Method for selecting optimal proxy station of sub-station in dual-mode system

Abstract

The application discloses a method for selecting an optimal proxy station of a substation in a dual-mode system, comprising the following steps: S1, obtaining the number of substations directly managed by each candidate proxy station and judging whether the candidate proxy station is overloaded according to the number, if the candidate proxy station is overloaded, the candidate proxy station is removed, and if the candidate proxy station is not overloaded, the candidate proxy station is reserved as a valid candidate proxy station; S2, comparing the total number of the existing proxy stations in the current network with the theoretical maximum capacity of the current network, and further screening the valid candidate proxy stations according to the comparison result; S3, obtaining the uplink communication path of each candidate proxy station to a central coordinator and further screening the candidate proxy stations according to the communication success rate; S4, quantifying the path delay of each candidate proxy station by using an equivalent level; S5, assigning weights to the influence quantities affecting the selection of the proxy station, calculating the comprehensive score of each candidate proxy station by using the weighted summation method, and selecting the proxy station with the highest score as the optimal proxy station.

Description

Technical Field

[0001] This invention relates to the field of low-voltage power distribution network technology, specifically to a method for a central coordinator to intelligently select the optimal proxy site for sub-sites waiting to join the network or needing to switch proxies in a tree-structured communication network with dual-mode hybrid networking of high-speed power line carrier (HPLC) and high-speed wireless communication (HRF). Background Technology

[0002] In the Advanced Measurement Infrastructure (AMI) of smart grids, stable and efficient data acquisition is a core requirement. HPLC technology utilizes existing power lines for data transmission, offering strong penetration, but is susceptible to grid noise, impedance variations, and physical topology limitations. HRF technology, on the other hand, uses wireless radio frequency communication, offering flexible deployment and the ability to cross transformer substations, but is vulnerable to distance, obstructions, and co-channel interference. The HPLC+HRF dual-mode communication system, through its complementary advantages, has become the mainstream solution for addressing the "last mile" coverage challenge in complex, large, or highly obstructed transformer substations.

[0003] In a dual-mode tree-structured communication network like HPLC+HRF, agent sites play a crucial role, aggregating data from their subordinate smart meters and forwarding it via the uplink to the Central Coordinator (CCO), ultimately transmitting it back to the master station. The selection strategy for agent sites directly determines the overall network performance, including data collection success rate, real-time performance, network robustness, and scalability.

[0004] Currently, most agent site selection schemes in the power grid industry are based on traditional HPLC single-mode communication scenarios. These schemes mainly fall into two categories: one is centralized intelligent decision-making, where the CCO collects network topology and link quality information and runs graph theory algorithms (such as shortest path algorithms) to globally calculate the optimal route; the other is distributed decision-making, where each site autonomously selects its parent site based on local neighbor information and simple rules (such as the strongest signal strength). However, these schemes have revealed significant shortcomings when applied to HPLC+HRF dual-mode systems:

[0005] 1. Ignoring channel differences: Existing solutions typically treat HPLC links and HRF links as equivalent, measuring path length only by the number of hops. In reality, HRF links differ from HPLC links by orders of magnitude in bandwidth, transmission rate, and media access delay.

[0006] 2. Limited Evaluation Dimensions: Traditional methods often focus on a single metric, such as instantaneous signal strength (RSSI) or historical communication success rate. This may lead to the selection of "hotspot" proxies that are already saturated with load, or proxies with hidden bottlenecks in the communication path.

[0007] 3. Lack of load balancing mechanism: The existing load of the proxy site and the overall network structure are not fully considered, which can easily lead to some proxy sites connecting to too many sub-sites, becoming a communication bottleneck.

[0008] 4. Incompatible with the dynamic characteristics of dual-mode communication: In dual-mode communication networks, the communication interfaces and link states of stations may change dynamically. Existing static or single-dimensional selection strategies cannot adaptively and comprehensively consider the mixed quality of dual-mode paths.

[0009] Therefore, existing technologies lack a proxy site selection scheme that can comprehensively adapt to HPLC+HRF dual-mode communication systems. Summary of the Invention

[0010] This invention aims to overcome the shortcomings of the prior art and provide an optimal proxy site selection method suitable for HPLC+HRF dual-mode tree-type communication networks. This method is centrally executed by a central coordinator (CCO), which performs multi-level progressive screening of candidate proxies and finally achieves the selection of the optimal proxy site with high success rate, low transmission latency, and load balancing based on multi-factor weighted decision-making. This solves the technical problems of existing proxy site selection methods in dual-mode communication networks, such as ignoring channel differences, having a single evaluation dimension, lacking load balancing, and being unsuitable for the dynamic characteristics of dual modes.

[0011] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: A method for selecting the optimal proxy site for a sub-site in a dual-mode system includes the following steps: Step S1, Initial screening of direct connection load capacity: Obtain the number of sub-sites currently directly managed by each candidate proxy site, and determine whether the corresponding candidate proxy site is overloaded based on the number of sub-sites. If overloaded, it is eliminated; if not overloaded, it is retained as a valid candidate proxy site. Step S2, Screening based on network scale and role compliance: Evaluate the current network topology scale, compare the total number of existing proxy sites in the current network with the theoretical maximum capacity of the network, and further screen the valid candidate proxy sites based on the comparison results. Step S3, Screening based on path end-to-end reliability: For the candidate proxy sites remaining after screening in Step S2, obtain their path end-to-end reliability from the central coordinator. The communication path is established and further filtered based on the corresponding communication success rate; Step S4, equivalent transmission delay calculation: For the candidate proxy sites remaining after step S3, their path delay is quantified using the equivalent level; Step S5, multi-dimensional weighted comprehensive decision: For the candidate proxy sites remaining after step S3, weights are assigned to the factors affecting proxy selection, and the comprehensive score of each candidate proxy site is calculated by weighted summation. The proxy site with the highest score is selected as the optimal proxy site for the sub-site initiating the network access request; wherein, the factors include: the minimum communication success rate on the path from each candidate proxy site to the central coordinator, the equivalent level, the number of sub-sites currently directly managed, and the signal quality between them and the sub-site issuing the request.

[0012] Further, step S1 specifically includes: querying the network-wide routing table maintained by the central coordinator to obtain the number of sub-sites currently directly managed by each candidate agent site; if the number of sub-sites currently directly managed by a candidate agent site exceeds the threshold calculated based on the communication protocol frame structure and network scale, it is determined that the direct-connected sites of the candidate agent site are overloaded or too heavy, and the candidate agent site is removed; otherwise, it is retained as a valid candidate agent site; if the number of valid candidate agent sites is not 0 after the judgment is completed, proceed to step S2, otherwise end.

[0013] Furthermore, the central coordinator's network-wide routing table stores the routing relationships of all sub-sites; in step S1, the central coordinator queries the network-wide routing table in response to a sub-site's network entry request, wherein the network entry request carries a list of candidate proxy sites detected by the sub-site.

[0014] Furthermore, in step S2, if the total number of existing proxy sites in the current network exceeds a preset value, then candidate proxy sites whose role is a normal site among the valid candidate proxy sites are eliminated; if the number does not exceed the preset value, then no elimination is performed; wherein, the preset value is the theoretical maximum capacity of the current network minus 3.

[0015] Further, step S3 specifically includes: obtaining the uplink communication paths from each candidate proxy site to the central coordinator and their corresponding minimum communication success rates after being filtered in step S2; determining whether the minimum communication success rate of each path is within a preset range; if so, retaining the candidate proxy site corresponding to the path and recording its index; if not, removing the candidate proxy site corresponding to the path; wherein, the preset range is set based on the statistical historical communication success rate.

[0016] Furthermore, the step of obtaining the minimum communication success rate in step S3 includes: for candidate agent sites whose paths contain more than two links, obtaining the historical communication success rate of each link and taking the minimum value as the minimum communication success rate of its path; for candidate agent sites whose paths have only one link, determining the minimum communication success rate of its path based on the signal strength value of its communication with the central coordinator; the smaller the signal strength value, the lower the minimum communication success rate.

[0017] Further, in step S3, for a candidate agent site with only one hop link in the path, if the signal strength of its communication with the central coordinator is lower than N2, then the minimum communication success rate of its path is set to a fixed value V; if the signal strength E of its communication with the central coordinator is not lower than N2, then the minimum communication success rate of its path = V + ((E-N2) / (S-N2))*(1-V); where N2 is the minimum signal strength threshold that the central coordinator can receive based on the overall network signal, V refers to the minimum communication success rate given when the signal strength is lower than N2, and S is the maximum signal strength value of the network.

[0018] Furthermore, step S4 utilizes the equivalent hierarchy to quantify path latency, specifically including: counting the number of HPLC links and HRF links in the uplink communication paths of each candidate proxy site remaining after screening in step S3, and calculating the equivalent hierarchy of each candidate proxy site according to the pre-calibrated conversion factor: equivalent hierarchy = HPLC hop count + conversion factor × HRF hop count.

[0019] Furthermore, step S5 also includes: checking and excluding the candidate proxy sites remaining after step S3 whose paths would form a loop with the sub-site that issued the request, and then assigning weights to the influence quantities of the remaining candidate proxy sites.

[0020] The present invention also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can implement the steps of the aforementioned method.

[0021] Compared with existing technologies, the beneficial effects of this invention are reflected in the following aspects: By combining multi-level progressive screening with multi-dimensional weighted decision-making, the feasibility of candidate agents in terms of single-point load and global network structure is first ensured. Then, the end-to-end reliability and equivalent transmission delay of the uplink path are evaluated in detail. Finally, a weighted model is used to comprehensively weigh multiple key performance indicators. This method overcomes the shortcomings of existing technologies that ignore the differences between dual-mode channels and have a single evaluation dimension. By introducing the concept of equivalent hierarchy, the delay differences of different communication media are quantified, and end-to-end reliability is guaranteed by the minimum communication success rate of the path. At the same time, intelligent balancing of network load is achieved by combining direct load and signal quality. Therefore, this invention can adapt to the dynamic characteristics of dual-mode networks and scientifically select the agent site with the best comprehensive performance in terms of reliability, delay, and load balancing, thereby comprehensively improving the overall performance of dual-mode tree-structured communication networks. Attached Figure Description

[0022] Figure 1 This is a flowchart of the method for selecting the optimal proxy site for a sub-site in a dual-mode system provided in this embodiment of the invention.

[0023] Figure 2This is the path end-to-end reliability screening process in this embodiment of the invention.

[0024] Figure 3 This is a flowchart of multi-dimensional weighted comprehensive calculation and decision-making in an embodiment of the present invention. Detailed Implementation

[0025] 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. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0026] The core of this invention lies in a multi-level progressive screening and weighted decision-making method executed by the Central Coordinator (CCO) to select the optimal proxy site for sub-sites requesting network access or proxy switching. This method progressively narrows down the candidate pool by screening four dimensions: direct connection load capacity, network size and role compliance, end-to-end path reliability, and equivalent transmission latency. Finally, the remaining high-quality candidate proxies are weighted and scored based on multiple factors to select the one with the highest overall score. This method fully considers the differences and dynamic characteristics of HPLC and HRF dual-mode communication, aiming to achieve network performance with high reliability, low latency, and good load balancing.

[0027] This invention provides a method for selecting the optimal proxy site for a sub-site in a dual-mode system. Please refer to [link / reference]. Figure 1 The selection method includes the following steps: After receiving the subsite's network access request, the process of selecting the optimal proxy site for it begins, which includes steps S1 to S5: Step S1: Initial Screening of Direct Connection Load Capacity: The central coordinator queries its maintained network routing table to obtain the number of sub-sites currently directly managed by each candidate proxy site. If the number of sub-sites currently directly managed by a candidate proxy site exceeds a threshold (e.g., 20) calculated based on the communication protocol frame structure and network size, it is determined that the direct connection site load of the candidate proxy site is full or excessive, and the candidate proxy site is eliminated; otherwise, it is retained as a valid candidate proxy site. The threshold can be calculated based on the frame structure (e.g., SOF frame capacity) and network size (e.g., total number of sites) specified in the specific communication protocol (e.g., the State Grid Dual-Mode Communication Interconnection Technical Specification Data Link Layer Communication Protocol). After the judgment is completed, if the number of valid candidate proxy sites is not 0, proceed to step S2; otherwise, the process ends.

[0028] Step S2, Network Size and Role Compliance Screening: Assess the current network topology size. If the total number of existing proxy sites in the current network has reached or is close to (e.g., the difference from the theoretical maximum capacity is less than or equal to 3) the theoretical maximum capacity of the network (i.e., the theoretical maximum value of the total number of proxy sites), then candidate proxy sites with the role of ordinary site (STA) among the valid candidate proxy sites are removed; if the theoretical maximum capacity has not been reached and the difference is greater than 3, then no removal is performed. After completing the screening in Step S2, the remaining candidate proxy sites are denoted as set P1.

[0029] Step S3, End-to-End Reliability Screening: For each candidate proxy site in set P1, firstly, obtain its uplink communication path to the central coordinator and its corresponding minimum communication success rate. Then, determine whether the minimum communication success rate of each path is within a preset range. If yes, retain the candidate proxy site corresponding to that path and record its index; otherwise, remove the candidate proxy site corresponding to that path. After completing this screening step, the remaining candidate proxy sites are denoted as set P2. Figure 2 The diagram illustrates the end-to-end reliability screening process for this step.

[0030] The preset interval is a high-reliability threshold range set based on statistically analyzed historical communication success rates, with a preferred range of 10%. When all historical communication success rates are high, the threshold range is relatively high, and vice versa. In short, the corresponding interval is set according to a 10% increment based on the statistically analyzed historical communication success rates. For example, if the majority of historical communication success rates are relatively high (e.g., above 80%), 90%~100% can be set as the preset interval; conversely, if the majority of historical communication success rates are not very high, 60%~70% can be set as the preset interval.

[0031] The minimum communication success rate for each path in step S3 can be obtained in the following way: For candidate proxy sites whose paths contain more than two hops, obtain the historical communication success rate of each hop and take the minimum of these as the minimum communication success rate of the path. For candidate proxy sites whose association request messages are sent directly to the central coordinator (without intermediate agents), i.e., candidate proxy sites with only a single-hop link in their path, the minimum communication success rate of their path is determined based on the signal strength value of their communication with the central coordinator. The lower the signal strength value, the lower the minimum communication success rate; conversely, the higher the signal strength value, the higher the minimum communication success rate. An exemplary method is as follows: for candidate proxy sites with only a single-hop link in their path, if the signal strength of their communication with the central coordinator is lower than N2, then the minimum communication success rate of their path is set to a fixed value V; if the signal strength E of their communication with the central coordinator is not lower than N2, then the minimum communication success rate of their path = V + ((E-N2) / (S-N2))*(1-V). Here, N2 is the minimum signal strength threshold that the central coordinator can receive, set according to the overall network signal strength, for example, N2=10; V refers to the minimum communication success rate given when the signal strength is lower than N2, for example, V=20%; and S is the maximum signal strength value of the network, for example, S=30. If the signal strength is below 10, the minimum communication success rate is set to the lowest level - 20%; if the signal strength is not below 10, for example, 20, the minimum communication success rate = 20% + ((20-10) / (30-10)) * (1-20%) = 60%.

[0032] Step S4, Equivalent Transmission Delay Calculation: For the candidate proxy site set P2 obtained after screening in Step S3, the path delay from each candidate proxy site to the CCO is quantified using the equivalent hierarchy. Specifically, the number of HPLC links and HRF links in the uplink communication path of each candidate proxy site in set P2 is counted, and the equivalent hierarchy of each candidate proxy site is calculated according to the pre-calibrated conversion factor: Equivalent Hierarchy = HPLC hop count + Conversion factor × HRF hop count.

[0033] Because of the communication rate difference between the HRF communication bandwidth (500kHz or 200kHz) and the HPLC communication frequency band (2.2MHz), the HRF hop count on the path of each candidate proxy site is counted, and a hierarchical correspondence between HRF links and HPLC links is established (e.g., a level 1 HRF link equals a level 3 HPLC link). The equivalent level is then calculated as: Equivalent Level = HPLC Hops + Conversion Factor × HRF Hops. The conversion factor can also be determined by experimentally measuring the average transmission delay of different links. In practice, the value of the conversion factor is related to the transmission mode and the HRF bandwidth. For example, it might be 4 or 5 at 200kHz, and 3 at 500kHz. Conversely, different coefficients will also affect the choice of transmission mode. Laboratory tests can roughly determine which conversion factors correspond to better wireless transmission performance.

[0034] Step S5: Multi-dimensional Weighted Comprehensive Decision-Making: After the aforementioned progressive screening, all candidate proxy sites in set P2 are proxy sites that perform well in specific dimensions. In this step, a multi-objective decision-making model is constructed through a central coordinator. Weights are assigned to the factors influencing proxy site selection, and a comprehensive score for each candidate proxy site is calculated using a weighted summation method. The proxy site with the highest score is selected as the optimal proxy site for the sub-site initiating the network access request, and this decision is distributed to that sub-site. The factors influencing proxy site selection include: the minimum communication success rate of each candidate proxy site, the equivalent level, the number of sub-sites currently directly managed, and the signal quality (such as RSSI value) between each candidate proxy site and the requesting sub-site. When assigning weights, the importance and magnitude of each influencing factor are comprehensively considered. For example, the minimum communication success rate is of higher importance and should be assigned a relatively large weight, but considering its large value range, its weight should be reduced. While the equivalent level is less important than the minimum communication success rate, its smaller value range means that its weight might even be greater than that of the minimum communication success rate. We have conducted multiple practical tests on the weight allocation of each influencing factor. Ultimately, the weights for the minimum communication success rate, equivalent level, number of currently directly managed sub-sites, and signal quality were set to 0.2, 0.6, 0.1, and 0.1, respectively. However, this is only an example; while ensuring the sum of the weights is 1, appropriate adjustments can be made to each weight according to the aforementioned allocation principles.

[0035] Preferably, in step S5, before making a comprehensive calculation decision, a screening process can be performed as follows: for candidate proxy sites in set P2, check and exclude proxy sites whose paths would form a loop with the requesting sub-site, and then assign weights to the influence quantities of the remaining candidate proxy sites and perform a weighted summation calculation. Figure 3 As shown, the multi-dimensional weighted comprehensive calculation and decision-making process of step S5 is illustrated.

[0036] Example 1 Suppose that in a low-voltage distribution area with hundreds of smart meters, the Central Coordinator (CCO) receives a network access request from a new meter site, Node_New, carrying a list of candidate proxies {Proxy_A, Proxy_B, Proxy_C, Proxy_D} discovered through surveillance. The CCO will perform the following steps to select the optimal proxies for Node_New:

[0037] Step S1: Initial screening of direct load capacity.

[0038] The CCO's routing table stores the routing relationships of all sub-sites across the network. When a Node_New joins the network, in response, the CCO queries its routing table to obtain the number of sub-sites currently directly managed by each candidate proxy site (referred to as "directly connected sub-sites"): Proxy_A: 18, Proxy_B: 25, Proxy_C: 15, Proxy_D: 22, Proxy_E: 10. In this example, the threshold calculated based on the communication protocol frame structure and network size is 20. Therefore, Proxy_B and Proxy_D are eliminated due to overload; the remaining candidate proxy sites are: {Proxy_A, Proxy_C, Proxy_E}.

[0039] Step S2: Network size and role compliance screening.

[0040] According to statistics, there are currently 48 proxy sites on the network. Based on the network size, the maximum number of proxies allowed on the current network is 50. Since the number of existing proxy sites (48) is close to the limit (50), according to the rules, candidate proxy sites with the role of STA in {Proxy_A, Proxy_C, Proxy_E} need to be removed. Assuming that Proxy_C is the STA in this example, and the other sites Proxy_A and Proxy_E are higher-level sites with stronger carrying capacity (such as the proxy coordinator PCO), then Proxy_C is removed, and the remaining candidate proxy sites are: {Proxy_A, Proxy_E}.

[0041] Step S3: Path end-to-end reliability screening.

[0042] The CCO queries the routing table and obtains the uplink communication path from Proxy_A to the CCO: Proxy_A--(HRF)→Proxy_X--(HPLC)→CCO. This means Proxy_A reaches the CCO via a two-hop link: one hop is the HRF link from Proxy_A to Proxy_X, and the other is the HPLC link from Proxy_X to the CCO. Historical statistics show a 97% success rate for the HRF link from Proxy_A to Proxy_X and a 94% success rate for the HPLC link from Proxy_X to the CCO. Therefore, the minimum success rate for this path is 94%, falling within the preset 90%~100% high reliability range, and Proxy_A passes the screening. Proxy_E's uplink communication path includes two pure HPLC hops, with success rates of 96% and 98% respectively, and a minimum success rate of 96%. At this point, both Proxy_A and Proxy_E are selected to proceed to the next step.

[0043] Step S4: Calculate the equivalent transmission delay.

[0044] The path from Proxy_A to CCO is: 1 hop HRF + 1 hop HPLC. Assuming a conversion factor of 3, the equivalent level = 1 + 3*1 = 4.

[0045] The path from Proxy_E to CCO is: 2-step HPLC (no conversion required), with an equivalent 2-stage HPLC.

[0046] Step S5: Multi-dimensional weighted comprehensive decision-making.

[0047] Weights are set as follows: communication success rate score weight W1 = 0.4, equivalent level score weight W2 = 0.3, load factor weight W3 = 0.2, and signal quality weight W4 = 0.1. Among them, communication success rate score = minimum communication success rate * 100; equivalent level score = (maximum allowed level - equivalent level) / maximum allowed level * 100. In this example, it is assumed that the maximum allowed level is 6 (which can be estimated according to the maximum level (15) specified by the State Grid dual-mode protocol and the estimated HRF hop ratio on a link. In this example, it is taken as 6); load factor = 1 / number of directly connected sub-sites * 100. Assume that the signal quality reported by the sub-site Node_New and each candidate proxy site is: Proxy_A: 85, Proxy_E: 80.

[0048] The formula for calculating the overall score of candidate proxy site Proxy_A is as follows: Communication success rate score × W1 + equivalent level score × W2 + load factor × W3 + signal quality × W4.

[0049] Communication success rate score × W1 = 94 * 0.4 = 37.6; Equivalent level score × W2 = (6 - 4) / 6 * 100 * 0.3 ≈ 9.9; Loading factor × W3 = (1 / 18) * 100 * 0.2 ≈ 1.1; Signal quality × W4 = 85 * 0.1 = 8.5; The overall score of candidate proxy site Proxy_A is: 37.6 + 9.9 + 1.1 + 8.5 = 57.1.

[0050] Similarly, the overall score of the candidate proxy site Proxy_E is calculated as follows: Communication success rate score × W1 = 96 * 0.4 = 38.4; Equivalent level score × W2 = (6 - 2) / 6 * 100 * 0.3 = 20.0; Loading factor × W3 = (1 / 10) * 100 * 0.2 = 2.0; Signal quality × W4 = 80 * 0.1 = 8.0; The overall score of candidate proxy site Proxy_E is: 38.4 + 20.0 + 2.0 + 8.0 = 68.4.

[0051] Comparing the overall scores, Proxy_E (68.4) > Proxy_A (57.1). Therefore, the CCO ultimately determines Proxy_E as the optimal proxy site for the requesting subsite Node_New, and sends this result to Node_New, instructing it to complete the network association.

[0052] The thresholds (such as the maximum number of directly connected sites, the maximum number of proxies, the success rate range, the HRF equivalent coefficient, etc.) in each step of the present invention, as well as the weight parameters in the weighted decision, can be pre-configured or dynamically adjusted according to the actual network equipment capabilities, communication protocols, and on-site operation requirements to adapt to different application scenarios.

[0053] In summary, compared with the prior art, the solution provided by the embodiments of the present invention has the following significant advantages: 1. Comprehensive improvement of communication reliability: Prioritize the stability of the entire uplink, significantly reducing the risk of systemic communication failures caused by single points of failure or weak links in the path.

[0054] 2. Precisely optimize network transmission latency: Innovatively quantify the performance differences of different communication media into a unified index, making the proxy selection results more consistent with the actual transmission experience and effectively reducing the end-to-end latency of data aggregation.

[0055] 3. Achieve intelligent load balancing: Prevents traffic from being concentrated on a few sites, promotes the even distribution of network resources and connection burden, and enhances the overall throughput and scalability of the network.

[0056] 4. Highly compatible with the characteristics of dual-mode systems: Its screening logic and evaluation model fully integrate the technical characteristics of the two communication modes, enabling the agent selection strategy to adapt to the dynamic changes of the dual-mode network.

[0057] 5. Scientific decision-making and strong adaptability: It adopts a framework of multi-level progressive screening combined with multi-factor weighted decision-making, with a clear structure and rigorous logic. Each parameter can be flexibly configured according to the actual network conditions.

[0058] Another embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can implement the steps of the aforementioned method. Based on this understanding, the technical solution of the aforementioned method of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (e.g., CD-ROM, USB flash drive, portable hard drive, etc.) and includes several instructions to cause a computer device (e.g., personal computer, server, or network device, etc.) to execute the steps of the method in various embodiments of the present invention.

Claims

1. A method for selecting the optimal proxy site for a sub-site in a dual-mode system, characterized in that, Includes the following steps: Step S1, Initial screening of direct connection load capacity: Obtain the number of sub-sites currently directly managed by each candidate proxy site, and determine whether the corresponding candidate proxy site is overloaded based on the number of sub-sites. If it is overloaded, it will be removed; if it is not overloaded, it will be retained as a valid candidate proxy site. Step S2, Network Scale and Role Compliance Screening: Assess the current network topology scale, compare the total number of existing proxy sites in the current network with the theoretical maximum capacity of the network, and further screen the effective candidate proxy sites based on the comparison results; Step S3, Path end-to-end reliability screening: For the candidate agent sites remaining after step S2, obtain their uplink communication path to the central coordinator and further screen them according to the corresponding communication success rate. Step S4, Equivalent transmission delay calculation: For the candidate proxy sites remaining after step S3, their path delay is quantified using the equivalent level. Step S5, Multi-dimensional Weighted Comprehensive Decision: For the candidate proxy sites remaining after screening in Step S3, assign weights to the factors affecting proxy selection, calculate the comprehensive score of each candidate proxy site by weighted summation, and select the proxy site with the highest score as the optimal proxy site for the sub-site initiating the network access request; wherein, the factors include: the minimum communication success rate on the path from each candidate proxy site to the central coordinator, the equivalent level, the number of sub-sites currently directly managed, and the signal quality between them and the sub-site that issued the request.

2. The selection method as described in claim 1, characterized in that, Step S1 specifically includes: The number of sub-sites currently directly managed by each candidate agent site can be obtained by querying the network-wide routing table maintained by the central coordinator. If the number of sub-sites directly managed by a candidate proxy site exceeds the threshold calculated based on the communication protocol frame structure and network scale, it is determined that the direct-connected sites of the candidate proxy site are overloaded or too heavy, and the candidate proxy site is removed; otherwise, it is retained as a valid candidate proxy site. If the number of valid candidate proxy sites is not 0 after the judgment is completed, proceed to step S2; otherwise, end the process.

3. The selection method as described in claim 2, characterized in that, The central coordinator stores the routing relationships of all sub-sites in its network-wide routing table. In step S1, the central coordinator queries the network-wide routing table in response to a sub-site's network entry request, wherein the network entry request carries a list of candidate proxy sites detected by the sub-site.

4. The selection method as described in claim 1, characterized in that, In step S2, if the total number of existing proxy sites in the current network exceeds a preset value, then candidate proxy sites whose role is a normal site among the valid candidate proxy sites will be removed. If the limit is not exceeded, no elimination will be performed; wherein, the preset value is the theoretical maximum capacity of the current network minus 3.

5. The selection method as described in claim 1, characterized in that, Step S3 specifically includes: Obtain the uplink communication path from each candidate agent site remaining after step S2 to the central coordinator and its corresponding minimum communication success rate. Determine whether the minimum communication success rate of each path is within a preset range. If so, retain the candidate proxy site corresponding to that path and record its index; otherwise, remove the candidate proxy site corresponding to that path. The preset interval is set based on the historical communication success rate.

6. The selection method as described in claim 5, characterized in that, Step S3, which involves obtaining the minimum communication success rate, includes the following steps: For candidate proxy sites whose paths contain more than two hops, obtain the historical communication success rate of each hop and take the minimum value as the minimum communication success rate of its path. For candidate agent sites with only one hop link in their path, the minimum communication success rate of their path is determined based on the signal strength value of their communication with the central coordinator; the smaller the signal strength value, the lower the minimum communication success rate.

7. The selection method as described in claim 6, characterized in that, In step S3, for a candidate agent site with only one hop link in its path, if the signal strength of its communication with the central coordinator is lower than N2, then the minimum communication success rate of its path is set to a fixed value V; if the signal strength E of its communication with the central coordinator is not lower than N2, then the minimum communication success rate of its path = V + ((E-N2) / (S-N2))*(1-V); where N2 is the minimum signal strength threshold that the central coordinator can receive based on the overall network signal, V refers to the minimum communication success rate given when the signal strength is lower than N2, and S is the maximum signal strength value of the network.

8. The selection method as described in claim 1, characterized in that, Step S4 utilizes equivalent hierarchical quantization of path delay, specifically including: The number of HPLC links and HRF links in the uplink communication paths of each candidate proxy site remaining after screening in step S3 is counted. Based on the pre-calibrated conversion factor, the equivalent level of each candidate proxy site is calculated: Equivalent level = HPLC hop count + conversion factor × HRF hop count.

9. The selection method as described in claim 1, characterized in that, Step S5 further includes: checking and excluding the candidate proxy sites remaining after step S3 whose paths would form a loop with the sub-site that issued the request, and then assigning weights to the influence quantities of the remaining candidate proxy sites.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program can perform the steps of the method according to any one of claims 1 to 9.

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