A global resource allocation method for a cross-regional highway toll management system

Abstract

This invention discloses a global resource allocation method for a cross-regional highway toll management system, relating to the field of intelligent highway toll management technology. The method involves collecting resource information from each resource scheduling and management node and each toll station to obtain a global resource status. Based on this global resource status, the method initializes the global allocation for each toll station, generating an initial global resource allocation structure. Then, based on the resource information of each toll station, the method dynamically adjusts the toll station allocation structure to obtain a resource-balanced allocation structure. The method monitors the resource status in the resource-balanced allocation structure in real time and calculates a resource imbalance index based on the resource status. The method then dynamically adjusts the resource-balanced allocation structure based on the resource imbalance index. By sensing the resource status of the entire system and performing dynamic cross-regional resource allocation based on a target optimization strategy, the overall resource utilization rate of the system is improved, and operating costs are reduced.

Description

Technical Field

[0001] This invention relates to the field of intelligent highway toll management technology, specifically to a global resource allocation method for cross-regional highway toll management systems. Background Technology

[0002] With the continuous expansion of the highway network and the rapid growth of traffic volume, the traditional centralized toll management model is struggling to meet the core demands for continuous improvement in operational efficiency, service capacity, and user experience. Traditional network-based toll collection requires the establishment of toll stations near each toll plaza. Therefore, actual highway networks necessitate numerous toll stations along road sections, along with toll information systems and management personnel. Even if a toll plaza experiences low traffic volume, the corresponding information resources and personnel must still be in place. In reality, many toll plazas with low traffic volume, and during periods of low traffic volume at most toll plazas, have relatively idle information and human resources. This "station-isolated" architecture statically binds computing, storage, and human resources to specific stations, creating rigid "resource islands" that cannot be dynamically allocated based on fluctuations in network traffic, resulting in low overall system resource utilization and high operating costs.

[0003] To address this, existing toll collection systems, previously deployed separately on individual lanes, have been transformed into a unified station-level transaction system deployed at the toll plaza, achieving centralized deployment and unified management of system resources. However, current intelligent cloud toll station construction focuses more on implementing the functions of individual cloud toll stations, making each toll station an independent single point of failure, with its business continuity entirely dependent on the reliability of the local system. If a station fails, the toll plaza's operations will immediately be paralyzed. Due to the strong binding of resources to stations, it is impossible to guarantee the continuity of core services through resource reorganization and business migration, resulting in high overall business risk.

[0004] As toll collection systems gradually become platform-based and networked, the key is to achieve global management of all types of resources in the highway toll collection management system and realize efficient and intelligent scheduling of global resources. Summary of the Invention

[0005] The purpose of this invention is to provide a global resource allocation method for a cross-regional highway toll management system. By constructing a unified and quantitative resource evaluation model, the system can perceive the resource status of the entire system in real time and perform dynamic resource allocation across regions based on target optimization strategies, thereby improving the overall resource utilization rate of the system and reducing operating costs.

[0006] To achieve the above objectives, this application provides the following technical solution:

[0007] This application provides a global resource allocation method for a cross-regional highway toll management system, specifically including the following steps:

[0008] S1. Collect resource information from each resource scheduling and management node and each toll station, and aggregate it at the global central management node to obtain the global resource status;

[0009] S2. Based on the global resource status, initialize the global allocation of each toll station, generate the initial global resource allocation structure, and dynamically adjust the toll stations in the initial global resource allocation structure according to the resource information of each toll station to obtain the resource balanced allocation structure in the resource balanced state.

[0010] S3. Obtain the current monitoring mode of the resource balance allocation structure, obtain the resource information of the toll station during the monitoring period corresponding to the current monitoring mode, and calculate the resource imbalance index based on the resource information of the toll station during the current monitoring period.

[0011] S4. Based on the resource information of the toll station and the resource imbalance index, comprehensively judge whether the resource allocation is unbalanced during the monitoring period. If the resource allocation is unbalanced, use an incremental adjustment algorithm based on local search to dynamically adjust the resource balance allocation structure.

[0012] S5. Based on the resource imbalance index calculated during the monitoring period, determine whether the current monitoring mode needs to be adjusted and the monitoring frequency adjusted accordingly to obtain the monitoring period for each monitoring session.

[0013] In some specific implementation plans, the resource information of toll stations includes the latitude and longitude location of each toll station, historical annual traffic volume, number of historical processed work orders, work order processing time, and the number of station-level cloud console modules set up within the toll station.

[0014] In some specific implementations, the process of generating the initial global resource allocation structure is as follows:

[0015] Determine the number K of resource scheduling and management nodes connected to the global resource status network, connect each resource scheduling node to the global central management node, and establish mutual access channels between the resource scheduling nodes through the cloud service network so that each resource scheduling node can serve as a backup node for the other.

[0016] Based on the jurisdiction of the resource scheduling management node and the latitude and longitude of the toll station, the toll stations located within the jurisdiction of the resource scheduling management node are incorporated into each resource scheduling management node, enabling each toll station to communicate with its corresponding resource scheduling management node to obtain the initial global resource allocation structure.

[0017] In some specific implementation schemes, the specific process of obtaining a resource-balanced allocation structure in a resource-balanced state is as follows:

[0018] S21. Calculate the historical annual traffic volume of all toll stations under the jurisdiction of each resource scheduling and management node, and the average historical traffic volume of all resource scheduling and management nodes;

[0019] S22. Compare the historical annual traffic flow of each resource scheduling management node, find the resource scheduling management node with the highest historical annual traffic flow Amax and the lowest historical annual traffic flow Amin, calculate the traffic flow difference between Amax and Amin, and determine whether the traffic flow difference is greater than the set traffic flow threshold.

[0020] S23. If it is greater than, then iterate through each toll station in the resource scheduling management node with the highest historical annual traffic volume, and recalculate the historical annual traffic volume A1 of all toll stations in the resource scheduling management node after moving each toll station out of or into the resource scheduling management node;

[0021] S24. Calculate the flow difference between A1 and Amin. If the flow difference is still greater than the set flow threshold, repeat steps S23-S24 until the flow difference between the resource scheduling management nodes is less than the set flow threshold.

[0022] S25. Repeat steps S22-S24 until the flow difference between all resource scheduling and management nodes is adjusted to within the set flow threshold. Stop the loop and output the final resource balance allocation structure.

[0023] In some specific implementation plans, the method for calculating the resource imbalance index is as follows:

[0024] S31. Statistically monitor the number of historical work orders processed by each toll station in each resource scheduling management node during the monitoring period, the work order processing time, and the number of station-level cloud seat modules. Calculate the total number of work orders T, the total number of station-level cloud seat modules N, and the average work order processing time t of the resource scheduling management node during the monitoring period.

[0025] The capacity C of the computing station-level cloud console module is calculated as C = N * H / t, where H represents the working duration of a single monitoring period.

[0026] S32. Calculate the load rate L=T / C for each resource scheduling and management node based on the total number of work orders T and the production capacity C;

[0027] S33. Calculate the average load L_Avg and the standard deviation L_Std of the load rate of all resource scheduling and management nodes. Based on the average load L_Avg and the standard deviation L_Std, calculate the resource imbalance index U=L_Std / L_Avg.

[0028] In some specific implementation plans, resource allocation imbalance is determined by comprehensively considering all of the following conditions:

[0029] Condition 1: When the resource imbalance index is greater than or equal to the preset maximum equilibrium threshold, a global imbalance is determined.

[0030] Condition 2: When the load rate L of any resource scheduling and management node is greater than 1.5*L_Avg or less than 0.5*L_Avg, a local imbalance is determined.

[0031] Condition 3: If global imbalance is detected in multiple consecutive monitoring periods, and the resource imbalance index shows an increasing trend in multiple monitoring periods, then the trend is judged to be out of control.

[0032] In some specific implementation schemes, the process of dynamically adjusting the resource balancing allocation structure using the incremental adjustment algorithm based on local search is as follows:

[0033] S41. Divide the resource scheduling management nodes in the resource balanced allocation structure into several pairs of resource scheduling management nodes, and calculate the load difference between each pair of resource scheduling management nodes.

[0034] S42. If the load difference is greater than the load threshold, calculate the difference between the resource imbalance index before and after the resource adjustment in the resource scheduling management node pair, obtain the migration benefit, and determine the resource balance allocation structure after the resource adjustment based on the migration benefit.

[0035] S43. Calculate the load rate and resource imbalance index of each resource scheduling and management node in the resource balanced allocation structure after resource adjustment.

[0036] S44. Determine whether a local imbalance has occurred based on the load rate of the resource scheduling and management node, and determine whether a global imbalance has occurred based on the resource imbalance index.

[0037] S45. Repeat steps S41-S44 until the migration benefit is less than or equal to 0 and there is no local imbalance or global imbalance, thus obtaining the final dynamically adjusted resource equilibrium allocation structure.

[0038] In some specific implementation plans, the process of determining the resource allocation structure after resource adjustment is as follows:

[0039] For the resource scheduling management node pair: the first node and the second node, calculate the migration benefit of moving any toll station from the first node to the second node, and traverse each toll station of the first node to obtain the migration benefit of moving each toll station.

[0040] Select the toll station with the highest migration benefit, and determine whether the load rate in the first and second nodes reverses after moving the toll station with the highest migration benefit to the second node.

[0041] If no reversal occurs, move the toll station with the highest migration benefit to the second node.

[0042] The beneficial effects of this invention are as follows:

[0043] This invention defines global rules for resource sharing and scheduling by generating a resource allocation structure in a resource-balanced state, fundamentally realizing the transformation of resources from "site-specific" to "region-shared" mode, which is the key to realizing cross-site business collaborative processing.

[0044] Based on global resources, the system achieves global optimization and dynamic adaptation in resource scheduling. Specifically, the intelligent scheduling algorithm breaks down the barriers of traditional models where human and computing resources are constrained by geographical location and single business nodes. By constructing a unified and quantitative resource evaluation model, the algorithm can perceive the business load status of the entire system in real time and perform dynamic resource allocation across regions based on target optimization strategies, thereby improving the overall resource utilization of the system and reducing operating costs. Attached Figure Description

[0045] Figure 1 A block diagram of the highway toll management system provided in an embodiment of the present invention;

[0046] Figure 2 A flowchart illustrating a global resource allocation method for a cross-regional highway toll management system, as provided in an embodiment of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0049] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0050] Furthermore, for clarity and brevity, descriptions of well-known structures, functions, and configurations may have been omitted. Those skilled in the art will recognize that various changes and modifications can be made to the examples described herein without departing from the spirit and scope of this disclosure.

[0051] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0052] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0053] Example 1

[0054] This embodiment 1 provides a global resource allocation method for a cross-regional highway toll management system, such as... Figure 1 As shown, the highway toll management system consists of a central cloud warehouse server, N regional cloud warehouse servers, and station-level management servers deployed at each toll station, all operating at multiple levels from top to bottom within the management area. The central cloud warehouse server serves as the global central management node, monitoring the working status of each resource scheduling management node and coordinating business collaboration among them based on their status. It verifies whether each resource scheduling management node is functioning normally or offline, determines if there are any faults, and schedules the resource scheduling management nodes accordingly. The regional cloud warehouse servers also serve as resource scheduling management nodes, with each node acting as a backup for the others. The station-level management servers include lane tolling modules deployed in each toll lane within the toll station and several station-level cloud agent modules.

[0055] In this system, a management region refers to a specific province. Each management region has a central cloud warehouse server that coordinates and manages all resources within the region. In the existing highway toll collection system, toll stations are deployed at the beginning and end of each highway. Each regional cloud warehouse server manages multiple station-level management servers. Each toll station has a station-level management server, and each toll station has multiple toll lanes. The station-level management server includes lane toll collection modules deployed in each toll lane within the toll station, as well as multiple station-level cloud agent modules that handle manual toll collection transactions. These station-level cloud agent modules are the terminal devices used by toll collection management personnel to receive manual toll collection transactions. The resource scheduling and management nodes consist of N (N>1) nodes physically distributed across different regions. Each regional cloud warehouse server can manage the operations of multiple toll stations within its region. For example, each regional cloud warehouse server can manage all toll stations on a specific highway. Thus, each regional cloud warehouse server manages all toll stations on a single road, with clearly defined regional divisions. To achieve full resource integration, a redundant backup structure is adopted. The global central management node and each resource scheduling management node serve as backup nodes for each other, and the resource scheduling management nodes themselves serve as backup nodes for each other. The toll lane registry and agent registry of each resource scheduling management node are backed up in real-time on at least M (M>1) backup nodes, including the global central management node and other resource scheduling management nodes. In this way, when one node fails, the remaining N-1 nodes can fully maintain all normal functions of the resource scheduling management node.

[0056] This embodiment's method is implemented based on the aforementioned three-tier architecture of the highway toll management system: central level, regional level, and station level. The global central management node, acting as the global resource allocation and configuration management center, is responsible for aggregating the operational status and workload data of toll stations within each resource scheduling management node, and generating optimization suggestions for the resource allocation structure based on this. Under the guidance of this resource allocation structure, the resources of each toll station within the resource scheduling management node are integrated into a shared pool. The resource scheduling management node is responsible for collecting specific business work orders from each station within its region and allocating and coordinating them. Toll station management personnel process business work orders from their own station or other toll stations within the resource scheduling management node through the station-level cloud console module. When the global central management node is working normally, global resource allocation is achieved through the global central management node. The specific process of the global resource allocation method is as follows:

[0057] S1. Data Acquisition: Collect resource information from each resource scheduling and management node and each toll station, and aggregate it at the global central management node to obtain the global resource status;

[0058] The resource information of each resource scheduling and management node includes the jurisdiction area, and the resource information of each toll station includes the latitude and longitude location of each toll station, the historical annual traffic volume, the number of historical processed work orders, the work order processing time, and the number of station-level cloud seat modules set up in the toll station.

[0059] S2. Intelligent resource scheduling based on global resource status: Based on the global resource status, the global allocation of each toll station is initialized, an initial global resource allocation structure is generated, and the toll stations with the initial global resource allocation structure are dynamically adjusted according to the resource information of each toll station to obtain a resource balanced allocation structure with balanced resource status.

[0060] 1. Based on the global resource status, initialize the global allocation for each toll station and generate the initial global resource allocation structure:

[0061] The process of determining the number K of resource scheduling and management nodes connected to the global resource status network, incorporating toll stations located within their jurisdictions into the resource scheduling and management nodes based on their latitude and longitude coordinates, and determining the resource allocation structure, is as follows:

[0062] Determine the number K of resource scheduling and management nodes connected to the global resource status network, connect each resource scheduling node to the global central management node, and establish mutual access channels between the resource scheduling nodes through the cloud service network so that each resource scheduling node can serve as a backup node for the other.

[0063] Based on the jurisdiction of the resource scheduling management node and the latitude and longitude of the toll station, the toll stations located within the jurisdiction of the resource scheduling management node are incorporated into each resource scheduling management node, enabling each toll station to communicate with its corresponding resource scheduling management node to obtain the initial global resource allocation structure.

[0064] 2. Based on the resource information of each toll station, a greedy algorithm is used to dynamically adjust the toll station's initial global resource allocation structure to obtain a resource-balanced allocation structure. The specific process is as follows:

[0065] S21. Calculate the historical annual traffic volume of all toll stations under the jurisdiction of each resource scheduling and management node, and the average historical traffic volume of all resource scheduling and management nodes, AvgTraffic.

[0066] S22. Compare the historical annual traffic flow of each resource scheduling management node, find the resource scheduling management node with the highest historical annual traffic flow Amax and the lowest historical annual traffic flow Amin, calculate the traffic difference between Amax and Amin, and determine whether the traffic difference is greater than the set traffic threshold (assuming the set balance threshold is 0.2*AvgTraffic, that is, the deviation of the traffic flow of each resource scheduling management node from the average value is allowed to be within 20%).

[0067] S23. If it is greater than, then iterate through each toll station in the resource scheduling management node with the highest historical annual traffic volume, and recalculate the historical annual traffic volume A1 of all toll stations in the resource scheduling management node after moving each toll station out of or into the resource scheduling management node;

[0068] S24. Calculate the flow difference between A1 and Amin. If the flow difference is still greater than the set flow threshold, repeat steps S23-S24 until the flow difference between the resource scheduling management nodes is less than the set flow threshold. At this time, the flow difference between the two nodes is the minimum.

[0069] S25. Repeat steps S22-S24 until the flow difference between all resource scheduling and management nodes is adjusted to within the set flow threshold. Stop the loop and output the final resource balance allocation structure.

[0070] S3. Monitor the resource status in the resource balance allocation structure in real time, calculate the resource imbalance index based on the resource status, and dynamically adjust the resource balance allocation structure according to the resource imbalance index. The specific process is as follows:

[0071] S31. Obtain the current monitoring mode of the resource balance allocation structure, and obtain the resource information of the toll station during the monitoring period corresponding to the current monitoring mode;

[0072] S32. Calculate the resource imbalance index based on the resource information of the toll stations during the current monitoring period;

[0073] The method for calculating the resource imbalance index is as follows:

[0074] S321. Calculate the number of historical work orders processed by each toll station in each resource scheduling and management node during the monitoring period, the work order processing time, and the number of station-level cloud console modules. Calculate the total number of work orders T, the total number of station-level cloud console modules N, and the average work order processing time t of the resource scheduling and management node during the monitoring period.

[0075] The capacity C of the computing station-level cloud console module is calculated as C = N * H / t, where H represents the working duration of a single monitoring period.

[0076] S322. Calculate the load rate L=T / C for each resource scheduling and management node based on the total number of work orders T and the production capacity C.

[0077] S323. Calculate the average load L_Avg and the standard deviation L_Std of the load rate of all resource scheduling and management nodes. Based on the average load L_Avg and the standard deviation L_Std, calculate the resource imbalance index U=L_Std / L_Avg.

[0078] S33. Based on the resource information of the toll station and the resource imbalance index, comprehensively judge whether the resource allocation is unbalanced during the monitoring period;

[0079] A comprehensive assessment of resource allocation imbalance is made when all of the following conditions are met:

[0080] Condition 1: When the resource imbalance index is greater than or equal to the preset maximum equilibrium threshold, a global imbalance is determined.

[0081] Condition 2: When the load rate L of any resource scheduling and management node is greater than 1.5*L_Avg or less than 0.5*L_Avg, a local imbalance is determined.

[0082] Condition 3: If global imbalance is detected in multiple consecutive monitoring periods, and the resource imbalance index shows an increasing trend in multiple monitoring periods, then the trend is judged to be out of control.

[0083] S34. If resource allocation is unbalanced, an incremental adjustment algorithm based on local search is used to dynamically adjust the resource allocation structure. The specific process is as follows:

[0084] S341. Divide the resource scheduling management node in the resource balanced allocation structure into several resource scheduling management node pairs, calculate the load difference between each resource scheduling management node pair, and if the load difference is less than the preset load threshold TH, it means that the load difference between the two nodes is too small, so skip it.

[0085] S342. If the load difference is greater than the load threshold TH, calculate the difference between the resource imbalance index before and after resource adjustment in the resource scheduling management node pair to obtain the migration benefit, and determine the resource balance allocation structure after resource adjustment based on the migration benefit. The specific process is as follows:

[0086] For the resource scheduling management node pair: the first node and the second node, calculate the migration benefit of moving any toll station from the first node to the second node, and traverse each toll station of the first node to obtain the migration benefit corresponding to moving each toll station.

[0087] Select the toll station with the highest relocation benefit and determine whether the load rate of the first and second nodes reverses after moving the toll station with the highest relocation benefit to the second node; that is, if the load rate of the first node is greater than that of the second node before the toll station is moved, the load rate of the second node cannot be greater than that of the first node after the toll station is moved.

[0088] If no reversal occurs, move the toll station with the highest migration benefit to the second node.

[0089] S343. Calculate the load rate and resource imbalance index of each resource scheduling and management node in the resource balanced allocation structure after resource adjustment.

[0090] S344. Determine whether a local imbalance has occurred based on the load rate of the resource scheduling and management node, and determine whether a global imbalance has occurred based on the resource imbalance index.

[0091] S345. Repeat steps S341-S344 to adjust the toll station scheduling among the resource scheduling nodes until the migration benefit is less than or equal to 0 and there is no local imbalance or global imbalance, thus obtaining the final dynamically adjusted resource balance allocation structure.

[0092] To make it easier to understand, take a pair of resource scheduling management nodes 1 and 2 as an example. Traverse each toll station of resource scheduling management node 1, simulate moving the modular management seat resources of toll station T from node 1 to node 2, calculate the migration benefit B, and select the toll station T with the highest migration benefit for movement. However, after the movement, there should be no load reversal within node 1 and node 2.

[0093] Repeat the above steps until no migration benefit greater than 0 is found, or condition one or condition two is not met, then stop.

[0094] S35. Based on the resource imbalance index calculated during the monitoring period, determine whether it is necessary to adjust the current monitoring mode and adjust the monitoring frequency accordingly to obtain the monitoring period for each monitoring session.

[0095] During each monitoring period, the system will re-determine the monitoring mode and frequency based on the resource imbalance index at the end of the monitoring period. The monitoring correspondence between the resource imbalance index and the monitoring frequency is shown in Table 1.

[0096] Table 1. The state represented by the resource imbalance index

[0097]

[0098] The monitoring frequency switching rules include two types: immediate upgrade and cautious downgrade. Immediate upgrade: When the imbalance index reaches the threshold of a higher tier, the monitoring frequency is immediately increased. Cautious downgrade: At a higher tier, the frequency can only be reduced if the index is consistently below the current tier threshold for three consecutive monitoring sessions. Adjustments to the resource balancing allocation structure in the traffic balance state are triggered when any of the following conditions are met:

[0099] Condition 1: When the resource imbalance index U ≥ 0.40, a global imbalance is determined;

[0100] Condition 2: When the load rate L of any resource scheduling and management node is greater than 1.5*L_Avg or less than 0.5*L_Avg, a local imbalance is determined.

[0101] Condition 3: If the resource imbalance index U monitored for three consecutive times under the "enhanced mode" continues to deteriorate (each time higher than the last), then the trend is judged to be out of control.

[0102] It is understandable that the core of this embodiment lies in the generation of the "resource allocation structure," which is the strategy engine of the entire method. It defines the global rules for resource sharing and scheduling, fundamentally realizing the transformation of resources from "site-specific" to "area-shared," and is key to achieving cross-site business collaborative processing. Specifically, resource information collected from each toll station is aggregated in the central management node to generate a global resource status view, and intelligent resource scheduling is based on this view. Based on the latitude and longitude of each toll station and its annual traffic volume, toll stations to be managed are divided for each area node, determining the initial resource allocation structure; the system imbalance index is dynamically monitored, and the monitoring level is divided into normal mode, enhanced mode, and emergency mode according to different indices; the system resource allocation is judged based on the index and the road network load rate to determine whether the entire system's resource allocation has reached a balanced state; if not, it is dynamically adjusted; finally, the system imbalance state is adjusted based on a local search incremental adjustment algorithm until balance is achieved, outputting the final resource allocation structure. This achieves global optimization and dynamic adaptation of resource scheduling. The intelligent scheduling algorithm of this invention breaks the barriers of traditional models where human and computing resources are constrained by geographical location and single business nodes. By constructing a unified and quantitative resource evaluation model, the algorithm can perceive the business load status of the global system in real time and perform dynamic resource allocation across regions based on the target optimization strategy, thereby improving the overall resource utilization of the system and reducing operating costs.

[0103] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Based on the technical essence of the present invention, any simple modifications, equivalent substitutions, and improvements made to the above embodiments within the spirit and principles of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A global resource allocation method for a cross-regional highway toll management system, characterized in that, Specifically, the following steps are included: S1. Collect resource information from each resource scheduling and management node and each toll station to obtain the global resource status; S2. Based on the global resource status, initialize the global allocation of each toll station, generate the initial global resource allocation structure, and dynamically adjust the toll stations in the initial global resource allocation structure according to the resource information of each toll station to obtain the resource balanced allocation structure in the resource balanced state. The specific process of obtaining the resource equilibrium allocation structure in a resource equilibrium state is as follows: S21. Calculate the historical annual traffic volume of all toll stations under the jurisdiction of each resource scheduling and management node, and the average historical traffic volume of all resource scheduling and management nodes; S22. Compare the historical annual traffic flow of each resource scheduling management node, find the resource scheduling management node with the highest historical annual traffic flow Amax and the lowest historical annual traffic flow Amin, calculate the traffic flow difference between Amax and Amin, and determine whether the traffic flow difference is greater than the set traffic flow threshold. The set traffic flow threshold is the average historical traffic flow multiplied by the deviation value. S23. If it is greater than, then iterate through each toll station in the resource scheduling management node with the highest historical annual traffic volume, and recalculate the historical annual traffic volume A1 of all toll stations in the resource scheduling management node after moving each toll station out of or into the resource scheduling management node. S24. Calculate the flow difference between A1 and Amin. If the flow difference is still greater than the set flow threshold, repeat steps S23-S24 until the flow difference between the resource scheduling management nodes is less than the set flow threshold. S25. Repeat steps S22-S24 until the flow difference between each resource scheduling and management node is adjusted to within the set flow threshold. Stop the loop and output the final resource balance allocation structure. S3. Obtain the current monitoring mode of the resource balance allocation structure, obtain the resource information of the toll station during the monitoring period corresponding to the current monitoring mode, and calculate the resource imbalance index based on the resource information of the toll station during the current monitoring period. S4. Based on the resource information of the toll station and the resource imbalance index, comprehensively judge whether the resource allocation is unbalanced during the monitoring period. If the resource allocation is unbalanced, use an incremental adjustment algorithm based on local search to dynamically adjust the resource balance allocation structure. S5. Based on the resource imbalance index calculated during the monitoring period, determine whether the current monitoring mode needs to be adjusted and the monitoring frequency adjusted accordingly to obtain the monitoring period for each monitoring session.

2. The global resource allocation method for a cross-regional highway toll management system according to claim 1, characterized in that, The resource information of each toll station includes its latitude and longitude location, historical annual traffic volume, number of historical processed work orders, work order processing time, and the number of station-level cloud console modules set up within the toll station.

3. The global resource allocation method for a cross-regional highway toll management system according to claim 2, characterized in that, The process of generating and initializing the global resource allocation structure is as follows: Determine the number K of resource scheduling and management nodes connected to the global resource status network, connect each resource scheduling node to the global central management node, and establish mutual access channels between the resource scheduling nodes through the cloud service network so that each resource scheduling node can serve as a backup node for the other. Based on the jurisdiction of the resource scheduling management node and the latitude and longitude of the toll station, the toll stations located within the jurisdiction of the resource scheduling management node are incorporated into each resource scheduling management node, enabling each toll station to communicate with its corresponding resource scheduling management node to obtain the initial global resource allocation structure.

4. The global resource allocation method for a cross-regional highway toll management system according to claim 1, characterized in that, The method for calculating the resource imbalance index is as follows: S31. Statistically monitor the number of historical work orders processed by each toll station in each resource scheduling management node during the monitoring period, the work order processing time, and the number of station-level cloud seat modules. Calculate the total number of work orders T, the total number of station-level cloud seat modules N, and the average work order processing time t of the resource scheduling management node during the monitoring period. The capacity C of the computing station-level cloud console module is calculated as C = N * H / t, where H represents the working duration of a single monitoring period. S32. Calculate the load rate L=T / C for each resource scheduling and management node based on the total number of work orders T and the production capacity C; S33. Calculate the average load L_Avg and the standard deviation L_Std of the load rate of all resource scheduling and management nodes. Based on the average load L_Avg and the standard deviation L_Std, calculate the resource imbalance index U=L_Std / L_Avg.

5. A global resource allocation method for a cross-regional highway toll management system according to claim 4, characterized in that, A comprehensive assessment of resource allocation imbalance is made when all of the following conditions are met: Condition 1: When the resource imbalance index is greater than or equal to the preset maximum equilibrium threshold, a global imbalance is determined. Condition 2: When the load rate L of any resource scheduling and management node is greater than 1.5*L_Avg or less than 0.5*L_Avg, a local imbalance is determined. Condition 3: If global imbalance is detected in multiple consecutive monitoring periods, and the resource imbalance index shows an increasing trend in multiple monitoring periods, then the trend is judged to be out of control.

6. A global resource allocation method for a cross-regional highway toll management system according to claim 4, characterized in that, The specific process of dynamically adjusting the resource equitable allocation structure using the incremental adjustment algorithm based on local search is as follows: S41. Divide the resource scheduling management nodes in the resource balanced allocation structure into several pairs of resource scheduling management nodes, and calculate the load difference between each pair of resource scheduling management nodes. S42. If the load difference is greater than the load threshold, calculate the difference between the resource imbalance index before and after the resource adjustment in the resource scheduling management node pair, obtain the migration benefit, and determine the resource balance allocation structure after the resource adjustment based on the migration benefit. S43. Calculate the load rate and resource imbalance index of each resource scheduling and management node in the resource balanced allocation structure after resource adjustment. S44. Determine whether a local imbalance has occurred based on the load rate of the resource scheduling and management node, and determine whether a global imbalance has occurred based on the resource imbalance index. S45. Repeat steps S41-S44 until the migration benefit is less than or equal to 0 and there is no local imbalance or global imbalance, thus obtaining the final dynamically adjusted resource balance allocation structure.

7. A global resource allocation method for a cross-regional highway toll management system according to claim 6, characterized in that, The specific process for determining the resource allocation structure after resource adjustment is as follows: For the resource scheduling management node pair: the first node and the second node, calculate the migration benefit of moving any toll station from the first node to the second node, and traverse each toll station of the first node to obtain the migration benefit of moving each toll station. Select the toll station with the highest migration benefit, and determine whether the load rate of the first and second nodes reverses after moving the toll station with the highest migration benefit to the second node. If no reversal occurs, move the toll station with the highest migration benefit to the second node.

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