A method and system for intelligent routing decision of mine multi-protocol converged communication

Abstract

The embodiment of the application discloses a kind of intelligent routing decision method and system of mining multi-protocol fusion communication, comprising: receiving session request;The session request is parsed, and standardization session description object is generated;Determine optimal transmission path and generate routing instruction based on the standardization session description object and multidimensional routing factor collected in real time;The routing instruction is received, the standard session description object is converted into the signaling format of target protocol, and call is initiated to next hop device.

Description

Technical Field

[0001] This specification relates to the field of computer technology, and in particular to an intelligent routing decision-making method and system for multi-protocol converged communication in mining applications. Background Technology

[0002] With the development of communication technology, the network environment is showing a trend of heterogeneity and convergence. In coal mines, communication terminals and access methods are becoming increasingly diverse in scenarios such as wired communication, wireless communication, Internet of Things (IoT), video guidance, and emergency communication command. For example, traditional telephone networks (PSTN / IP-PBX) use the SIP protocol, web or mobile applications widely adopt the WebRTC protocol, live push and pull streams commonly use the RTMP / RTSP protocol, while massive IoT devices use lightweight protocols such as MQTT and CoAP, and intercom systems use the DMR protocol.

[0003] In existing technologies, although routing decision-making software has certain protocol conversion capabilities, it suffers from rigid protocol adaptation, simplistic routing decisions, and a lack of global optimization. This results in poor system scalability and maintainability, a lack of comprehensive consideration of network quality, transmission costs, service types, and terminal capabilities, and an inability to achieve optimal resource allocation and path selection across protocol sessions. Consequently, it leads to uneven network resource utilization and inconsistent user experience.

[0004] Therefore, an intelligent routing decision-making method for multi-protocol converged communication in mining is needed. Summary of the Invention

[0005] This specification provides an intelligent routing decision-making method and system for multi-protocol converged communication in mining, which addresses the following technical problems: In the prior art, although the related software for routing decision-making has a certain protocol conversion capability, its protocol adaptation is rigid, its routing decision is singular, and it lacks global optimization, resulting in poor system scalability and maintainability. It also lacks comprehensive consideration of network quality, transmission cost, service type, and terminal capabilities, and cannot achieve optimal resource allocation and path selection for cross-protocol sessions, leading to uneven network resource utilization and inconsistent user experience.

[0006] To solve the above-mentioned technical problems, the embodiments in this specification are implemented as follows:

[0007] This specification provides an intelligent routing decision-making method for multi-protocol converged communication in mining applications, including:

[0008] Receive session request;

[0009] The session request is parsed to generate a standardized session description object;

[0010] Based on the standardized session description object and the real-time collected multi-dimensional routing factors, the optimal transmission path is determined and routing instructions are generated.

[0011] Upon receiving the routing instruction, the standard session description object is converted into the signaling format of the target protocol, and a call is initiated to the next-hop device.

[0012] This specification also provides an intelligent routing decision system for multi-protocol converged communication in mining applications, comprising:

[0013] The receiving module receives session requests;

[0014] The parsing module parses the session request and generates a standardized session description object;

[0015] The decision module determines the optimal transmission path and generates routing instructions based on the standardized session description object and the real-time collected multi-dimensional routing factors.

[0016] The communication module receives the routing instruction, converts the standard session description object into the signaling format of the target protocol, and initiates a call to the next-hop device.

[0017] The intelligent routing decision-making method for multi-protocol converged communication in mining provided in this specification involves receiving a session request; parsing the session request to generate a standardized session description object; determining the optimal transmission path and generating a routing instruction based on the standardized session description object and real-time collected multi-dimensional routing factors; receiving the routing instruction; converting the standardized session description object into the signaling format of the target protocol; and initiating a call to the next-hop device. This method can quickly support new communication protocols through a pluggable unified signaling adaptation layer without reconstructing the core system. The introduction of multi-dimensional decision factors upgrades routing selection from "connectivity is sufficient" to "comprehensive optimization," effectively balancing cost, quality, and business needs. It improves resource utilization and user experience, and enables dynamic fault avoidance and switching. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of the system architecture of an intelligent routing decision method for multi-protocol converged communication in mining, provided in the embodiments of this specification;

[0020] Figure 2A flowchart illustrating an intelligent routing decision-making method for multi-protocol converged communication in mining, provided as an embodiment of this specification;

[0021] Figure 3 This is a schematic diagram of an intelligent routing decision system for multi-protocol converged communication in mining, provided as an embodiment of this specification. Detailed Implementation

[0022] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0023] In existing technologies, most are static, one-to-one protocol gateways. Adding a new protocol or combination of protocols requires the development of a specific conversion module. Routing decisions are usually based only on the called number or simple rules, lacking comprehensive consideration. Each protocol gateway works independently, lacking a unified session view and intelligent decision center, and cannot achieve optimal resource allocation and path selection across protocol sessions.

[0024] Therefore, embodiments of this specification provide a method and system capable of intelligently identifying and uniformly adapting to multiple heterogeneous communication protocols, and dynamically selecting the optimal transmission path based on multi-dimensional factors, so as to achieve efficient, low-cost, and highly reliable converged communication.

[0025] Figure 1 This is a schematic diagram of the system architecture for an intelligent routing decision-making method for multi-protocol fusion communication in mining, provided as an embodiment of this specification. Figure 1 As shown, system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105. Network 104 serves as the medium for providing communication links between terminal devices 101, 102, and 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0026] Terminal devices 101, 102, and 103 interact with server 105 via network 104 to receive or send messages, etc. Various client applications can be installed on terminal devices 101, 102, and 103, such as dedicated programs for intelligent routing decision-making methods in multi-protocol converged communication for mining applications.

[0027] Terminal devices 101, 102, and 103 can be either hardware or software. When terminal devices 101, 102, and 103 are hardware, they can be various dedicated or general-purpose electronic devices, including but not limited to smartphones, tablets, laptops, and desktop computers. When terminal devices 101, 102, and 103 are software, they can be installed in the electronic devices listed above. They can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services) or as a single software program or software module.

[0028] Server 105 can be a server that provides various services, such as a backend server that provides services to client applications installed on terminal devices 101, 102, and 103. For example, the server can make intelligent routing decisions for mining multi-protocol converged communication so that the results of the intelligent routing decisions for mining multi-protocol converged communication can be displayed on terminal devices 101, 102, and 103.

[0029] Server 105 can be either hardware or software. When server 105 is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When server 105 is software, it can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services), or as a single software program or software module.

[0030] Figure 2 This is a flowchart illustrating an intelligent routing decision-making method for multi-protocol converged communication in mining, provided as an embodiment of this specification. From a programming perspective, the execution entity of the process can be a program mounted on an application server or application terminal. It is understood that this method can be executed by any device, equipment, platform, or cluster of devices with computing and processing capabilities. Figure 2 As shown, the intelligent routing decision-making method includes:

[0031] Step S201: Receive session request.

[0032] In the embodiments of this specification, the session request includes: caller / callee identifier, service type, media parameters, service scenario tag, transmission priority, protocol type and access link information, and terminal capability information.

[0033] Specifically, the service types include: voice, video, or emergency; media parameters include: encoding format, bandwidth requirements, and encryption requirements; service scenario tags include: daily dispatch, emergency rescue, and equipment inspection; protocol types include: SIP, WebRTC, RTMP, and MQTT; access link information includes: 5G public network, mining area private network, wired Ethernet, and mining optical cable; transmission priorities include: emergency calls are marked as the highest priority P0, daily dispatch is marked as P1, and data-assisted communication is marked as P2; terminal capability information includes: whether the underground terminal supports noise suppression, whether encrypted transmission is required, and whether it has mobility.

[0034] Step S203: Parse the session request and generate a standardized session description object.

[0035] In this embodiment of the specification, parsing the session request and generating a standardized session description object specifically includes:

[0036] Based on the session request, determine the target protocol type;

[0037] Based on the target protocol type, the corresponding protocol abstraction plugin is invoked;

[0038] The protocol object plugin is used to parse the session request and generate a standardized session description object.

[0039] In the embodiments described in this specification, the target protocol type is determined using a session request.

[0040] Step S205: Based on the standardized session description object and the real-time collected multi-dimensional routing factors, determine the optimal transmission path and generate routing instructions.

[0041] In the embodiments described in this specification, the multi-dimensional routing factors collected in real time are obtained or queried in real time through multiple channels by a context awareness device, which is related to the current session. The context awareness device includes: terminal and device context, network link context, service and policy context, and environment and scenario context.

[0042] The terminal and device context includes: the physical location of the called terminal (underground working face / tunneling face / ground dispatch center / underground chamber), online status (verified in real time via 5G / wired heartbeat packets), device load (terminal CPU utilization, battery power (mobile terminal)), and fault status (whether there is a line short circuit / open circuit warning).

[0043] The network link context includes: the real-time status of each candidate transmission link, including bandwidth utilization (≤70% is the available threshold for the mining area private network), transmission latency (≤100ms for emergency calls), packet loss rate (≤0.5% according to industrial communication standards), and link reliability (whether it is a dual redundant link and the frequency of historical failures). In particular, given the characteristics of 5G signal blind spots in underground coal mines and the susceptibility of wired links to geological influences, the status of backup links is collected first.

[0044] Business and strategy contexts include: session business priority (emergency rescue > personnel dispatch > equipment data transmission), security and compliance requirements (such as underground and surface communication must go through a mining encryption gateway), and resource constraints (concurrent call capacity of the target area gateway and remaining media processing resources).

[0045] The environment and scenario context includes: real-time environmental parameters in the coal mine (such as gas concentration and dust content). When the environment reaches a dangerous threshold, the priority of emergency call routing is automatically increased to ensure that rescue instructions are transmitted first.

[0046] The context sensor collects network device status via the SNMPv3 protocol, obtains device information through terminal heartbeat feedback, and synchronizes environmental data through the mining area environmental monitoring system interface. The collection frequency is 10 times / second to ensure the real-time performance of routing factors.

[0047] In the embodiments of this specification, the multi-dimensional routing factors include: network factors, service factors, geographical factors, and terminal factors. Network factors include: real-time network latency, jitter, packet loss rate, and bandwidth (which can be obtained from third-party monitoring services or probes); service factors include: service type (voice, video, IoT data); geographical factors include: the geographical locations of the calling and receiving terminals; terminal factors include: the terminal's supported encoding and decoding capabilities; and auxiliary factors include: power supply information (power supply, backup power supply, battery level, etc.).

[0048] In the embodiments of this specification, the step of determining the optimal transmission path and generating routing instructions based on the standardized session description object and real-time collected multi-dimensional routing factors specifically includes:

[0049] Based on the standardized session description object, routing policy rules are determined from the preset policy library;

[0050] Based on the routing policy rules, the hierarchical analysis method is used to assign dynamic weights to the multidimensional routing factors;

[0051] Based on the dynamic weights, the comprehensive score of the candidate path is calculated using the TOPSIS model;

[0052] The optimal transmission path is determined based on the comprehensive score, and routing instructions are generated.

[0053] In the embodiments of this specification, the preset policy library includes: business scenario policies, security compliance policies, network quality policies, device status policies, and fault response policies. Specifically, business scenario policies define the priorities and processing logic for different business types; security compliance policies define specific routing behaviors triggered by parameters in the underground environment; network quality policies define dynamic path selection adjustments based on real-time link status; device status policies define the resource status of terminals and gateways to achieve load balancing and energy consumption optimization; and fault response policies define rapid switching mechanisms in abnormal situations, including link interruptions and device crashes.

[0054] In the embodiments described in this specification, routing policy rules are determined from the preset policy library based on the standardized session description object, using existing technology, which will not be elaborated here.

[0055] In the embodiments of this specification, the method of assigning dynamic weights to the multidimensional routing factors based on the routing policy rules using the analytic hierarchy process (AHP) specifically includes:

[0056] A hierarchical model is constructed to decompose the intelligent routing decision problem in coal mines into: target layer, criterion layer, and solution layer;

[0057] Based on the routing strategy rules, each factor in the criterion layer is compared pairwise, and a judgment matrix is ​​constructed using the 1-9 scaling method.

[0058] The maximum eigenvalue of the judgment matrix and its corresponding eigenvector are calculated using the sum-product method or the square root method. After normalization, the initial weight vector of each routing factor is obtained.

[0059] The validity of the initial weight vector is verified using consistency indicators and consistency ratios, and dynamic weights are assigned to the multidimensional routing factors.

[0060] In the embodiments described in this specification, the target layer is used to select the optimal routing path; the criterion layer includes: network quality C1, economic cost C2, and business compliance C3; the solution layer includes: delay C11, jitter C12, packet loss rate C13, etc. The system administrator, or based on historical data, uses a 1-9 scale to compare the importance of factors at the same level pairwise, forming a judgment matrix. Calculate the eigenvectors of the matrix and normalize them to obtain the weight vector. Calculate the consistency ratio (CR). If CR < 0.1, the test is passed and the weight is valid. This weight can be pre-configured and quickly switched based on different "business templates" (such as "high-definition video conferencing," "low-cost IoT data," and "cross-border voice communication").

[0061] In the embodiments described in this specification, the different scenarios include emergency call scenarios and routine dispatch scenarios;

[0062] In emergency call scenarios, the dynamic weights are: link latency weight 40%, link reliability weight 30%, device load weight 10%, and bandwidth utilization weight 20%.

[0063] In daily scheduling scenarios, the dynamic weights are: device load weight 30%, bandwidth utilization weight 25%, link latency weight 25%, and link reliability weight 20%.

[0064] In the embodiments of this specification, the calculation of the comprehensive score of the candidate path based on the dynamic weights using the TOPSIS model specifically includes:

[0065] Construct an initial decision matrix, where the rows of the initial decision matrix represent candidate routing paths and the columns represent the multidimensional routing factors;

[0066] The initial decision matrix is ​​standardized to obtain a standardized decision matrix;

[0067] The standardized decision matrix is ​​weighted according to the dynamic weights to obtain a weighted standardized decision matrix.

[0068] Determine the positive and negative ideal solutions;

[0069] Calculate the Euclidean distance from each candidate route to the positive and negative ideal solutions;

[0070] The relative proximity of each candidate route is calculated based on the Euclidean distance, and the relative proximity is a comprehensive score.

[0071] In the embodiments described in this specification, the specific components include:

[0072] Step B1: Construct the initial decision matrix.

[0073] Given m candidate paths and n evaluation factors, form a matrix. }. Where x_{ij} is the quantization value of the i-th path on the j-th factor (e.g., a delay of 150ms).

[0074] Step B2: Matrix standardization and normalization.

[0075] To eliminate the influence of dimensions, vector normalization is used: z_{ij}=x_{ij} / \sqrt{\sum_{i=1}^{m}x_{ij}^2}.

[0076] Step B3: Construct the weighted normalization matrix.

[0077] Combine the weights W obtained in the first stage with the standardized matrix: v_{ij}=w_j\cdot z_{ij}.

[0078] Step B4: Determine the positive and negative ideal solutions.

[0079] Positive Ideal Solution ,in (For benefit-related factors, such as available bandwidth) or (For cost-related factors, such as delays and expenses). The key improvement of this invention lies in the ability to dynamically define the "ideal" direction for each factor based on the strategy.

[0080] Negative ideal solution ,in (Efficiency-oriented) or (Cost-based).

[0081] Step B5: Calculate the distance from each path to the positive / negative ideal solution.

[0082] ,

[0083] Step B6: Calculate the proximity of each path (overall score).

[0084] C_i = \frac{D_i^-}{D_i^+ + D_i^-}

[0085] The value of C_i is between 0 and 1. The larger the value, the closer the path is to the ideal solution.

[0086] Step B7: Sorting and Decision. Sort the candidate paths in descending order of C_i value, and select the path with the largest C_i value as the optimal route.

[0087] In the embodiments of this specification, the coal mining industry-specific strategy library includes an emergency dispatch routing strategy, a fault redundancy strategy, and a load balancing strategy. Specifically, the emergency dispatch routing strategy automatically routes the signaling to both the main ground dispatch console and the backup dispatch console when an underground emergency call request is received, ensuring dual-call support. The fault redundancy strategy immediately triggers an avoidance mechanism when a gateway line is detected to be broken or a node fails, automatically switching to a pre-configured backup gateway or redundant path. The load balancing strategy automatically diverts new sessions to a backup gateway with lower load in the same area when concurrent calls to a single gateway reach a preset threshold.

[0088] Step S207: Receive the routing instruction, convert the standard session description object into the signaling format of the target protocol, and initiate a call to the next-hop device.

[0089] In the embodiments of this specification, the routing instructions include: next-hop device identifier, media transmission path, QoS parameter configuration, security encryption scheme, and resource allocation list; wherein, the next-hop device identifier includes: mining gateway ID, dispatch console number, and terminal MAC address; the media transmission path includes: primary link and backup link; the QoS parameter configuration includes: bandwidth reservation value, latency threshold, and packet loss retransmission strategy; the security encryption scheme includes: encryption algorithm and key negotiation method; and the resource allocation list includes: media processing module and echo cancellation / noise suppression resources.

[0090] After receiving the optimal routing instruction, the session control and media routing layer initiates a two-dimensional execution logic to ensure real-time performance and reliability in coal mine scenarios:

[0091] Protocol Adaptation and Call Initiation: Based on the next-hop device protocol type in the routing instructions, the corresponding protocol adaptation plugin is invoked (e.g., WebRTC request → SIP plugin, 5G industrial terminal request → mining-specific protocol plugin) to convert the standardized session description object into the signaling format of the target protocol and initiate a call to the next-hop device. For example, when an underground WebRTC mobile terminal calls a ground SIP dispatch console, the SIP plugin automatically encapsulates the call signaling, sends it to the ground dispatch gateway via the mining area's private network, and includes an "underground emergency" tag to trigger an audible and visual alarm on the dispatch console.

[0092] Media processing resource configuration: Dedicated media processing resources are automatically activated to address the high-noise, high-interference environment of underground coal mines.

[0093] Audio optimization: Enable mining-grade echo cancellation (supports 128ms echo delay compensation), noise suppression (suppresses industrial noise below 85dB), and voice enhancement (improves voice signal-to-noise ratio by ≥15dB);

[0094] Security measures: The media stream encryption module is activated to perform end-to-end encryption of voice / video data in accordance with coal mine safety regulations. The key is transmitted through a dedicated encryption channel to prevent data leakage.

[0095] Resource reservation: Dedicated media processing threads are reserved for high-priority sessions to ensure that resources are not preempted during emergency calls;

[0096] Link and resource monitoring: Real-time monitoring of the response status of the next-hop device and the media resource usage. If the next-hop device does not respond (timeout ≤ 500ms), rerouting is triggered immediately. If media resources are insufficient, the backup resource pool is automatically scheduled to supplement them to avoid session establishment failure.

[0097] After the preceding steps, the system establishes an end-to-end session, enabling stable, low-latency, and highly secure media stream transmission in coal mine scenarios. Key features include:

[0098] Rapid establishment: Total session establishment latency ≤ 300ms (meets the "second-level response" requirement for emergency dispatch), of which signaling interaction latency ≤ 100ms, resource configuration latency ≤ 150ms, and link negotiation latency ≤ 50ms;

[0099] Stable transmission: Based on the dual-mode transmission mechanism of 5G private network in the mining area + wired redundant link, when the main link (such as 5G) is attenuated due to underground blockage or equipment movement, the media stream is seamlessly switched to the backup link (such as mining optical cable), with a switching latency of ≤50ms and no perceptible interruption;

[0100] Quality Assurance: Through a dynamic QoS adjustment mechanism, we ensure that the media stream transmission packet loss rate is <1%, latency jitter is <20ms, voice clarity is ≥95% (adapting to noisy environments in coal mines), and video resolution is adapted as needed (prioritizing frame rate ≥25fps in emergency scenarios, and supporting 1080P high-definition transmission in daily scenarios).

[0101] Status monitoring and anomaly handling: During the session, the system collects link quality, media parameters, and device status data in real time. If anomalies such as excessive packet loss rate or sudden increase in latency are detected, the system automatically adjusts the encoding format or switches the link. If the terminal experiences problems such as line disconnection or device failure, the system immediately pushes an alarm to the scheduling platform and retains the session context to support rapid reconnection after fault recovery.

[0102] The intelligent routing decision-making method for multi-protocol converged communication in mining provided in this specification involves receiving a session request; parsing the session request to generate a standardized session description object; determining the optimal transmission path and generating a routing instruction based on the standardized session description object and real-time collected multi-dimensional routing factors; receiving the routing instruction; converting the standardized session description object into the signaling format of the target protocol; and initiating a call to the next-hop device. This method can quickly support new communication protocols through a pluggable unified signaling adaptation layer without reconstructing the core system. The introduction of multi-dimensional decision factors upgrades routing selection from "connectivity is sufficient" to "comprehensive optimization," effectively balancing cost, quality, and business needs. It improves resource utilization and user experience, and enables dynamic fault avoidance and switching.

[0103] The above content details an intelligent routing decision-making method for multi-protocol converged communication in mining. Correspondingly, this specification also provides an intelligent routing decision-making system for multi-protocol converged communication in mining, such as... Figure 3 As shown. Figure 3 This is a schematic diagram of an intelligent routing decision system for multi-protocol converged communication in mining, provided in an embodiment of this specification. The intelligent routing decision system includes:

[0104] Receiver module 301 receives session requests;

[0105] The parsing module 303 parses the session request and generates a standardized session description object;

[0106] Decision module 305 determines the optimal transmission path and generates routing instructions based on the standardized session description object and the real-time collected multi-dimensional routing factors.

[0107] The communication module 307 receives the routing instruction, converts the standard session description object into the signaling format of the target protocol, and initiates a call to the next-hop device.

[0108] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0109] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments for apparatus, electronic devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0110] The apparatus, electronic device, and non-volatile computer storage medium and method provided in the embodiments of this specification are corresponding. Therefore, the apparatus, electronic device, and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, electronic device, and non-volatile computer storage medium will not be repeated here.

[0111] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0112] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0113] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0114] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0115] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0116] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0117] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0118] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0119] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0120] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0121] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0122] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0123] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside on local and remote computer storage media, including storage devices.

[0124] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0125] The above description is merely an embodiment of this specification and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. A smart routing decision-making method for multi-protocol fusion communication in mining, characterized in that, The intelligent routing decision method includes: Receive session request; The session request is parsed to generate a standardized session description object; Based on the standardized session description object and the real-time collected multi-dimensional routing factors, the optimal transmission path is determined and routing instructions are generated. Upon receiving the routing instruction, the standard session description object is converted into the signaling format of the target protocol, and a call is initiated to the next-hop device.

2. The intelligent routing decision method as described in claim 1, characterized in that, The session request includes: caller / callee identifier, service type, media parameters, service scenario tag, transmission priority, protocol type and access link information, and terminal capability information.

3. The intelligent routing decision method as described in claim 1, characterized in that, The step of parsing the session request and generating a standardized session description object specifically includes: Based on the session request, determine the target protocol type; Based on the target protocol type, the corresponding protocol abstraction plugin is invoked; The protocol object plugin is used to parse the session request and generate a standardized session description object.

4. The intelligent routing decision method as described in claim 1, characterized in that, The process of determining the optimal transmission path and generating routing instructions based on the standardized session description object and real-time collected multi-dimensional routing factors specifically includes: Based on the standardized session description object, routing policy rules are determined from the preset policy library; Based on the routing policy rules, the hierarchical analysis method is used to assign dynamic weights to the multidimensional routing factors; Based on the dynamic weights, the comprehensive score of the candidate path is calculated using the TOPSIS model; The optimal transmission path is determined based on the comprehensive score, and routing instructions are generated.

5. The intelligent routing decision method as described in claim 4, characterized in that, The process of assigning dynamic weights to the multidimensional routing factors based on the routing policy rules, using the analytic hierarchy process (AHP), specifically includes: A hierarchical model is constructed to decompose the intelligent routing decision problem in coal mines into: target layer, criterion layer, and solution layer; Based on the routing strategy rules, each factor in the criterion layer is compared pairwise, and a judgment matrix is ​​constructed using the 1-9 scaling method. The maximum eigenvalue of the judgment matrix and its corresponding eigenvector are calculated using the sum-product method or the square root method. After normalization, the initial weight vector of each routing factor is obtained. The validity of the initial weight vector is verified using consistency metrics and consistency ratios, and dynamic weights are assigned to the multidimensional routing factors.

6. The intelligent routing decision method as described in claim 4, characterized in that, The different scenarios include emergency call scenarios and routine dispatch scenarios; In emergency call scenarios, the dynamic weights are: link latency weight 40%, link reliability weight 30%, device load weight 10%, and bandwidth utilization weight 20%. In daily scheduling scenarios, the dynamic weights are: device load weight 30%, bandwidth utilization weight 25%, link latency weight 25%, and link reliability weight 20%.

7. The intelligent routing decision method as described in claim 4, characterized in that, The calculation of the comprehensive score of the candidate path based on the dynamic weights using the TOPSIS model specifically includes: Construct an initial decision matrix, where the rows of the initial decision matrix represent candidate routing paths and the columns represent the multidimensional routing factors; The initial decision matrix is ​​standardized to obtain a standardized decision matrix; The standardized decision matrix is ​​weighted according to the dynamic weights to obtain a weighted standardized decision matrix. Determine the positive and negative ideal solutions; Calculate the Euclidean distance from each candidate route to the positive and negative ideal solutions; The relative proximity of each candidate route is calculated based on the Euclidean distance, and the relative proximity is a comprehensive score.

8. The intelligent routing decision method as described in claim 4, characterized in that, The coal mining industry-specific strategy library includes emergency dispatch routing strategies, fault redundancy strategies, and load balancing strategies. Specifically, the emergency dispatch routing strategy automatically routes the signaling to both the main ground dispatch console and the backup dispatch console when an underground emergency call request is received, ensuring dual-call support. The fault redundancy strategy immediately triggers an avoidance mechanism when a gateway line is detected to be broken or a node fails, automatically switching to a pre-configured backup gateway or redundant path. The load balancing strategy automatically diverts new sessions to a backup gateway with lower load in the same area when concurrent calls to a single gateway reach a preset threshold.

9. The intelligent routing decision method as described in claim 1, characterized in that, The routing instructions include: next-hop device identifier, media transmission path, QoS parameter configuration, security encryption scheme, and resource allocation list; wherein, the next-hop device identifier includes: mining gateway ID, dispatch console number, and terminal MAC address; the media transmission path includes: primary link and backup link; the QoS parameter configuration includes: bandwidth reservation value, latency threshold, and packet loss retransmission strategy; the security encryption scheme includes: encryption algorithm and key negotiation method; and the resource allocation list includes: media processing module and echo cancellation / noise suppression resources.

10. A smart routing decision-making system for multi-protocol converged communication in mining applications, characterized in that, The intelligent routing decision system includes: The receiving module receives session requests; The parsing module parses the session request and generates a standardized session description object; The decision module determines the optimal transmission path and generates routing instructions based on the standardized session description object and the real-time collected multi-dimensional routing factors. The communication module receives the routing instruction, converts the standard session description object into the signaling format of the target protocol, and initiates a call to the next-hop device.

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