load as 0.

[0061] c. The target object tends to schedule resources from the largest / most energy-efficient / most computationally efficient resource pool or network. Therefore, the target computing power requirement for performance metrics indicating scale, energy efficiency, and computational efficiency (e.g., computing power scale, total bandwidth, energy efficiency ratio, computational efficiency ratio) can be set to infinity to indicate the maximum value for that performance metric. Alternatively, the target computing power requirement for that performance metric can be set to the maximum value of all available resource pools in the current system for that performance metric.

[0062] d. The target computing power requirement for load balancing will be determined as the average of the current load of each available resource pool.

[0063] Step 103: Determine business preferences based on attribute information and / or business requirements, and then determine the configuration information for each service based on these preferences.

[0064] The business preferences may include reliability preferences, performance preferences, cost preferences, security preferences, latency preferences, etc., and the configuration information may include service mode, device model, network access method, etc. This application does not impose any restrictions on these.

[0065] In this application, the reliability preference of the target object can be determined based on the industry to which the target object belongs. For example, if the industry to which the target object belongs is finance, energy, power, or chemical, the reliability preference of the target object can be determined as "high reliability".

[0066] Optionally, the performance preference of the target object can be determined based on the customer classification corresponding to the target object. For example, if the target object's customer classification is large state-owned enterprises, large private enterprises, etc., the performance preference of the target object can be determined as "optimal performance".

[0067] Optionally, the security preferences of the target object can be determined based on the industry to which the target object belongs. For example, if the target object's industry is finance or other industries that involve privacy data, the security preference of the target object can be determined to be "high security".

[0068] Optionally, the performance preference of the target object can be determined based on the demand in the business requirements. For example, if the number of video channels or the number of channels with intelligent processing algorithms enabled exceeds a threshold, it indicates that the target object is not price-sensitive, and the performance preference of the target object can be determined as "optimal performance".

[0069] Optionally, the price preference of the target audience can be determined based on the customer category corresponding to the target audience. For example, if the target audience's customer category is small and medium-sized state-owned enterprises, individual businesses, etc., the price preference of the target audience can be determined as "lowest cost".

[0070] In this application, after determining the target object's business preferences, the configuration information of each service in the computing power fusion product can be determined based on these preferences. For example, if the business preference is "high reliability" or "optimal performance," the service mode is determined to be dedicated mode. If the business preference is "lowest price," the service mode is determined to be shared mode.

[0071] Furthermore, device models can be determined based on performance preferences. For example, in intelligent video products, if the business preference is "optimal performance," the camera model will be determined to be the model corresponding to a high-end camera, and the processor model will be determined to be the model corresponding to a bare-metal processor (including general-purpose bare-metal, GPU bare-metal, etc.). If the business preference is "optimal performance," the camera model will be determined to be the model corresponding to a low-end camera, and the processor model will be determined to be the model corresponding to a virtual machine (including general-purpose virtual machine, GPU virtual machine, etc.) or a lightweight container (including lightweight CPU container, lightweight GPU container).

[0072] The network access method can also be determined based on performance preferences. For example, if the security preference is "high security," the network access method will be determined to be access via SPN hard slicing or OTN hard pipe. If the security preference is "low security," the network access method will be determined to be access via internet leased line or ordinary PON cloud networking leased line. If the latency preference is "short latency," the network access method will be determined to be access via 5G premium slicing or OTN hard pipe.

[0073] Optionally, SMEs may have business needs requiring "optimal performance" or "high reliability," while large private enterprises may have needs requiring "lowest price." Therefore, the business preferences corresponding to the target audience can be set via the client and sent to the activation device. Subsequently, configuration information can be determined based on the user's set business preferences to meet personalized business preference requirements.

[0074] Step 104: Match the target computing power requirement with the status data of each available resource pool to determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools. Based on the configuration information and business preferences, determine the target resource pool from the candidate resource pools.

[0075] The available resource pool refers to the deployed resource pool that is capable of providing services normally. Status data includes computing power status data and network performance data. Computing power status data includes resource quantity, performance data, and alarm data. Resource quantity includes total resources, remaining resources, and allocated resources. Performance data includes resource utilization, energy consumption, response time, and load. Alarm data includes alarm type and alarm time. Network performance data includes total bandwidth, idle bandwidth, latency, packet loss rate, and jitter.

[0076] In this application, any monitoring device can be used to monitor all devices (storage devices, servers, network devices, etc.) in each available resource pool and collect status data for each available resource pool. The activation device can interact with the detection device to obtain status data for each available resource pool.

[0077] Next, the target computing power requirement is matched with the status data of each available resource pool. If the status data of an available resource pool meets the target computing power requirement, that available resource pool is designated as a candidate resource pool. Then, a pre-defined resource pool configuration table is obtained, and the configuration information is matched with the configuration information corresponding to each candidate resource pool in the resource pool configuration table to determine the candidate resource pools that support the configuration information. Finally, among the candidate resource pools that support the configuration information, the target resource pool is determined based on business preferences. For example, if the business preference is "lowest price," then the candidate resource pool with the lowest price that supports the configuration information can be determined as the target resource pool.

[0078] Optionally, the process of matching the target computing power requirement with the status data of each available resource pool to determine candidate resource pools is as follows: First, determine the network reference point closest to the target object and measure the network performance data of the reference network path between the network reference point and each available resource pool. Then, monitor each available resource pool and obtain its computing power status data. If the network performance data corresponding to a certain reference network path and the computing power status data of the available resource pool it connects to meet the target computing power requirement, the available resource pool connected to that reference network path is determined as a candidate resource pool, and that reference network path is determined as the target network path between its corresponding candidate resource pool and the target object.

[0079] The process for determining whether the network performance data corresponding to a reference network path and the computing power status data corresponding to the available resource pool it connects to meet the target computing power requirement can be described as follows: Assuming that the network latency requirement in the target computing power requirement is no less than 5ms, if the network latency corresponding to a certain reference network path is greater than 5ms, then it is determined that the network performance data of that reference network path does not meet the target computing power requirement. Similarly, it can be determined whether the jitter and packet loss rate of the network path meet the target computing power requirement.

[0080] The process of matching the target computing power requirement with the status data of each available resource pool to determine the candidate resource pools and the target network paths corresponding to the candidate resource pools can be described in the following steps:

[0081] 1. Construct a status data matrix corresponding to each available resource pool.

[0082]

[0083] Each row in the status data matrix represents part or all of the network performance data corresponding to a reference network path between the available resource pool and the target object, as well as part or all of the computing power status data of the available resource pool.

[0084] 2. Establish the target vector I = {I1, I2, I3, ..., I...} n The target vector contains the target computing power requirements for each dimension. Furthermore, components at the same position in each row of the target vector and the state data matrix correspond to the same state data dimension or performance metric.

[0085] 3. Calculate the difference between each row vector in the state data matrix and the target vector, and obtain the difference matrix:

[0086]

[0087] That is, D ij =|P ij -Ij |

[0088] 4. Normalize the difference matrix to obtain T. ij =D ij / max{D 1j D 2j ,…,D mj},

[0089]

[0090] 5. Set up a weight matrix based on the target audience's business preferences.

[0091]

[0092] Each row of the matrix contains only one value, representing the weight of the indicator corresponding to the performance matrix P. The number of rows in the matrix corresponds to the number of columns in the performance matrix P, representing the number of indicators. The sum of all weight values ​​is 1.

[0093] If the target business prioritizes high reliability, assign higher weights to reliability-related performance metrics such as jitter and packet loss rate in the weight matrix. If the target business prioritizes optimal performance, assign higher weights to performance-related metrics such as latency.

[0094] 6. Calculate the cross product of matrix T and weight matrix W to obtain the path cost matrix.

[0095] 7. The reference network path corresponding to the minimum component in the path cost matrix is ​​determined as the target network path between the available resource pool and the target object. If the minimum component in the path cost matrix corresponding to an available resource pool is less than a preset threshold, that available resource pool is determined as a candidate resource pool.

[0096] Step 105: Based on the configuration information of each service and the relationship between each service, activate the computing network convergence product for the target object in the target resource pool, and establish a connection between the target object and the target resource pool through the target network path corresponding to the target resource pool.

[0097] In this application, the relationships between each service corresponding to the computing power fusion product can be pre-set in the system. Then, based on the configuration information of each service, instances are created in the target resource pool, and connections are established between the computing resources corresponding to each service based on the relationships between them. This enables each service corresponding to the computing power fusion product to work collaboratively. Finally, a connection is established between the target object and the target resource pool based on the target network path corresponding to the target resource pool.

[0098] For example, activating intelligent video products includes edge computing power activation, video access node deployment, video storage node deployment, camera registration, video processing algorithm application quota allocation / deployment and algorithm activation, network activation between the computing resources corresponding to video access services and video storage services (i.e., network activation between the user and the video cloud), and network activation between the computing resources corresponding to video storage services and video processing services (network activation between the video cloud and video processing algorithm applications), etc. Detailed steps are as follows:

[0099] (1) Call the capabilities opened by the cloud platform or cloud management system to create computing node instances on the target resource pool according to the device type and other information in the configuration information, such as bare metal, CPU virtual machine and GPU virtual machine.

[0100] (2) In dedicated service mode, a new VPC is created, and all newly created computing node instances are managed within the same VPC. In shared service mode, newly created computing node instances are added to the existing cluster.

[0101] (3) Newly created computing node instances are equipped with a Kubernetes agent, incorporated into the unified management of the Kubernetes cluster, and deployed with Kubernetes orchestration capabilities to provide application containers for video access, video storage, and video processing algorithm inference. Services are provided through newly created (in dedicated mode) or existing (in shared mode) service gateways. The service gateways use Kubernetes Ingress and load balancing hardware or software solutions.

[0102] (4) Based on the network access method in the configuration information, the target network path corresponding to the target resource pool is opened through the capabilities of the network management system. For example, Internet leased lines, PON cloud leased lines, PTN cloud leased lines, or 5G cloud leased lines are opened.

[0103] (5) Capability platform registration and activation. For example, registering a camera on the video cloud platform, activating a video processing algorithm on the video cloud platform (the video cloud platform pushes the stream to the video processing algorithm application), or binding a camera to the video processing algorithm application (the video processing algorithm application actively pulls the stream from the video cloud platform).

[0104] In this application, an ordering page is displayed on the interface to obtain the computing-network converged product selected by the target object and the business requirements set by the target object. Simultaneously, after obtaining the target object's attribute information, the target computing power requirement for each service corresponding to the computing-network converged product is determined based on the business requirements. Furthermore, business preferences are determined based on the attribute information and / or business requirements, and the configuration information for each service is determined accordingly. Then, the target computing power requirement is matched with the status data of each available resource pool to determine candidate resource pools and their corresponding target network paths. Based on the configuration information and business preferences, the target resource pool is determined from the candidate resource pools. Finally, based on the configuration information of each service and the relationships between services, the computing-network converged product is activated for the target object in the target resource pool, and a connection is established between the target object and the target resource pool through the target network path corresponding to the target resource pool. This achieves one-stop ordering and automated activation of multiple computing resources, while simultaneously matching the target object's computing resource requirements with a matching resource pool. This improves the efficiency and accuracy of collaborative activation of computing resources.

[0105] Figure 2 This is a flowchart illustrating a collaborative activation method for computing resources provided in an embodiment of this application.

[0106] like Figure 2 As shown, the collaborative activation method for this computing resource includes the following steps:

[0107] Step 201: Display the order page on the display interface to obtain the computing network convergence product selected by the target object on the order page and the business requirements set by the target object, and at the same time obtain the attribute information of the target object.

[0108] Step 202: Based on business needs, determine the target computing power requirement for each service corresponding to the computing network convergence product.

[0109] Step 203: Determine business preferences based on attribute information and / or business requirements, and then determine the configuration information for each service based on these preferences.

[0110] Step 204: Match the target computing power requirement with the status data of each available resource pool to determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools.

[0111] The specific implementation process of steps 201-204 in this application can be found in the detailed description of any embodiment of this application, and will not be repeated here.

[0112] Step 205: Determine the cost, reliability, and performance metrics for each candidate resource pool.

[0113] In this application, the cost per unit of computing power for each candidate resource pool can be determined in advance based on a cost calculation algorithm. For example, the cost index per unit of computing power for each candidate resource pool can be determined based on factors such as computing efficiency ratio, energy efficiency ratio, computing power specifications (e.g., CPU, GPU, container, virtual machine, bare metal, etc.), and load balancing rate. The higher the cost index, the lower the cost.

[0114] Reliability metrics for candidate resource pools can be determined based on reliability-related status data. For example, the reliability metrics of a candidate resource pool can be determined based on its alarm count, load rate, etc. The fewer the alarm counts and the lower the load rate, the higher the reliability metric.

[0115] Performance metrics for candidate resource pools can be determined based on performance-related state data. For example, performance metrics can be determined based on the response time and latency of the candidate resource pool. The shorter the response time and latency of the candidate resource pool, the higher the performance metrics.

[0116] Step 206: Based on the cost, reliability, and performance metrics of each candidate resource pool, sort them according to business preferences to determine the candidate resource pool queue.

[0117] For example, assuming the business preference is "lowest cost," each candidate resource pool can be sorted according to its cost, generating a candidate resource pool list. The earlier a candidate resource pool appears in the list, the lower its cost. Similarly, assuming the business preference is "optimal performance," each candidate resource pool can be sorted according to its performance metrics, generating a candidate resource pool list. The earlier a candidate resource pool appears in the list, the better its performance. Likewise, assuming the business preference is "high reliability," each candidate resource pool can be sorted according to its reliability metrics, generating a candidate resource pool list. The earlier a candidate resource pool appears in the list, the higher its reliability.

[0118] Assuming business preferences encompass multiple aspects such as "high reliability, optimal performance, and lowest cost," the performance, reliability, and cost metrics for each candidate resource pool can be weighted to determine a comprehensive score for each pool. Then, based on this comprehensive score, each candidate resource pool is ranked, generating a candidate resource pool list. Candidate resource pools ranking higher in this list have superior overall reliability, performance, and cost performance.

[0119] Step 207: The first candidate resource pool in the candidate resource pool queue that can support configuration information is determined as the target resource pool.

[0120] Step 208: Based on the configuration information of each service and the relationship between each service, activate the computing network convergence product for the target object in the target resource pool, and establish a connection between the target object and the target resource pool through the target network path corresponding to the target resource pool.

[0121] The specific implementation process of steps 207-208 in this application can be found in the detailed description of any embodiment of this application, and will not be repeated here.

[0122] In this application, an ordering page is displayed on the interface to obtain the computing-network converged product selected by the target object and the business requirements set by the target object. After obtaining the attribute information of the target object, the target computing power requirement for each service corresponding to the computing-network converged product is determined according to the business requirements. Based on the attribute information and / or business requirements, business preferences are determined, and the configuration information of each service is determined according to the business preferences. Then, the target computing power requirement is matched with the status data of each available resource pool to determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools. The cost indicators, reliability indicators, and performance indicators of each candidate resource pool are determined. Based on the cost indicators, reliability indicators, and performance indicators of each candidate resource pool, they are sorted according to business preferences to determine the candidate resource pool queue. The first candidate resource pool in the candidate resource pool queue that can support the configuration information is determined as the target resource pool. Then, based on the configuration information of each service and the relationship between each service, the computing-network converged product is activated for the target object in the target resource pool, and the connection between the target object and the target resource pool is established through the target network path corresponding to the target resource pool. This enables one-stop ordering and automated activation of various computing resources, while simultaneously matching the target user's computing resource needs with a suitable resource pool. This improves the efficiency and accuracy of collaborative activation of computing resources.

[0123] To implement the above embodiments, this application also proposes a collaborative activation device for computing resources.

[0124] Figure 3 This is a schematic diagram of a collaborative activation device for computing resources provided in an embodiment of this application.

[0125] like Figure 3 As shown, the collaborative activation device for computing resources includes an acquisition module 310, a first determination module 320, a second determination module 330, a third determination module 340, and an activation module 350.

[0126] The acquisition module 310 is used to display the ordering page on the display interface to obtain the computing network convergence product selected by the target object on the ordering page and the business requirements set by the target object, and at the same time obtain the attribute information of the target object;

[0127] The first determining module 320 is used to determine the target computing power requirement for each service corresponding to the computing network convergence product based on business needs.

[0128] The second determining module 330 is used to determine business preferences based on attribute information and / or business requirements, so as to determine the configuration information of each service based on the business preferences;

[0129] The third determining module 340 is used to match the target computing power requirement with the status data of each available resource pool, determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools, and determine the target resource pool from the candidate resource pools according to the configuration information and business preferences.

[0130] The activation module 350 is used to activate the computing network convergence product for the target object in the target resource pool based on the configuration information of each service and the relationship between each service, and to establish a connection between the target object and the target resource pool through the target network path corresponding to the target resource pool.

[0131] Furthermore, in one possible implementation of this application embodiment, the service preferences include reliability preferences, performance preferences, cost preferences, and security preferences, and the configuration information includes service mode, device model, and network access method.

[0132] Furthermore, in one possible implementation of this application embodiment, the third determining module 340 is used for:

[0133] Determine the cost, reliability, and performance metrics for each candidate resource pool;

[0134] Based on the cost, reliability and performance metrics of each candidate resource pool, the candidate resource pool queue is determined by sorting them according to business preferences.

[0135] The first candidate resource pool in the candidate resource pool queue that can support configuration information is determined as the target resource pool.

[0136] Furthermore, in one possible implementation of this application embodiment, when the computing network convergence product is an intelligent video product, the aforementioned first determining module 320 is used to:

[0137] Based on the number of video streams and the bitrate corresponding to the video resolution in the business requirements, determine the target computing power requirement for the video access service.

[0138] Based on the number of video streams, storage period, and bitrate in the business requirements, determine the target computing power requirement for the video storage service.

[0139] Determine the target computing power requirement for the video processing service based on the number of video streams;

[0140] Based on the number of video streams, storage period, and bitrate in the business requirements, determine the target computing power requirement for network transmission.

[0141] Furthermore, in one possible implementation of this application embodiment, the third determining module 340 is used for:

[0142] Identify the network reference point closest to the target object and measure the network performance data of the reference network path between the network reference point and each available resource pool;

[0143] Monitor each available resource pool and obtain the computing power status data of each available resource pool;

[0144] If the network performance data corresponding to any reference network path and the computing power status data corresponding to the available resource pool it connects to meet the target computing power requirement, the available resource pool connected to any reference network path is determined as a candidate resource pool, and any reference network path is determined as the target network path corresponding to the candidate resource pool it connects to.

[0145] It should be noted that the explanation of the above-mentioned method embodiment for collaborative activation of computing resources also applies to the collaborative activation device for computing resources in this embodiment, and will not be repeated here.

[0146] In this application, an ordering page is displayed on the interface to obtain the computing-network converged product selected by the target object and the business requirements set by the target object. Simultaneously, after obtaining the target object's attribute information, the target computing power requirement for each service corresponding to the computing-network converged product is determined based on the business requirements. Furthermore, business preferences are determined based on the attribute information and / or business requirements, and the configuration information for each service is determined accordingly. Then, the target computing power requirement is matched with the status data of each available resource pool to determine candidate resource pools and their corresponding target network paths. Based on the configuration information and business preferences, the target resource pool is determined from the candidate resource pools. Finally, based on the configuration information of each service and the relationships between services, the computing-network converged product is activated for the target object in the target resource pool, and a connection is established between the target object and the target resource pool through the target network path corresponding to the target resource pool. This achieves one-stop ordering and automated activation of multiple computing resources, while simultaneously matching the target object's computing resource requirements with a matching resource pool. This improves the efficiency and accuracy of collaborative activation of computing resources.

[0147] To implement the above embodiments, this application also proposes an electronic device, including: a processor and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0148] To implement the above embodiments, this application also proposes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods provided in the foregoing embodiments.

[0149] To implement the above embodiments, this application also proposes a computer program product, including a computer program that, when executed by a processor, implements the methods provided in the foregoing embodiments.

[0150] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0151] It should be noted that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold outside of these legitimate uses. Furthermore, such collection / sharing should only be conducted after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes authorization of relevant user information before the user uses the function. In addition, any necessary steps must be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0152] This application is intended to provide an implementation scheme for users to selectively prevent the use or access to their personal information data. Specifically, this application is intended to provide hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, risks can be minimized by restricting data collection and deleting data. Furthermore, where applicable, such personal information is de-identified to protect user privacy.

[0153] In the foregoing descriptions of the embodiments, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0154] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0155] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0156] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0157] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0158] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0159] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0160] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for collaboratively opening up computing resources, characterized in that, The method includes: The ordering page is displayed on the display interface to obtain the computing network convergence product selected by the target object on the ordering page and the business requirements set by the target object, and at the same time obtain the attribute information of the target object; Based on the aforementioned business requirements, determine the target computing power requirement for each service corresponding to the computing network convergence product; Based on the attribute information and / or business requirements, business preferences are determined, and configuration information for each service is determined based on the business preferences. The target computing power requirement is matched with the status data of each available resource pool to determine candidate resource pools and their corresponding target network paths. Based on the configuration information and service preferences, a target resource pool is determined from the candidate resource pools. This matching process includes: determining the network reference point closest to the target object and measuring network performance data of the reference network path between the network reference point and each available resource pool; monitoring each available resource pool and obtaining computing power status data for each pool; and determining the target computing power requirement if the network performance data of any reference network path and the computing power status data of its connected available resource pools meet the target computing power requirement, thus identifying the available resource pool connected to the reference network path as a candidate resource pool and the reference network path as the target network path for that candidate resource pool. Based on the configuration information of each service and the relationship between each service, the computing network convergence product is activated for the target object in the target resource pool, and a connection is established between the target object and the target resource pool through the target network path corresponding to the target resource pool.

2. The method as described in claim 1, characterized in that, The service preferences include reliability preferences, performance preferences, cost preferences, and security preferences, and the configuration information includes service mode, device model, and network access method.

3. The method as described in claim 1, characterized in that, The step of determining the target resource pool from the candidate resource pool based on the configuration information and the service preferences includes: Determine the cost, reliability, and performance metrics for each candidate resource pool; Based on the cost, reliability, and performance metrics of each candidate resource pool, the candidate resource pool queue is determined according to the business preferences. The first candidate resource pool in the candidate resource pool queue that can support the configuration information is determined as the target resource pool.

4. The method as described in claim 1, characterized in that, When the computing-network convergence product is an intelligent video product, determining the target computing power requirement for each service corresponding to the computing-network convergence product based on the business needs includes: Based on the number of video streams and the bitrate corresponding to the video resolution in the business requirements, determine the target computing power requirement for the video access service. Based on the number of video streams and storage period, and the bitrate in the business requirements, determine the target computing power requirement for the video storage service. The target computing power requirement for the video processing service is determined based on the number of video streams. Based on the number of video streams and storage period, and the bitrate in the business requirements, the target computing power requirement for network transmission is determined.

5. A device for collaborative activation of computing resources, characterized in that, The device includes: The acquisition module is used to display the ordering page on the display interface to acquire the computing network convergence product selected by the target object on the ordering page and the business requirements set by the target object, and at the same time acquire the attribute information of the target object; The first determining module is used to determine the target computing power requirement for each service corresponding to the computing network convergence product based on the business requirements. The second determining module is used to determine business preferences based on the attribute information and / or business requirements, so as to determine the configuration information of each service based on the business preferences; The third determining module is used to match the target computing power requirement with the status data of each available resource pool, determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools, and determine the target resource pool from the candidate resource pools according to the configuration information and the service preference; wherein, the step of matching the target computing power requirement with the status data of each available resource pool to determine the candidate resource pools in the available resource pools and the target network path corresponding to the candidate resource pools includes: determining the network reference point closest to the target object, and measuring and obtaining the network performance data of the reference network path between the network reference point and each available resource pool; monitoring each available resource pool and obtaining the computing power status data of each available resource pool; if the network performance data corresponding to any reference network path and the computing power status data corresponding to the available resource pool connected to it meet the target computing power requirement, determining the available resource pool connected to any reference network path as a candidate resource pool, and determining the any reference network path as the target network path corresponding to the candidate resource pool connected to it; The activation module is used to activate the computing network converged product for the target object in the target resource pool based on the configuration information of each service and the association between each service, and to establish a connection between the target object and the target resource pool through the target network path corresponding to the target resource pool.

6. The apparatus as claimed in claim 5, characterized in that, The service preferences include reliability preferences, performance preferences, cost preferences, and security preferences, and the configuration information includes service mode, device model, and network access method.

7. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-4.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-4.

9. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-4.

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