Queue scheduling method and device, electronic equipment and storage medium

Abstract

The invention discloses a queue scheduling method and device, electronic equipment and a storage medium. Comprising the following steps: receiving a to-be-transmitted data packet corresponding to a target power system, and determining a data packet classification identifier of the to-be-transmitted data packet; determining target queue scheduling information corresponding to the to-be-transmitted data packet based on the data packet classification identifier and queue scheduling configuration information, the queue scheduling configuration information including static queue scheduling configuration information and dynamic queue scheduling configuration information, the dynamic queue scheduling configuration information comprises dynamic queue scheduling information updated based on power grid state change data of the target power system, and the target queue scheduling information comprises flow queue scheduling information, user queue scheduling information and port queue scheduling information; and executing multi-level queue scheduling through a preset scheduling algorithm based on each item of information in the target queue scheduling information, so as to transmit the to-be-transmitted data packet to a target data receiving end. The target queue scheduling information is dynamically determined, so that the accuracy and the adaptability of queue scheduling are improved.

Description

Technical Field

[0001] This invention relates to the field of smart grid technology, and in particular to a queue scheduling method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the rapid development of smart grids, the digitalization and intelligence levels of power grids are constantly improving. Power communication networks have evolved from simple data carrier networks into "neural networks" deeply coupled with the physical system of the power grid. They not only need to transmit traditional production control services (such as relay protection and stability control), but also need to carry a large number of emerging services (such as precision load control, distributed energy regulation, and advanced metering). These services place extremely high and differentiated demands on the real-time performance, reliability, and determinism of communication.

[0003] Current scheduling decisions rely entirely on the network layer QoS tags (such as service priority DSCP values) of data packets, completely isolated from the real-time operating status of the power system they serve. Once configured, service priority DSCP and user weights typically remain unchanged, failing to respond to dynamic changes in the power grid. Scheduling decisions are based entirely on communication layer information, unrelated to the real-time state of the power grid's physical system. This makes it impossible to accurately serve the core requirement of safe and stable power grid operation during grid failures, resulting in queue scheduling failing to adapt to the actual operating conditions of the power system, thus exhibiting poor accuracy and adaptability. Summary of the Invention

[0004] This invention provides a queue scheduling method, apparatus, electronic device, and storage medium to solve the problems of poor accuracy and poor adaptability in queue scheduling.

[0005] According to one aspect of the present invention, a queue scheduling method is provided, comprising:

[0006] Receive the data packets to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packets to be transmitted;

[0007] The target queue scheduling information corresponding to the data packet to be transmitted is determined based on the data packet classification identifier and queue scheduling configuration information. The queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information. The dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system. The target queue scheduling information includes flow queue scheduling information, user queue scheduling information and port queue scheduling information.

[0008] Based on stream queue scheduling information, user queue scheduling information, and port queue scheduling information, a multi-level queue scheduling is performed using a preset scheduling algorithm to transmit the data packets to be transmitted to the target data receiving end.

[0009] Optionally, determining the data packet classification identifier of the data packet to be transmitted includes: parsing the data packet to be transmitted, extracting the quintuple information corresponding to the data packet to be transmitted, hashing the quintuple information, and generating the data packet classification identifier of the data packet to be transmitted.

[0010] Optionally, determining the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and queue scheduling configuration information includes: matching the data packet classification identifier with dynamic queue scheduling configuration information and static queue scheduling configuration information to obtain valid queue scheduling information, wherein the valid queue scheduling information includes the target flow queue identifier, flow queue scheduling priority, flow queue scheduling weight, user queue scheduling weight, and target user queue identifier; determining flow queue scheduling information based on the target flow queue identifier and target user queue identifier; determining user queue scheduling information based on the flow queue scheduling priority, flow queue scheduling weight, and target user queue identifier; and determining port queue scheduling information based on the flow queue scheduling priority and user queue scheduling weight.

[0011] Optionally, the valid queue scheduling information is obtained by matching the packet classification identifier with the dynamic queue scheduling configuration information and the static queue scheduling configuration information. This includes: matching the packet classification identifier with the dynamic queue scheduling configuration information to obtain a matching result; if the matching result is successful, obtaining the first matching information from the dynamic queue scheduling configuration information, determining the valid queue scheduling information based on the first matching information, and stopping the matching of the packet classification identifier with the dynamic queue scheduling configuration information; if the matching result is unsuccessful, matching the packet classification identifier with the dynamic queue scheduling configuration information to obtain the second matching information, and determining the valid queue scheduling information based on the second matching information.

[0012] Optionally, the preset scheduling algorithm includes a first scheduling algorithm, a second scheduling algorithm, and a third scheduling algorithm. Based on flow queue scheduling information, user queue scheduling information, and port queue scheduling information, multi-level queue scheduling is performed using the preset scheduling algorithm to transmit the data packet to be transmitted to the target data receiving end. This includes: transmitting the data packet to be transmitted to the target flow queue based on the flow queue scheduling information; when the target flow queue receives the data packet to be transmitted, scheduling the target flow queue based on the flow queue scheduling information using the first scheduling algorithm to transmit the data packet to the target user queue, wherein the first scheduling algorithm is a scheduling algorithm constructed based on a first-in-first-out scheduling rule; and when the target user queue receives the data packet to be transmitted... In the case of a target port queue receiving a data packet, the system obtains user queue scheduling information and schedules the target user queue using a second scheduling algorithm based on this information. This second scheduling algorithm is a hybrid scheduling model combining strict priority scheduling and weighted fair queue scheduling. When the target port queue receives the data packet, the system obtains port queue scheduling information and schedules the target port queue using a third scheduling algorithm. This third scheduling algorithm manages the forwarding of the data packet and transmits it to the target data receiver via the physical port corresponding to the target port queue. This third scheduling algorithm is a hybrid scheduling model combining strict priority scheduling and token bucket scheduling.

[0013] Optionally, the method further includes: receiving grid state change data of the target power system, determining abnormal event information based on the grid state change data, wherein the abnormal event information includes an abnormal event type and an abnormal device identifier; obtaining a preset power topology map of the target power system, determining the abnormal event-associated device based on the abnormal event type, the abnormal device identifier, and the power topology map; obtaining a preset service flow and function mapping relationship, matching the abnormal event-associated device with the preset service flow and function mapping relationship to obtain abnormal event-associated service flow information; determining dynamic queue scheduling parameter adjustment information based on the abnormal event-associated service flow information, and updating the dynamic queue scheduling information in the dynamic queue scheduling configuration information based on the dynamic queue scheduling parameter adjustment information.

[0014] Optionally, the abnormal event-related service flow information includes the basic priority, security impact score, and timeliness impact score of at least one abnormal event-related service flow; based on the abnormal event-related service flow information, dynamic queue scheduling parameter adjustment information is determined, including: determining the dynamic functional priority score corresponding to each abnormal event-related service flow based on the basic priority, security impact score, and timeliness impact score of at least one abnormal event-related service flow; obtaining the estimated bandwidth data corresponding to each of the at least one abnormal event-related service flows, and determining the dynamic flow queue weight corresponding to each abnormal event-related service flow based on the estimated bandwidth data and the corresponding functional priority score; determining the corresponding dynamic user queue identifier and dynamic user queue weight based on the dynamic functional priority score of each abnormal event-related service flow; and constructing dynamic queue scheduling parameter adjustment information based on the dynamic functional priority score, dynamic flow queue weight, dynamic user queue identifier, and dynamic user queue weight of each abnormal event-related service flow.

[0015] According to another aspect of the present invention, a queue scheduling apparatus is provided, comprising:

[0016] The data packet classification identifier determination module is used to receive the data packet to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packet to be transmitted;

[0017] The target queue scheduling information determination module is used to determine the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and queue scheduling configuration information. The queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information. The dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system. The target queue scheduling information includes flow queue scheduling information, user queue scheduling information and port queue scheduling information.

[0018] The multi-level queue scheduling execution module is used to perform multi-level queue scheduling based on stream queue scheduling information, user queue scheduling information, and port queue scheduling information through a preset scheduling algorithm, so as to transmit the data packets to be transmitted to the target data receiving end.

[0019] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0020] At least one processor; and

[0021] A memory that is communicatively connected to at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the queue scheduling method of any embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the queue scheduling method of any embodiment of the present invention.

[0024] The technical solution of this invention involves receiving a data packet to be transmitted corresponding to a target power system and determining the data packet classification identifier of the data packet; determining the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and queue scheduling configuration information, wherein the queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information, the dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system, and the target queue scheduling information includes flow queue scheduling information, user queue scheduling information, and port queue scheduling information; and performing multi-level queue scheduling based on the flow queue scheduling information, user queue scheduling information, and port queue scheduling information using a preset scheduling algorithm to transmit the data packet to be transmitted to the target data receiving end. This solution implements end-to-end serial data packet classification and identification, dynamic and static combined scheduling configuration, and multi-level queue scheduling. It achieves differentiated management of data packets through classification and identification, adapts to the real-time operating status of the power grid through dynamic configuration, and optimizes resource allocation through multi-level scheduling. This ensures priority transmission of critical business data, improves overall transmission efficiency and resource utilization, and solves the problems of poor accuracy and adaptability of queue scheduling. It improves the accuracy and adaptability of queue scheduling, helps to enhance the stability, flexibility and adaptability of power system data transmission, and effectively supports the efficient operation of the system.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of a queue scheduling method provided in Embodiment 1 of the present invention;

[0028] Figure 2 This is a flowchart of a queue scheduling method provided in Embodiment 2 of the present invention;

[0029] Figure 3 This is a schematic diagram of the structure of a queue scheduling device provided in Embodiment 3 of the present invention;

[0030] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the queue scheduling method of this invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] Example 1

[0034] Figure 1 This is a flowchart of a queue scheduling method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations requiring queue scheduling. The method can be executed by a queue scheduling device, which can be implemented in hardware and / or software. This queue scheduling device can be configured in electronic devices such as computers and servers. Figure 1 As shown, the method includes:

[0035] S110. Receive the data packet to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packet to be transmitted.

[0036] The target power system specifically refers to the system requiring queue scheduling, encompassing power generation, transmission, transformation, and distribution. It represents a complete technological system for power production, scheduling, monitoring, and control, including various power equipment, communication networks, and data processing units. It is the source of data packet generation and the application carrier. The data packets to be transmitted can be understood as various data sets generated by the target power system during operation and needing to be transmitted between internal modules or with external systems. These include, but are not limited to, scheduling instructions, equipment operating parameters, fault monitoring information, and status feedback data. They are the core carrier for information exchange within the power system. The packet classification identifier can be understood as a standardized and unique mark representing the packet to be transmitted. It can be generated by hashing the key features of the packet (such as the IP 5-tuple) or by forming the corresponding flow key value based on the 5-tuple information according to the preset concatenation method. The obtained unique identifier or unique flow key value is determined as the packet classification identifier, which serves as the core matching basis for subsequent queue scheduling. This ensures that the packet is accurately associated with the corresponding flow queue, user queue and port queue, and ensures that different types of packets enter the appropriate scheduling link according to the preset rules. It provides basic support for hierarchical scheduling, bandwidth allocation and priority control, and avoids low transmission efficiency or insufficient core business guarantee caused by business flow confusion.

[0037] Specifically, a stable connection is established with the target power system through a standardized communication protocol. Various data packets to be transmitted generated by the system are received. Then, by parsing the header feature fields, core data content, or transmission-related information of the data packets, such as quintuple information, and combining the extracted information with a preset identifier generation method, a unique and identifiable data packet identifier is assigned to each data packet, thus completing the accurate definition of the identifier. The data packet classification identifier generation method includes, but is not limited to, hash operation, feature encoding, and information splicing methods.

[0038] In this embodiment, each data packet to be transmitted can be individually tracked and managed through a unique data packet classification identifier, providing an accurate identification basis for subsequent queue scheduling and data transmission. This not only ensures the traceability of data flow but also simplifies data differentiation and processing logic, improves the efficiency and accuracy of power system data transmission and management, and lays the foundation for differentiated processing of various types of data.

[0039] Optionally, determining the data packet classification identifier of the data packet to be transmitted includes: parsing the data packet to be transmitted, extracting the quintuple information corresponding to the data packet to be transmitted, hashing the quintuple information, and generating the data packet classification identifier of the data packet to be transmitted.

[0040] Specifically, the data packets to be transmitted are first parsed in a structured manner to extract the core information of the five-tuple, which includes the source IP address, destination IP address, source port, destination port, and transmission protocol. Then, the extracted five-tuple information is processed by a preset hash algorithm (such as MD5, SHA-1, etc.) to generate a unique and fixed-length hash value, which is used as the data packet classification identifier of the data packets to be transmitted, thus completing the accurate determination of the classification identifier.

[0041] In this embodiment, hash processing based on 5-tuple information can quickly generate unique classification identifiers, ensuring a strong correlation between the identifier and the data packet. It also simplifies the classification logic and improves the efficiency of identifier generation through standardized hash operations, providing a reliable basis for subsequent differentiated transmission, security verification, and other processing. Furthermore, the fixed length of the hash value facilitates system storage and rapid retrieval, further optimizing the data management process.

[0042] S120. Determine the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and queue scheduling configuration information. The queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information. The dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system. The target queue scheduling information includes flow queue scheduling information, user queue scheduling information and port queue scheduling information.

[0043] Queue scheduling configuration information can be specifically understood as the core configuration set used in the power system to regulate the queue scheduling behavior of data packets to be transmitted. It includes two key types of configuration information: static queue scheduling configuration information and dynamic queue scheduling configuration information. Static queue scheduling configuration information refers to fixed scheduling rules preset based on the basic business needs of the power system. These rules do not change with system operating status, providing a stable basis for queue scheduling and can be pre-stored in medium to fast storage areas. Dynamic queue scheduling configuration information refers to scheduling information updated in real time based on the grid status change data of the target power system, ensuring that the scheduling strategy can adapt to the dynamic operating needs of the system. Target queue scheduling information specifically refers to the dedicated scheduling scheme determined for queue scheduling of data packets to be transmitted. It can be determined by accurately matching the specific data packet to be transmitted with the queue scheduling configuration information based on its classification identifier. It covers specific execution parameters in three dimensions: flow queues, user queues, and port queues, and serves as the direct basis for guiding efficient data packet transmission.

[0044] Specifically, the preset queue scheduling configuration information is first retrieved, and then the determined classification identifier of the data packet to be transmitted is accurately matched with the configuration information. Combined with the scheduling information corresponding to data packets with different classification identifiers in the configuration, the specific execution parameters for adaptation are determined from three dimensions: flow queue scheduling, user queue scheduling, and port queue scheduling, and finally, the target queue scheduling information for the data packet to be transmitted is formed.

[0045] For example, a power grid status awareness module can be set up to receive real-time power grid status change data and judge the data according to preset abnormal event judgment rules to determine the abnormal event judgment result. In the event of an abnormal event, the dynamic queue scheduling information in the dynamic queue scheduling configuration information is updated. This allows for advance resource pre-allocation when the power system enters a "sub-healthy" or "alert" state, prioritizing one or more "early warning" business flows used to prevent the escalation of accidents. The specific steps for updating the dynamic queue scheduling information include:

[0046] a. Based on the preset power topology map, analyze the power grid range affected by the event, i.e., determine the equipment associated with the abnormal event. First, locate the equipment corresponding to the event in the preset power topology map based on the equipment identifier in the abnormal event information. Then, starting from this equipment, perform graph traversal according to the electrical connection relationship of the power grid. After the traversal, a list of affected power grid equipment is obtained. For example, for events such as tripping and faults, the strategy engine analysis focuses on the power outage / functional impairment range. The system will traverse downstream to find all equipment and sites that have lost power as a result. For example, the tripping of circuit breaker 302 will cause line L1 to lose power, which will in turn cause all or part of the load of substation C to lose power. Therefore, the affected range includes all or part of the load of substation C. For overload and limit-crossing events, the analysis focuses on the critical path. Along the critical path, find the power path and load path that caused the excessive load of the equipment in the preset power topology map. The related equipment on these paths are all at risk, i.e., the affected range includes the related equipment on the path.

[0047] b. Query the preset business flow and function mapping relationship to find the business flows that match the Relevant_Grid_Equipment field with the device associated with the abnormal event. For example, find all business flows related to "Substation C" and "Line L1", such as "Standard power supply switching control flow of Substation C" and "Fault recording flow of Line L1".

[0048] c. Calculate the functional priority score for the corresponding business flow: Use a utility function model to calculate a quantified priority score for each associated business flow, rather than simply using "high, medium, low" labels. It's important to note that the quantified priority score for each business flow here is the same as the priority score of the corresponding flow queue. The utility function is as follows:

[0049] ;

[0050] in, For quantified priority scores, The static base priority of the business flow can be set in advance in the static configuration information; The safety impact score is 0-10, which quantifies the importance of the business flow in mitigating the current power grid failure. Specifically, it can be obtained by querying the power function field of the business flow in the preset business flow and function mapping relationship. Business flows related to fault recovery and emergency communication have a higher safety impact score, and vice versa. The specific value can be preset, or it can be obtained by scoring after combining the results of AI model and natural language parsing. The real-time urgency is rated from 0 to 10, which is used to quantify the sensitivity of the service flow to latency. The specific rating can be mapped to the latency level required by the service flow. , These are weighting coefficients used to balance the decision-making weights of security and real-time performance.

[0051] d. Flow queue (relative weight within its user queue) weight calculation. The calculation formula is as follows:

[0052] ;

[0053] in, For the priority of business flow i, Let j be the estimated or target bandwidth requirement of service flow i, j be the index of the flow queue in the same user queue, and n be the total number of flow queues in the same user queue.

[0054] e. User queue weight calculation. First, calculate the dynamic importance score of the k-th user queue. Specifically, it is the sum of the priority scores of all business flows carried by the user queue, as shown in the following formula:

[0055] .

[0056] User queue weights were then allocated proportionally. And introduce minimum weight guarantee:

[0057] ;

[0058] Where l is the index of the user queue in the same port, and n is the total number of user queues in the same port. It has the minimum weight.

[0059] The calculated flow queue function priority score, flow queue weight, and user queue weight are then stored according to a preset message format and encapsulated into a configuration data model that network devices can recognize. For example, the preset message format could be {Flow_Key, dynamic function priority score}. Dynamic stream queue weights and {User_ID, dynamic user queue weight} Using standard network configuration protocols, the encapsulated configuration data model is sent to the control plane CPU of the target network forwarding device via a secure channel. The control plane CPU then programs the corresponding policy configuration into the data plane hardware. The specific programming process is as follows: After receiving the instruction, the control plane CPU decodes it; then, through the chip's internal bus (such as PCIe or a dedicated configuration bus), it writes the service priority score and weight into the storage unit of the corresponding flow queue in the dynamic attribute storage area; simultaneously, it writes the user queue weight value into the storage unit of the corresponding user queue. For scenarios requiring changes to flow queue affiliation, the control plane CPU dynamically updates the programmable mapping table. Thus, when the data plane chip's scheduler performs subsequent hardware scheduling, it no longer relies on fixed static attributes but on these dynamically updated values, thereby achieving real-time synchronization between the network scheduling policy and the power grid status.

[0060] In this embodiment, by combining static and dynamic queue scheduling configuration information, the basic stability of queue scheduling is ensured, and the scheduling strategy can be dynamically adjusted according to changes in the power grid status to ensure that the scheduling adapts to the real-time operation requirements of the power system. At the same time, the target queue scheduling information covers multiple scheduling dimensions, which can realize fine-grained scheduling of data packets, improve the utilization rate of transmission resources and the targeting of data transmission. Furthermore, through the accurate matching of classification identifiers and configuration information, the scheduling decision-making process can be simplified, the scheduling response time can be shortened, the priority transmission of key data can be ensured, and the reliability and efficiency of power system data transmission can be enhanced.

[0061] S130. Based on the stream queue scheduling information, user queue scheduling information, and port queue scheduling information, multi-level queue scheduling is performed using a preset scheduling algorithm to transmit the data packets to be transmitted to the target data receiving end.

[0062] Specifically, the preset scheduling algorithm can be understood as a standardized scheduling algorithm pre-set in power system data transmission. It is specifically used to prioritize, allocate transmission resources, and execute queue scheduling for data packets to be transmitted based on multi-dimensional scheduling information such as flow queues, user queues, and port queues. It includes, but is not limited to, the weighted fair queue algorithm, the priority queue algorithm, and the deficit weighted round-robin algorithm. It is used to automate and standardize the multi-level queue scheduling of data packets through fixed and configurable operation rules, avoid transmission conflicts and resource waste, and ensure the orderliness and efficiency of data transmission.

[0063] Specifically, after clarifying the three types of scheduling information corresponding to the data packets to be transmitted—the flow queue, the user queue, and the port queue—the preset scheduling algorithm is invoked to perform scheduling according to the multi-level progressive logic of flow queue → user queue → port queue. First, the data packets are imported into the corresponding flow queue and sorted by priority based on the flow queue scheduling information. Then, resources are allocated and forwarded to the target user queue based on the user queue scheduling weight. Finally, the optimal physical port is matched through the port queue scheduling rules to transmit the data packets to the target data receiving end in an orderly manner.

[0064] In this embodiment, multi-level queue scheduling, combined with multi-dimensional scheduling information and preset algorithms, can achieve fine-grained control over data packet transmission, ensuring that high-priority business data occupies resources first, and can dynamically balance the transmission load at the flow, user, and port levels, avoiding congestion in a single link and improving the overall utilization of the transmission channel. At the same time, the standardized scheduling process can reduce the risk of transmission conflicts and data loss, enhance the stability, orderliness, and efficiency of power system data transmission, and ensure the accurate delivery of various business data.

[0065] Optionally, the preset scheduling algorithm includes a first scheduling algorithm, a second scheduling algorithm, and a third scheduling algorithm. Based on flow queue scheduling information, user queue scheduling information, and port queue scheduling information, multi-level queue scheduling is performed using the preset scheduling algorithm to transmit the data packet to be transmitted to the target data receiving end. This includes: transmitting the data packet to be transmitted to the target flow queue based on the flow queue scheduling information; when the target flow queue receives the data packet to be transmitted, scheduling the target flow queue based on the flow queue scheduling information using the first scheduling algorithm to transmit the data packet to the target user queue, wherein the first scheduling algorithm is a scheduling algorithm constructed based on a first-in-first-out scheduling rule; and when the target user queue receives the data packet to be transmitted... In the case of a target port queue receiving a data packet, the system obtains user queue scheduling information and schedules the target user queue using a second scheduling algorithm based on this information. This second scheduling algorithm is a hybrid scheduling model combining strict priority scheduling and weighted fair queue scheduling. When the target port queue receives the data packet, the system obtains port queue scheduling information and schedules the target port queue using a third scheduling algorithm. This third scheduling algorithm manages the forwarding of the data packet and transmits it to the target data receiver via the physical port corresponding to the target port queue. This third scheduling algorithm is a hybrid scheduling model combining strict priority scheduling and token bucket scheduling.

[0066] Specifically, based on the scheduling requirements of different queue levels, the preset scheduling algorithm can include a first scheduling algorithm, a second scheduling algorithm, and a third scheduling algorithm. When performing multi-level queue scheduling, the data packets to be transmitted are first imported into the corresponding target flow queue according to the flow queue scheduling information. After the target flow queue receives the data packets, it schedules the queue based on the flow queue scheduling information using the first scheduling algorithm constructed according to the first-in-first-out rule, and transmits the data packets to the target user queue. After the target user queue receives the data packets to be transmitted, it schedules them using the second scheduling algorithm, which combines strict priority scheduling and weighted fair queue scheduling, in conjunction with the user queue scheduling information, and forwards the data packets to the target port queue. After the target port queue receives the data packets to be transmitted, it implements forwarding control based on the port queue scheduling information using the third scheduling algorithm, which combines strict priority scheduling and token bucket, and finally transmits the data packets accurately to the target data receiving end through the physical port corresponding to the target port queue.

[0067] In this embodiment, a three-level scheduling algorithm is used, each with its own function and interconnected. The first scheduling algorithm ensures the orderly transmission of data in the streaming queue, the second scheduling algorithm takes into account the priority and fairness of user queue scheduling, and the third scheduling algorithm ensures the priority transmission of key data in the port queue and avoids port congestion by controlling traffic through the token bucket. The multi-level scheduling collaboration realizes the fine-grained and orderly management of data packet transmission, which not only improves the utilization rate of transmission resources, but also ensures the real-time and reliability of key business data of the power system, and effectively reduces the risk of data transmission conflicts and loss.

[0068] Based on the above embodiments, the method further includes: receiving grid state change data of the target power system, determining abnormal event information based on the grid state change data, wherein the abnormal event information includes an abnormal event type and an abnormal device identifier; obtaining a preset power topology map of the target power system, determining the abnormal event associated device based on the abnormal event type, the abnormal device identifier, and the power topology map; obtaining a preset service flow and function mapping relationship, matching the abnormal event associated device with the preset service flow and function mapping relationship to obtain abnormal event associated service flow information; determining dynamic queue scheduling parameter adjustment information based on the abnormal event associated service flow information, and updating the dynamic queue scheduling information in the dynamic queue scheduling configuration information based on the dynamic queue scheduling parameter adjustment information.

[0069] Specifically, grid status change data can be understood as grid status data that can cause changes in the relative importance of various service flows on the communication network. This can be achieved by running a software-based grid status awareness module, which establishes a connection with the power system's grid monitoring system via standard power communication protocols (such as IEC 61850 MMS or GOOSE) and subscribes to its alarm and status change information. When relevant messages are received, the grid status awareness module parses, verifies, and timestamps the messages to obtain grid status change data, providing a data basis for subsequent identification of abnormal event information. Abnormal event information can be understood as a detailed record of abnormal situations such as grid faults and equipment malfunctions. The grid status change data can be judged according to preset event judgment rules to obtain corresponding abnormal event information, including but not limited to abnormal event type and abnormal equipment identifier. The preset power topology diagram refers to the pre-defined electrical connection relationships of grid equipment stored in a graph structure. Abnormal event-associated devices refer to power grid hardware devices directly related to abnormal events. Once abnormal event information is determined, these devices can be located and matched against a pre-defined power topology map to identify them. For example, for event types such as tripping or faults, the strategy engine analysis focuses on the scope of power outages / functional impairments. The system will traverse downstream along the pre-defined power topology map to find all devices and sites that have lost power as a result. Pre-defined business flow and function mapping relationships refer to pre-defined matching rules between power business processes and corresponding system functions. These can be pre-stored in high-speed memory (TCAM or SRAM). For example, the format of a data entry could be: [Flow_Key (business flow 5-tuple), Default_Priority (default priority), Assigned_Electrical_Function (specified power function), Relevant_Grid_Equipment (related grid equipment), ...]. Abnormal event-associated business flow information refers to details of relevant power business processes triggered or involved by abnormal events, which can be obtained by matching abnormal event-associated devices against the pre-defined business flow and function mapping relationships. Dynamic queue scheduling parameter adjustment information refers to the business processing queue scheduling parameter data obtained after processing information such as power grid status and abnormal situations according to a preset dynamic parameter calculation method. Together, they provide data support for power grid anomaly handling and business scheduling.

[0070] Specifically, the system can receive real-time data on changes in the power grid status of the target power system, identify anomalies through data analysis, and determine anomaly information including the type of anomaly and the identifier of the abnormal device. Then, it retrieves the system's preset power topology map, and by combining the anomaly type, the identifier of the abnormal device, and the device connection relationships in the topology map, it locates the associated devices related to the anomaly. Subsequently, it obtains the preset business flow and function mapping relationship, matches the devices associated with the anomaly with this mapping relationship, and filters out the corresponding business flow information associated with the anomaly. Finally, based on the priority, weight, and bandwidth information of the associated business flow information, it determines the dynamic queue scheduling parameter adjustment information and uses this information to update the dynamic scheduling content in the dynamic queue scheduling configuration information in real time, ensuring that the scheduling strategy adapts to the abnormal state of the power grid.

[0071] In this embodiment, anomalies are accurately captured by data on changes in power grid status and associated with relevant equipment and business flows. This enables intelligent and real-time updates of dynamic queue scheduling configurations. This ensures the priority transmission of critical business flows in abnormal scenarios and avoids the impact of anomaly propagation on data transmission efficiency. At the same time, it allows the queue scheduling strategy to dynamically adapt to the power grid operating status, improving the flexibility, reliability, and emergency response capabilities of power system data transmission.

[0072] Optionally, the abnormal event-related service flow information includes the basic priority, security impact score, and timeliness impact score of at least one abnormal event-related service flow; based on the abnormal event-related service flow information, dynamic queue scheduling parameter adjustment information is determined, including: determining the dynamic functional priority score corresponding to each abnormal event-related service flow based on the basic priority, security impact score, and timeliness impact score of at least one abnormal event-related service flow; obtaining the estimated bandwidth data corresponding to each of the at least one abnormal event-related service flows, and determining the dynamic flow queue weight corresponding to each abnormal event-related service flow based on the estimated bandwidth data and the corresponding functional priority score; determining the corresponding dynamic user queue identifier and dynamic user queue weight based on the dynamic functional priority score of each abnormal event-related service flow; and constructing dynamic queue scheduling parameter adjustment information based on the dynamic functional priority score, dynamic flow queue weight, dynamic user queue identifier, and dynamic user queue weight of each abnormal event-related service flow.

[0073] The dynamic functional priority score can be understood as representing the functional importance level of service flows associated with abnormal events. It is quantified by combining the basic priority, security impact score, and timeliness impact score of the service flows associated with abnormal events, resulting in the dynamic functional priority score, which is used to distinguish the processing priority of service flows. Estimated bandwidth data refers to the predicted network transmission bandwidth required by each service flow associated with an abnormal event, reflecting the resource consumption requirements of the service flows. Dynamic flow queue weight represents the scheduling priority ratio of different service flows in the transmission queue. It is determined by the linkage between the estimated bandwidth data and the dynamic functional priority score and is used to adjust the transmission scheduling weight of service flows. Dynamic user queue weight can be understood as representing the processing priority weight of the corresponding user queue. It is set based on the dynamic functional priority score and works in conjunction with the dynamic user queue identifier to achieve differentiated adjustment of the processing priority of different user queues. These four elements together provide core data support for dynamic queue scheduling in abnormal power grid scenarios, ensuring reasonable resource allocation and priority processing of critical services.

[0074] Specifically, the core evaluation dimensions of the business flows associated with abnormal events are first identified, namely basic priority, security impact score, and timeliness impact score. Then, the dynamic functional priority score of each business flow is calculated by integrating these three types of indicators. Next, the estimated bandwidth data of each business flow is obtained, and the dynamic flow queue weight is determined by combining the dynamic functional priority score. At the same time, the corresponding dynamic user queue identifier and weight are assigned according to the dynamic functional priority score. Finally, the dynamic functional priority score, flow queue weight, and user queue identifier and weight are integrated to form dynamic queue scheduling parameter adjustment information.

[0075] In this embodiment, the importance of business flows is quantified with multi-dimensional indicators to avoid the limitations of single priority assessment. Resource utilization efficiency is improved by linking bandwidth and priority. Furthermore, the dual weight design of dynamic user queues and flow queues can accurately adapt to the real-time and security requirements of power grid anomaly handling, making scheduling parameter adjustments more in line with actual business scenarios and ensuring priority processing of critical business flows.

[0076] Based on the above embodiments, the method further includes: when it is detected that the power grid has returned to normal or the abnormal event has been handled, clearing the "dynamic functional priority" and "dynamic flow queue weight" of the relevant flow queue, so that it resumes using static service priority and default weight; restoring the weight of the user queue to the default static configuration value, for example, issuing a new instruction to the network forwarding device to clear the priority data and / or weight data of the corresponding queues. This mechanism enables the network scheduling policy to automatically recover as the power grid status normalizes, avoiding the problem of "policy residue" where network resources are still improperly occupied after the fault is eliminated, and ensuring the system's resilience, fairness, and long-term operational stability.

[0077] In a specific embodiment, a typical architecture with separate control plane and data plane is adopted. It consists of several key hardware components, including a power grid monitoring system, a network policy controller, and network forwarding devices. Among them, the power grid monitoring system is located in the control center of the power system. Its main hardware includes SCADA / EMS servers and wide-area measurement system phasor data concentrators, which are used to collect and generate power grid state change data of power grid operation; the network policy controller can be an independent server or a high-end control board. The hardware includes a high-performance general-purpose CPU server. The policy engine software runs on the hardware. The network policy controller is responsible for receiving power grid state change data, performing scheduling policy calculations, and issuing scheduling instructions; the network forwarding devices are such as power gateways, routers, or switches. The hardware includes a control plane and a data plane. The processor corresponding to the control plane is specifically an embedded processor, which is responsible for communicating with the network policy controller and receiving and forwarding policy instructions; the data plane is a dedicated hardware chip such as ASIC / FPGA / NPU, which is used to implement high-speed queue modulation. The dedicated hardware chip contains: (1) a flow classifier and parser, which is used to parse the packet header. (2) a three-level queue hardware, which is a storage unit for physically implemented flow queues, user queues, and port queues, such as on-chip memory or cache. (3) The scheduler logic unit is a logic circuit used for hard-wired execution of scheduling algorithms such as PQ and WFQ. (4) The shaper logic unit is a hardware circuit used to implement shaping algorithms such as token bucket. (5) The policy execution memory is a fast storage area, such as TCAM or SRAM, used to store the dynamic priority mapping table and weight configuration issued by the control plane. It should be noted that the tree-like three-level queue architecture is constructed at the hardware level, and the hardware capabilities of the dedicated hardware chip of the data plane of the network forwarding device are solidified in the chip design stage, providing physical queue resources. The network policy controller receives the power grid status information in real time, calculates the dynamic function priority through the built-in policy engine, and then issues the dynamic priority to the network forwarding device. The dedicated hardware chip of the data plane of the network forwarding device implements packet classification, flow queue and user queue scheduling, as well as port queue scheduling and physical data transmission. When the data packet to be transmitted enters the inlet port of the network forwarding device, the flow classifier hardware module in the dedicated hardware chip of the data plane performs the following operations to complete the queue scheduling:

[0078] 1. Extract the five-tuple information of the data packet, including the source IP address, destination IP address, protocol number, source port number, and destination port number. Concatenate the source IP address, destination IP address, protocol number, source port number, and destination port number according to the preset concatenation rules to form a stream key value;

[0079] 2. The stream key value is sent to the Tri-State Content Addressable Memory (TCAM) for high-speed lookup. Its output includes static service tags and a preset mapping relationship between the stream key value, service tags, and stream queue identifiers. The TCAM at least pre-stores the mapping relationship between the stream key value, service tags, and stream queue identifiers.

[0080] 3. Access the dynamic attribute storage area in the chip's fast memory, where dynamic queue scheduling configuration information is stored. The classifier uses the stream key value or the stream queue identifier calculated from it as an index to query the priority and weight corresponding to the stream queue. If the query result in the dynamic attribute storage area is valid, for example, if there is a non-zero or non-default value matching the index, the scheduling priority and weight corresponding to the data packet are extracted from the query result. If the query result is invalid, for example, not configured, a default value, or not found, the priority contained in the static service tag matched by TCAM is used as the final scheduling priority, and the weight is evenly distributed among all service flows in the corresponding user queue that do not match the static queue scheduling configuration information. The final output is as follows: <target stream queue identifier, stream queue scheduling priority, stream queue scheduling weight, user queue weight, target user queue identifier>.

[0081] 4. Perform queue scheduling:

[0082] (1) Flow queue scheduling: Data packets are stored in the designated target flow queue according to the classification results. It should be noted that each flow queue is logically an independent first-in-first-out buffer. Since a flow queue usually corresponds to a business flow, the scheduling priority of all data packets in the same flow queue is the same. The flow queue itself does not have complex scheduling capabilities. Its function is to buffer and sort.

[0083] (2) User queue scheduling: This step is the key to achieving service priority and fairness within the user queue. It adopts a hybrid scheduling model of PQ and WFQ within a user queue and dynamically manages the weight of WFQ. The first level of scheduling within the user queue is strict priority scheduling. The user queue is logically divided into multiple priority groups. Subordinate flow queues are divided into different priority groups according to their corresponding final scheduling priority. The user queue scheduler first performs strict priority scheduling among these priority groups. The scheduling logic is that the scheduler always prioritizes serving the highest priority non-empty group. Only when all higher priority groups are empty will it serve the next lower priority group. In this way, the policy mapping engine can dynamically promote specific service flows (such as fault recording during a fault) to higher priority groups according to the power grid status, or even fix them to the absolute priority PQ group, ensuring that they get zero-wait scheduling opportunities within the user queue. The second level of scheduling within the user queue is Weighted Fair Queue Scheduling (WQF). When the PQ scheduler selects a specific priority group, it uses the WQF algorithm to schedule the multiple flow queues within that group, ensuring fairness and proportional bandwidth allocation. Virtual Finish Time (VFT) is a "theoretical completion time" assigned to each queue's data packets in the WQ algorithm, used to determine the forwarding order of the packets. The core of VFT is to ensure that queues with different weights "fairly" occupy bandwidth; queues with higher weights have slower VFT increases and are forwarded first. When the k-th data packet arrives in the i-th flow queue, the scheduler immediately performs the following operation:

[0084] a. Obtain the virtual time V(t). V(t) is a global variable that is updated immediately to the virtual completion time of the most recently sent data packet whenever the packet is sent. If processing the first data packet, the current actual time is used as V(t).

[0085] b. Calculate the virtual completion time of the data packet using the following formula:

[0086] ;

[0087] in, Let be the virtual completion time of the k-th packet in the i-th stream queue. The length of the package. Let be the weight of the i-th stream queue. This is the virtual completion time of the last scheduled packet in the flow queue. If this packet is the first packet in the queue, then... This item is ignored.

[0088] c. Calculate this... The value is associated with the data packet as an immutable attribute and is stored in the queue's descriptor.

[0089] Then, whenever the scheduler needs to decide "which packet to send," it simply compares the packets at the head of all queues within the group. Value, and select the one with the smallest value. The corresponding data packets are sent based on the value. When the virtual completion times of data packets from different queues conflict (i.e., the virtual completion times are exactly the same), the queue identifiers of these conflicting queues can be compared, with the queue identifier smaller taking precedence. Alternatively, random selection or round-robin selection methods can be used to determine the priority queue in case of a conflict. The overall bandwidth quota for a user queue is determined by its user weight at the port queue layer. The decision is made based on the weight of the stream queue. This determines the specific proportion that each stream queue can receive within the user's total quota.

[0090] (3)Port Queue Scheduling: The data packets after user queue scheduling are sent to the port queue layer. The port queue usually consists of multiple independent physical queues, and each queue corresponds to a scheduling priority level. The classifier of the port queue reads the priority label carried by each data packet. This label includes the effective one of the pre-calculated priority score and the static service priority, and places it into the corresponding port priority queue according to this label. That is, the priority label includes the flow queue priority. Among them, the static service priority and the port queue priority division are the same, and the data packet can be directly placed into the corresponding port queue based on the static service priority. If the priority label is the priority score, it is necessary to map the priority score to the range of port priorities through a preset mapping function, and then place the data packet into the corresponding port queue based on the mapping result. This can achieve global absolute priority scheduling across user queues, ensuring that the most critical services are not blocked by any other services at the final egress. Then, the scheduler of the port queue adopts a strict priority queue scheduling algorithm. To prevent high-priority services from completely starving low-priority services and control the total port traffic not to exceed the physical bandwidth, a port-level token bucket shaper is deployed after the port scheduler. Among them, the shaper maintains a token bucket with a depth of B (bucket capacity, unit: byte), and tokens are injected into the bucket at a fixed committed information rate R (unit: byte / second). When a data packet with a length of L bytes is ready to be sent, check the number of tokens T in the bucket. If T≥L, consume L tokens and send the data packet immediately; if T<L, the data packet must wait until enough tokens accumulate. The data packets after port queue scheduling and shaping are handed over to the media access control module and the physical layer chip of the network forwarding device. These modules follow standard protocols such as IEEE802.3 and are responsible for encapsulating the data packets into appropriate frame formats and converting them into electrical or optical signals to be sent out through the physical link. Further, when the policy engine detects through the power grid status awareness module that the power grid has returned to the normal state, for example, the fault has been isolated and the power supply has been restored, it will automatically trigger the policy rollback mechanism: send new instructions to the network forwarding device to clear the "dynamic function priority" and "dynamic flow queue weight" of the relevant flow queues, so that they resume using the static service priority and the default weight; restore the weight of the user queue to the default static configuration value. This mechanism enables the network scheduling policy to automatically recover with the normalization of the power grid status, avoiding the "policy residue" problem that network resources are still improperly occupied after the fault is eliminated, and ensuring the elasticity, fairness and long-term operation stability of the system. It completes the complete closed loop from "perception - decision - execution - feedback".

[0091] The technical solution of this embodiment receives data packets to be transmitted generated by the target power system and parses the data packets to obtain data packet classification identifiers. Then, it retrieves a queue scheduling configuration set containing fixed static queue scheduling configuration information and dynamic queue scheduling configuration information updated in real time based on power grid state changes. The data packet classification identifiers are precisely matched with this configuration information to identify the appropriate target queue scheduling information for three categories: flow queues, user queues, and port queues. Finally, relying on a preset scheduling algorithm, multi-level queue scheduling is performed in combination with the three types of scheduling information. Transmission resources are allocated and transmission priorities are sorted according to predetermined rules, ensuring that the data packets to be transmitted are transmitted to the target data receiving end in an orderly and accurate manner. This solution realizes the end-to-end serialization of data packet classification identifiers, dynamic and static combined scheduling configurations, and multi-level queue scheduling. It achieves differentiated management of data packets through classification identifiers, adapts to the real-time operating status of the power grid through dynamic configuration, and optimizes resource allocation through multi-level scheduling. This ensures priority transmission of critical business data, improves overall transmission efficiency and resource utilization, and solves the problems of poor accuracy and adaptability in queue scheduling. It improves the accuracy and adaptability of queue scheduling, helps enhance the stability, flexibility, and adaptability of power system data transmission, and effectively supports the efficient operation of the system.

[0092] Example 2

[0093] Figure 2 This is a flowchart of a queue scheduling method provided in Embodiment 2 of the present invention. The method in this embodiment is a further optimization of the method in the above embodiments. Optionally, it involves matching data packet classification identifiers with dynamic and static queue scheduling configuration information to obtain valid queue scheduling information. The valid queue scheduling information includes a target flow queue identifier, flow queue scheduling priority, flow queue scheduling weight, user queue scheduling weight, and target user queue identifier. Flow queue scheduling information is determined based on the target flow queue identifier and the target user queue identifier. User queue scheduling information is determined based on the flow queue scheduling priority, flow queue scheduling weight, and target user queue identifier. Port queue scheduling information is determined based on the flow queue scheduling priority and user queue scheduling weight. Figure 2 As shown, the method includes:

[0094] S210. Receive the data packet to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packet to be transmitted.

[0095] S220. Based on the packet classification identifier, the dynamic queue scheduling configuration information and the static queue scheduling configuration information are matched to obtain the valid queue scheduling information. The valid queue scheduling information includes the target flow queue identifier, the flow queue scheduling priority, the flow queue scheduling weight, the user queue scheduling weight and the target user queue identifier.

[0096] Among them, the effective queue scheduling information is a set of core scheduling parameters that are selected and integrated in the power system data transmission scheduling by accurately matching the data packet classification identifier with the static and dynamic queue scheduling configuration information. It includes the target flow queue identifier, flow queue scheduling priority, flow queue scheduling weight, user queue scheduling weight, and target user queue identifier. This information clarifies the scheduling rules of data packets from the dimensions of queue affiliation, scheduling priority, and scheduling weight allocation, providing a direct basis for the accurate execution of subsequent multi-level queue scheduling and ensuring that data transmission adapts to the power grid status and business needs.

[0097] Specifically, the classification identifier of the data packet to be transmitted is first obtained, and then it is compared and matched with the static queue scheduling configuration information preset by the power system and the dynamic queue scheduling configuration information updated based on the power grid status change data. The effective queue scheduling information that is suitable for the data packet is then selected and integrated, which includes the target flow queue identifier, flow queue scheduling priority, flow queue scheduling weight, user queue scheduling weight and target user queue identifier.

[0098] In this embodiment, by accurately matching the classification identifier with the dynamic and static configuration information, it is ensured that the effective scheduling information conforms to both fixed rules and adapts to the real-time state of the power grid. The integration of multi-dimensional scheduling parameters can provide comprehensive support for subsequent multi-level queue scheduling, while improving the accuracy and flexibility of scheduling rule matching, and ensuring the accuracy and efficiency of power system data transmission scheduling.

[0099] Optionally, the valid queue scheduling information is obtained by matching the packet classification identifier with the dynamic queue scheduling configuration information and the static queue scheduling configuration information. This includes: matching the packet classification identifier with the dynamic queue scheduling configuration information to obtain a matching result; if the matching result is successful, obtaining the first matching information from the dynamic queue scheduling configuration information, determining the valid queue scheduling information based on the first matching information, and stopping the matching of the packet classification identifier with the dynamic queue scheduling configuration information; if the matching result is unsuccessful, matching the packet classification identifier with the dynamic queue scheduling configuration information to obtain the second matching information, and determining the valid queue scheduling information based on the second matching information.

[0100] Specifically, the classification identifier of the data packet to be transmitted is first matched with the dynamic queue scheduling configuration information. If the match is successful, the first matching information is directly obtained from the dynamic configuration information and the valid queue scheduling information is determined, while the subsequent matching is terminated. If the dynamic matching fails, the classification identifier is then matched with the static queue scheduling configuration information to obtain the second matching information and determine the valid queue scheduling information accordingly.

[0101] In this embodiment, by adopting a matching logic that prioritizes dynamic matching and provides a safety net of static matching, the system prioritizes adapting to the real-time state of the power grid to ensure scheduling flexibility, while using static configuration as a safety net to avoid matching failures. Once a match is successful, the process is terminated immediately to improve efficiency. At the same time, the system accurately extracts matching information to ensure the reliability of effective scheduling information, providing stable support for subsequent queue scheduling.

[0102] S230. Determine the flow queue scheduling information based on the target flow queue identifier and the target user queue identifier; determine the user queue scheduling information based on the flow queue scheduling priority, the flow queue scheduling weight, and the target user queue identifier; determine the port queue scheduling information based on the flow queue scheduling priority and the user queue scheduling weight.

[0103] Specifically, based on valid queue scheduling information, the flow queue to which the data packet belongs is first identified by the target flow queue identifier. Combined with the target user queue identifier, the associated user queues are defined, jointly determining the flow queue scheduling information. This clarifies the flow queue to which the data packet to be transmitted belongs and the associated user queues, defining the scheduling affiliation and basic rules of data at the flow level. Next, based on the flow queue scheduling priority and weight, and in conjunction with the target user queue identifier, the scheduling rules for the user queues are clarified, forming user queue scheduling information. Focusing on the user queue dimension, the scheduling priority ranking and weight allocation standards for this queue are defined. Finally, based on the flow queue scheduling priority and user queue scheduling weight, port-level scheduling standards are further formulated, generating port queue scheduling information. Flow queue scheduling information, user queue scheduling information, and port queue scheduling information correspond to the three-level scheduling hierarchy of "flow-user-port," progressing layer by layer and interconnected, jointly forming a complete information system supporting multi-level queue scheduling of power system data.

[0104] In this embodiment, scheduling information is derived according to the hierarchical progression of "flow queue - user queue - port queue". Each step relies on the core parameters in the effective information to ensure that the scheduling information is accurately matched with the data packet attributes and power grid requirements. The hierarchical design makes the scheduling rules clear and orderly, laying a solid foundation for the efficient execution of subsequent multi-level queue scheduling.

[0105] S240. Based on the stream queue scheduling information, user queue scheduling information, and port queue scheduling information, multi-level queue scheduling is performed using a preset scheduling algorithm to transmit the data packets to be transmitted to the target data receiving end.

[0106] The technical solution of this embodiment receives data packets to be transmitted from the target power system and determines their classification identifiers. Then, it matches the classification identifiers with dynamic and static queue scheduling configuration information to obtain valid queue scheduling information containing target flow / user queue identifiers, scheduling priorities, and weights. Subsequently, it derives scheduling information at the flow-user-port level, determines flow queue scheduling information based on flow and user queue identifiers, generates user queue scheduling information by combining flow queue scheduling priorities, weights, and user queue identifiers, and formulates port queue scheduling information based on flow queue scheduling priorities and user queue weights. Finally, it executes multi-level queue scheduling through a preset scheduling algorithm to transmit the data packets to the target receiving end. This achieves end-to-end serialized data packet classification identification, dynamic and static combined scheduling configuration, and multi-level queue scheduling. It achieves differentiated management of data packets through classification identifiers, adapts to the real-time operating status of the power grid through dynamic configuration, and optimizes resource allocation through multi-level scheduling. This ensures priority transmission of critical business data, improves overall transmission efficiency and resource utilization, and solves the problems of poor accuracy and adaptability in queue scheduling. It enhances the accuracy and adaptability of queue scheduling, helps improve the stability, flexibility, and adaptability of power system data transmission, and effectively supports efficient system operation.

[0107] Example 3

[0108] Figure 3 This is a schematic diagram of a queue scheduling device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes:

[0109] The data packet classification identifier determination module 310 is used to receive the data packet to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packet to be transmitted.

[0110] The target queue scheduling information determination module 320 is used to determine the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and queue scheduling configuration information. The queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information. The dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system. The target queue scheduling information includes flow queue scheduling information, user queue scheduling information and port queue scheduling information.

[0111] The multi-level queue scheduling execution module 330 is used to perform multi-level queue scheduling based on stream queue scheduling information, user queue scheduling information, and port queue scheduling information through a preset scheduling algorithm, so as to transmit the data packets to be transmitted to the target data receiving end.

[0112] The technical solution of this embodiment involves a data packet classification identifier determination module receiving a data packet to be transmitted corresponding to the target power system and determining the data packet classification identifier of the data packet to be transmitted; a target queue scheduling information determination module determining the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and queue scheduling configuration information, wherein the queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information, the dynamic queue scheduling configuration information including dynamic queue scheduling information updated based on the grid state change data of the target power system, and the target queue scheduling information including flow queue scheduling information, user queue scheduling information, and port queue scheduling information; and a multi-level queue scheduling execution module executing multi-level queue scheduling based on the flow queue scheduling information, user queue scheduling information, and port queue scheduling information using a preset scheduling algorithm to transmit the data packet to be transmitted to the target data receiving end. This solution implements end-to-end serial data packet classification and identification, dynamic and static combined scheduling configuration, and multi-level queue scheduling. It achieves differentiated management of data packets through classification and identification, adapts to the real-time operating status of the power grid through dynamic configuration, and optimizes resource allocation through multi-level scheduling. This ensures priority transmission of critical business data, improves overall transmission efficiency and resource utilization, and solves the problems of poor accuracy and adaptability of queue scheduling. It improves the accuracy and adaptability of queue scheduling, helps to enhance the stability, flexibility and adaptability of power system data transmission, and effectively supports the efficient operation of the system.

[0113] Based on the above embodiments, optionally, the data packet classification identifier determination module 310 is specifically used to receive the data packet to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packet to be transmitted.

[0114] Optionally, the target queue scheduling information determination module 320 is specifically used to match the packet classification identifier with the dynamic queue scheduling configuration information and the static queue scheduling configuration information to obtain valid queue scheduling information. The valid queue scheduling information includes the target flow queue identifier, flow queue scheduling priority, flow queue scheduling weight, user queue scheduling weight, and target user queue identifier. The module determines the flow queue scheduling information based on the target flow queue identifier and the target user queue identifier; determines the user queue scheduling information based on the flow queue scheduling priority, the flow queue scheduling weight, and the target user queue identifier; and determines the port queue scheduling information based on the flow queue scheduling priority and the user queue scheduling weight.

[0115] Optionally, the target queue scheduling information determination module 320 is specifically used to match the data packet classification identifier with the dynamic queue scheduling configuration information to obtain a matching result; if the matching result is successful, the first matching information is obtained from the dynamic queue scheduling configuration information, the valid queue scheduling information is determined based on the first matching information, and the matching of the data packet classification identifier with the dynamic queue scheduling configuration information is stopped; if the matching result is unsuccessful, the data packet classification identifier is matched with the dynamic queue scheduling configuration information to obtain a second matching information, and the valid queue scheduling information is determined based on the second matching information.

[0116] Optionally, the preset scheduling algorithms include a first scheduling algorithm, a second scheduling algorithm, and a third scheduling algorithm; the multi-level queue scheduling execution module 330 is specifically used to transmit the data packet to be transmitted to the target flow queue based on the flow queue scheduling information; when the target flow queue receives the data packet to be transmitted, it schedules the target flow queue according to the first scheduling algorithm based on the flow queue scheduling information to transmit the data packet to the target user queue, wherein the first scheduling algorithm is a scheduling algorithm constructed based on the first-in-first-out scheduling rule; when the target user queue receives the data packet to be transmitted, it obtains the user queue scheduling information, and schedules the target user queue according to the second scheduling algorithm based on the user queue scheduling information to transmit the data packet to the target port queue, wherein the second scheduling algorithm is a hybrid scheduling model of strict priority scheduling and weighted fair queue scheduling; when the target port queue receives the data packet to be transmitted, it obtains the port queue scheduling information, and schedules the target port queue according to the third scheduling algorithm based on the port queue scheduling information to perform forwarding control on the data packet to be transmitted, and transmits the data packet to be transmitted to the target data receiving end through the physical port corresponding to the target port queue, wherein the third scheduling algorithm is a hybrid scheduling model of strict priority scheduling and token bucket.

[0117] Optionally, the device is further configured to receive grid state change data of the target power system, determine abnormal event information based on the grid state change data, wherein the abnormal event information includes abnormal event type and abnormal device identifier; acquire a preset power topology map of the target power system, determine the abnormal event associated device based on the abnormal event type, abnormal device identifier, and power topology map; acquire a preset service flow and function mapping relationship, match the abnormal event associated device with the preset service flow and function mapping relationship to obtain abnormal event associated service flow information; determine dynamic queue scheduling parameter adjustment information based on the abnormal event associated service flow information, and update the dynamic queue scheduling information in the dynamic queue scheduling configuration information based on the dynamic queue scheduling parameter adjustment information.

[0118] Optionally, the device is further configured to: determine the dynamic functional priority score corresponding to each abnormal event-related service flow based on the basic priority, security impact score, and timeliness impact score of at least one abnormal event-related service flow; acquire the estimated bandwidth data corresponding to each of the at least one abnormal event-related service flows; determine the dynamic flow queue weight corresponding to each abnormal event-related service flow based on the estimated bandwidth data and the corresponding functional priority score; determine the corresponding dynamic user queue identifier and dynamic user queue weight based on the dynamic functional priority score corresponding to each abnormal event-related service flow; and construct dynamic queue scheduling parameter adjustment information based on the dynamic functional priority score, dynamic flow queue weight, dynamic user queue identifier, and dynamic user queue weight corresponding to each abnormal event-related service flow.

[0119] The queue scheduling device provided in the embodiments of the present invention can execute the queue scheduling method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0120] Example 4

[0121] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0122] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0123] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0124] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as queue scheduling methods.

[0125] In some embodiments, the queue scheduling method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the queue scheduling method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to execute the queue scheduling method by any other suitable means (e.g., by means of firmware).

[0126] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0127] Computer programs for implementing the queue scheduling method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0128] Example 5

[0129] Embodiment 5 of the present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to execute a queue scheduling method, the method comprising:

[0130] Receive the data packets to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packets to be transmitted;

[0131] The target queue scheduling information corresponding to the data packet to be transmitted is determined based on the data packet classification identifier and queue scheduling configuration information. The queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information. The dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system. The target queue scheduling information includes flow queue scheduling information, user queue scheduling information and port queue scheduling information.

[0132] Based on stream queue scheduling information, user queue scheduling information, and port queue scheduling information, a multi-level queue scheduling is performed using a preset scheduling algorithm to transmit the data packets to be transmitted to the target data receiving end.

[0133] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0134] To provide interaction with an object, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the object; and a keyboard and pointing device (e.g., a mouse or trackball) through which the object provides input to the electronic device. Other types of devices can also be used to provide interaction with the object; for example, feedback provided to the object can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the object can be received in any form (including sound input, voice input, or tactile input).

[0135] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., a computer with a graphical user interface or web browser through which an item can interact with the implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0136] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0137] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0138] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A queue scheduling method, characterized in that, include: Receive the data packet to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packet to be transmitted; The target queue scheduling information corresponding to the data packet to be transmitted is determined based on the data packet classification identifier and queue scheduling configuration information. The queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information. The dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system. The target queue scheduling information includes flow queue scheduling information, user queue scheduling information and port queue scheduling information. Based on the stream queue scheduling information, user queue scheduling information, and port queue scheduling information, a multi-level queue scheduling is performed using a preset scheduling algorithm to transmit the data packet to be transmitted to the target data receiving end.

2. The method according to claim 1, characterized in that, Determining the data packet classification identifier of the data packet to be transmitted includes: The data packet to be transmitted is parsed to extract the quintuple information corresponding to the data packet to be transmitted, and the quintuple information is hashed to generate a data packet classification identifier for the data packet to be transmitted.

3. The method according to claim 1, characterized in that, The step of determining the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and queue scheduling configuration information includes: Based on the matching of the packet classification identifier with the dynamic queue scheduling configuration information and the static queue scheduling configuration information, valid queue scheduling information is obtained, wherein the valid queue scheduling information includes the target flow queue identifier, flow queue scheduling priority, flow queue scheduling weight, user queue scheduling weight, and target user queue identifier; The flow queue scheduling information is determined based on the target flow queue identifier and the target user queue identifier; the user queue scheduling information is determined based on the flow queue scheduling priority, the flow queue scheduling weight, and the target user queue identifier; the port queue scheduling information is determined based on the flow queue scheduling priority and the user queue scheduling weight.

4. The method according to claim 3, characterized in that, The process of matching the data packet classification identifier with the dynamic queue scheduling configuration information and the static queue scheduling configuration information to obtain valid queue scheduling information includes: The data packet classification identifier is matched with the dynamic queue scheduling configuration information to obtain the matching result; If the matching result is a successful match, then the first matching information is obtained from the dynamic queue scheduling configuration information, the queue scheduling validity information is determined based on the first matching information, and the matching of the data packet classification identifier with the dynamic queue scheduling configuration information is stopped. If the matching result is a failure, the data packet classification identifier is matched with the dynamic queue scheduling configuration information to obtain second matching information, and the queue scheduling validity information is determined based on the second matching information.

5. The method according to claim 1, characterized in that, The preset scheduling algorithm includes a first scheduling algorithm, a second scheduling algorithm, and a third scheduling algorithm; the step of performing multi-level queue scheduling based on the stream queue scheduling information, user queue scheduling information, and port queue scheduling information using the preset scheduling algorithm to transmit the data packet to be transmitted to the target data receiving end includes: Based on the stream queue scheduling information, the data packet to be transmitted is transmitted to the target stream queue; When the target flow queue receives the data packet to be transmitted, the target flow queue is scheduled according to the flow queue scheduling information using the first scheduling algorithm to transmit the data packet to the target user queue. The first scheduling algorithm is a scheduling algorithm based on the first-in-first-out scheduling rule. When the target user queue receives the data packet to be transmitted, user queue scheduling information is obtained, and the target user queue is scheduled according to the second scheduling algorithm based on the user queue scheduling information to transmit the data packet to the target port queue. The second scheduling algorithm is a hybrid scheduling model of strict priority scheduling and weighted fair queue scheduling. When the target port queue receives the data packet to be transmitted, port queue scheduling information is obtained, and the target port queue is scheduled according to the third scheduling algorithm based on the port queue scheduling information to forward and control the data packet to be transmitted. The data packet to be transmitted is then transmitted to the target data receiving end through the physical port corresponding to the target port queue. The third scheduling algorithm is a hybrid scheduling model of strict priority scheduling and token bucket.

6. The method according to claim 1, characterized in that, The method further includes: Receive grid state change data of the target power system, and determine abnormal event information based on the grid state change data, wherein the abnormal event information includes abnormal event type and abnormal equipment identifier; Obtain a preset power topology map of the target power system, and determine the devices associated with the abnormal event based on the abnormal event type, the abnormal device identifier, and the power topology map; Obtain the preset business flow and function mapping relationship, match the abnormal event associated device with the preset business flow and function mapping relationship, and obtain the abnormal event associated business flow information; Based on the abnormal event-related business flow information, dynamic queue scheduling parameter adjustment information is determined, and the dynamic queue scheduling information in the dynamic queue scheduling configuration information is updated based on the dynamic queue scheduling parameter adjustment information.

7. The method according to claim 6, characterized in that, The abnormal event-related service flow information includes at least one abnormal event-related service flow's basic priority, security impact score, and timeliness impact score; the step of determining dynamic queue scheduling parameter adjustment information based on the abnormal event-related service flow information includes: Based on the basic priority, security impact score, and timeliness impact score of the at least one abnormal event-related business flow, determine the dynamic functional priority score corresponding to each of the abnormal event-related business flows; Obtain the estimated bandwidth data corresponding to the at least one abnormal event-related service flow, and determine the dynamic flow queue weight corresponding to each abnormal event-related service flow based on the estimated bandwidth data corresponding to the at least one abnormal event-related service flow and the corresponding functional priority score. The corresponding dynamic user queue identifier and dynamic user queue weight are determined based on the dynamic function priority score of each abnormal event-related business flow. The dynamic queue scheduling parameter adjustment information is constructed based on the dynamic function priority score, dynamic flow queue weight, dynamic user queue identifier, and dynamic user queue weight corresponding to each abnormal event-related business flow.

8. A queue scheduling device, characterized in that, include: The data packet classification identifier determination module is used to receive the data packet to be transmitted corresponding to the target power system and determine the data packet classification identifier of the data packet to be transmitted; The target queue scheduling information determination module is used to determine the target queue scheduling information corresponding to the data packet to be transmitted based on the data packet classification identifier and the queue scheduling configuration information. The queue scheduling configuration information includes static queue scheduling configuration information and dynamic queue scheduling configuration information. The dynamic queue scheduling configuration information includes dynamic queue scheduling information updated based on the grid state change data of the target power system. The target queue scheduling information includes flow queue scheduling information, user queue scheduling information and port queue scheduling information. The multi-level queue scheduling execution module is used to perform multi-level queue scheduling based on the stream queue scheduling information, user queue scheduling information, and port queue scheduling information through a preset scheduling algorithm, so as to transmit the data packet to be transmitted to the target data receiving end.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the queue scheduling method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the queue scheduling method according to any one of claims 1-7.

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