A service request processing method, device and terminal equipment

Abstract

The application provides a service request processing method and device and a terminal device. The method comprises the following steps: receiving a service request uploaded by a service request node in a current area to a local edge computing terminal and calculating a first delay required for the local edge computing terminal to process the service request based on a first delay calculation formula; performing an interaction attribute judgment on the local edge computing terminal, and distributing a processing object of the service request based on a judgment result of the interaction attribute; when the local edge computing terminal does not have the interaction attribute, distributing the service request to the local edge computing terminal; when the local edge computing terminal has the interaction attribute, obtaining a first service response node having an interaction relationship with the local edge computing terminal, and calculating a second delay required for each first service response node to process the service request in cooperation with the local edge computing terminal, and distributing the service request to a service response node having the minimum delay. The application can improve the service processing real-time performance and reliability of a power distribution network system.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a service request processing method, apparatus and terminal equipment. Background Technology

[0002] The distribution network is a component of the power system, responsible for further distributing electricity from the high-voltage transmission network to end users. It includes facilities such as distribution transformers, distribution lines, and switching equipment. Its main function is to step down the voltage of electricity from the high-voltage transmission network and distribute it to various users to meet their electricity needs. With the continuous advancement of the construction of new power systems, modern distribution networks increasingly adopt intelligent devices (such as smart meters, sensors, and automated switches). The distribution network has become a place where a large number of distributed power sources, energy storage devices, and flexible loads are widely connected. These devices generate a large quantity and variety of distribution network business / data, which requires processing and analysis. Most existing distribution network business processing adopts a master-slave station data processing method. Terminal equipment uses sensing devices or low-voltage carrier channels to transmit data to nearby slave stations, and the information from the slave stations is then aggregated and uploaded to the cloud computing center. In some areas, edge computing terminals are deployed on top of existing slave stations or transformer substations, turning the master station into a cloud computing center (hereinafter referred to as the cloud). Some cloud computing center business functions are offloaded to the edge computing terminals. If the edge computing terminals cannot meet the needs, the business is then uploaded to the cloud computing center for processing.

[0003] However, the aforementioned master-slave station business processing method relies on master station resources and network communication resources, which can easily lead to network congestion on the master station side and affect the master station's data processing capabilities. Secondly, under the cloud and unilateral collaborative processing method, the edge computing terminals at the slave stations only interact with the cloud computing center, resulting in a relatively singular resource utilization method and failing to fully leverage the collaborative role of intelligent devices. Therefore, providing a more advanced distributed data processing method is of great significance for improving the real-time performance and reliability of data processing in distribution network systems. Summary of the Invention

[0004] The present invention aims to provide a service request processing method, apparatus and terminal equipment to solve the above-mentioned technical problems and improve the real-time performance and reliability of service data processing in power distribution network systems.

[0005] To address the aforementioned technical problems, this invention provides a business request processing method, comprising:

[0006] Receive service requests uploaded by service request nodes in the current area to the local edge computing terminal and calculate the first delay required for the local edge computing terminal to process the service request based on the first delay calculation formula;

[0007] The interaction attributes of the local edge computing terminal are determined, and the processing object of the service request is assigned based on the result of the interaction attribute determination; wherein, the interaction attribute determination is to detect whether the local edge computing terminal has the conditions to interact with other service response nodes in the distribution network.

[0008] When the local edge computing terminal does not have interactive attributes, the service request is assigned to the local edge computing terminal so that the local edge computing terminal can process the received service request;

[0009] When the local edge computing terminal has interactive attributes, the first service response node that has an interactive relationship with the local edge computing terminal is obtained, and the second latency required for each first service response node to coordinate with the local edge computing terminal to process the service request is calculated, and the service request is allocated to the service response node with the minimum latency.

[0010] In the above solution, by introducing local edge computing terminals, business request processing tasks are distributed to various edge computing nodes, effectively reducing the load on the main station and network transmission latency, thus alleviating the pressure on the main station's network resources and improving its processing capacity. Using edge computing terminals for initial processing of business requests, combined with latency calculation formulas to optimize the request processing path, can significantly reduce overall processing latency. By allocating business requests to the most suitable processing nodes, the system can process business requests more efficiently and improve real-time response capabilities. Under the business collaborative processing architecture, the edge computing terminals of substations can dynamically select processing nodes based on actual conditions and interaction attributes. This flexible processing mechanism enables the system to cope with the processing needs of different business requests, improving the overall system's robustness and elasticity.

[0011] In one implementation, calculating the first latency required for the local edge computing terminal to process the service request based on the first latency calculation formula specifically includes:

[0012] The first delay required for the local edge computing terminal to process the service request is calculated based on a first delay calculation formula; wherein the first delay includes computation delay and communication delay, and the expression of the first delay calculation formula is:

[0013]

[0014] w 边,e =∑ a w a x a,e ;

[0015]

[0016] In the formula, t边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; c 边,e For edge computing terminal e, the amount of data transmitted u 边,e The communication delay caused by data transmission; s 边,e The computing resource capacity of edge computing terminal e; w a The computational load of service a; x a,e This represents the mapping relationship between service a and edge computing terminal e, with values ​​of 0 and 1.

[0017] In one implementation, the step of determining the interaction attributes of the local edge computing terminal specifically includes:

[0018] When a completed interactive communication network exists between the local edge computing terminal and the other service response nodes, and the service response nodes have undergone software authentication, the local edge computing terminal is determined to have interactive attributes.

[0019] In one implementation, the step of acquiring a first service response node that interacts with the local edge computing terminal and calculating a second delay for each first service response node to coordinate with the local edge computing terminal in processing the service request specifically includes:

[0020] The system monitors the operating status information of the local edge computing terminal in real time and controls the local edge computing terminal to send the operating status information to the first edge computing terminal; wherein the first edge computing terminal is an edge computing terminal in an adjacent area.

[0021] The system acquires a first service response node that interacts with the local edge computing terminal, and controls the local edge computing terminal to forward a preset percentage of the service requests to the first service response node; wherein, the first service response node includes any one or both of the cloud main station and the first edge computing terminal.

[0022] When the first service response node is the cloud master station, the second delay for the cloud master station to coordinate with the local edge computing terminal to process the service request is calculated based on the second delay calculation formula.

[0023] When the first service response node is the first edge computing terminal, the third delay for the first edge computing terminal to coordinate with the local edge computing terminal to process the service request is calculated based on the third delay calculation formula.

[0024] In one implementation, calculating the second latency for the cloud master station to coordinate with the local edge computing terminal in processing the service request based on the second latency calculation formula specifically includes:

[0025] The cloud master station calculates the first computational latency required to process a preset percentage of the service requests based on the second latency calculation formula, and the first communication latency generated by the cloud master station interacting with the local edge computing terminal; wherein, the expression of the second latency calculation formula is:

[0026]

[0027] w 云 =∑ a w a y a,云 ;

[0028]

[0029] In the formula, t 云 The first computational delay incurred when the cloud main station processes business; w 云 The total computing load of services undertaken by the cloud host site; s 云 The computing resource capacity of the cloud main site; y a,云 This refers to the mapping relationship between business 'a' and the cloud main site; w a The computational load of service a; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction; v 云,e This refers to the communication resource capacity when the cloud master station interacts with the edge computing terminal e.

[0030] The first computation delay and the first communication delay are combined to generate the first delay for the cloud master station to coordinate with the local edge computing terminal to process the service request.

[0031] In one implementation, calculating the third latency for the first edge computing terminal to collaborate with the local edge computing terminal in processing the service request based on the third latency calculation formula specifically includes:

[0032] The second communication delay generated by the interaction between the first edge computing terminal and the local edge computing terminal is calculated based on the third delay calculation formula; wherein, the expression of the third delay calculation formula is:

[0033]

[0034] In the formula, c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 The second communication delay generated during interaction; v 边,e1,e2 The communication resource capacity when edge computing terminal e1 interacts with edge computing terminal e2;

[0035] Calculate the fourth delay required by the first edge computing terminal to process a preset proportion of the service requests based on the first delay calculation formula;

[0036] The third delay is generated by combining the second communication delay and the fourth delay to allow the first edge computing terminal to coordinate with the local edge computing terminal in processing the service request.

[0037] In one implementation, when controlling the local edge computing terminal to forward a preset proportion of the service requests to the first service response node, resource constraints and latency constraints need to be applied, specifically:

[0038] A predetermined percentage of the service requests are forwarded to the first service response node; wherein the resources occupied by the predetermined percentage of service requests shall not exceed the resources allocated by the first service response node;

[0039] Resource constraints are applied to the service requests forwarded by the local edge computing terminal based on a resource constraint formula; wherein the expression of the resource constraint formula is:

[0040]

[0041] In the formula, s 边,max s 云,max These are the maximum computing resource capacities for the first edge computing terminal and the cloud master station, respectively; v 边,e1,e2，min This represents the minimum communication resource capacity between edge computing terminal e1 and edge computing terminal e2; v 云,e，min This represents the minimum communication resource capacity between the cloud master station and the edge computing terminal e.

[0042] The delay constraint is applied to the service request received by the first service response node based on the delay constraint formula; wherein, the expression of the delay constraint formula is:

[0043] t 边,e x a,e +t 云 y a,云 +c 边,e1,e2 x a,e1 x a,e2 +c 云,e x a,e y a,云 ≤T a ;

[0044] In the formula, t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; x a,e This represents the mapping relationship between service a and edge computing terminal e; t 云The first computational delay incurred when processing business on the cloud main station; y a,云 The mapping relationship between business a and the cloud main site; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 Communication delays generated during interaction; x a,e1 The mapping relationship between service a and edge computing terminal e1; x a,e2 The mapping relationship between service a and edge computing terminal e2; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during the interaction; T a Let A be the latency tolerance for business a.

[0045] In one implementation, the business request processing method further includes: optimizing the allocation of the business requests based on a preset objective function; wherein the preset objective function aims to minimize latency, and the expression of the preset objective function is:

[0046] min f(a)=f1(a)+f2(a);

[0047] f1(a)=∑ a (t 边,e +t 云 );

[0048] f2(a)=∑ a (c 边,e +c 边,e1,e2 +c 云,e );

[0049] In the formula, min f(a) is the minimum delay; f1(a) is the computation delay; f2(a) is the communication delay; t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; t 云 The first computational delay incurred when the cloud main station processes business; c 边,e For edge computing terminal e, the amount of data transmitted u 边,e Communication delays caused by data transmission; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 Communication delays generated during interaction; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction.

[0050] Secondly, this application also provides a business request processing apparatus, including: a request receiving module, an attribute judgment module, a first allocation module, and a second allocation module;

[0051] The request receiving module is used to receive service requests uploaded by service request nodes in the current area to the local edge computing terminal and calculate the first delay required by the local edge computing terminal to process the service request based on the first delay calculation formula.

[0052] The attribute judgment module is used to judge the interaction attributes of the local edge computing terminal and allocate the processing object of the service request based on the interaction attribute judgment result; wherein, the interaction attribute judgment is to detect whether the local edge computing terminal has the conditions to interact with other service response nodes in the distribution network.

[0053] When the local edge computing terminal does not have interactive attributes, the first allocation module allocates the service request to the local edge computing terminal so that the local edge computing terminal can process the received service request.

[0054] The second allocation module is used to, when the local edge computing terminal has interactive attributes, obtain the first service response node that has an interactive relationship with the local edge computing terminal, calculate the second latency required for each of the first service response nodes to coordinate with the local edge computing terminal to process the service request, and allocate the service request to the service response node with the minimum latency.

[0055] In the above solution, by introducing local edge computing terminals, business request processing tasks are distributed to various edge computing nodes, effectively reducing the load on the main station and network transmission latency, thus alleviating the pressure on the main station's network resources and improving its processing capacity. Using edge computing terminals for initial processing of business requests, combined with latency calculation formulas to optimize the request processing path, can significantly reduce overall processing latency. By allocating business requests to the most suitable processing nodes, the system can process business requests more efficiently and improve real-time response capabilities. Under the business collaborative processing architecture, the edge computing terminals of substations can dynamically select processing nodes based on actual conditions and interaction attributes. This flexible processing mechanism enables the system to cope with the processing needs of different business requests, improving the overall system's robustness and elasticity.

[0056] In one implementation, calculating the first latency required for the local edge computing terminal to process the service request based on the first latency calculation formula specifically includes:

[0057] The first delay required for the local edge computing terminal to process the service request is calculated based on a first delay calculation formula; wherein the first delay includes computation delay and communication delay, and the expression of the first delay calculation formula is:

[0058]

[0059] w 边,e =∑ a w a x a,e ;

[0060]

[0061] In the formula, t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; c 边,e For edge computing terminal e, the amount of data transmitted u 边,e The communication delay caused by data transmission; s 边,e The computing resource capacity of edge computing terminal e; w a The computational load of service a; x a,e This represents the mapping relationship between service a and edge computing terminal e, with values ​​of 0 and 1.

[0062] In one implementation, the step of determining the interaction attributes of the local edge computing terminal specifically includes:

[0063] When a completed interactive communication network exists between the local edge computing terminal and the other service response nodes, and the service response nodes have undergone software authentication, the local edge computing terminal is determined to have interactive attributes.

[0064] In one implementation, the step of acquiring a first service response node that interacts with the local edge computing terminal and calculating a second delay for each first service response node to coordinate with the local edge computing terminal in processing the service request specifically includes:

[0065] The system monitors the operating status information of the local edge computing terminal in real time and controls the local edge computing terminal to send the operating status information to the first edge computing terminal; wherein the first edge computing terminal is an edge computing terminal in an adjacent area.

[0066] The system acquires a first service response node that interacts with the local edge computing terminal, and controls the local edge computing terminal to forward a preset percentage of the service requests to the first service response node; wherein, the first service response node includes any one or both of the cloud main station and the first edge computing terminal.

[0067] When the first service response node is the cloud master station, the second delay for the cloud master station to coordinate with the local edge computing terminal to process the service request is calculated based on the second delay calculation formula.

[0068] When the first service response node is the first edge computing terminal, the third delay for the first edge computing terminal to coordinate with the local edge computing terminal to process the service request is calculated based on the third delay calculation formula.

[0069] In one implementation, calculating the second latency for the cloud master station to coordinate with the local edge computing terminal in processing the service request based on the second latency calculation formula specifically includes:

[0070] The cloud master station calculates the first computational latency required to process a preset percentage of the service requests based on the second latency calculation formula, and the first communication latency generated by the cloud master station interacting with the local edge computing terminal; wherein, the expression of the second latency calculation formula is:

[0071]

[0072] w 云 =∑ a w a y a,云 ;

[0073]

[0074] In the formula, t 云 The first computational delay incurred when the cloud main station processes business; w 云 The total computing load of services undertaken by the cloud host site; s 云 The computing resource capacity of the cloud main site; y a,云 This refers to the mapping relationship between business 'a' and the cloud main site; w a The computational load of service a; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction; v 云,e This refers to the communication resource capacity when the cloud master station interacts with the edge computing terminal e.

[0075] The first computation delay and the first communication delay are combined to generate the first delay for the cloud master station to coordinate with the local edge computing terminal to process the service request.

[0076] In one implementation, calculating the third latency for the first edge computing terminal to collaborate with the local edge computing terminal in processing the service request based on the third latency calculation formula specifically includes:

[0077] The second communication delay generated by the interaction between the first edge computing terminal and the local edge computing terminal is calculated based on the third delay calculation formula; wherein, the expression of the third delay calculation formula is:

[0078]

[0079] In the formula, c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 The second communication delay generated during interaction; v 边,e1,e2 The communication resource capacity when edge computing terminal e1 interacts with edge computing terminal e2;

[0080] Calculate the fourth delay required by the first edge computing terminal to process a preset proportion of the service requests based on the first delay calculation formula;

[0081] The third delay is generated by combining the second communication delay and the fourth delay to allow the first edge computing terminal to coordinate with the local edge computing terminal in processing the service request.

[0082] In one implementation, when controlling the local edge computing terminal to forward a preset proportion of the service requests to the first service response node, resource constraints and latency constraints need to be applied, specifically:

[0083] A predetermined percentage of the service requests are forwarded to the first service response node; wherein the resources occupied by the predetermined percentage of service requests shall not exceed the resources allocated by the first service response node;

[0084] Resource constraints are applied to the service requests forwarded by the local edge computing terminal based on a resource constraint formula; wherein the expression of the resource constraint formula is:

[0085]

[0086] In the formula, s 边,max s 云,max These are the maximum computing resource capacities for the first edge computing terminal and the cloud master station, respectively; v 边,e1,e2，min This represents the minimum communication resource capacity between edge computing terminal e1 and edge computing terminal e2; v 云,e，min This represents the minimum communication resource capacity between the cloud master station and the edge computing terminal e.

[0087] The delay constraint is applied to the service request received by the first service response node based on the delay constraint formula; wherein, the expression of the delay constraint formula is:

[0088] t 边,e x a,e +t 云 y a,云 +c 边,e1,e2 x a,e1 x a,e2 +c 云,e x a,ey a,云 ≤T a ;

[0089] In the formula, t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; x a,e This represents the mapping relationship between service a and edge computing terminal e; t 云 The first computational delay incurred when processing business on the cloud main station; y a,云 The mapping relationship between business a and the cloud main site; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 Communication delays generated during interaction; x a,e1 The mapping relationship between service a and edge computing terminal e1; x a,e2 The mapping relationship between service a and edge computing terminal e2; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during the interaction; T a Let A be the latency tolerance for business a.

[0090] In one implementation, the service request processing device further includes: optimizing the allocation of the service requests based on a preset objective function; wherein the preset objective function aims to minimize latency, and the expression of the preset objective function is:

[0091] min f(a)=f1(a)+f2(a);

[0092] f1(a)=∑ a (t 边,e +t 云 );

[0093] f2(a)=∑ a (c 边,e +c 边,e1,e2 +c 云,e );

[0094] In the formula, min f(a) is the minimum delay; f1(a) is the computation delay; f2(a) is the communication delay; t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; t 云 The first computational delay incurred when the cloud main station processes business; c 边,e For edge computing terminal e, the amount of data transmitted u 边,e Communication delays caused by data transmission; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u边,e1,e2 Communication delays generated during interaction; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction.

[0095] Thirdly, this application also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the service request method described above. Attached Figure Description

[0096] Figure 1 This is a flowchart illustrating a business request processing method provided in one embodiment of the present invention;

[0097] Figure 2 This invention provides a cloud-edge multi-entity collaborative power distribution network service processing architecture in one embodiment.

[0098] Figure 3 This is a schematic flowchart of a feasible embodiment of a business request processing method provided in one embodiment of the present invention;

[0099] Figure 4 This is a schematic diagram of a business request processing method provided in one embodiment of the present invention. Detailed Implementation

[0100] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0101] The terms "first" and "second," etc., in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes 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 such processes, methods, products, or apparatus.

[0102] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0103] First, some of the terms used in this application will be explained to facilitate understanding by those skilled in the art.

[0104] (1) Edge computing terminals: These are key components in edge computing architecture, referring to computing devices or systems that perform data processing and analysis near the data source. By processing data close to the data source, they can reduce data transmission latency, alleviate the burden on the central cloud computing platform, and provide faster response times.

[0105] Example 1

[0106] See Figure 1 , Figure 1 This is a flowchart illustrating a business request processing method according to an embodiment of the present invention. The embodiment of the present invention provides a business request processing method, including steps 101 to 104, each step being as follows:

[0107] Step 101: Receive the service request uploaded by the service request node in the current area to the local edge computing terminal and calculate the first delay required for the local edge computing terminal to process the service request based on the first delay calculation formula.

[0108] This invention provides a service request processing method that receives service requests uploaded by service request nodes within a current power distribution network area to a local edge computing terminal. The local edge computing terminal is used to handle the service requests from the service request nodes within the current area. See also... Figure 2 , Figure 2This invention provides a cloud-edge multi-entity collaborative power distribution network service processing architecture in one embodiment. In this architecture, the service request node, also known as the data source node, generates pending service data in the power distribution network, typically from power users or power equipment. Service response nodes, also called resource supply nodes, include edge computing terminals and cloud master stations. In a traditional master-slave type power distribution network service processing architecture, edge computing terminals are deployed at slave stations, and the cloud master station is deployed at the power distribution master station. The communication link serves as the data channel connecting the service request node (data source node), the edge computing terminal, and the cloud master station; data uploading and downloading are both accomplished through the communication link. Power lines are the paths for power transmission in the system, completing the power delivery. The local edge computing terminal handles the services requested by the data source nodes within its local area and is the only intelligent device interacting with the data source nodes; that is, one edge computing terminal is deployed in each area as the local edge computing terminal. Because the types and data of data source nodes differ in different areas, the types and quantities of services requested from the local edge computing terminal vary. Generally, the type of service requested by the service request node is determined based on the object monitored by the service request node. If the service request node represents a reactive power regulation device, the service request sent to the local edge computing terminal generally includes the status of the reactive power regulation device, the adjustable capacity, the voltage and current of the current node, etc. In addition, the service request node can also send service requests such as switch status, current direction, protection device action information, equipment event information, photovoltaic or wind turbine processing size, and energy storage device charging and discharging status to the service response node.

[0109] In one embodiment, calculating the first latency required for the local edge computing terminal to process the service request based on the first latency calculation formula specifically includes:

[0110] The first delay required for the local edge computing terminal to process the service request is calculated based on a first delay calculation formula; wherein the first delay includes computation delay and communication delay, and the expression of the first delay calculation formula is:

[0111]

[0112] w 边,e =∑ a w a x a,e ;

[0113]

[0114] In the formula, t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; c 边,e For edge computing terminal e, the amount of data transmitted u 边,eThe communication delay caused by data transmission; s 边,e The computing resource capacity of edge computing terminal e; w a The computational load of service a; x a,e This represents the mapping relationship between service a and edge computing terminal e, with values ​​of 0 and 1.

[0115] In this embodiment of the invention, a first delay required for a single edge computing terminal to process a service request is calculated using a first delay calculation formula; wherein, the first delay includes computation delay and communication delay. Service computation load w 边,e The size of the value is related to the type and number of services handled by the edge computing terminal e. The mapping relationship between services and edge computing terminals means that if service a is handled by the edge computing terminal e, the mapping relationship between the two is 1; if service a is not handled by the edge computing terminal e, the mapping relationship between the two is 0.

[0116] Step 102: Perform interaction attribute judgment on the local edge computing terminal, and allocate the processing object of the service request based on the interaction attribute judgment result; the interaction attribute judgment is to detect whether the local edge computing terminal has the interaction conditions with other service response nodes in the distribution network.

[0117] In one embodiment, the step of determining the interaction attributes of the local edge computing terminal specifically includes: when there is a completed interactive communication network between the local edge computing terminal and other service response nodes and the service response nodes have undergone software authentication, it is determined that the local edge computing terminal has interactive attributes.

[0118] In this invention, the processing method and processing object assigned to the business requests uploaded by the business request nodes depend on whether the local edge computing terminal has interactive attributes. The conditions for interaction between the local edge computing terminal and other business response nodes are: first, whether the two parties have established an interactive communication network; and second, whether both parties have undergone software authentication. It is essential to ensure that the network connection between the edge computing terminal and other edge terminals or the cloud master station is stable and available. This includes the physical network (such as wired or wireless connections) and network configuration (such as IP address allocation and network protocol support). The interactive communication network is used to integrate different devices and systems, enabling them to work collaboratively and share resources and information. It ensures that data can be smoothly transmitted between the edge terminal and the cloud master station, supporting data synchronization, backup, and sharing. Software authentication is used to confirm that the communication software of the local edge computing terminal and other business response nodes is authenticated and compatible. This includes API interface compatibility and data format matching. It ensures consistent data transmission and processing results between different systems, avoiding data errors due to software compatibility issues. Determining whether a local edge computing terminal is capable of interacting with other response nodes involves ensuring the stability of network connectivity and communication protocols, as well as software compatibility and security. These criteria help ensure the system functions properly, preventing service interruptions due to network or software issues; optimizing data transmission and processing to improve overall system performance and responsiveness; and preventing data leakage or tampering, protecting system and user data privacy.

[0119] Step 103: When the local edge computing terminal does not have interactive attributes, the service request is assigned to the local edge computing terminal so that the local edge computing terminal can process the received service request.

[0120] In this embodiment of the invention, if the local edge computing terminal does not have the conditions to interact with other service response nodes, the service requests uploaded by the service request node can only be processed by the local edge computing terminal, i.e., the processing method of the local edge computing terminal.

[0121] Step 104: When the local edge computing terminal has interactive attributes, obtain the first service response node that has an interactive relationship with the local edge computing terminal, calculate the second latency required for each first service response node to coordinate with the local edge computing terminal to process the service request, and allocate the service request to the service response node with the minimum latency.

[0122] In this embodiment of the invention, when the local edge computing terminal has interactive attributes, it is necessary to calculate the first delay required for the local edge computing terminal to process the service request, and the second delay generated by the local edge computing terminal coordinating the processing of the service request based on each of the first service response nodes, and select the processing object with the smaller delay to allocate the service request.

[0123] In one embodiment, the step of acquiring a first service response node that interacts with the local edge computing terminal and calculating a second latency based on each first service response node coordinating with the local edge computing terminal to process the service request specifically includes: real-time monitoring of the operating status information of the local edge computing terminal and controlling the local edge computing terminal to send the operating status information to a first edge computing terminal; wherein, the first edge computing terminal is an edge computing terminal in an adjacent region; acquiring a first service response node that interacts with the local edge computing terminal and controlling the local edge computing terminal to forward a preset percentage of the service request to the first service response node; wherein, the first service response node includes any one or both of a cloud master station and a first edge computing terminal; when the first service response node is the cloud master station, calculating the second latency of the cloud master station coordinating with the local edge computing terminal to process the service request based on a second latency calculation formula; when the first service response node is the first edge computing terminal, calculating the third latency of the first edge computing terminal coordinating with the local edge computing terminal to process the service request based on a third latency calculation formula.

[0124] In this embodiment of the invention, the operating status information of the local edge computing terminal is monitored in real time. This operating status information includes the current idle resource capacity and the terminal's operating status. The local edge computing terminal is controlled to send its own operating status information to edge computing terminals in adjacent areas, so that edge computing terminals can take over services forwarded by other edge computing terminals based on their own idle resource capacity. When the local edge computing terminal has interactive attributes, the latency required for the local edge computing terminal and each first service response node to collaboratively process service requests is calculated, and the collaborative processing scheme with the minimum latency is selected.

[0125] In one embodiment, calculating the second latency for the cloud master station to coordinate with the local edge computing terminal in processing the service request based on the second latency calculation formula specifically includes:

[0126] The cloud master station calculates the first computational latency required to process a preset percentage of the service requests based on the second latency calculation formula, and the first communication latency generated by the cloud master station interacting with the local edge computing terminal; wherein, the expression of the second latency calculation formula is:

[0127]

[0128] w 云 =∑ a w a y a,云 ;

[0129]

[0130] In the formula, t 云 The first computational delay incurred when the cloud main station processes business; w 云 The total computing load of services undertaken by the cloud host site; s 云 The computing resource capacity of the cloud main site; y a,云 This refers to the mapping relationship between business 'a' and the cloud main site; w a The computational load of service a; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction; v 云,e This refers to the communication resource capacity when the cloud master station interacts with the edge computing terminal e.

[0131] The first computation delay and the first communication delay are combined to generate a second delay for the cloud master station to coordinate with the local edge computing terminal to process the service request.

[0132] When the first service response node is the cloud master station, it is necessary to calculate the first computational latency required for the cloud master station to process the service forwarded by the local edge computing terminal. The first communication latency generated by the interaction between the local edge computing terminal and the cloud master station is used as the total latency, i.e., the second latency. Here, the mapping relationship y between service a and the cloud master station is... a,云 This refers to defining a mapping of service a to the cloud master station when service a is processed by the cloud master station. In this case, "y" a,云 =1”; If business a is not processed by the cloud main site, then “y a,云 =0".w 云 The total computing load of the services handled by the cloud master station is an additive amount. For example, if the cloud master station only processes service 1 (computing load w1) and service 2 (computing load w2), then "w..." 云 =w1+w2”; the cloud master station processes service 1 (computing load is w1), service 2 (computing load is w2), and service 3 (computing load is w3), then “w 云 =w1 + w2 + w3". The total computing load of the cloud master station can be obtained by following this logic. 云 The computing resource capacity of a cloud main site depends on multiple factors, including business needs, technical architecture, hardware resources, network bandwidth, security and reliability requirements, and cost budget, and should be determined based on the specific circumstances.

[0133] In one embodiment, calculating the third latency for the first edge computing terminal to coordinate with the local edge computing terminal in processing the service request based on the third latency calculation formula specifically includes:

[0134] The second communication delay generated by the interaction between the first edge computing terminal and the local edge computing terminal is calculated based on the third delay calculation formula; wherein, the expression of the third delay calculation formula is:

[0135]

[0136] In the formula, c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 The second communication delay generated during interaction; v 边,e1,e2 The communication resource capacity when edge computing terminal e1 interacts with edge computing terminal e2;

[0137] The fourth delay required for the first edge computing terminal to process a preset percentage of the service requests is calculated based on the first delay calculation formula; the second delay for the first edge computing terminal to coordinate with the local edge computing terminal to process the service requests is generated by combining the second communication delay and the fourth delay.

[0138] In this embodiment of the invention, the third delay calculation formula is used to calculate the communication delay generated when two edge computing terminals interact with each other, and the communication delay is equal to the data volume divided by the communication resource capacity. 边,e1,e2 The communication resource capacity is defined as the resource allocated by the edge computing terminal e1 to the service during interaction with the edge computing terminal e2, and its size is affected by the total amount of data transmitted by the edge computing terminal. Furthermore, a fourth delay is required for the first edge computing terminal to process the received service request, calculated according to the first delay calculation formula. This delay includes computation delay and communication delay. A third delay is generated by combining the second communication delay between the two edge computing terminals and the fourth delay required for the first edge computing terminal to process the service request in collaboration with the local edge computing terminal.

[0139] In one embodiment, when controlling the local edge computing terminal to forward a preset proportion of the service requests to the first service response node, resource constraints and latency constraints need to be applied, specifically:

[0140] A predetermined percentage of the service requests are forwarded to the first service response node; wherein the resources occupied by the predetermined percentage of service requests shall not exceed the resources allocated by the first service response node;

[0141] Resource constraints are applied to the service requests forwarded by the local edge computing terminal based on a resource constraint formula; wherein the expression of the resource constraint formula is:

[0142]

[0143] In the formula, s 边,max s 云,max These are the maximum computing resource capacities for the first edge computing terminal and the cloud master station, respectively; v 边,e1,e2，min This represents the minimum communication resource capacity between edge computing terminal e1 and edge computing terminal e2; v 云,e，min This represents the minimum communication resource capacity between the cloud master station and the edge computing terminal e.

[0144] The delay constraint is applied to the service request received by the first service response node based on the delay constraint formula; wherein, the expression of the delay constraint formula is:

[0145] t 边,e x a,e +t 云 y a,云 +c 边,e1,e2 x a,e1 x a,e2 +c 云,e x a,e y a,云 ≤T a ;

[0146] In the formula, t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; x a,e This represents the mapping relationship between service a and edge computing terminal e; t 云 The first computational delay incurred when processing business on the cloud main station; y a,云 The mapping relationship between business a and the cloud main site; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 Communication delays generated during interaction; x a,e1 The mapping relationship between service a and edge computing terminal e1; x a,e2 The mapping relationship between service a and edge computing terminal e2; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during the interaction; T a Let A be the latency tolerance for business a.

[0147] When using multiple themes for collaborative processing of distribution network services, certain constraints are required, including resource constraints and latency constraints. Resource constraints refer to the requirement that the computing and communication resources available for processing distribution services using edge computing terminals or cloud master stations do not exceed the resources allocated to the edge computing terminals and cloud master stations. For example, if the cloud master station interacts with the e-th edge computing terminal, and the amount of data exchanged is 10MB, then "data volume u"... 云,e =10MB”; Meanwhile, when the cloud master station interacts with the e-th edge computing terminal, the available communication resources are 100MB / s, then “communication resource capacity v” 云,e =100MB / s", then when the cloud master station and the e-th edge computing terminal interact and transmit 10MB of data, the communication latency is 0.1s. The upper limit of communication resource capacity depends on the bandwidth of the edge computing terminal. If the bandwidths of the two communicating parties are not equal, the smaller value is taken. This is because the one with larger bandwidth completes data transmission first, resulting in a smaller data transmission latency; while the one with smaller bandwidth takes longer to fully receive the data. During communication, the latency from data transmission to reception is based on the latency of complete data reception. The lower limit is generally not less than 0, but considering the actual processing latency of business operations, it is generally less than 0. The processing delay of a service (including computation delay and communication delay) can be assumed to be entirely communication delay (in this case, computational resources are infinitely large, so computational delay is infinitely small, hence the service processing delay is communication delay). This communication delay can be used to calculate the lower limit. The delay tolerance of service 'a' refers to the maximum delay that the distribution network can accept when processing services or responding to requests. This delay tolerance is crucial for ensuring the stability and efficient operation of the power system and depends on multiple factors such as service type and requirements, system architecture, network latency, system load, fault-tolerant and redundancy design, service continuity requirements, and application design.

[0148] As an optimized solution of this embodiment of the invention, the business request processing method further includes: optimizing the allocation of the business requests based on a preset objective function; wherein, the preset objective function aims to minimize latency, and the expression of the preset objective function is:

[0149] min f(a)=f1(a)+f2(a);

[0150] f1(a)=∑ a (t 边,e +t 云 );

[0151] f2(a)=∑ a (c 边,e +c 边,e1,e2 +c 云,e );

[0152] In the formula, min f(a) is the minimum delay; f1(a) is the computation delay; f2(a) is the communication delay; t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; t 云 The first computational delay incurred when the cloud main station processes business; c 边,e For edge computing terminal e, the amount of data transmitted u 边,e Communication delays caused by data transmission; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 The second communication delay generated during interaction; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction.

[0153] In this embodiment of the invention, an objective function is established with the goal of minimizing latency to optimize the allocation of service requests. This optimization considers three main aspects: First, after receiving service requests from data source nodes (i.e., service request nodes), the edge computing terminals in each region calculate the required computing resources and forward the information to other edge computing terminals. Second, the types and number of services handled by the edge computing terminals are optimized. Third, the service scheduling between the cloud master station and the edge computing terminals is optimized. The objective function is mainly divided into two parts: computation latency f1(a) and communication latency f2(a), both of which are only related to the mapping relationship between services on the edge computing terminals and the cloud master station. If the resources of the edge computing terminals are sufficient, each service can be completed by the local edge computing terminal, thus satisfying the latency constraint formula. If the resources of the edge computing terminals are insufficient, to satisfy the latency constraint formula, available resources within the power distribution network system must be called. To minimize the total processing latency of services, some communication latency can be sacrificed to achieve lower computation latency.

[0154] See Figure 3 , Figure 3 This is a schematic flowchart of a feasible embodiment of a service request processing method provided in one embodiment of the present invention. A local edge computing terminal receives service request information uploaded by a data source node in its local area, i.e., a service request node; then calculates the first latency required for the local edge computing terminal to process the service, the first latency including computation latency and communication latency; sends idle resource capacity and terminal operating status to a first edge computing terminal in an adjacent area; the local edge computing terminal decides to transfer some services to an edge computing terminal with more idle resource capacity, analyzing the reduced computation latency and increased communication latency; analyzes the increased communication latency and reduced computation latency that would occur if the services from the edge computing terminal were transferred to the cloud master station; and then selects the service scheduling result with the minimum latency based on different latency calculation results.

[0155] In this embodiment of the invention, a business request processing device is also provided, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the above-described business request processing method.

[0156] In this embodiment of the invention, a computer-readable storage medium is also provided, which includes a stored computer program, wherein the computer program controls the device where the computer-readable storage medium is located to execute the above-described business request processing method when it is running.

[0157] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a business request processing device.

[0158] The service request processing device can be a desktop computer, laptop, handheld computer, or cloud server, etc. The service request processing device may include, but is not limited to, a processor, memory, and a display. Those skilled in the art will understand that the above components are merely examples of the service request processing device and do not constitute a limitation on the device. It may include more or fewer components, or a combination of certain components, or different components. For example, the service request processing device may also include input / output devices, network access devices, buses, etc.

[0159] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the service request processing device, connecting all parts of the device through various interfaces and lines.

[0160] Memory can be used to store computer programs and / or modules. The processor, by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory, implements various functions of the multi-device access platform processing device. Memory can mainly include a program storage area and a data storage area. The program storage area can store the operating system, at least one application program required for a function (such as sound playback, text conversion, etc.); the data storage area can store data created based on the use of the mobile phone (such as audio data, text message data, etc.). Furthermore, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital cards (SD cards), flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0161] In this invention, if the business request processing module is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. Those skilled in the art can understand and implement this invention without any inventive effort.

[0162] This invention provides a business request processing method. By introducing a local edge computing terminal, business request processing tasks are distributed to various edge computing nodes, effectively reducing the load on the main station and network transmission latency, alleviating the pressure on the main station's network resources, and thus improving the main station's processing capacity. Using the edge computing terminal for initial processing of business requests, and optimizing the request processing path using a latency calculation formula, can significantly reduce overall processing latency. By allocating business requests to the most suitable processing nodes, the system can process business requests more efficiently and improve real-time response capabilities. In the business collaborative processing architecture, the edge computing terminal of the sub-station can dynamically select processing nodes based on actual conditions and interaction attributes. This flexible processing mechanism enables the system to cope with the processing needs of different business requests, improving the overall system's robustness and elasticity.

[0163] Example 2

[0164] See Figure 4 , Figure 4 This is a schematic diagram of a service request processing method provided in one embodiment of the present invention. The present invention also provides a service request processing apparatus, including: a request receiving module 201, an attribute judgment module 202, a first allocation module 203, and a second allocation module 204.

[0165] The request receiving module 201 is used to receive service requests uploaded by service request nodes in the current area to the local edge computing terminal and calculate the first delay required by the local edge computing terminal to process the service request based on the first delay calculation formula.

[0166] The attribute judgment module 202 is used to judge the interaction attributes of the local edge computing terminal and allocate the processing object of the service request based on the interaction attribute judgment result; wherein, the interaction attribute judgment is to detect whether the local edge computing terminal has the conditions for interaction with other service response nodes in the distribution network.

[0167] When the local edge computing terminal does not have interactive attributes, the first allocation module 203 allocates the service request to the local edge computing terminal so that the local edge computing terminal can process the received service request;

[0168] The second allocation module 204 is used to obtain the first service response node that has an interactive relationship with the local edge computing terminal when the local edge computing terminal has interactive attributes, calculate the second delay required for each first service response node to cooperate with the local edge computing terminal to process the service request, and allocate the service request to the service response node with the minimum delay.

[0169] In one embodiment, calculating the first latency required for the local edge computing terminal to process the service request based on the first latency calculation formula specifically includes:

[0170] The first delay required for the local edge computing terminal to process the service request is calculated based on a first delay calculation formula; wherein the first delay includes computation delay and communication delay, and the expression of the first delay calculation formula is:

[0171]

[0172] w 边,e =∑ a w a x a,e ;

[0173]

[0174] In the formula, t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; c 边,e For edge computing terminal e, the amount of data transmitted u 边,e The communication delay caused by data transmission; s 边,e The computing resource capacity of edge computing terminal e; w a The computational load of service a; x a,e This represents the mapping relationship between service a and edge computing terminal e, with values ​​of 0 and 1.

[0175] In one embodiment, the step of determining the interaction attributes of the local edge computing terminal specifically includes:

[0176] When a completed interactive communication network exists between the local edge computing terminal and the other service response nodes, and the service response nodes have undergone software authentication, the local edge computing terminal is determined to have interactive attributes.

[0177] In one embodiment, the step of acquiring a first service response node that interacts with the local edge computing terminal and calculating a second latency for each first service response node to coordinate with the local edge computing terminal in processing the service request specifically includes:

[0178] The system monitors the operating status information of the local edge computing terminal in real time and controls the local edge computing terminal to send the operating status information to the first edge computing terminal; wherein the first edge computing terminal is an edge computing terminal in an adjacent area.

[0179] The system acquires a first service response node that interacts with the local edge computing terminal, and controls the local edge computing terminal to forward a preset percentage of the service requests to the first service response node; wherein, the first service response node includes any one or both of the cloud main station and the first edge computing terminal.

[0180] When the first service response node is the cloud master station, the second delay for the cloud master station to coordinate with the local edge computing terminal to process the service request is calculated based on the second delay calculation formula.

[0181] When the first service response node is the first edge computing terminal, the third delay for the first edge computing terminal to coordinate with the local edge computing terminal to process the service request is calculated based on the third delay calculation formula.

[0182] In one embodiment, calculating the second latency for the cloud master station to coordinate with the local edge computing terminal in processing the service request based on the second latency calculation formula specifically includes:

[0183] The cloud master station calculates the first computational latency required to process a preset percentage of the service requests based on the second latency calculation formula, and the first communication latency generated by the cloud master station interacting with the local edge computing terminal; wherein, the expression of the second latency calculation formula is:

[0184]

[0185] w 云 =∑ a w a y a,云 ;

[0186]

[0187] In the formula, t 云 The first computational delay incurred when the cloud main station processes business; w 云 The total computing load of services undertaken by the cloud host site; s 云 The computing resource capacity of the cloud main site; y a,云 This refers to the mapping relationship between business 'a' and the cloud main site; w a The computational load of service a; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction; v 云,e This refers to the communication resource capacity when the cloud master station interacts with the edge computing terminal e.

[0188] The first computation delay and the first communication delay are combined to generate the first delay for the cloud master station to coordinate with the local edge computing terminal to process the service request.

[0189] In one embodiment, calculating the third latency for the first edge computing terminal to coordinate with the local edge computing terminal in processing the service request based on the third latency calculation formula specifically includes:

[0190] The second communication delay generated by the interaction between the first edge computing terminal and the local edge computing terminal is calculated based on the third delay calculation formula; wherein, the expression of the third delay calculation formula is:

[0191]

[0192] In the formula, c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 The second communication delay generated during interaction; v 边,e1,e2 The communication resource capacity when edge computing terminal e1 interacts with edge computing terminal e2;

[0193] Calculate the fourth delay required by the first edge computing terminal to process a preset proportion of the service requests based on the first delay calculation formula;

[0194] The third delay is generated by combining the second communication delay and the fourth delay to allow the first edge computing terminal to coordinate with the local edge computing terminal in processing the service request.

[0195] In one embodiment, when controlling the local edge computing terminal to forward a preset proportion of the service requests to the first service response node, resource constraints and latency constraints need to be applied, specifically:

[0196] A predetermined percentage of the service requests are forwarded to the first service response node; wherein the resources occupied by the predetermined percentage of service requests shall not exceed the resources allocated by the first service response node;

[0197] Resource constraints are applied to the service requests forwarded by the local edge computing terminal based on a resource constraint formula; wherein the expression of the resource constraint formula is:

[0198]

[0199] In the formula, s 边,max s 云,max These are the maximum computing resource capacities for the first edge computing terminal and the cloud master station, respectively; v 边,e1,e2，min This represents the minimum communication resource capacity between edge computing terminal e1 and edge computing terminal e2; v 云,e，minThis represents the minimum communication resource capacity between the cloud master station and the edge computing terminal e.

[0200] The delay constraint is applied to the service request received by the first service response node based on the delay constraint formula; wherein, the expression of the delay constraint formula is:

[0201] t 边,e x a,e +t 云 y a,云 +c 边,e1,e2 x a,e1 x a,e2 +c 云,e x a,e y a,云 ≤T a ;

[0202] In the formula, t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; x a,e This represents the mapping relationship between service a and edge computing terminal e; t 云 The first computational delay incurred when processing business on the cloud main station; y a,云 The mapping relationship between business a and the cloud main site; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 Communication delays generated during interaction; x a,e1 The mapping relationship between service a and edge computing terminal e1; x a,e2 The mapping relationship between service a and edge computing terminal e2; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during the interaction; T a Let A be the latency tolerance for business a.

[0203] In one embodiment, the service request processing device further includes: optimizing the allocation of the service requests based on a preset objective function; wherein the preset objective function aims to minimize latency, and the expression of the preset objective function is:

[0204] min f(a)=f1(a)+f2(a);

[0205] f1(a)=∑ a (t 边,e +t 云 );

[0206] f2(a)=∑ a (c 边,e +c 边,e1,e2 +c 云,e);

[0207] In the formula, min f(a) is the minimum delay; f1(a) is the computation delay; f2(a) is the communication delay; t 边,e To handle the computing load for edge computing terminals e 边,e The resulting computational delay; t 云 The first computational delay incurred when the cloud main station processes business; c 边,e For edge computing terminal e, the amount of data transmitted u 边,e Communication delays caused by data transmission; c 边,e1,e2 For edge computing terminal e1 and edge computing terminal e2, the data volume is u 边,e1,e2 Communication delays generated during interaction; c 云,e For the cloud master station and edge computing terminal e, the data volume u 云,e The first communication delay generated during interaction.

[0208] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0209] This invention provides a business request processing device. By introducing a local edge computing terminal, business request processing tasks are distributed to various edge computing nodes, effectively reducing the load on the main station and network transmission latency, alleviating the pressure on the main station's network resources, and thus improving the main station's processing capacity. Using the edge computing terminal for initial processing of business requests, and optimizing the request processing path using latency calculation formulas, can significantly reduce overall processing latency. By allocating business requests to the most suitable processing nodes, the system can process business requests more efficiently and improve real-time response capabilities. In the business collaborative processing architecture, the edge computing terminal of the sub-station can dynamically select processing nodes based on actual conditions and interaction attributes. This flexible processing mechanism enables the system to cope with the processing needs of different business requests, improving the overall system's robustness and elasticity.

[0210] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make several improvements and substitutions without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A business request processing method, characterized in that, include: Receive service requests uploaded by service request nodes in the current area to the local edge computing terminal and calculate the first delay required for the local edge computing terminal to process the service request based on the first delay calculation formula; The interaction attributes of the local edge computing terminal are determined, and the processing object of the service request is assigned based on the result of the interaction attribute determination; wherein, the interaction attribute determination is to detect whether the local edge computing terminal has the conditions to interact with other service response nodes in the distribution network. When the local edge computing terminal does not have interactive attributes, the service request is assigned to the local edge computing terminal so that the local edge computing terminal can process the received service request; When the local edge computing terminal has interactive attributes, the system obtains the first service response node that has an interactive relationship with the local edge computing terminal, calculates the second latency required for each of the first service response nodes to coordinate with the local edge computing terminal to process the service request, and allocates the service request to the service response node with the minimum latency. The step of acquiring the first service response node that has an interaction relationship with the local edge computing terminal, and calculating the second latency for each first service response node to coordinate with the local edge computing terminal in processing the service request, specifically includes: The system monitors the operating status information of the local edge computing terminal in real time and controls the local edge computing terminal to send the operating status information to the first edge computing terminal; wherein the first edge computing terminal is an edge computing terminal in an adjacent area. The system acquires a first service response node that interacts with the local edge computing terminal, and controls the local edge computing terminal to forward a preset percentage of the service requests to the first service response node; wherein, the first service response node includes any one or both of the cloud main station and the first edge computing terminal. When the first service response node is the cloud master station, the second delay for the cloud master station to coordinate with the local edge computing terminal to process the service request is calculated based on the second delay calculation formula. When the first service response node is the first edge computing terminal, the second delay for the first edge computing terminal to coordinate with the local edge computing terminal to process the service request is calculated based on the third delay calculation formula; The business request processing method further includes: The allocation of the service requests is optimized based on a preset objective function, wherein the preset objective function aims to minimize latency.

2. The business request processing method as described in claim 1, characterized in that, The calculation of the first latency required for the local edge computing terminal to process the service request based on the first latency calculation formula specifically includes: The first delay required for the local edge computing terminal to process the service request is calculated based on a first delay calculation formula; wherein the first delay includes computation delay and communication delay, and the expression of the first delay calculation formula is: ； ； ； In the formula, For edge computing terminals Processing business computing load The resulting computational delay; For edge computing terminals Processing the amount of data transmitted Communication delays caused by data transmission; For edge computing terminals The computing resource capacity; For business Calculate the load size; This represents the mapping relationship between service a and edge computing terminal e, with values ​​of 0 and 1.

3. The business request processing method as described in claim 1, characterized in that, The step of determining the interaction attributes of the local edge computing terminal specifically includes: When a completed interactive communication network exists between the local edge computing terminal and the other service response nodes, and the service response nodes have undergone software authentication, the local edge computing terminal is determined to have interactive attributes.

4. The business request processing method as described in claim 1, characterized in that, The calculation of the second latency for the cloud master station to coordinate with the local edge computing terminal in processing the service request based on the second latency calculation formula specifically includes: The cloud master station calculates the first computational latency required to process a preset percentage of the service requests based on the second latency calculation formula, and the first communication latency generated by the cloud master station interacting with the local edge computing terminal; wherein, the expression of the second latency calculation formula is: ； ； ； ； In the formula, The first computational delay incurred when processing business for the cloud main station; The total computing load of the services undertaken by the cloud host site; The computing resource capacity of the cloud main site; For business Mapping relationship between the cloud main site and the cloud main site; For business Calculate the load size; For cloud main station and edge computing terminal Perform data volume The first communication delay generated during interaction; For cloud main station and edge computing terminal The capacity of communication resources during interaction; The first computation delay and the first communication delay are combined to generate a second delay for the cloud master station to coordinate with the local edge computing terminal to process the service request.

5. The business request processing method as described in claim 1, characterized in that, The calculation of the second latency for the first edge computing terminal to coordinate with the local edge computing terminal in processing the service request based on the third latency calculation formula specifically includes: The second communication delay generated by the interaction between the first edge computing terminal and the local edge computing terminal is calculated based on the third delay calculation formula; wherein, the expression of the third delay calculation formula is: ； In the formula, For edge computing terminals With edge computing terminals The amount of data to be processed is The second communication delay generated during interaction; For edge computing terminals With edge computing terminals The capacity of communication resources during interaction; Calculate the fourth delay required by the first edge computing terminal to process a preset proportion of the service requests based on the first delay calculation formula; The second communication delay and the fourth delay are combined to generate a second delay for the first edge computing terminal to coordinate with the local edge computing terminal to process the service request.

6. The business request processing method as described in claim 1, characterized in that, When controlling the local edge computing terminal to forward a preset proportion of the service requests to the first service response node, resource constraints and latency constraints need to be applied, specifically: A predetermined percentage of the service requests are forwarded to the first service response node; wherein the resources occupied by the predetermined percentage of service requests shall not exceed the resources allocated by the first service response node; Resource constraints are applied to the service requests forwarded by the local edge computing terminal based on a resource constraint formula; wherein the expression of the resource constraint formula is: ； ； In the formula, , These are the maximum computing resource capacities of the first edge computing terminal and the cloud master station, respectively. For edge computing terminals With edge computing terminals The minimum value of communication resource capacity between them; For cloud main station and edge computing terminal The minimum value of communication resource capacity between them; v 边,e1,e2 x a,e1 x a,e2 Communication resource capacity for interaction between edge computing terminal e1 and edge e2 for service a; v 云,e x a,e y a,云 The communication resource capacity for edge computing terminal e to interact with cloud master station for business a; The delay constraint is applied to the service request received by the first service response node based on the delay constraint formula; wherein, the expression of the delay constraint formula is: ； In the formula, For edge computing terminals Processing business computing load The resulting computational delay; For business With edge computing terminals The mapping relationship between them; The first computational delay incurred when processing business for the cloud main station; For business Mapping relationship between the cloud main site and the cloud main site; For edge computing terminals With edge computing terminals The amount of data to be processed is Communication delays generated during interaction; For business With edge computing terminals The mapping relationship between them; For business With edge computing terminals The mapping relationship between them; For cloud main station and edge computing terminal Perform data volume The first communication delay generated during interaction; For business Delay tolerance.

7. A service request processing apparatus, characterized in that, include: Request receiving module, attribute judgment module, first allocation module and second allocation module; The request receiving module is used to receive service requests uploaded by service request nodes in the current area to the local edge computing terminal and calculate the first delay required by the local edge computing terminal to process the service request based on the first delay calculation formula. The attribute judgment module is used to judge the interaction attributes of the local edge computing terminal and allocate the processing object of the service request based on the interaction attribute judgment result; wherein, the interaction attribute judgment is to detect whether the local edge computing terminal has the conditions for interaction with other service response nodes in the distribution network. When the local edge computing terminal does not have interactive attributes, the first allocation module allocates the service request to the local edge computing terminal so that the local edge computing terminal can process the received service request. The second allocation module is used to, when the local edge computing terminal has interactive attributes, obtain the first service response node that has an interactive relationship with the local edge computing terminal, calculate the second latency required for each of the first service response nodes to coordinate with the local edge computing terminal to process the service request, and allocate the service request to the service response node with the minimum latency; The step of acquiring the first service response node that has an interaction relationship with the local edge computing terminal, and calculating the second latency for each first service response node to coordinate with the local edge computing terminal in processing the service request, specifically includes: The system monitors the operating status information of the local edge computing terminal in real time and controls the local edge computing terminal to send the operating status information to the first edge computing terminal; wherein the first edge computing terminal is an edge computing terminal in an adjacent area. The system acquires a first service response node that interacts with the local edge computing terminal, and controls the local edge computing terminal to forward a preset percentage of the service requests to the first service response node; wherein, the first service response node includes any one or both of the cloud main station and the first edge computing terminal. When the first service response node is the cloud master station, the second delay for the cloud master station to coordinate with the local edge computing terminal to process the service request is calculated based on the second delay calculation formula. When the first service response node is the first edge computing terminal, the second delay for the first edge computing terminal to coordinate with the local edge computing terminal to process the service request is calculated based on the third delay calculation formula; The service request processing device further includes: The allocation of the service requests is optimized based on a preset objective function, wherein the preset objective function aims to minimize latency.

8. A terminal device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement a service request processing method as described in any one of claims 1 to 6.

Images