A time slot resource dynamic scheduling method for a wireless communication network based on local resource exchange

Abstract

The application provides a wireless communication network time slot resource dynamic scheduling method based on local resource exchange, and relates to the technical field of wireless communication, which comprises the following steps: constructing a wireless communication network topology model; calculating the load priority of each service based on the service priority and the required time slot resource number, and sorting the services according to the load priority; obtaining the individual utility function of each network node under the current allocated time slot resource number based on the sorting result; and establishing a dynamic scheduling problem model with the optimization objective of maximizing the network global utility based on the individual utility function; solving the dynamic scheduling problem model, in the solving process, each network node performs fitness calculation with the neighbor nodes, judges whether to perform time slot resource exchange, obtains the global decision time slot resource number, and completes the time slot resource dynamic scheduling. The application solves the problems of insufficient environmental adaptability, real-time and complexity contradiction of the existing method.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a method for dynamic scheduling of time slot resources in wireless communication networks based on local resource exchange. Background Technology

[0002] Wireless communication networks typically use time division multiple access (TDMA) to enable multi-node access. In dynamic task environments, network topology, service requirements, and channel conditions change frequently, requiring real-time adjustments to time slot resource allocation strategies to ensure the transmission quality of high-priority services.

[0003] In existing technologies, time slot resource scheduling methods are mainly divided into two categories: centralized and distributed. Centralized scheduling methods allocate time slot resources uniformly through a central node. While this can achieve global optimization, it suffers from high signaling overhead, poor scalability, and a high risk of single-point failures, making it difficult to adapt to highly dynamic and adversarial communication environments. Distributed scheduling methods, through autonomous decision-making by each node, offer better scalability and robustness. However, existing distributed scheduling methods still have the following technical shortcomings: (1) Insufficient environmental adaptability: The simulation and verification environment of existing methods is too idealized and does not fully consider real extreme events such as electromagnetic interference, deliberate deception by the other party, and sudden disconnection of nodes. In actual strong confrontation environment, the performance drops sharply.

[0004] (2) The contradiction between real-time performance and complexity: Although complex algorithms such as differential evolution, particle swarm optimization and deep reinforcement learning can achieve better optimization results, they have high computational complexity and put a lot of computational pressure on resource-constrained platforms (such as airborne equipment), making it difficult to meet real-time requirements.

[0005] Therefore, there is an urgent need for a dynamic scheduling method for time slot resources that can achieve high efficiency, real-time performance, and robustness in highly dynamic and adversarial environments. This method should ensure the transmission quality of high-priority services while reducing signaling overhead and computational complexity, and quickly adapt to changes in task requirements to improve overall network performance. Summary of the Invention

[0006] To address the aforementioned problems, this invention provides a dynamic scheduling method for time slot resources in wireless communication networks based on local resource exchange. In the highly dynamic and highly adversarial environment of wireless communication networks, this method solves the technical problems of insufficient environmental adaptability and the contradiction between real-time performance and complexity in existing methods.

[0007] This invention provides a method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange, the method comprising: Construct a wireless communication network topology model; the wireless communication network topology model includes multiple network nodes, each network node is configured with at least one service, and each service has a service priority, required number of time slot resources, and allocated number of time slot resources; The load priority of each service is calculated based on the service priority and the number of required time slot resources, and the services are sorted according to the load priority. Based on the ranking results, the individual utility function of each network node under the current number of allocated time slot resources is obtained; and a dynamic scheduling problem model with the optimization objective of maximizing the global utility of the network is established based on the individual utility function. The dynamic scheduling problem model is solved. During the solution process, each network node performs fitness calculations with its neighboring nodes to determine whether to exchange time slot resources, thereby obtaining the global decision time slot resource count and completing the dynamic scheduling of time slot resources.

[0008] Furthermore, network nodes The Service load priority for similar services The calculation method is as follows: ; in, Indicates business priority; Indicates the number of time slot resources required; Indicates the load factor; This indicates the highest service priority preset in the wireless communication network.

[0009] Furthermore, when sorting services based on load priority, a high-priority preemption rule is also used for sorting, specifically including: If the difference in service priority between the first service with high service priority and the second service with low service priority exceeds the preset preemption level, the first service will skip the load priority sorting and directly preempt the resource allocation order of the second service.

[0010] Furthermore, the method also includes: introducing a smoothing factor to fine-tune the load priority of the preempted service, ensuring that it is between the preceding service and the preempted service.

[0011] Furthermore, individual utility function for: ; in, Represents network nodes Number of decision-making time slot resources satisfy and ; Represents network nodes The Load priority for similar business types; Represents network nodes The Number of time slot resources required for similar business types; This indicates that business has been seized. Represents network nodes The number of time slot resources required; This represents the penalty factor.

[0012] Furthermore, the dynamic scheduling problem model is as follows: ; .

[0013] Furthermore, during the solution process, each network node performs fitness calculations with its neighboring nodes to determine whether to perform time slot resource exchange, specifically including: Calculate the marginal utility of each network node, and determine whether each network node should exchange time slot resources with its neighboring nodes, and the number of time slot resources exchanged, based on the marginal utility; continuously update the resource allocation status of network nodes until the network reaches an equilibrium state, and obtain the global decision time slot resource count.

[0014] Furthermore, the marginal utility of each network node is calculated, specifically including: calculating the left difference and the right difference; wherein, the left difference is the amount of utility reduction caused by reducing a unit of time slot resources, and the right difference is the amount of utility increase caused by increasing a unit of time slot resources.

[0015] Furthermore, determining whether each network node exchanges time slot resources with its neighboring nodes specifically includes: if the left difference of the current network node is less than the right difference of a certain neighboring node, then exchanging time slot resources with that neighboring node.

[0016] Furthermore, determining the number of time slot resources to be exchanged specifically includes taking the smaller value between the time slot resource redundancy number corresponding to the left difference of the current network node and the time slot resource gap number corresponding to the right difference of its neighboring nodes.

[0017] In summary, this invention provides a method for dynamic scheduling of time slot resources in wireless communication networks based on local resource exchange, which achieves the following advantages compared with existing technologies: (1) This invention eliminates the complex global optimization calculation and frequent central node coordination by using a distributed closed loop of load priority sorting, marginal utility calculation and local resource exchange. This enables the system to autonomously and quickly approach the optimal resource configuration in real environments with limited resources, changing topologies and sudden business outbreaks. It realizes the distributed and adaptive dynamic scheduling of time slot resources in wireless communication networks, solves the technical problems of insufficient environmental adaptability and contradiction between real-time performance and complexity in traditional methods in highly dynamic and highly adversarial environments, and significantly improves the overall task guarantee capability of wireless communication networks.

[0018] (2) By introducing load priority calculation and high priority preemption rules, this invention combines service priority with resource demand, realizes differentiated resource guarantee between services with different priorities, and effectively improves the transmission reliability and latency performance of high priority services.

[0019] (3) Based on the distributed resource exchange decision of individual utility function and marginal utility, this invention enables each network node to interact with its corresponding neighbor node only locally, without the need for global information collection and centralized control, which significantly reduces scheduling signaling overhead and computational complexity, and improves the scalability and real-time performance of the system.

[0020] (4) This invention ensures that the network can quickly converge to a stable state in a dynamic business environment by asynchronously executing resource exchange and convergence judgment of the balanced state. It has good environmental adaptability and robustness and can effectively cope with changes in business load and dynamic changes in network topology. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the method steps of a method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange, provided by the present invention. Figure 2 This is a schematic diagram illustrating the principle of a method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange, provided by the present invention. Figure 3 This is a schematic diagram of a wireless communication network topology model for a method of dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange, provided by the present invention. Figure 4This is a schematic diagram of the network topology and network node benefits during the solution process of a dynamic scheduling method for time slot resources in a wireless communication network based on local resource exchange, provided by the present invention. Figure 5 This is a schematic diagram of the first iteration of time slot resource scheduling in a time slot resource dynamic scheduling method for wireless communication networks based on local resource exchange provided by the present invention. Figure 6 This is a schematic diagram of the second iteration of time slot resource scheduling in a method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange provided by the present invention. Figure 7 This is a schematic diagram of the third iteration of the time slot resource scheduling method for a wireless communication network based on local resource exchange, provided by the present invention. Figure 8 This is a schematic diagram of the fourth iteration of the time slot resource scheduling method for a wireless communication network based on local resource exchange provided by the present invention. Figure 9 This is a schematic diagram of the fifth iteration of the time slot resource scheduling method of the wireless communication network time slot resource dynamic scheduling method based on local resource exchange provided by the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0024] It should be noted that, in the description of the embodiments of the present invention, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a method, step, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to the method, step, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the method, step, or apparatus that includes said element.

[0025] To address the technical challenges of insufficient environmental adaptability and the trade-off between real-time performance and complexity in existing time slot resource scheduling methods for wireless communication networks under highly dynamic and adversarial environments, this invention proposes a dynamic scheduling method for time slot resources in wireless communication networks based on local resource exchange. By employing load priority ranking, marginal utility calculation, and local resource exchange, this method achieves distributed, adaptive, and efficient dynamic scheduling of time slot resources in wireless communication networks, meeting the dynamic scheduling requirements for time slot resources in complex environments.

[0026] Specifically, such as Figure 1 and Figure 2 As shown, the method includes: S100: Construct a wireless communication network topology model; the wireless communication network topology model includes multiple network nodes, each network node is configured with at least one service, and each service has a service priority, required number of time slot resources, and allocated number of time slot resources.

[0027] A wireless communication network topology model is constructed by determining the state information of multiple network nodes participating in scheduling, the network topology relationships between these nodes, and the total network time slot resources. For example, Figure 3 The diagram shows a schematic of a wireless communication network topology model. It can visualize the status information of each network node and the network topology relationship between each network node. The shade of the network node's color represents the scarcity of time slot resources, that is, the time slot resource satisfaction rate of the network node, which provides an intuitive guide for subsequent resource flow.

[0028] Network nodes are the basic units in wireless communication networks. The status information of network nodes includes: service attributes and highest service priority. Loading factor Priority seizure level Smoothing factor Each network node possesses a certain number of time slot resources and carries at least one service. Each service includes three key attributes: service priority, required time slot resources, and allocated time slot resources.

[0029] Specifically, business priority is a numerical value used to characterize the importance of a business; the larger the value, the higher the priority. Required time slots are the number of time slot resources that the business needs under ideal conditions to ensure service quality. Allocated time slot resources are the number of time slot resources that the business has actually been allocated in the current state.

[0030] It's important to note that during the dynamic scheduling of time slot resources in a wireless communication network, the time slot resource requirements of each network node vary depending on the types of services it undertakes. Ideally, time slot resources are abundant enough to satisfy the time slot resource requests of all network nodes, allowing resource allocation to be based on their specific needs. However, in reality, time slot resources are limited and cannot simultaneously meet the time slot resource requests of all network nodes. Therefore, in practice, the time slot resources allocated to each network node cannot exceed the total number of time slot resources in the existing network. In other words, during resource allocation, each network node is assigned a specific number of time slot resources, and the sum of the time slot resources allocated to each network node is less than or equal to the total number of time slot resources.

[0031] For example, a wireless communication network topology model includes There are heterogeneous network nodes (members of a wireless communication network); heterogeneity refers to differences in platform type, platform responsibilities, platform services, and resource consumption. The number of time slots required by each network node in the wireless communication network at a given moment is denoted as... The number of allocated time slots for each network node is denoted as . ;and .

[0032] Furthermore, because each network node undertakes different responsibilities and performs different tasks, the service priorities and the number of allocated time slots for each service also differ across network nodes. If we consider network nodes... The current responsibility Class of business is denoted as Then network nodes The business priorities of each business are denoted as follows: The number of demand slot resources is denoted as ,and The number of allocated time slot resources is recorded as follows: ,and , .

[0033] In dynamically changing task environments, the service requirements of wireless communication network nodes are not static, and this change directly drives the need to reallocate time slot resources. Dynamic scheduling of time slot resources can be triggered by setting time thresholds, meaning a dynamic scheduling update is performed periodically; or it can be precisely triggered based on service changes, meaning a dynamic scheduling update is only performed when the service changes.

[0034] To effectively address sudden changes in mission requirements and accurately model the dynamic nature of business needs in a highly dynamic and adversarial real-world environment, enabling efficient resource scheduling, services are categorized into terminating services, changing services, and new services. As an example, service changes include terminating services, changing services, and new services. Only when any of these services occur is the service configuration of the relevant network nodes in the wireless communication network topology model re-initialized, triggering a dynamic scheduling process for time slot resources.

[0035] Termination of service refers to the termination of services provided by a network node after the task requirements have been met and no further service support is required. If a network node... have For services that are terminated, these terminated services should be removed from the service list, and the time slot resources they occupy should be released simultaneously. Let the terminated services be denoted as... ,Should The time slot resources occupied by terminated services are released and then allocated to other services. This allows for the timely recovery of resources released by terminated services, enabling them to serve new or changed services and greatly improving resource utilization.

[0036] Change services refer to services within the original services provided by a network node that undergo changes in priority or the number of required time slots based on task requirements during the task progress. If a network node... have When the business priority of a business type changes, the changed business is recorded as... The changed business priority is recorded as follows: If network nodes have When the number of time slot resources required for a business type changes, the changed business is recorded as follows: The changed number of demand slot resources is denoted as This ensures that high-priority services can quickly obtain the resources they need, meeting the real-time requirements of dynamic environments.

[0037] New services refer to new services generated by new tasks during the task process. If network nodes... have For each new business category, the business priority of each new business is denoted as follows: The number of resource slots required is denoted as .

[0038] The occurrence of any type of business will trigger a new round of dynamic scheduling of time slot resources, update the priority list of network nodes and the number of global decision time slot resources, and recalculate the load priority and marginal utility of network nodes. This makes scheduling no longer a periodic blind operation, but a dynamic drive based on changes in business events, resulting in more timely responses and lower computational overhead.

[0039] S200: Calculate the load priority of each service based on service priority and the number of time slot resources required, and sort the services according to the load priority.

[0040] Taking into account network nodes Bearing Considering factors such as service priority, required time slot resources, allocated time slot resources, and high service priority preemption rules, this invention introduces load priority. Based on service priority, it takes into account the required time slot resources of the service to ensure that services with the same priority but fewer required time slot resources are transmitted first. In fact, services with lower service priority are transmitted first because their required time slot resources are much smaller than those with higher service priority, thereby improving the transmission reliability of high-priority services.

[0041] As an example, network node The Service load priority for similar services The calculation method is as follows: ; in, Indicates business priority; Indicates the number of time slot resources required; Indicates the load factor; This represents the highest preset service priority in the wireless communication network. The load factor represents the baseline impact of service priority on the number of time slots required.

[0042] For example, suppose there are two business priorities, both 5, but business A requires a certain number of time slot resources. Business B's required number of time slot resources After calculation, the load priority of service A will be much higher than that of service B. This means the system will tend to prioritize service A's needs because a task of equal importance can be completed with fewer resources, thus improving overall resource utilization efficiency. In some cases, a service with a priority of 3 but requiring only 1 time slot resource may have a higher load priority than a service with a priority of 6 but requiring 20 time slot resources. This better reflects actual task requirements and avoids high-priority, high-resource-demand services blocking a large number of low-priority, low-resource-demand services.

[0043] To ensure reliable transmission of high-priority services, and to prevent high-priority services with high time slot requirements from being unable to transmit due to an excessive number of low-priority services with limited time slot resources, this invention introduces a high-priority preemption rule. When sorting services according to load priority, this high-priority preemption rule is used for sorting.

[0044] As an example, when sorting services according to load priority, a high-priority preemption rule is also used for sorting. Specifically, if the difference in service priority between a first service with high service priority and a second service with low service priority exceeds a preset preemption level, the first service will skip the load priority sorting and directly preempt the resource allocation order of the second service.

[0045] Specifically, if the priority of the first service is significantly higher than that of the second service, the first service with higher priority can directly bypass the service load priority and preempt the time slot resources of the second service with lower priority, thus ensuring that the first service with higher priority is transmitted first. It should be noted that the "high" and "low" in "high service priority" and "low service priority" are relative terms.

[0046] If network node Shared responsibility For similar businesses, The business priority of the class is denoted as: The number of resource slots required is denoted as .in, Similar businesses refer to those in the original Based on similar business, Class termination business, Class change business, This invention addresses the addition of new services. Services are sorted according to load priority and high-priority preemption rules. To prevent discontinuity in individual utility functions caused by preemption, a smoothing factor is further introduced to fine-tune the load priority of preempted services, ensuring it falls between the preceding and preempted services, thus satisfying the principle of diminishing marginal utility in extended discrete services.

[0047] In other words, this invention also smooths the load priority of the first service with high business priority that meets the high-priority preemption rules by introducing a smoothing factor. To smoothly satisfy the load priority of services that meet the preemption rules This makes the load priority Both greater than the business being preempted It is also smaller than the preceding business of the preempted business. Specifically, if the preempted service is ranked [number]th in the load priority order... If the position is: .

[0048] Furthermore, when That is, the business that was seized. When there are no preceding services, the load priority of services that meet the preemption rules is determined. The highest: .

[0049] As a specific implementation, suppose there are three services on a network node, ordered from highest to lowest load priority: Service A (load priority 12, service priority 4, required time slots 5), Service B (load priority 8, service priority 2, required time slots 15), and Service C (load priority 6, service priority 6, required time slots 2). Based on the load priority order A > B > C, resources will be allocated preferentially to Service A. When a high-priority preemption rule is introduced, a preemption level is preset. Business C's priority level of 6 is 4 levels higher than Business B's priority level of 2, exceeding that of Business C. Therefore, service C disregards the load priority-based ordering and forcibly preempts service B. At this point, the service allocation order becomes: A > C > B.

[0050] However, this hard preemption disrupts the smoothness of the utility function. Therefore, this invention further introduces a smoothing factor. ,For example This is not simply putting service C back in its original position, but rather smoothing the load priority of service C so that its value falls between the load priorities of services A and B. For example, when inserting service C between services A and B and smoothing it out, the load priority of service C = the load priority of service B + ε × (the load priority of service A - the load priority of service B) = 8 + 0.1 × (12 - 8) = 8.4, to ensure that the load priority of C after smoothing is between that of services A and B.

[0051] Furthermore, if service B is the highest priority service, that is, when the preempted service B has no preceding service, when service C is inserted before service B, service C becomes the highest priority service. At this time, when smoothing is performed, the load priority of service C after adjustment = (1 + ε) × load priority of service B = 1.1 × 8 = 8.8, which is greater than 8.

[0052] This ensures that high-priority service C can obtain resources before low-priority service B, meeting the transmission needs of critical services. Furthermore, the smoothing process avoids abrupt changes in the utility function, ensuring that subsequent marginal utility-based switching algorithms can converge stably and efficiently.

[0053] S300: Based on the ranking results, obtain the individual utility function of each network node under the current number of allocated time slot resources; and establish a dynamic scheduling problem model based on the individual utility function with the optimization objective of maximizing the global utility of the network.

[0054] When the network node is completed After prioritizing all services undertaken, the network node is calculated based on the number of allocated time slots. The resulting individual utility function. Based on priority ranking, network nodes calculate their individual utility function under the current resource quantity. This function simulates the diminishing marginal utility in economics: when allocated resources are close to demand, utility increases rapidly; when resources are surplus, utility increases slowly or even decreases due to waste, which is reflected through a penalty term.

[0055] As an example, individual utility function for: ; in, Represents network nodes Number of decision-making time slot resources satisfy and ; Represents network nodes The Load priority for similar business types; Represents network nodes The Number of time slot resources required for similar business types; This indicates that business has been seized. Represents network nodes The number of time slot resources required; This represents the penalty factor.

[0056] Specifically, individual utility function For a piecewise function, the individual utility function must satisfy the principle of diminishing marginal utility, i.e. .

[0057] when When resources are insufficient, network nodes need to allocate the limited number of time slots according to the priority of services. The utility value equals the sum of the load priorities of services that have been satisfied, plus the utility of partially satisfied services calculated proportionally. When the resource requirement is met, the utility value reaches its maximum, equal to the sum of the products of the load priority of all services and their required time slots. At this point, all service requirements are perfectly satisfied. When there is excess, it indicates that resources are in surplus, and the utility value is equal to the maximum utility value minus a penalty term, because excess resources cannot bring additional benefits and may instead cause waste.

[0058] It should be noted that when the number of time slots currently allocated to a network node exceeds the total number of time slots required, it will result in a waste of time slot resources. Therefore, a penalty term is introduced. Resource over-allocation is constrained and used to penalize time slot resources that exceed demand.

[0059] Due to the heterogeneity of network nodes, the revenue generated by each node when occupying the same time slot resource differs; therefore, a single network node can be represented by an individual utility function, denoted as . The global utility function of the entire wireless communication network topology model is denoted as: .

[0060] It should be noted that the total number of time slots in a wireless communication network is finite. A feasible time slot allocation strategy, i.e., the global decision-making time slot resource number for the entire wireless communication network topology model, is... Then the number of global decision time slot resources It cannot exceed the total number of existing time slot resources in the wireless communication network. That is to say, Furthermore, within a single network node, the number of time slot resources is allocated sequentially according to load priority.

[0061] Therefore, the ultimate goal of dynamic scheduling of time slot resources in wireless communication networks is to exchange the number of time slot resources among various network nodes to maximize the global utility of the entire wireless communication network; that is, to meet the demand for time slots of higher priority services as much as possible, so as to maximize the utilization rate of the network's time slot resources.

[0062] This invention transforms the dynamic scheduling process of time slot resources in wireless communication networks into a dynamic scheduling problem model and solves it. As an example, the dynamic scheduling problem model is as follows: ; .

[0063] S400: Solve the dynamic scheduling problem model. During the solution process, each network node performs fitness calculations with its neighboring nodes to determine whether to exchange time slot resources, obtain the global decision time slot resource count, and complete the dynamic scheduling of time slot resources.

[0064] Dynamic scheduling of time slot resources in wireless communication networks is a rapid adjustment of time slot resources based on changes in time slot resource requirements caused by dynamic task / service demands in the current frame. After establishing a problem model for dynamic scheduling of time slot resources in wireless communication networks, a dynamic scheduling method for time slot resources based on local resource exchange is used to solve the problem model, obtaining the amount of time slot resources allocated to each network node. Within a single network node, the number of time slot resources is allocated sequentially according to load priority, thus completing the dynamic scheduling of time slot resources.

[0065] It should be noted that global decision variables The solution process is a process of pursuing the maximization of global utility under a distributed architecture, guided by the individual utility function defined by the load priority rule.

[0066] For example, network nodes in a wireless network bear Similar businesses, The business priority of the class is denoted as: The number of resource slots required is denoted as This information will be generated at the end of the previous moment. This data is initialized during dynamic scheduling. At time... The time slot allocation value for each network node Perform initialization to satisfy... and ,in, This represents the total number of time slots for the entire network; simultaneously, it initializes the service priorities and required time slots for each network node to meet the requirements. and , .

[0067] Based on the population dynamics characteristics of strategy switching in network evolutionary game theory, the number of time slot resources allocated to each network node in the global decision variables during dynamic resource scheduling is: ; in, Indicates time Network Nodes The number of time slot resources allocated; Represents network nodes get The benefit of using resources, also known as marginal utility, ; Indicates the current global decision variable Next network node average returns ; Represents network nodes The total number of time slots required. These are all mathematical expressions of calculus for problems in continuous spaces.

[0068] As an example, during the solution process, each network node performs fitness calculations with its neighboring nodes to determine whether to perform time slot resource exchange, specifically including: Calculate the marginal utility of each network node, and determine whether each network node should exchange time slot resources with its neighboring nodes, and the number of time slot resources exchanged, based on the marginal utility; continuously update the resource allocation status of network nodes until the network reaches an equilibrium state, and obtain the global decision time slot resource count.

[0069] Furthermore, the marginal utility of each network node is calculated, specifically including: calculating the left difference marginal utility and the right difference marginal utility; wherein, the left difference marginal utility is the amount of utility reduction caused by reducing a unit of time slot resources, and the right difference marginal utility is the amount of utility increase caused by increasing a unit of time slot resources.

[0070] It should be noted that the left difference represents the utility lost by a network node when it reduces one time slot; a network node with a large left difference indicates that its resource utilization efficiency is high and the cost of reducing resources is high. The right difference represents the additional utility that a network node can gain by adding one time slot; a node with a large right difference indicates that its resources are extremely scarce and the benefit of increasing resources is high.

[0071] In the dynamic scheduling problem of time slot resources in wireless communication networks, time slot resources exist as discrete, indivisible units, satisfying the principle of diminishing marginal utility in extended discrete networks; furthermore, network nodes... The final allocation of time slot resources is based on the load priority after service smoothing. It equals the marginal utility value.

[0072] Specifically, based on Computing network nodes left difference and right difference , recorded as and The right difference is the current network node. The difference between the point and the next point to the right is denoted as . The left difference is the current network node. The difference between the point and its left adjacent (previous) point is denoted as . .

[0073] In the number of time slot resources Below, wireless communication network nodes Calculate the fitness value (marginal utility value) of each network node. The left and right differences are calculated; and the network nodes are computed. The individual with the largest right difference among its neighbors ,Right now: ;in, Represents network nodes The set of neighboring nodes, individual Indicates connection to network nodes Individuals that exchange time-slot resources. In other words, each network node searches for the neighbor node with the largest right difference among its communication neighbors; this node is the one that most needs to exchange resources at that moment.

[0074] As an example, determining whether each network node exchanges time slot resources with its neighboring nodes specifically includes: if the left difference of the current network node is less than the right difference of a certain neighboring node, then exchanging time slot resources with that neighboring node.

[0075] If satisfied For network nodes with neighboring nodes Perform time slot resource exchange, time slot resource adjustment number (denoted as ( ) represents the network nodes under the current time slot resource allocation scheme. The number of time slots that can be released by the left difference and neighboring nodes The smaller value of the right differential time slot gap number can be expressed as: ;in, For neighboring nodes Number of time slot resource gaps under right difference For network nodes The number of time slots allocated under left difference. In other words, a network node only exchanges time slots with its neighbor node that has the largest right difference among its neighbors, and the amount exchanged is... Ultimately, global resource optimization is achieved through asynchronous iteration.

[0076] As an example, determining the number of time slot resources to be exchanged specifically includes: taking the smaller value between the time slot resource redundancy corresponding to the left difference of the current network node and the time slot resource gap corresponding to the right difference of its neighboring nodes.

[0077] In other words, the number of time slot resources exchanged is the smaller of two values: the number of time slot resource redundancies corresponding to the left difference in the network node; and the number of resource gaps corresponding to the right difference in the neighboring node. This ensures that the exchange is accurate and efficient and does not cause new waste.

[0078] Furthermore, network nodes Its neighboring nodes The exchange of time slot resources can be represented as: ; This completes the time-slot resource scheduling for network nodes. with neighboring nodes The left and right differences, as well as the number of time slots under the left difference and the number of time slot gaps under the right difference, are updated.

[0079] It should be noted that the time slot resource transfer is performed asynchronously. That is, network nodes transfer the calculated number of time slots to neighboring nodes, and each node in the network completes the exchange independently at different times, without the need for global synchronization, thus reducing communication complexity and latency.

[0080] As an example, a network reaches equilibrium when the left difference of all network nodes is not less than the right difference of all their neighbor nodes, and at this point, no node pair satisfies the time slot resource exchange condition. That is to say, all network nodes... All meet This indicates that the network has reached a balanced state, and the time slot resource scheduling converges and stops.

[0081] Repeated updates occur, and after each iteration, resources flow from nodes with relatively low utilization efficiency (smaller left difference) to nodes with more urgent needs (larger right difference). As iterations progress, resource allocation among nodes gradually optimizes, making the conditions for exchange increasingly difficult to meet. When all nodes no longer meet the exchange conditions (…),… When the network reaches equilibrium, it means that any small resource adjustment can no longer improve the overall network efficiency. At this point, the system reaches equilibrium, the algorithm converges and stops iterating, and the whole process ultimately achieves global optimization through local interactions.

[0082] To verify the feasibility of this invention, a method as follows was constructed. Figure 3 The wireless communication network topology model shown has 13 network nodes; the network node connectivity rate is 0.6, which is used to control network connectivity when generating the network topology model; the total number of network time slots is 600; the total number of network node services is 54; the preset highest service priority of the network nodes is 10; the number of service priority preemption levels is 2; the load factor is 2; the smoothing factor is 0.1; the penalty factor is 0.01; the priority of each service in the network node is randomly generated in the interval [1, 10]; the number of time slots required by each service in the network node is randomly generated in the interval [1, 32].

[0083] Each network node also includes information such as the total number of time slots, the number of time slots required by all services it supports, the number of allocated time slots, the time slot utilization rate (number of allocated time slots / total number of time slots for the network node), and the time slot fulfillment rate (total number of time slots for the network node / total number of time slots required by all services). The color intensity of the network nodes in the topology indicates their time slot fulfillment rate.

[0084] During the solution process, each network node will perform fitness calculations with its neighbors to determine whether to exchange time slot resources. During the solution process, the benefits of some network nodes and the overall network benefit are as follows: Figure 4 As shown, wireless communication networks can quickly achieve algorithm convergence.

[0085] Figures 5-9 The different stages of time slot resource scheduling among wireless communication network nodes after each update iteration are given. It can be seen that during the algorithm solution process, the number of time slot resource scheduling times and the number of time slot resource scheduling times gradually decrease. Based on a distributed strategy, this invention realizes the exchange of time slot resources between network nodes and neighboring nodes, enabling the time slot resources occupied by low-priority services of network nodes to be quickly scheduled to high-priority services of neighboring nodes, which can quickly reach a stable network state. This greatly enhances the algorithm's fast convergence capability.

[0086] In summary, this invention addresses the dynamic scheduling problem of time slot resources in wireless communication networks, where time slot resources are discrete and indivisible units. The discrete nature of these time slots allows for strategy switching in network evolutionary games to follow group dynamics characteristics. Through load priority, high-priority preemption rules, and balancing strategies, the invention ensures that the marginal utility of extended discrete resources diminishes. This enables the system to autonomously and rapidly approach optimal resource allocation in real-world environments characterized by resource constraints, topological variations, and sudden service disruptions. This achieves distributed, adaptive, and dynamic scheduling of time slot resources in wireless communication networks, solving the technical problems of insufficient environmental adaptability and the contradiction between real-time performance and complexity inherent in traditional methods under highly dynamic and adversarial environments. Ultimately, this significantly improves the overall task assurance capability of wireless communication networks.

[0087] It should be noted that, for the sake of simplicity, the foregoing embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0088] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0089] In the several embodiments provided in this application, it should be understood that the disclosed methods or systems can be implemented in other ways. For example, the embodiments described above are merely illustrative. For instance, the division of 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.

[0090] 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.

[0091] 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.

[0092] 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 device. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0093] Those skilled in the art will understand that all or part of the circuits in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0094] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

[0095] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0096] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange, characterized in that, The method includes: Construct a wireless communication network topology model; the wireless communication network topology model includes multiple network nodes, each network node is configured with at least one service, and each service has a service priority, required number of time slot resources, and allocated number of time slot resources; The load priority of each service is calculated based on the service priority and the number of required time slot resources, and the services are sorted according to the load priority. Based on the ranking results, the individual utility function of each network node under the current number of allocated time slot resources is obtained; and a dynamic scheduling problem model with the optimization objective of maximizing the global utility of the network is established based on the individual utility function. The dynamic scheduling problem model is solved. During the solution process, each network node performs fitness calculations with its neighboring nodes to determine whether to exchange time slot resources, thereby obtaining the global decision time slot resource count and completing the dynamic scheduling of time slot resources.

2. The method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 1, characterized in that, Network Nodes The Service load priority for similar services The calculation method is as follows: ; in, Indicates business priority; Indicates the number of time slot resources required; Indicates the load factor; This indicates the highest service priority preset in the wireless communication network.

3. The method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 2, characterized in that, When sorting services according to load priority, a high-priority preemption rule is also used for sorting, specifically including: If the difference in service priority between the first service with high service priority and the second service with low service priority exceeds the preset preemption level, the first service will skip the load priority sorting and directly preempt the resource allocation order of the second service.

4. The method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 3, characterized in that, The method further includes: introducing a smoothing factor to fine-tune the load priority of the preempted service, ensuring that it is between the preceding service and the preempted service.

5. The method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 1, characterized in that, Individual utility function for: ； in, Represents network nodes Number of decision-making time slot resources satisfy and ; Represents network nodes The Load priority for similar business types; Represents network nodes The Number of time slot resources required for similar business types; This indicates that business has been seized. Represents network nodes The number of time slot resources required; This represents the penalty factor.

6. The method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 5, characterized in that, The dynamic scheduling problem model is as follows: ； 。 7. A method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to any one of claims 1 to 5, characterized in that, During the solution process, each network node performs fitness calculations with its neighboring nodes to determine whether to perform time slot resource exchange, specifically including: Calculate the marginal utility of each network node, and determine whether each network node should exchange time slot resources with its neighboring nodes, and the number of time slot resources exchanged, based on the marginal utility; continuously update the resource allocation status of network nodes until the network reaches an equilibrium state, and obtain the global decision time slot resource count.

8. The method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 7, characterized in that, Calculating the marginal utility of each network node specifically includes: calculating the left difference and the right difference; wherein the left difference is the decrease in utility caused by reducing a unit of time slot resources, and the right difference is the increase in utility caused by increasing a unit of time slot resources.

9. A method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 8, characterized in that, Determining whether each network node exchanges time slot resources with its neighboring nodes specifically includes: if the left difference of the current network node is less than the right difference of a certain neighboring node, then exchanging time slot resources with that neighboring node.

10. A method for dynamic scheduling of time slot resources in a wireless communication network based on local resource exchange according to claim 8, characterized in that, Determining the number of time slot resources to be exchanged specifically includes taking the smaller value between the time slot resource redundancy number corresponding to the left difference of the current network node and the time slot resource gap number corresponding to the right difference of its neighboring nodes.

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