Service quality scheduling method and system, electronic equipment and computer storage medium

Abstract

The invention relates to the technical field of communication, in particular to a service quality scheduling method and system, electronic equipment and a computer storage medium. The method comprises the following steps: acquiring service flow feature information, wireless channel state information and network topology structure information in a wireless network; and executing a flow admission control decision according to the service flow feature information, the wireless channel state information and the network topology structure information. And adjusting the priority mapping relationship of the service flow according to the network topology structure information and the service flow feature information. And according to the priority mapping relation and the network topology structure information, executing time domain resource scheduling allocation. And iteratively optimizing a time domain resource scheduling strategy and priority mapping relation according to the change of the service quality index after the scheduling is executed. The method can autonomously learn and adapt to network changes, overcomes strategy conflicts among devices, eliminates channel fluctuation interference by means of a feedback iteration mechanism, and improves the adaptability and reliability of the network in a high-density and sparse scene.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a quality of service scheduling method, system, electronic device, and computer storage medium. Background Technology

[0002] With the widespread application of Wireless Local Area Networks (WLANs), QoS (Quality of Service) management in WLANs has become a key mechanism to ensure the efficient and reliable operation of the network.

[0003] Current QoS mechanisms in WLANs are primarily based on the IEEE 802.11e standard. This standard, through the Enhanced Distributed Channel Access (EDCA) mechanism, divides traffic into four access categories: voice, video, best-effort, and background, and configures differentiated channel contention parameters for different categories, giving high-priority traffic a higher probability of channel access. RFC 8325 further defines the mapping relationship between IP layer (Internet Protocol, network layer) DSCP and radio priority, while the 802.11e ADDTS protocol allows devices to request specific QoS resource guarantees.

[0004] In existing technologies, there are various QoS management solutions. For example, some technologies achieve automatic traffic classification and dynamic queue allocation by analyzing packet characteristics, establishing dedicated transmission channels for critical services; other solutions dynamically adjust QoS parameters based on real-time network conditions, and optimize configuration through feedback iteration to adapt to network changes.

[0005] However, existing technologies still have significant limitations: First, the QoS decisions of each device are independent of each other, lacking a global collaborative perspective, which can easily lead to priority policy conflicts; second, existing solutions rely too much on preset static rules and lack the ability to learn autonomously from the inherent characteristics of traffic; third, when evaluating the effectiveness of policies, it is impossible to effectively distinguish between performance improvements caused by policy adjustments and changes caused by natural channel fluctuations, which can easily lead to misjudgments in parameter adjustments. Summary of the Invention

[0006] This application provides a quality of service (QoS) scheduling method, system, electronic device, and computer storage medium. It can autonomously learn and adapt to network changes, overcome policy conflicts between devices, optimize packet and resource allocation based on topology awareness, significantly reduce transmission conflicts and latency, and eliminate channel fluctuation interference through a feedback iteration mechanism, thereby improving the network's adaptability and reliability in high-density and sparse scenarios.

[0007] Firstly, this application provides a quality of service (QoS) scheduling method, which includes: acquiring service flow characteristic information, wireless channel state information, and network topology information in a wireless network; performing traffic admission control decisions based on the service flow characteristic information, wireless channel state information, and network topology information; adjusting the priority mapping relationship of service flows based on the network topology information and service flow characteristic information; performing time-domain resource scheduling and allocation based on the priority mapping relationship and network topology information; and iteratively optimizing the time-domain resource scheduling strategy and priority mapping relationship based on changes in QoS indicators after scheduling execution.

[0008] In some implementations, acquiring service flow characteristic information, wireless channel state information, and network topology information in a wireless network includes: identifying service types by analyzing the packet characteristics of service flows to obtain service flow characteristic information, where packet characteristics include at least one or more of the following: packet transmission frequency, packet length, data volume, protocol address, protocol type, and port. Determining wireless channel state information by monitoring wireless channel state parameters, where state parameters include at least one or more of the following: channel occupancy rate, packet error rate, transmission rate, and channel noise floor. Obtaining network topology information by learning network topology relationships through protocol interactions between devices, where network topology information includes interference relationships between devices and hidden node relationships between devices.

[0009] In some implementations, traffic admission control decisions are performed based on service flow characteristic information, radio channel state information, and network topology information. This includes: assessing the available bandwidth resources of the current network based on the service flow characteristic information and radio channel state information; determining whether the resource requirements of a new service flow exceed the available bandwidth resources; if the resource requirements of the new service flow do not exceed the available bandwidth resources, then the new service flow is accepted and corresponding time-domain resources are allocated according to the network topology information; if the resource requirements of the new service flow exceed the available bandwidth resources, then the new service flow is rejected and degraded transmission processing is triggered.

[0010] In some implementations, the priority mapping of service flows is adjusted, including at least one of the following adjustment strategies: if network resources are scarce, some high-priority service flows are remapped to lower-priority access categories; the priority mapping strategies of different devices are adjusted based on the competition among devices; and the priority mapping levels are modified based on the actual service quality requirements of the service flows.

[0011] In some implementations, time-domain resource scheduling and allocation are performed, including at least one of the following scheduling modes: Centralized control scheduling mode: Deterministic packet transmission time slots are allocated to each device based on priority mapping relationships. Distributed cooperative scheduling mode: Packet transmission time slots are allocated by adjusting the channel contention parameters and network topology information of each device.

[0012] In some implementations, the time-domain resource scheduling strategy is iteratively optimized based on changes in service quality indicators (QoS) after scheduling execution. This includes: collecting QoS indicator change data after time-domain resource scheduling; identifying and excluding QoS indicator changes caused by natural fluctuations in the wireless channel; analyzing the actual impact of time-domain resource scheduling on QoS indicators and obtaining analysis results; and iteratively optimizing the time-domain resource scheduling strategy based on the analysis results.

[0013] In some implementations, the iterative optimization step further includes: identifying and eliminating the impact of sudden or periodic changes in service quality indicators on the data based on changes in service flow characteristic information.

[0014] In some implementations, the method further includes: performing traffic shaping on service flows in the network based on channel occupancy information in the wireless channel state information, and using peak-shifting scheduling to make the channel occupancy of the entire network tend to be averaged over time, thereby reducing conflicts between devices within the network.

[0015] Secondly, this application provides a service quality scheduling system, which includes an information collection module and a control management module.

[0016] The information collection module is used to collect service flow characteristic information, wireless channel status information, and network topology information in the wireless network.

[0017] The control and management module is used to execute traffic access control decisions based on service flow characteristic information, wireless channel status information, and network topology information.

[0018] The control and management module is also used to adjust the priority mapping relationship of service flows based on network topology information and service flow characteristic information.

[0019] The control and management module is also used to perform time-domain resource scheduling and allocation based on priority mapping relationships and network topology information.

[0020] The control and management module is also used to iteratively optimize the time-domain resource scheduling strategy based on changes in service quality indicators after scheduling execution.

[0021] In some implementations, the information collection module is specifically used to: identify service types by analyzing the message characteristics of service flows, obtaining service flow characteristic information, where message characteristics include at least one or more of the following: packet transmission frequency, message length, data volume, protocol address, protocol type, and port; determine wireless channel state information by monitoring wireless channel state parameters, where state parameters include at least one or more of the following: channel occupancy rate, packet error rate, transmission rate, and channel noise floor; and obtain network topology information by learning network topology relationships through protocol interactions between devices, where network topology information includes interference relationships between devices and hidden node relationships between devices.

[0022] In some implementations, the system supports one of the following scheduling architectures: a centralized control scheduling architecture or a distributed collaborative scheduling architecture. If the QoS scheduling system adopts a centralized control scheduling architecture, the control and management module is a management device. Specifically, the management device is used to allocate deterministic packet transmission time slots to each device according to priority mapping relationships. If the QoS scheduling system adopts a distributed collaborative scheduling architecture, the control and management module is a wireless access point. Specifically, the wireless access point is used to allocate packet transmission time slots by adjusting the channel contention parameters and network topology information of each device.

[0023] Thirdly, this application provides a service quality scheduling device, including an acquisition module and a processing module.

[0024] The acquisition module is used to acquire service flow characteristic information, wireless channel status information, and network topology information in the wireless network.

[0025] The processing module is used to execute traffic admission control decisions based on service flow characteristic information, wireless channel state information, and network topology information.

[0026] The processing module is also used to adjust the priority mapping relationship of service flows based on network topology information and service flow characteristic information.

[0027] The processing module is also used to perform time-domain resource scheduling and allocation based on priority mapping relationships and network topology information.

[0028] The processing module is also used to iteratively optimize the time-domain resource scheduling strategy and priority mapping relationship based on the changes in service quality indicators after scheduling execution.

[0029] Fourthly, this application provides a chip for performing the methods described in any of the first aspects above.

[0030] Fifthly, this application provides an electronic device including a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the method as described in any of the first aspects above. Alternatively, Electronic devices include chips, as described in the fourth aspect.

[0031] In a sixth aspect, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method as described in any of the first aspects above.

[0032] In a seventh aspect, this application provides a computer program product storing a computer program that, when executed by a processor, implements the method as described in any of the first aspects above.

[0033] In the technical solution provided in this application, the device can first acquire service flow characteristic information, wireless channel state information, and network topology information in the wireless network, and then execute traffic admission control decisions based on these information. Furthermore, based on the network topology information and service flow characteristic information, it adjusts the priority mapping relationship of service flows, and performs time-domain resource scheduling and allocation based on the priority mapping relationship and network topology information. Finally, based on the changes in service quality indicators after scheduling execution, iteratively optimizes the time-domain resource scheduling strategy and priority mapping relationship. In the technical solution provided in this application, the device can upgrade the traditional static and isolated scheduling system into a globally collaborative scheduling system by acquiring service flow characteristic information, wireless channel state information, and network topology information. This global collaboration resolves policy conflicts between devices, ensures the effectiveness of critical services, guarantees the accuracy and reliability of scheduling strategies, and significantly improves overall network capacity, critical service experience, and the level of operational automation. The device can also learn and adapt to network changes autonomously, overcome policy conflicts between devices, optimize grouping and resource allocation based on topology awareness, significantly reduce transmission conflicts and delays, and eliminate channel fluctuation interference through feedback iteration mechanism, thereby improving the adaptability and reliability of the network in high-density and sparse scenarios. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a network topology diagram illustrating a quality of service scheduling method provided in an embodiment of this application; Figure 2 This is a schematic diagram of a service quality scheduling process provided in an embodiment of the present application for a service quality scheduling method; Figure 3This is a schematic diagram of an information acquisition process for a service quality scheduling method provided in this application embodiment; Figure 4 This is a hierarchical scheduling block diagram of a service quality scheduling method provided in an embodiment of this application; Figure 5 This is a schematic diagram illustrating the learning and interaction process of hidden node relationships between devices in a central control scheduling architecture of a service quality scheduling method provided in this application embodiment; Figure 6 This is a schematic diagram of the traffic admission acceptance process of a central control scheduling architecture for a quality of service scheduling method provided in this application embodiment; Figure 7 This is a schematic diagram of a traffic admission and rejection process within a central control scheduling architecture of a quality of service scheduling method provided in this application embodiment; Figure 8 This is a schematic diagram of the traffic admission acceptance process of a distributed collaborative scheduling architecture for a quality of service scheduling method provided in this application embodiment; Figure 9 This is a schematic diagram of a distributed collaborative scheduling architecture traffic admission and rejection process for a quality of service scheduling method provided in this application embodiment; Figure 10 This is a schematic diagram of a priority allocation air interface shortage handling process under a central control scheduling architecture provided in an embodiment of the service quality scheduling method of this application; Figure 11 This is a flowchart illustrating a mapping strategy feedback iteration process for a service quality scheduling method provided in this application embodiment; Figure 12 This is a schematic diagram illustrating a traffic shaping process for resolving instantaneous channel occupancy exceeding the limit, provided in an embodiment of the Quality of Service scheduling method of this application. Figure 13 This is a schematic diagram illustrating the traffic shaping effect of a service quality scheduling method provided in this application embodiment; Figure 14 This is a schematic diagram of the structure of a quality of service scheduling device 140 provided in an embodiment of this application; Figure 15 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0036] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0037] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0038] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0039] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0040] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0041] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0042] With the widespread application of Wireless Local Area Networks (WLANs) in home networks, enterprise offices, public services, and the Internet of Things (IoT), QoS (Quality of Service) management has become a key mechanism for ensuring efficient and reliable network operation. Due to the shared medium nature of WLANs (all devices compete for the same channel), without effective QoS management, the network is prone to congestion and chaos.

[0043] The core of the QoS mechanism was introduced by the IEEE 802.11e standard, which defines the Enhanced Distributed Channel Access (EDCA) mechanism. EDCA divides data streams into four Access Categories (ACs): Voice (VO), Video (VI), Best Effort (BE), and Background (BK). Each AC is assigned differentiated channel contention parameters, including AIFS (Arbitration Inter-Frame Interval) and CWmin / CWmax (Minimum / Maximum Contention Window). By configuring shorter AIFS and smaller contention windows for high-priority ACs (such as VO and VI), EDCA gives these traffic a higher probability of access in channel contention, thereby improving the performance of real-time applications.

[0044] To further achieve refined QoS control, relevant standards and protocols provide supplementary mechanisms: RFC 8325: Defines the mapping relationship between DiffServ (Differentiated Service) DSCP values ​​and IEEE 802.11 Priority Identifiers (TIDs) and Access Control Points (ACs), providing a standard basis for QoS transmission between the IP layer and the radio layer. IEEE 802.11e ADDTS protocol: Allows stations (STAs) to request specific QoS resources (such as bandwidth and latency guarantees) from access points (APs) through Flow Specifications (TSPECs). The AP decides whether to accept the request based on network load and ensures that data flows are correctly classified to the corresponding AC through the Traffic Classification (TCLAS) parameter. 5G QoS Identifier (5QI): In 5G mobile communication, 3GPP TS 23.501 defines 5QI as a core QoS parameter, supporting both dynamic configuration and standardized mapping tables to map service requirements to DSCP values, achieving consistent QoS guarantees across networks.

[0045] In practical applications, several technologies have attempted to improve service reliability and real-time performance through QoS mapping and resource management. For example, multi-level slicing edge switching devices automatically classify traffic and dynamically allocate queues by analyzing packet characteristics (such as DSCP and VLAN tags), establishing dedicated transmission channels for critical services and preventing low-priority traffic from preempting resources. Another example is in mobile communication environments, where QoS priorities and protocol parameters are dynamically adjusted based on real-time network conditions (such as signal strength and available bandwidth), and configurations are optimized through feedback iterations to adapt to changing network conditions.

[0046] While the above mechanisms and solutions have improved QoS management to some extent, they still have the following limitations: Lack of a global collaborative perspective: Existing QoS decisions are mostly based on local device information and lack cross-device collaborative scheduling mechanisms, which can easily lead to priority policy conflicts between different devices and make it impossible to achieve reasonable sorting and resource coordination of network-wide service flows.

[0047] Reliance on static rules and limited knowledge: Existing solutions mostly rely on preset IP layer information (such as DSCP, 5-tuple) for traffic classification, lacking the ability to learn autonomously about the inherent characteristics and changing patterns of traffic, making it difficult to adapt to dynamic business environments and new application scenarios.

[0048] Failure to effectively distinguish between policy effects and channel fluctuations: When evaluating the effects of QoS policy adjustments, existing technologies fail to effectively separate the performance improvements brought about by policy optimization from the transmission fluctuations caused by natural changes in the wireless channel (such as interference and signal attenuation), which can easily lead to misjudgments in parameter adjustments and affect the convergence of scheduling optimization.

[0049] In summary, the existing technical solutions have obvious limitations: First, the QoS decisions of each device are independent and lack a global collaborative perspective, which can easily lead to priority policy conflicts; second, the existing solutions rely too much on preset static rules and lack the ability to learn autonomously from the inherent characteristics of traffic; third, when evaluating the effect of the policy, it is impossible to effectively distinguish between the performance improvement brought about by the policy adjustment and the changes caused by the natural fluctuations of the channel, which can easily lead to misjudgment of parameter adjustments.

[0050] In view of this, embodiments of this application provide a quality of service scheduling method that can autonomously learn and adapt to network changes, overcome policy conflicts between devices, optimize grouping and resource allocation based on topology awareness, significantly reduce transmission conflicts and delays, and eliminate channel fluctuation interference by using a feedback iteration mechanism, thereby improving the adaptability and reliability of the network in high-density and sparse scenarios.

[0051] The technical solutions of the embodiments of this application are described below with reference to the examples in the accompanying drawings.

[0052] Figure 1 This is a network topology diagram illustrating a quality of service scheduling method provided in an embodiment of this application. Figure 1 As shown, the network topology provided in this application embodiment may include a management center, multiple APs (Access Points) and multiple IPCs (IP Cameras).

[0053] Figure 1The network topology shown can be applied to two different scheduling architectures (centralized control scheduling architecture and distributed collaborative scheduling architecture). In the centralized control scheduling architecture, each terminal device (e.g., AP, IPC, etc.) can perform traffic identification, radio information collection, and topology learning processes, and periodically report the acquired information (traffic identification, radio information collection, and topology learning related data) to the management center. The management center responds to the received information by executing policy decisions and traffic admission. It should be understood that when a device requests traffic admission, the terminal device immediately reports the traffic admission request to the management center, without waiting for periodic reports. The management center then executes traffic admission and policy decisions, and reconfigures the determined priority mapping, packet scheduling, and other rules onto the terminal devices through protocol interaction, where they take effect.

[0054] In a distributed collaborative scheduling architecture, terminal devices can perform traffic identification, wireless information collection, and topology learning processes. The AP is responsible for deciding whether to allow the IPC's traffic admission request. The AP and IPC are each responsible for their own priority mapping, time-domain resource allocation, and other decisions. It should be understood that in a distributed collaborative scheduling architecture, decision-making and execution are mainly carried out collaboratively by the AP and terminal devices in a distributed manner, while the management center focuses on network monitoring and management, as well as other management functions.

[0055] Figure 2 This is a schematic diagram of a service quality scheduling process provided in an embodiment of this application. Figure 2 As shown, the service quality scheduling process may include the following steps S201 to S205.

[0056] Step S201: Obtain service flow characteristic information, wireless channel state information, and network topology information in the wireless network.

[0057] Figure 3 This application provides a schematic diagram of an information acquisition process for a quality of service scheduling method according to an embodiment of the present application. The method by which a terminal device acquires service flow characteristic information, wireless channel state information, and network topology information in a wireless network can be as follows: Figure 3 As shown, it includes steps S201-1 to S201-3.

[0058] Step S201-1: Identify the service type by analyzing the message characteristics of the service flow, and obtain the service flow characteristic information. The message characteristics include at least one or more of the following: packet sending frequency, message length, data volume, protocol address, protocol type, and port.

[0059] In the technical solution provided in this application embodiment, since IPC and other devices can understand various characteristics of their own service traffic (packet frequency, message length, data volume, IP, protocol, port, etc.) and transmission requirement indicators (maximum latency, jitter time, etc.), IPC and other devices can report these characteristic information to the management center, AP and other devices so that AP and other devices can identify the service type and obtain service flow characteristic information.

[0060] Access points (APs) and similar devices can identify service types and obtain service flow characteristic information based on TCP (Transmission Control Protocol) streams. Specifically, APs can identify service types (video, audio, or signaling) based on preset rules such as IP address and port, or based on traffic characteristics such as packet length and frame interval. For example, APs can distinguish different service flows based on a five-tuple consisting of IP address, protocol, and port. Then, based on various service traffic characteristic identification rules, they can identify the nature of the traffic they are forwarding and its corresponding transmission requirements. By analyzing packet sending and receiving statistics, they can confirm whether new service traffic has been added and the changes in traffic characteristics (packet frequency, packet length, data volume), thereby obtaining service flow characteristic information.

[0061] It should be understood that, on the one hand, service flow characteristic information can be used to determine the priority and urgency of traffic transmission (based on the traffic type in the service flow characteristic information), thereby enabling reasonable traffic classification. On the other hand, service flow characteristic information can be used to statistically analyze the size and changing patterns of various types of traffic to determine whether air interface resources are sufficient, facilitating traffic access control.

[0062] Figure 4 This is a hierarchical scheduling block diagram of a service quality scheduling method provided in an embodiment of this application. For example... Figure 4As shown, the system includes multiple modules such as information collection, traffic admission, transmission strategy, priority classification mapping, and time-domain resource allocation. The information collection module includes traffic identification, wireless channel collection, and topology learning sub-modules. The traffic identification sub-module can be used for service packet parsing, traffic feature learning, and feature rule matching. The wireless information collection sub-module can be used for channel occupancy rate collection, PER (packet error rate) collection, and rate collection. The topology learning sub-module can be used for wireless association relationship acquisition and hidden node relationship acquisition. The traffic admission module can be used for bandwidth margin assessment and ADDTS (Add Flow to Service) protocol requirement verification. During the information collection process, the service flow feature information collected by the information collection module can be applied to the traffic identification module. Specifically, the traffic identification module can use the service flow feature information for service packet parsing, traffic feature learning, and feature rule matching, etc., which is not limited here. The priority classification mapping module includes a traffic classification sub-module and a packet priority mapping sub-module. The traffic classification sub-module can be used for service flow classification and queue priority mapping. The packet priority mapping sub-module can be used for AC mapping. The time-domain resource partitioning module includes a channel reservation submodule and a packet scheduling submodule. The packet scheduling submodule can be used for node scheduling, AC queue scheduling, and EDCA parameter configuration.

[0063] Step S201-2: Determine the wireless channel status information by monitoring the status parameters of the wireless channel. The status parameters include at least one or more of the following: channel occupancy rate, packet error rate, transmission rate, and channel noise floor.

[0064] In the technical solution provided in this application, the state parameters of the wireless channel can include various state indicators at the wireless layer, such as channel occupancy, PER (Packet Error Rate), transmission rate, and channel noise floor. The state parameters of the wireless channel are used to calculate wireless channel state information, which can include the network bandwidth provided by the wireless capability. This network bandwidth can be used for bandwidth margin assessment to determine whether the wireless bandwidth is sufficient to handle traffic identification, thereby providing a basis for traffic admission and priority mapping methods.

[0065] Terminal devices (APs or management centers) can also compare wireless status data (transmission rate, PER, channel occupancy, etc.) before and after wireless priority mapping adjustment, and clean up and remove cases where there are significant changes in wireless channel quality, so as to avoid accidental changes in wireless link quality, sudden interference, etc., from having a significant impact on the optimization effect and misjudging the result as the direction of policy parameter iteration caused by policy parameter adjustment.

[0066] Step S201-3: Learn the network topology relationship through protocol interaction between devices to obtain network topology information, which includes interference relationship between devices and hidden node relationship between devices.

[0067] IPC and other devices can interact through proprietary protocols to learn network topology relationships (including but not limited to identifying whether the distance between devices will cause interference) and learn the hidden node relationships between devices to obtain network topology information.

[0068] Under the central control and scheduling architecture, each AP and IPC can be used to execute the network topology learning process. Specifically, each AP and IPC can interact through messages (such as Probe messages, Action messages, etc.) to determine whether there are other devices within the wireless communication range, and periodically report the acquired network topology information to the management center. The management center then calculates the complete topology relationship based on the network topology information, so as to reasonably group the packets sent by the devices and avoid simultaneous packet sending.

[0069] Figure 5 This diagram illustrates the hidden node relationship learning and interaction process between devices within a central control scheduling architecture, which is part of a service quality scheduling method provided in this application embodiment. Figure 5 As shown, the management center, acting as the decision-making device in the central control and scheduling architecture, can receive network topology information uploaded by STAs (including STA1, STA2, and STA3). Specifically, STAs can periodically declare their existence (this can be done through broadcast messages, etc., which are not limited to this application). After the AP discovers the discovery message broadcast by the STA via private data frames, it forwards it to other STAs (if the STA that declared its existence is STA1, the AP forwards it to STA2 and STA3), and the STAs (including STA1, STA2, and STA3) maintain the node list. STAs can also periodically trigger wireless probes, sending connectionless wireless probe messages to other STAs. STAs that receive the connectionless wireless probe messages can maintain the visibility relationship between nodes and maintain and report network topology information (including changes in topology visibility relationship) to the management center, which then updates the entire network topology and maintains hidden node relationships.

[0070] In a distributed collaborative scheduling architecture, IPCs can exchange messages (such as probe messages and action messages) to determine whether other devices exist within the wireless communication range. They also broadcast their associated BSSID data frames (data frames that can be received by all devices within the link) and channel information via a private device discovery protocol. For devices that can be discovered via the device discovery protocol but are outside the communication range, the IPC is configured as a hidden node, requiring collaborative scheduling to avoid simultaneous packet transmission.

[0071] Step S202: Execute traffic admission control decisions based on service flow characteristic information, wireless channel state information, and network topology information.

[0072] In the technical solutions provided in this application, the traffic access control decision-making processes under the central control scheduling architecture and the distributed collaborative scheduling architecture are different. Under the central control scheduling architecture, the traffic access control decision-making process may include the following steps Step-A1 to Step-A4.

[0073] Step-A1: Assess the available bandwidth resources of the current network based on service flow characteristics and wireless channel state information.

[0074] Figure 6 This diagram illustrates a traffic admission acceptance process within a central control scheduling architecture for a quality of service (QoS) scheduling method provided in this application. When service traffic changes (e.g., adding or reducing traffic pulled from IPCs), the STA initiates a traffic admission request to the AP (the traffic admission request carries service flow characteristic information, including traffic characteristics, physical layer transmission rate, and traffic size), declaring a change in air interface requirements. The AP then forwards the traffic admission request to the management center. The management center can then assess the available bandwidth resources of the current network using the service flow characteristic information and the received radio channel status information to determine whether the air interface is sufficient to support the traffic request.

[0075] In the technical solution provided in this application embodiment, when the management center makes traffic access judgments, it can calculate the air interface time to be allocated to the STA based on the service flow characteristic information (packet size, packet length, etc.), wireless channel status information (such as PER, channel occupancy rate, etc., used to calculate the actual wireless air interface required for transmission traffic) and network topology information (hidden node relationships can be learned through topology learning. Based on the service packet transmission requirements, a certain proportion of air interface needs to be reserved to cope with sudden interference, contention, and other situations. Hidden nodes require a larger proportion of air interface reservation than scenarios without hidden nodes). Then, it can assess whether the current air interface is sufficient.

[0076] Step-A2: Determine whether the resource requirements of the new service flow exceed the available bandwidth resources.

[0077] The management center can determine whether the resource demand of new service flows exceeds the available bandwidth resources by calculating air interface margin and air interface reservation.

[0078] Step-A3: If the resource requirements of the new service flow do not exceed the available bandwidth resources, then the new service flow is accepted and the corresponding time domain resources are allocated according to the network topology information.

[0079] See also Figure 6If the resource requirements of a new service flow do not exceed the available bandwidth resources (service traffic is not overloaded), the management center returns an acceptance message to the AP. This message declares the air interface time reserved for the STA (specifically, how much air interface time is allocated to the STA). The AP then forwards the acceptance message to the STA. In response to the received acceptance message, the STA sends packets according to the reserved air interface time specified in the message (this reserved air interface time limits its packet sending at the corresponding priority), and limits the packet sending time to no more than a threshold. If the reserved air interface time is exhausted, the STA lowers its priority for packet sending to avoid excessive air interface usage by a single STA and ensures fairness in data transmission.

[0080] Step-A4: If the resource requirements of a new service flow exceed the available bandwidth resources, the new service flow is rejected and a degraded transmission process is triggered.

[0081] Figure 7 This is a schematic diagram of a traffic admission rejection process within a central control scheduling architecture, providing a service quality scheduling method according to an embodiment of this application. In the technical solution provided by this embodiment, if the resource demand of a new service flow exceeds the available bandwidth resources (service traffic overload), the management center returns rejection information to the AP. This rejection information indicates that the management center rejects the traffic admission request issued by the STA. The AP then forwards the rejection information to the STA. In response to the received rejection information, the STA either lowers the priority of the service traffic transmission or roams the service traffic to other APs with sufficient reserved air interfaces.

[0082] In the technical solution provided in this application embodiment, the traffic admission control decision process under the distributed collaborative scheduling architecture has the same or similar control principle as the traffic admission control decision process under the centralized control scheduling architecture. The difference is that the AP executes the process of determining whether the resource demand of a new service flow exceeds the available bandwidth resources.

[0083] Figure 8This is a schematic diagram of a distributed collaborative scheduling architecture traffic admission acceptance process for a service quality scheduling method provided in this application embodiment. When service traffic changes (such as adding or reducing traffic pulled from IPC), the STA initiates a traffic admission request to the AP (the traffic admission request carries service flow characteristic information, including traffic characteristics, physical layer transmission rate, traffic size, etc.), declaring the change in air interface requirements. The AP calculates the reserved space time for the STA and determines whether the resource requirements of the new service flow exceed the available bandwidth resources (whether the service traffic is overloaded). If the resource requirements of the new service flow do not exceed the available bandwidth resources, the AP returns acceptance information to the STA. The received information is used to declare the reserved air interface time for the STA (specifically including how much air interface time is allocated to the STA). In response to the received acceptance information, the STA sends packets according to the reserved air interface time specified in the acceptance information (the reserved air interface time limits its own packet sending at the corresponding priority), and limits the packet sending time to not exceed the threshold. If the reserved air interface time is exhausted, the priority of packet sending is reduced to avoid a single STA excessively occupying the air interface and to ensure the fairness of data transmission.

[0084] Figure 9 This is a schematic diagram of a distributed collaborative scheduling architecture traffic admission and rejection process for a quality of service scheduling method provided in this application embodiment. Figure 9 As shown, if the resource demand of a new service flow exceeds the available bandwidth resources (service traffic overload), the AP returns a rejection message to the STA. The rejection message indicates that the AP rejects the traffic admission request issued by the STA. In response to the received rejection message, the STA either downgrades the service traffic or replaces the front-end AP.

[0085] Step S203: Adjust the priority mapping relationship of service flows based on network topology information and service flow characteristic information.

[0086] Adjust the priority mapping relationship of business flows, including at least one of the following adjustment strategies: The first approach is to remap some high-priority service flows to lower-priority access categories if network resources are scarce.

[0087] The second approach is to adjust the priority mapping strategy for different devices based on the competition between them.

[0088] The third approach is to adjust the priority mapping level based on the actual service quality requirements of the business flow.

[0089] Specifically, in the technical solutions provided in this application embodiment, the need to prioritize network devices in the user's actual environment comes from device-level competition or network-level (BSS-level) competition.

[0090] For device-level contention, the current limited number of IP QoS priorities makes it difficult to cover diverse service latency requirements. When different devices share the same priority, without global coordination, channel contention among devices can easily lead to imbalances (such as aggressive IPC parameters blocking speaker audio). To address this, the technical solution provided in this application statistically assesses and defines the mapping rules from IP QoS to TID by statistically analyzing the transmission requirements of services across devices in the network. For STA devices with unreasonable IP QoS settings or excessive contention, their mapping relationships can be dynamically adjusted, forcibly downgrading them to a lower-priority AC queue, thereby ensuring the transmission quality of critical services.

[0091] In network-level (BSS-level) competition scenarios where the user network simultaneously carries both private networks (such as high-priority services like industrial signaling and video surveillance) and overlay networks (ordinary internet access), without inter-BSS coordination, massive overlay network traffic can overwhelm critical private network services. For example, in a VR experience center, VR headsets and speakers are associated with different BSSs of the same access point; a large amount of VR downlink traffic will affect the real-time performance of the speaker audio. Therefore, this solution ensures reasonable relative priorities between different BSSs by uniformly designing QoS mapping rules for each BSS, thereby achieving cross-BSS critical service assurance.

[0092] Depending on the complexity of the topology, two architectures can be adopted: a centralized control scheduling architecture and a distributed collaborative scheduling architecture, to complete the priority level mapping of the entire network and adjust the priority mapping relationship of service flows.

[0093] Figure 10 This is a schematic diagram illustrating the priority allocation and air interface shortage handling process under a central control scheduling architecture, which is a service quality scheduling method provided in an embodiment of this application. Figure 10 As shown, under the centralized control and scheduling architecture, the management center can proactively assess whether the current air interface resources meet service requirements and dynamically adjust the priority mapping strategy. If the assessment result indicates insufficient air interface resources, the management center will map some service traffic to lower-priority ACs for aggregation and transmission according to the mapping rules defined by the private protocol (IP DSCP → User Priority, TID → AC), replacing the protocol's default mapping table. The degradation process is executed sequentially from low to high according to the TID queue, gradually mapping to BE priority ACs. If the assessment result indicates sufficient air interface resources, the management center will use the protocol's default mapping method to ensure the real-time transmission of high-priority packets.

[0094] The distributed collaborative scheduling architecture relies on parameter interaction between devices to achieve collaborative optimization, flexibly adapting to network scale and load conditions. When the number of devices is large: to avoid n²-level interaction overhead, each device autonomously optimizes its mapping strategy based on locally collected wireless status (such as channel occupancy rate and packet error rate PER). For example, under conditions of high local channel occupancy rate and high PER, more traffic is mapped to low-priority ACs for aggregation and transmission, reducing AC conflicts and improving aggregation efficiency and air interface utilization. When the number of devices is small or the topology is simple, if few terminals are detected on the same channel and the network bottleneck is mainly due to external conflicts (rather than internal competition), the default AC mapping is used; if CCA (Channel Busy) or NAV (Virtual Carrier Sense) occupancy is continuously high at the same time, some TIDs are upgraded and mapped to high-priority ACs to enhance the local channel contention capability.

[0095] Step S204: Perform time-domain resource scheduling and allocation based on priority mapping relationships and network topology information.

[0096] The execution of time-domain resource scheduling and allocation includes at least one of the following scheduling modes: Centralized control scheduling mode: Deterministic packet transmission time slots are allocated to each device based on priority mapping relationships. Distributed cooperative scheduling mode: Packet transmission time slots are allocated by adjusting the channel contention parameters and network topology information of each device.

[0097] The allocation of time-domain resources can include two parts: internal network coordinated scheduling strategy and external air interface preemption strategy.

[0098] For intra-network collaborative scheduling strategies, if inter-device collaborative interaction is required for each TXOP, excessive overhead will occur. Therefore, intra-network time-domain resource allocation adopts a centralized control scheduling architecture and a distributed collaborative scheduling architecture. The centralized control scheduling architecture supports a deterministic channel reservation mechanism. The distributed collaborative scheduling architecture cannot perform deterministic scheduling; it can only indirectly adjust resource allocation by adjusting EDCA parameters to influence the success rate of device channel contention.

[0099] The following mechanisms are supported under the centralized control and scheduling architecture: TDMA mechanism: Utilizing uplink OFDMA and other TDMA mechanisms specified by the wireless protocol, a precise time slice is allocated to a designated STA for uplink transmission based on the packet transmission requirements declared by the STA, while other devices remain silent during this period to avoid internal network conflicts.

[0100] EDCA Fairness Optimization Mechanism: When STAs use the same EDCA parameters, differences in RSSI may lead to different channel contention success rates (STAs with stronger RSSI are more likely to succeed). The management center collects radio information such as RSSI and PER to identify STAs with weaker RSSI and insufficient contention capabilities, and dynamically adjusts their EDCA parameters to enhance their channel contention capabilities and improve communication latency.

[0101] Channel reservation mechanism: The management center reserves channel usage time slots for different devices. During the reserved period, other devices within the network that may interfere with the communication will not access the channel, thus avoiding internal conflicts. This mechanism does not rely on physical layer TDMA and can resolve conflicts during uplink OFDMA transmissions from STAs under different APs.

[0102] The following mechanisms are supported under the distributed collaborative scheduling architecture: Dynamic EDCA adjustment mechanism: STA can adjust EDCA parameters independently to enhance competitiveness and reduce latency when the latency is too high and cannot meet business needs, based on PER and communication latency.

[0103] Grouping Competition Mechanism: Based on wireless association relationships and hidden node information, terminal devices can collaboratively group themselves (e.g., assigning hidden node devices to different groups) and restricting each group to sending data only within a specified time slice. By reducing the number of devices transmitting simultaneously and avoiding concurrent transmission by hidden node devices, the probability of collisions is reduced. This grouping strategy can also be combined with traffic shaping to achieve staggered transmission of traffic from different groups of terminals.

[0104] For the external air interface preemption strategy, when a high-priority message urgently needs to be sent due to communication blockage by other uncontrollable devices (including external devices or internal ordinary wireless devices), the sending device can adopt the following preemption strategy.

[0105] Forced transmission of weak signals: If the air interface is occupied by weak signals, the NAV / CCA mechanism can be ignored, and the signal can be forcibly transmitted at a lower rate to resist external interference.

[0106] Enhance competitiveness: Improve channel contention success rate through strategies.

[0107] If the transmitting device is an AP: Temporarily reject the STA's uplink RTS request. Temporarily issue new EDCA parameters to the STA via Beacon or private signaling (such as increasing the STA's AIFSN and CW) to make it easier for the AP to compete for the channel.

[0108] If the sending device is a STA: appropriately reduce the local EDCA parameters such as AIFSN and CW to improve the success rate of contention.

[0109] Preemption strategies are not used in a conventional manner and require a trigger interval to avoid escalating packet conflicts due to continuous execution. Under the EDCA mechanism, to prevent multiple devices from triggering preemption simultaneously, it should be used in conjunction with the aforementioned emergency traffic resource protection strategy to ensure that only a single device is allowed to perform preemption.

[0110] Step S205: Based on the changes in service quality indicators after scheduling execution, iteratively optimize the priority mapping relationship and the time-domain resource scheduling strategy.

[0111] Based on the changes in service quality indicators (QoS) after scheduling execution, the time-domain resource scheduling strategy is iteratively optimized. This includes: collecting QoS indicator change data after time-domain resource scheduling; identifying and eliminating QoS indicator changes caused by natural fluctuations in the wireless channel; analyzing the actual impact of time-domain resource scheduling on QoS indicators; and obtaining the analysis results. Based on the analysis results, the time-domain resource scheduling strategy is iteratively optimized. The iterative optimization step also includes: identifying and eliminating the impact of sudden or periodic changes in service traffic itself on QoS indicator change data based on changes in service flow characteristic information.

[0112] The adjustment of service flow priority mapping and the allocation of time-domain resources will affect the real-time performance of service interactions and wireless metrics such as channel occupancy and packet loss rate. The system can monitor these impacts to determine the effectiveness of policy adjustments and identify future optimization directions.

[0113] In some embodiments, besides policy parameter adjustments, the following two variables (traffic fluctuation interference and wireless channel quality changes) may also cause fluctuations in QoS indicators such as latency and jitter, and must be excluded when evaluating the policy effect: Traffic fluctuation interference: Based on the traffic identification results (which can come from STA proactive reporting or AP packet transmission and reception statistics), it is necessary to confirm whether the service traffic remains stable in order to eliminate the interference caused by air interface resource fluctuations due to sudden or periodic changes in traffic.

[0114] Wireless channel quality changes: Based on wireless information such as channel occupancy, PER, and channel noise floor, the sampled data needs to be cleaned. If sudden interference occurs, such as a sudden increase in noise floor, a sudden increase in background channel occupancy, or a sharp deterioration in PER, the data for the corresponding time period should be excluded from the strategy effectiveness evaluation.

[0115] Assuming the above-mentioned abnormal factors are ruled out and the input conditions are kept stable, it can be concluded that the changes in QoS indicators are mainly caused by policy adjustments. The system then iteratively optimizes based on this: if the indicators improve after policy adjustment, the adjustment continues in the same direction, but does not exceed the maximum range allowed by the policy; if the indicators deteriorate after policy adjustment, it is determined that over-adjustment may have occurred, and parameters need to be appropriately adjusted back.

[0116] Figure 11 This document presents a flowchart illustrating a mapping strategy feedback iteration process for a service quality scheduling method provided in an embodiment of this application. Figure 11 As shown, the terminal device can first execute the indicator collection process (including traffic information, channel quality, and service quality indicators). For traffic information, the terminal device can first adjust the traffic model, and then perform data cleaning on the processed traffic information. For channel quality data, the terminal device can first perform mutation detection on the channel quality data, and then perform data cleaning based on the mutation detection results. Furthermore, the correlation between the cleaned traffic information, channel quality, and service quality indicators and the policy effect is evaluated to facilitate policy iteration. For detailed data processing procedures and methods, please refer to [link to documentation]. Figure 2 The corresponding processing procedures will not be elaborated here.

[0117] In some embodiments, the device (management center or AP) can also perform traffic shaping on the service flow in the network based on the channel occupancy information in the wireless channel status information, and make the channel occupancy of the entire network tend to be averaged in time through peak scheduling, thereby reducing the conflict between devices within the network.

[0118] To ensure the completeness of the system description, the device (management center or AP) can resolve the issue of instantaneous channel occupancy exceeding the limit through traffic shaping. Two different scheduling architectures (centralized control scheduling architecture and distributed collaborative scheduling architecture) correspond to different traffic shaping processes.

[0119] Under the centralized control and scheduling architecture, each device continuously samples and statistically analyzes channel occupancy (e.g., at 100ms intervals, calculating the overall channel occupancy and the proportion of channels occupied by its own transmissions). The management center periodically (e.g., every second) collects the sampling results from each device to determine if there are significant peaks in channel occupancy caused by multiple devices simultaneously sending packets. If such conflicts exist, the management center will configure traffic shaping strategies for the relevant devices to stagger their transmission times, thereby making the channel occupancy across the entire network more even over time and reducing the probability of conflicts between devices within the network.

[0120] Figure 12 This is a schematic diagram illustrating a traffic shaping process for resolving instantaneous channel occupancy exceeding limits, provided as an embodiment of the Quality of Service (QoS) scheduling method in this application. Figure 12As shown, the management center can obtain channel occupancy rate through a private protocol. Each device, in response to the channel occupancy rate information (such as STA) sent by the management center, fills in the channel occupancy rate sampling result and returns the channel occupancy rate sampling result to the management center through the private protocol. The management center can then check whether there is a momentary exceedance of the global channel occupancy rate based on the channel occupancy rate, and identify the source device occupying the channel occupancy when the global channel occupancy rate momentarily exceeds the limit. Then, it controls the traffic shaping strategy through the private protocol and controls the delay through traffic control system to perform traffic equalization.

[0121] In a distributed collaborative scheduling architecture, STA devices autonomously implement traffic shaping. Based on the channel occupancy sampling statistics, each device analyzes the changing patterns of channel occupancy and appropriately delays packet transmission within the allowable range of service availability to avoid peak channel occupancy periods, thereby reducing conflicts between devices.

[0122] Figure 13 This is a schematic diagram illustrating the traffic shaping effect of a service quality scheduling method provided in an embodiment of this application. Figure 13 As shown, without traffic shaping, the overlapping time periods (as indicated by the dashed box) result in a large number of terminals sending packets concurrently, which can easily lead to conflicts and packet loss. After traffic shaping, the peak packet sending times of different devices can be staggered (there is no overlap in packet sending times), thereby reducing packet conflicts and packet loss.

[0123] In the technical solution provided in this application embodiment, the device can first acquire service flow characteristic information, wireless channel state information, and network topology information in the wireless network, and then perform traffic admission control decisions based on these information. Furthermore, based on the network topology information and service flow characteristic information, it adjusts the priority mapping relationship of service flows, and performs time-domain resource scheduling allocation based on the priority mapping relationship and network topology information. Finally, based on the changes in service quality indicators after scheduling execution, iteratively optimizes the time-domain resource scheduling strategy and priority mapping relationship. In the technical solution provided in this application embodiment, the device can upgrade the traditional static and isolated scheduling system into a globally collaborative scheduling system by acquiring service flow characteristic information, wireless channel state information, and network topology information. This global collaboration resolves policy conflicts between devices, ensures the effectiveness of critical services, guarantees the accuracy and reliability of scheduling strategies, and significantly improves overall network capacity, critical service experience, and the level of operational automation. The device can also learn and adapt to network changes autonomously, overcome policy conflicts between devices, optimize grouping and resource allocation based on topology awareness, significantly reduce transmission conflicts and delays, and eliminate channel fluctuation interference through feedback iteration mechanism, thereby improving the adaptability and reliability of the network in high-density and sparse scenarios.

[0124] It should be understood that, provided there are no logical conflicts, the above-described embodiments can be combined and implemented to adapt to actual application needs. These combined embodiments or implementation schemes are still within the scope of protection of this application.

[0125] Corresponding to the service quality scheduling method in the above embodiments, this application provides a service quality scheduling system, which includes an information collection module and a control management module.

[0126] The information collection module is used to collect service flow characteristic information, wireless channel status information, and network topology information in the wireless network.

[0127] The control and management module is used to execute traffic access control decisions based on service flow characteristic information, wireless channel status information, and network topology information.

[0128] The control and management module is also used to adjust the priority mapping relationship of service flows based on network topology information and service flow characteristic information.

[0129] The control and management module is also used to perform time-domain resource scheduling and allocation based on priority mapping relationships and network topology information.

[0130] The control and management module is also used to iteratively optimize the time-domain resource scheduling strategy based on changes in service quality indicators after scheduling execution.

[0131] The information collection module is specifically used for: identifying service types by analyzing the message characteristics of service flows, obtaining service flow characteristic information, which includes at least one or more of the following: packet transmission frequency, message length, data volume, protocol address, protocol type, and port. It also determines wireless channel state information by monitoring wireless channel state parameters, which include at least one or more of the following: channel occupancy rate, packet error rate, transmission rate, and channel noise floor. Finally, it learns network topology relationships through protocol interactions between devices, obtaining network topology structure information, including interference relationships between devices and hidden node relationships between devices.

[0132] The system supports one of the following scheduling architectures: centralized control scheduling architecture or distributed collaborative scheduling architecture. If the QoS scheduling system adopts a centralized control scheduling architecture, the control and management module is a management device. Specifically, the management device is used to allocate deterministic packet transmission time slots to each device based on priority mapping relationships. If the QoS scheduling system adopts a distributed collaborative scheduling architecture, the control and management module is a wireless access point. Specifically, the wireless access point is used to allocate packet transmission time slots by adjusting the channel contention parameters and network topology information of each device.

[0133] It should be noted that the information interaction and execution process between the units / modules in the above-mentioned service quality scheduling system are based on the same concept as the method embodiment of this application. For details on their specific functions and technical effects, please refer to the method embodiment section, which will not be repeated here.

[0134] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0135] Based on the same inventive concept, this application provides a service quality scheduling device 140. This service quality scheduling device 140 can be implemented as part or all of a computer device by software, hardware or a combination of both, and is used to execute the steps in the service quality scheduling method in the above embodiments.

[0136] Figure 14 A schematic diagram of a service quality scheduling device 140 provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown.

[0137] Reference Figure 14 The quality of service scheduling device 140 includes an acquisition module 1410 and a processing module 1420.

[0138] The acquisition module 1410 is used to acquire service flow characteristic information, wireless channel status information and network topology information in the wireless network.

[0139] The processing module 1420 is used to perform traffic admission control decisions based on service flow characteristic information, wireless channel state information and network topology information.

[0140] The processing module 1420 is also used to adjust the priority mapping relationship of service flows based on network topology information and service flow characteristic information.

[0141] The processing module 1420 is also used to perform time-domain resource scheduling and allocation based on priority mapping relationships and network topology information.

[0142] The processing module 1420 is also used to iteratively optimize the strategy and priority mapping relationship of time-domain resource scheduling based on the changes in service quality indicators after scheduling execution.

[0143] In some embodiments, the acquisition module 1410 is specifically used to: identify the service type by analyzing the message characteristics of the service flow, and obtain service flow characteristic information, wherein the message characteristics include at least one or more of the following: packet transmission frequency, message length, data volume, protocol address, protocol type, and port; determine the wireless channel state information by monitoring the state parameters of the wireless channel, wherein the state parameters include at least one or more of the following: channel occupancy rate, packet error rate, transmission rate, and channel noise floor; and obtain network topology information by learning network topology relationships through protocol interaction between devices, wherein the network topology information includes interference relationships between devices and hidden node relationships between devices.

[0144] In some embodiments, the processing module 1420 is specifically configured to: assess the available bandwidth resources of the current network based on service flow characteristic information and wireless channel state information; determine whether the resource requirements of a new service flow exceed the available bandwidth resources; if the resource requirements of the new service flow do not exceed the available bandwidth resources, then accept the new service flow and allocate corresponding time-domain resources according to the network topology information; if the resource requirements of the new service flow exceed the available bandwidth resources, then reject the new service flow and trigger degraded transmission processing.

[0145] In some embodiments, adjusting the priority mapping relationship of service flows includes at least one of the following adjustment strategies: if network resources are scarce, remapping some high-priority service flows to lower-priority access categories; adjusting the priority mapping strategies of different devices based on the competition among devices; and modifying the priority mapping level based on the actual service quality requirements of the service flows.

[0146] In some embodiments, time-domain resource scheduling and allocation are performed, including at least one of the following scheduling modes: Centralized control scheduling mode: Deterministic packet transmission time slots are allocated to each device according to priority mapping relationships. Distributed cooperative scheduling mode: Packet transmission time slots are allocated by adjusting the channel contention parameters and network topology information of each device.

[0147] In some embodiments, the processing module 1420 is specifically used to: collect service quality index change data after time-domain resource scheduling; identify and exclude index changes caused by natural fluctuations in the wireless channel from the service quality index change data; analyze the actual impact of time-domain resource scheduling on service quality indicators and obtain analysis results; and iteratively optimize the time-domain resource scheduling strategy based on the analysis results.

[0148] In some embodiments, the processing module 1420 is further configured to: identify and exclude the impact of sudden or periodic changes in the service quality indicator data on the changes in the service flow characteristic information based on the changes in the service flow characteristic information.

[0149] In some embodiments, the processing module 1420 is further configured to: perform traffic shaping on the service flow in the network according to the channel occupancy information in the wireless channel state information, and make the channel occupancy of the entire network tend to be averaged in time through peak scheduling, thereby reducing the conflict between devices within the network.

[0150] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0151] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0152] Based on the same inventive concept, embodiments of this application also provide an electronic device.

[0153] Figure 15 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 15 As shown, the electronic device 150 of this embodiment includes: at least one processor 1510 ( Figure 15 Only one is shown in the diagram), memory 1520, and communication module 1530. Memory 1520 stores a computer program 1540 that may run on processor 1510. When processor 1510 executes computer program 1540, it implements the steps in the above-described embodiments of the quality of service scheduling method, for example... Figure 2 Steps S201 to S205 are shown. Alternatively, when processor 1510 executes computer program 1540, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 14 The monitoring module 1410 to the processing module 1420 shown have the following functions. The communication module 1530 can be a separate communication unit used to communicate with external servers or terminal devices.

[0154] Electronic device 150 may include, but is not limited to, a processor 1510 and a memory 1520. Those skilled in the art will understand that... Figure 15 This is merely an example of electronic device 150 and does not constitute a limitation on electronic device 150. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 150 may also include input transmitting devices, network access devices, buses, etc.

[0155] The processor 1510 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0156] In some embodiments, memory 1520 may be an internal storage unit of electronic device 150, such as a hard disk or memory of electronic device 150. Memory 1520 may also be an external storage device of electronic device 150, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on electronic device 150. Memory 1520 may also include both internal and external storage units of electronic device 150. Memory 1520 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer program 1540. Memory 1520 may also be used for temporary storage of data that has been sent or will be sent.

[0157] Furthermore, those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. In the various embodiments of this application, each functional unit can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0158] This application provides a computer-readable storage medium storing a computer program that, when run on an electronic device, causes the electronic device to perform the steps described in the various method embodiments above.

[0159] This application provides a chip, which includes a processor and a memory. The memory stores a computer program, which, when executed by the processor, implements the steps in the various method embodiments described above.

[0160] This application provides a computer program product that, when run on an electronic device, causes the electronic device to execute the steps described in the various method embodiments above.

[0161] It should be understood that the processor mentioned in the embodiments of this application can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0162] It should also be understood that the memory mentioned in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0163] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0164] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0165] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0166] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0167] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0168] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0169] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a large-screen device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0170] Finally, it should be noted that the above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A service quality scheduling method, characterized in that, The method includes: Acquire service flow characteristic information, wireless channel state information, and network topology information in the wireless network; Based on the service flow characteristic information, the wireless channel state information, and the network topology information, traffic admission control decisions are executed. Based on the network topology information and service flow characteristic information, adjust the priority mapping relationship of service flows; Based on the priority mapping relationship and the network topology information, perform time-domain resource scheduling and allocation; Based on the changes in service quality indicators after scheduling execution, the time-domain resource scheduling strategy and the priority mapping relationship are iteratively optimized.

2. The service quality scheduling method according to claim 1, characterized in that, The acquisition of service flow characteristic information, wireless channel state information, and network topology information in the wireless network includes: By analyzing the message characteristics of the service flow, the service type is identified, and the service flow characteristic information is obtained. The message characteristics include at least one or more of the following: packet sending frequency, message length, data volume, protocol address, protocol type, and port. The wireless channel status information is determined by monitoring the status parameters of the wireless channel. The status parameters include at least one or more of the following: channel occupancy rate, packet error rate, transmission rate, and channel noise floor. The network topology relationships are learned through protocol interactions between devices to obtain the network topology information, which includes interference relationships between devices and hidden node relationships between devices.

3. The service quality scheduling method according to claim 2, characterized in that, The step of performing traffic admission control decisions based on the service flow characteristic information, the wireless channel state information, and the network topology information includes: The available bandwidth resources of the current network are assessed based on the service flow characteristic information and the wireless channel state information; Determine whether the resource requirements of the new service flow exceed the available bandwidth resources; If the resource requirements of the new service flow do not exceed the available bandwidth resources, the new service flow will be accepted and corresponding time-domain resources will be allocated according to the network topology information. If the resource requirements of the new service flow exceed the available bandwidth resources, the new service flow is rejected and a downgraded transmission process is triggered.

4. The service quality scheduling method according to claim 2, characterized in that, The adjustment of the priority mapping relationship of the business flow includes at least one of the following adjustment strategies: If network resources are scarce, some high-priority service flows will be remapped to lower-priority access categories; Adjust the priority mapping strategy for different devices based on the competition among them; Adjust the priority mapping level based on the actual service quality requirements of the business flow.

5. The service quality scheduling method according to claim 1, characterized in that, The execution time-domain resource scheduling and allocation includes at least one of the following scheduling modes: Central control and scheduling mode: Based on the priority mapping relationship, a deterministic packet sending time period is allocated to each device; Distributed cooperative scheduling mode: By adjusting the channel contention parameters of each device and the network topology information, packet transmission time periods are allocated.

6. The service quality scheduling method according to claim 1, characterized in that, The strategy for iteratively optimizing the time-domain resource scheduling based on changes in service quality indicators after scheduling execution includes: Collect service quality index change data after the time-domain resource scheduling; Identify and exclude service quality indicator changes caused by natural fluctuations in the wireless channel from the service quality indicator change data; The actual impact of the aforementioned time-domain resource scheduling on service quality indicators was analyzed, and the analysis results were obtained. Based on the analysis results, the time-domain resource scheduling strategy is iteratively optimized.

7. The service quality scheduling method according to claim 6, characterized in that, The iterative optimization step also includes: Based on the changes in the business flow characteristic information, identify and eliminate the impact of sudden or periodic changes in the business flow itself on the changes in the service quality indicator data.

8. The service quality scheduling method according to claim 1, characterized in that, The method further includes: Based on the channel occupancy information in the wireless channel state information, traffic shaping is performed on the service flow in the network. Through peak-shaving scheduling, the channel occupancy of the entire network tends to be averaged over time, reducing conflicts between devices within the network.

9. A service quality scheduling system, characterized in that, The system includes: an information collection module and a control and management module; The information collection module is used to collect service flow characteristic information, wireless channel status information and network topology information in the wireless network; The control and management module is used to execute traffic access control decisions based on the service flow characteristic information, the wireless channel state information, and the network topology information. The control and management module is also used to adjust the priority mapping relationship of service flows based on the network topology information and service flow characteristic information. The control and management module is also used to perform time-domain resource scheduling and allocation based on the priority mapping relationship and the network topology information; The control and management module is also used to iteratively optimize the time-domain resource scheduling strategy based on changes in service quality indicators after scheduling execution.

10. The service quality scheduling system according to claim 9, characterized in that, The information collection module is specifically used for: By analyzing the message characteristics of the service flow, the service type is identified, and the service flow characteristic information is obtained. The message characteristics include at least one or more of the following: packet sending frequency, message length, data volume, protocol address, protocol type, and port. The wireless channel status information is determined by monitoring the status parameters of the wireless channel. The status parameters include at least one or more of the following: channel occupancy rate, packet error rate, transmission rate, and channel noise floor. The network topology relationships are learned through protocol interactions between devices to obtain the network topology information, which includes interference relationships between devices and hidden node relationships between devices.

11. The service quality scheduling system according to claim 9, characterized in that, The system supports one of the following scheduling architectures: centralized control scheduling architecture or distributed collaborative scheduling architecture: If the service quality scheduling system adopts the central control scheduling architecture, the control management module is a management device; The management device is specifically used to allocate a deterministic packet sending time period to each device according to the priority mapping relationship; If the service quality scheduling system adopts the distributed collaborative scheduling architecture, the control and management module is a wireless access point; The wireless access point is specifically used to allocate packet transmission time periods by adjusting the channel contention parameters of each device and the network topology information.

12. An electronic device, characterized in that, It includes a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the quality of service scheduling method as described in any one of claims 1 to 8.

13. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the quality of service scheduling method as described in any one of claims 1 to 8.

Images