Communication equipment networking system and method based on micro-service architecture

Abstract

The invention discloses a communication device networking system and method based on a micro-service architecture, and relates to the technical field of micro-services, and the method comprises the steps: obtaining a neighbor set of each communication device through judgment according to the communication radius of the communication device; the method comprises the following steps of: decomposing a calculation task in communication equipment networking into parallel subtasks, and constructing a directed acyclic graph by utilizing a dependency relationship between the subtasks; constructing a matching energy efficiency function and a constraint condition, and allocating each sub-task to the optimal communication equipment for execution; formulating a scheduling sequence of the sub-tasks by utilizing a dependency relationship in the directed acyclic graph, and setting a starting time constraint mechanism of each sub-task; analyzing the starting time, judging whether execution of the subtasks fails or not, and after execution of all the subtasks in the directed acyclic graph succeeds, aggregating execution results of all the subtasks in the first subtask in the scheduling sequence to obtain a calculation task execution result.

Description

Technical Field

[0001] The present invention relates to the field of microservice technology, and in particular to a communication device networking system and method based on a microservice architecture. Background Art

[0002] In the early days of communications equipment networking systems, monolithic architectures integrated all functions, making them easy to develop and maintain at a smaller scale. However, with the growth of communications services and the continuous expansion of functionality, monolithic architectures became cumbersome, difficult to scale, and expensive to maintain. For example, adding new communications functionality or supporting new device types may require large-scale modifications and redeployment of the entire system. To address the issues of monolithic architectures, SOA (Service-Oriented Architecture) splits the system into multiple services. However, using complex communication protocols (such as SOAP) can lead to performance bottlenecks and high coupling between services. For example, in communications equipment networking, the complexity of the SOAP protocol can increase latency between different services, affecting communication efficiency. The rise of technologies such as cloud computing and containerization has provided strong support for the development of microservices architectures. Cloud platforms can dynamically provide computing, storage, and network resources to meet the elastic scalability requirements of microservices architectures. Container technology can encapsulate microservices and their dependencies, enabling independent operation and efficient resource isolation, making the application of microservices architectures in communications equipment networking possible.

[0003] In today's traditional communication networks, the integration of devices requires overall maintenance when a device fails, seriously affecting efficiency. However, using a distributed structure, different tasks may deadlock during execution due to contention for device resources. Therefore, it is crucial to ensure the success rate of tasks while accelerating the efficiency of communication equipment task execution. Summary of the Invention

[0004] The purpose of the present invention is to provide a communication device networking system and method based on a microservice architecture to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions: A communication device networking method based on a microservice architecture, the method comprising the following steps: S100, calculating the relative distance between communication devices, determining the neighbor set of each communication device based on the communication radius of the communication device; registering the microservice capability vector in each communication device; Furthermore, the specific steps for registering the microservice capability vector in each communication device are as follows: S101. Extract the location coordinates of each communication device in the communication device network, calculate the relative distance between all communication devices using the Euclidean distance formula, and assume that the communication radius of the communication device is R. comm, for communication equipment d i Use the communication radius to measure the communication equipment d i The relative distance with other communication devices is judged to obtain the communication device d i The neighbor device set is constructed as follows: ; In the formula, N i represents the set of neighboring devices of the i-th communication device, dist (d i , d j ) represents the relative distance between the i-th communication device and the j-th communication device; the same method is used to construct the neighbor device set of each communication device in the communication device network; S102: Extract all microservice capabilities in the communication device. Microservices include but are not limited to central processing units and main memories. Convert the values ​​of all microservice capabilities into vector form, so that the registered microservice capability vector of each communication device is: ; In the formula, c i represents the microservice capability vector registered by the i-th communication device, ServiceType1, ServiceType1, ... represent the 1st, 2nd, ... microservice vectors registered by the i-th communication device; CPU represents the central processing unit capability vector, and RAM represents the main memory capability vector.

[0006] S200, decomposing computing tasks in the communication device network into parallel subtasks, constructing a directed acyclic graph using dependencies between subtasks, and defining the structure of each subtask; By finding the neighboring devices of each communication device, building a set of neighboring devices, and combining the communication devices to form a cellular collaborative architecture, when processing tasks, the cellular collaborative architecture is used to reduce data transmission delays, reduce network load, and improve communication efficiency.

[0007] The microservice capabilities of communication devices are converted into vector form and registered, including key indicators such as CPU and RAM, to provide accurate device capability information for subsequent task allocation, making task allocation more reasonable.

[0008] Furthermore, the specific steps for setting the restriction criteria for each subtask decomposition are as follows: S201. For a computing task in a communication device network, parse the computing task description and quantify the task feature vector T = {Input+Size, Output_Size, Computation_Complexity, Deadline}, where Input+Size represents the amount of input data for the computing task, Output_Size represents the amount of output data for the computing task, Computation_Complexity represents the computational complexity coefficient of the computing task, and Deadline represents the actual completion limit of the computing task; the computational complexity coefficient represents the number of floating-point operations involved in processing each byte of data; S202. Decompose the computing task into parallel subtasks using professional knowledge, and calculate the optimal number of subtasks based on the characteristic vector of the computing task. The formula is: ; In the formula, K represents the optimal number of subtasks, K max Indicates the maximum number of subtasks allowed in the communication equipment network, C base Indicates the baseline computing capacity of a single communication device; When decomposing the computing task, the optimal number of subtasks is met, and the input and output data of each subtask are determined. For any two subtasks, when the output of one subtask is the input of the other subtask, the two subtasks are determined to be dependent. The subtask dependencies are used as edges and the subtasks are used as nodes to construct a directed acyclic graph, specifically: G = (V, E), where G represents a directed acyclic graph, V represents a node set, and E represents an edge set; V = {v1, v2, v3, ..., v K}, v1, v2, v3, ..., v K Represents the 1st, 2nd, 3rd, ..., Kth subtask nodes in the directed acyclic graph; S203, for each subtask in the directed acyclic graph, define the structure as: V k = <ID k , input k , output k , f k , deadline k > ID k Indicates the unique identifier of the k-th subtask, input k represents the input of the kth subtask, output k represents the output of the kth subtask, f k Represents the calculation function of the kth subtask, deadline k represents the time constraint of the kth subtask.

[0009] The optimal number of subtasks is calculated based on the characteristic vector of the computing task (input data volume, output data volume, computational complexity, and completion time limit) to ensure that task decomposition fully utilizes parallel processing capabilities while avoiding increased management overhead caused by too many factor tasks, thereby improving task processing efficiency.

[0010] A directed acyclic graph is constructed with subtasks as nodes and dependencies as edges to clarify the execution order of tasks, provide a clear basis for subsequent scheduling sequence formulation, avoid task execution confusion, and ensure the correctness of task execution.

[0011] S300: Construct a matching energy efficiency function and constraint conditions, pair subtasks and communication devices, and assign each subtask to the optimal communication device for execution; Furthermore, the specific steps of allocating each subtask to the optimal communication device for execution are: S301. Extract the resource requirement req of each subtask in the directed acyclic graph of the subtasks and construct a matching energy efficiency function: ; In the formula, U (v k , d i ) represents the matching energy efficiency between the i-th communication device and the k-th subtask, α, β and γ represent the weight coefficients, CPU i Indicates the CPU capability of the i-th communication device, RAM i Indicates the main memory capacity of the i-th communication device, prop_delay i represents the transmission delay of the i-th communication device; The construction constraints are: ; In the formula, t calc (v k ) represents the computation time of the kth subtask; S302: All subtasks and communication devices are screened and matched using the matching energy efficiency function and the constraint conditions. When the constraint conditions are met and the matching energy efficiency is maximized, the matching is successful, and each subtask is assigned to the best communication device for execution.

[0012] By matching the energy efficiency function, factors such as CPU capacity, RAM size, and transmission delay are comprehensively considered. Combined with the constraints (CPU and RAM resources meet the requirements and the transmission delay does not exceed the time constraint), each subtask is assigned to the best communication device for execution, ensuring that the task achieves optimal resource utilization while meeting the time requirements.

[0013] The precise matching process enables each subtask to run on the most suitable device, thereby improving the execution speed and quality of tasks and reducing the task failure rate caused by insufficient or mismatched device resources.

[0014] S400, using the dependency relationship in the directed acyclic graph to formulate a scheduling sequence for subtasks, and setting a start time constraint mechanism for each subtask; Furthermore, the specific steps for setting the start time constraint mechanism for each subtask are as follows: S401. Sort the execution order of subtasks by using the dependency relationship between subtasks in the directed acyclic graph. Let the scheduling sequence be , and set the conditions for the scheduling sequence as: ; The condition indicates that the order of any subtask from u to v belongs to a directed acyclic graph, where Indicates the position index of the u-th subtask in the scheduling sequence, Indicates the position index of the vth subtask in the scheduling sequence; S402, set the startup time constraint mechanism to: ; In the formula, t start (v v ) represents the start time of the vth subtask, t finish (v u ) represents the predecessor subtask v of the vth subtask u Completion time, t data_trans (v u →v v ) indicates the execution of subtask v u To execute subtask v v Data transmission time.

[0015] The dependency relationships in the directed acyclic graph are used to formulate the scheduling sequence of subtasks, ensuring that subtasks with dependencies are executed in the correct order, avoiding task failures due to sequence errors, and ensuring the smooth completion of the entire computing task.

[0016] S500, monitor the real-time subtask execution time; analyze the start time to determine whether the subtask execution fails, and initiate a rematching strategy when the task fails; Furthermore, when a task fails, the specific steps to start the rematching strategy are as follows: S501, real-time monitoring of the execution time of each subtask is ts, and the real-time execution time is judged. When ts k >t start (v k )+t calc(v k ), it is judged that the kth subtask fails to execute; where ts k Indicates the execution time of the kth subtask; the execution time of all subtasks is judged; S502. When it is determined that the subtask has failed to execute, a rematching strategy is initiated. The matching strategy is as follows: in the set of neighboring devices of the communication device whose subtask execution failed, all communication devices corresponding to the communication device whose subtask execution failed are removed, and the matching energy efficiency of the remaining communication devices and the subtasks whose execution failed is recalculated, and the maximum matching energy efficiency is selected for rematching.

[0017] When a task fails, the rematching strategy is activated to reselect a suitable device from the neighbor device set to perform the task, reducing the impact of the task failure on the entire system and improving the reliability and availability of the system.

[0018] S600: After all subtasks in the directed acyclic graph are successfully executed, the first subtask in the scheduling sequence aggregates the execution results of all subtasks to obtain the execution result of the computing task, and then sends a resource release signal to execute the next round of computing tasks.

[0019] Furthermore, the specific steps for the first subtask to aggregate the execution results of all subtasks in the scheduling sequence are: S601. When all subtasks in the directed acyclic graph are successfully executed, the first subtask in the scheduling sequence aggregates the execution results of all subtasks. The formula is: ; In the formula, Result T Indicates the final result of the calculation task T, output k represents the output result of the kth subtask, and g represents the aggregation function; after obtaining the execution result of the computing task, a resource release signal is issued to execute the next round of computing tasks.

[0020] A communication equipment networking system based on a microservice architecture, which includes a device analysis module, a task decomposition module, a matching module, a scheduling sequence module, a rematching module, and an aggregation module; The device analysis module is used to calculate the relative distance between communication devices, determine the neighbor set of each communication device based on the communication radius of the communication device; and register the microservice capability vector in each communication device; The task decomposition module is used to decompose the computing tasks in the communication device network into parallel subtasks, construct a directed acyclic graph using the dependency relationship between subtasks, and define the structure of each subtask; The matching module is used to construct a matching energy efficiency function and constraint conditions, pair subtasks and communication devices, and assign each subtask to the optimal communication device for execution; The scheduling sequence module is used to formulate the scheduling sequence of subtasks using the dependency relationship in the directed acyclic graph and set the start time constraint mechanism for each subtask; The rematching module is used to monitor the execution time of real-time subtasks; analyze the start time to determine whether the subtask has failed to execute, and initiate the rematching strategy when the task fails; The aggregation module is used to aggregate the execution results of all subtasks in the scheduling sequence to obtain the execution result of the computing task, and then send a resource release signal to execute the next round of computing tasks.

[0021] The matching module includes a matching energy efficiency unit and a constraint condition unit; The matching energy efficiency unit is used to calculate the matching energy efficiency of each subtask and all communication devices; The constraint condition unit is used to compare and judge the microservice capabilities of the communication device and the required resources in the subtask.

[0022] The scheduling sequence module includes an execution ordering unit and a time constraint unit; The execution sorting unit is used to sort the execution order of all subtasks according to the dependency relationship of each subtask; The time constraint unit is used to constrain the start time of each subtask.

[0023] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention greatly improves the efficiency of communication equipment networking computing tasks and improves resource utilization by integrating microservice architecture and edge computing.

[0024] 2. The present invention processes tasks through a cellular framework, and can achieve local self-healing when equipment fails, reducing the complexity of operation and maintenance of communication equipment.

[0025] 3. The present invention establishes the execution order of subtasks through the dependency relationship in the directed acyclic graph, thereby avoiding deadlock caused by device resource contention in multi-stage pipeline tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a module distribution diagram of the communication device networking system based on the microservice architecture of the present invention; Figure 2 The figure is a schematic diagram of the steps of the communication device networking method based on the microservice architecture of the present invention. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0028] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution. A communication device networking method based on a microservice architecture, the method comprising the following steps: S100, calculating the relative distance between communication devices, determining the neighbor set of each communication device based on the communication radius of the communication device; registering the microservice capability vector in each communication device; The specific steps to register the microservice capability vector in each communication device are: S101. Extract the location coordinates of each communication device in the communication device network, calculate the relative distance between all communication devices using the Euclidean distance formula, and assume that the communication radius of the communication device is R. comm , for communication equipment d i Use the communication radius to measure the communication equipment d i The relative distance with other communication devices is judged to obtain the communication device d i The neighbor device set is constructed as follows: ; In the formula, N i represents the set of neighboring devices of the i-th communication device, dist (d i , d j ) represents the relative distance between the i-th communication device and the j-th communication device; the same method is used to construct the neighbor device set of each communication device in the communication device network; S102: Extract all microservice capabilities in the communication device. Microservices include but are not limited to central processing units and main memories. Convert the values ​​of all microservice capabilities into vector form, so that the registered microservice capability vector of each communication device is: ; In the formula, c i represents the microservice capability vector registered by the i-th communication device, ServiceType1, ServiceType1, ... represent the 1st, 2nd, ... microservice vectors registered by the i-th communication device; CPU represents the central processing unit capability vector, and RAM represents the main memory capability vector.

[0029] S200, decomposing computing tasks in the communication device network into parallel subtasks, constructing a directed acyclic graph using dependencies between subtasks, and defining the structure of each subtask; By finding the neighboring devices of each communication device, building a set of neighboring devices, and combining the communication devices to form a cellular collaborative architecture, when processing tasks, the cellular collaborative architecture is used to reduce data transmission delays, reduce network load, and improve communication efficiency.

[0030] The microservice capabilities of communication devices are converted into vector form and registered, including key indicators such as CPU and RAM, to provide accurate device capability information for subsequent task allocation, making task allocation more reasonable.

[0031] The specific steps for setting the constraint criteria for each subtask decomposition are: S201. For a computing task in a communication device network, parse the computing task description and quantify the task feature vector T = {Input+Size, Output_Size, Computation_Complexity, Deadline}, where Input+Size represents the amount of input data for the computing task, Output_Size represents the amount of output data for the computing task, Computation_Complexity represents the computational complexity coefficient of the computing task, and Deadline represents the actual completion limit of the computing task; the computational complexity coefficient represents the number of floating-point operations involved in processing each byte of data; S202. Decompose the computing task into parallel subtasks using professional knowledge, and calculate the optimal number of subtasks based on the characteristic vector of the computing task. The formula is: ; In the formula, K represents the optimal number of subtasks, K max Indicates the maximum number of subtasks allowed in the communication equipment network, C base Indicates the baseline computing capacity of a single communication device; When decomposing the computing task, the optimal number of subtasks is met, and the input and output data of each subtask are determined. For any two subtasks, when the output of one subtask is the input of the other subtask, the two subtasks are determined to be dependent. The subtask dependencies are used as edges and the subtasks are used as nodes to construct a directed acyclic graph, specifically: G = (V, E), where G represents a directed acyclic graph, V represents a node set, and E represents an edge set; V = {v1, v2, v3, ..., v K}, v1, v2, v3, ..., v K Represents the 1st, 2nd, 3rd, ..., Kth subtask nodes in the directed acyclic graph; S203, for each subtask in the directed acyclic graph, define the structure as: V k = <ID k , input k , output k , f k , deadline k > ID k Indicates the unique identifier of the k-th subtask, input k represents the input of the kth subtask, output k represents the output of the kth subtask, f k Represents the calculation function of the kth subtask, deadline k represents the time constraint of the kth subtask.

[0032] The optimal number of subtasks is calculated based on the characteristic vector of the computing task (input data volume, output data volume, computational complexity, and completion time limit) to ensure that task decomposition fully utilizes parallel processing capabilities while avoiding increased management overhead caused by too many factor tasks, thereby improving task processing efficiency.

[0033] A directed acyclic graph is constructed with subtasks as nodes and dependencies as edges to clarify the execution order of tasks, provide a clear basis for subsequent scheduling sequence formulation, avoid task execution confusion, and ensure the correctness of task execution.

[0034] S300: Construct a matching energy efficiency function and constraint conditions, pair subtasks and communication devices, and assign each subtask to the optimal communication device for execution; The specific steps for assigning each subtask to the optimal communication device for execution are: S301. Extract the resource requirement req of each subtask in the directed acyclic graph of the subtasks and construct a matching energy efficiency function: ; In the formula, U (v k , d i ) represents the matching energy efficiency between the i-th communication device and the k-th subtask, α, β and γ represent the weight coefficients, CPU i Indicates the CPU capability of the i-th communication device, RAM i Indicates the main memory capacity of the i-th communication device, prop_delay i represents the transmission delay of the i-th communication device; The construction constraints are: ; In the formula, t calc (v k) represents the computation time of the kth subtask; S302: All subtasks and communication devices are screened and matched using the matching energy efficiency function and the constraint conditions. When the constraint conditions are met and the matching energy efficiency is maximized, the matching is successful, and each subtask is assigned to the best communication device for execution.

[0035] By matching the energy efficiency function, factors such as CPU capacity, RAM size, and transmission delay are comprehensively considered. Combined with the constraints (CPU and RAM resources meet the requirements and the transmission delay does not exceed the time constraint), each subtask is assigned to the best communication device for execution, ensuring that the task achieves optimal resource utilization while meeting the time requirements.

[0036] The precise matching process enables each subtask to run on the most suitable device, thereby improving the execution speed and quality of tasks and reducing the task failure rate caused by insufficient or mismatched device resources.

[0037] S400, using the dependency relationship in the directed acyclic graph to formulate a scheduling sequence for subtasks, and setting a start time constraint mechanism for each subtask; The specific steps to set the start time constraint mechanism for each subtask are: S401. Sort the execution order of subtasks by using the dependency relationship between subtasks in the directed acyclic graph. Let the scheduling sequence be , and set the conditions for the scheduling sequence as: ; The condition indicates that the order of any subtask from u to v belongs to a directed acyclic graph, where Indicates the position index of the u-th subtask in the scheduling sequence, Indicates the position index of the vth subtask in the scheduling sequence; S402, set the startup time constraint mechanism to: ; In the formula, t start (v v ) represents the start time of the vth subtask, t finish (v u ) represents the predecessor subtask v of the vth subtask u Completion time, t data_trans (v u →v v ) indicates the execution of subtask v u To execute subtask v v Data transmission time.

[0038] The dependency relationships in the directed acyclic graph are used to formulate the scheduling sequence of subtasks, ensuring that subtasks with dependencies are executed in the correct order, avoiding task failures due to sequence errors, and ensuring the smooth completion of the entire computing task.

[0039] S500, monitor the real-time subtask execution time; analyze the start time to determine whether the subtask execution fails, and initiate a rematching strategy when the task fails; The specific steps to start the rematching strategy when a task fails are: S501, real-time monitoring of the execution time of each subtask is ts, and the real-time execution time is judged. When ts k >t start (v k )+t calc (v k ), it is judged that the kth subtask fails to execute; where ts k Indicates the execution time of the kth subtask; the execution time of all subtasks is judged; S502. When it is determined that the subtask has failed to execute, a rematching strategy is initiated. The matching strategy is as follows: in the set of neighboring devices of the communication device whose subtask execution failed, all communication devices corresponding to the communication device whose subtask execution failed are removed, and the matching energy efficiency of the remaining communication devices and the subtasks whose execution failed is recalculated, and the maximum matching energy efficiency is selected for rematching.

[0040] When a task fails, the rematching strategy is activated to reselect a suitable device from the neighbor device set to perform the task, reducing the impact of the task failure on the entire system and improving the reliability and availability of the system.

[0041] S600: After all subtasks in the directed acyclic graph are successfully executed, the first subtask in the scheduling sequence aggregates the execution results of all subtasks to obtain the execution result of the computing task, and then sends a resource release signal to execute the next round of computing tasks.

[0042] The specific steps for the first subtask to aggregate the execution results of all subtasks in the scheduling sequence are: S601. When all subtasks in the directed acyclic graph are successfully executed, the first subtask in the scheduling sequence aggregates the execution results of all subtasks. The formula is: ; In the formula, Result T Indicates the final result of the calculation task T, output k represents the output result of the kth subtask, and g represents the aggregation function; after obtaining the execution result of the computing task, a resource release signal is issued to execute the next round of computing tasks.

[0043] Communication device networking system based on microservice architecture. The communication device networking system includes a device analysis module, a task decomposition module, a matching module, a scheduling sequence module, a re-matching module, and an aggregation module; The device analysis module is used to calculate the relative distance between communication devices, and judge the neighbor set of each communication device according to the communication radius of the communication device; register the microservice capability vector in each communication device; The task decomposition module is used to decompose the computing tasks in the communication device networking into parallel subtasks, construct a directed acyclic graph by using the dependency relationship between subtasks; define the structure of each subtask; The matching module is used to construct a matching energy efficiency function and constraint conditions, pair the subtasks and communication devices, and allocate each subtask to the best communication device for execution; The scheduling sequence module is used to formulate the scheduling sequence of subtasks by using the dependency relationship in the directed acyclic graph, and set the start time constraint mechanism for each subtask; The re-matching module is used to monitor the real-time subtask execution time; analyze the start time, judge whether the subtask fails, and start the re-matching strategy when the task fails; The aggregation module is used to aggregate all subtask execution results in the first subtask in the scheduling sequence, obtain the computing task execution result, and then send out a resource release signal to execute the next round of computing tasks.

[0044] The matching module includes a matching energy efficiency unit and a constraint condition unit; The matching energy efficiency unit is used to calculate the matching energy efficiency of each subtask and all communication devices; The constraint condition unit is used to compare and judge the microservice capabilities of communication devices and the required resources in subtasks.

[0045] The scheduling sequence module includes an execution sorting unit and a time constraint unit; The execution sorting unit is used to sort the execution order of all subtasks according to the dependency relationship of each subtask; The time constraint unit is used to constrain the start time of each subtask. Embodiment

[0046] For a subtask structure: V3 = <ID: VID123 - 03, input: Video chunk 1 (20MB), output: Detection result (0.2MB), f: YOLOv5_Detect, deadline: deadline - 35ms> Let the resources required by this subtask for CPU be: req = 2GHz, RAM be: 500M, deadline = 100ms, tcalc =80ms; There are three communication devices, and their microservice capabilities are shown in Table 1: Table 1 Microservice Capabilities

[0047] After judgment, it is found that the subtask is successfully matched with the d1 device; It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A communication device networking method based on a microservice architecture, characterized by: The method comprises the following steps: S100, calculating the relative distance between communication devices, determining the neighbor set of each communication device based on the communication radius of the communication device; registering the microservice capability vector in each communication device; S200, decomposing computing tasks in the communication device network into parallel subtasks, constructing a directed acyclic graph using dependencies between subtasks, and defining the structure of each subtask; S300: Construct a matching energy efficiency function and constraint conditions, pair subtasks and communication devices, and assign each subtask to the optimal communication device for execution; S400, using the dependency relationship in the directed acyclic graph to formulate a scheduling sequence for subtasks, and setting a start time constraint mechanism for each subtask; S500, monitor the real-time subtask execution time; analyze the start time to determine whether the subtask execution fails, and initiate a rematching strategy when the task fails; S600: After all subtasks in the directed acyclic graph are successfully executed, the first subtask in the scheduling sequence aggregates the execution results of all subtasks to obtain the execution result of the computing task, and then sends a resource release signal to execute the next round of computing tasks.

2. The method for networking communication devices based on a microservice architecture according to claim 1, wherein: The specific steps of registering the microservice capability vector in each communication device in S100 are: S101. Extract the location coordinates of each communication device in the communication device network, calculate the relative distance between all communication devices using the Euclidean distance formula, and assume that the communication radius of the communication device is R. comm , for communication equipment d i Use the communication radius to measure the communication equipment d i The relative distance with other communication devices is judged to obtain the communication device d i The neighbor device set is constructed as follows: ； In the formula, N i represents the set of neighboring devices of the i-th communication device, dist (d i , d j ) represents the relative distance between the i-th communication device and the j-th communication device; the same method is used to construct the neighbor device set of each communication device in the communication device network; S102: Extract all microservice capabilities in the communication device. Microservices include but are not limited to central processing units and main memories. Convert the values ​​of all microservice capabilities into vector form, so that the registered microservice capability vector of each communication device is: ； In the formula, c i represents the microservice capability vector registered by the i-th communication device, ServiceType1, ServiceType1, ... represent the 1st, 2nd, ... microservice vectors registered by the i-th communication device; CPU represents the central processing unit capability vector, and RAM represents the main memory capability vector.

3. The method for networking communication devices based on a microservice architecture according to claim 2, wherein: The specific steps of setting the restriction criteria for decomposing each subtask in S200 are: S201. For a computing task in a communication device network, parse the computing task description and quantify the task feature vector T = {Input+Size, Output_Size, Computation_Complexity, Deadline}, where Input+Size represents the amount of input data for the computing task, Output_Size represents the amount of output data for the computing task, Computation_Complexity represents the computational complexity coefficient of the computing task, and Deadline represents the actual completion limit of the computing task; the computational complexity coefficient represents the number of floating-point operations involved in processing each byte of data; S202. Decompose the computing task into parallel subtasks using professional knowledge, and calculate the optimal number of subtasks based on the characteristic vector of the computing task. The formula is: ； In the formula, K represents the optimal number of subtasks, K max Indicates the maximum number of subtasks allowed in the communication equipment network, C base Indicates the baseline computing capacity of a single communication device; When decomposing the computing task, the optimal number of subtasks is met, and the input and output data of each subtask are determined. For any two subtasks, when the output of one subtask is the input of the other subtask, the two subtasks are determined to be dependent. The subtask dependencies are used as edges and the subtasks are used as nodes to construct a directed acyclic graph, specifically: G = (V, E), where G represents a directed acyclic graph, V represents a node set, and E represents an edge set; V = {v1, v2, v3, ..., v K }, v1, v2, v3, ..., v K Represents the 1st, 2nd, 3rd, ..., Kth subtask nodes in the directed acyclic graph; S203, for each subtask in the directed acyclic graph, define the structure as: V k = <ID k , input k , output k , f k , deadline k > ID k Indicates the unique identifier of the k-th subtask, input k represents the input of the kth subtask, output k represents the output of the kth subtask, f k Represents the calculation function of the kth subtask, deadline k represents the time constraint of the kth subtask.

4. The method for networking communication devices based on a microservice architecture according to claim 3, wherein: The specific steps of allocating each subtask to the optimal communication device for execution in S300 are: S301. Extract the resource requirement req of each subtask in the directed acyclic graph of the subtasks and construct a matching energy efficiency function: ； In the formula, U (v k , d i ) represents the matching energy efficiency between the i-th communication device and the k-th subtask, α, β and γ represent the weight coefficients, CPU i Indicates the CPU capability of the i-th communication device, RAM i Indicates the main memory capacity of the i-th communication device, prop_delay i represents the transmission delay of the i-th communication device; The construction constraints are: ； In the formula, t calc (v k ) represents the computation time of the kth subtask; S302: All subtasks and communication devices are screened and matched using the matching energy efficiency function and the constraint conditions. When the constraint conditions are met and the matching energy efficiency is maximized, the matching is successful, and each subtask is assigned to the best communication device for execution.

5. The method for networking communication devices based on microservice architecture according to claim 4, characterized in that: The specific steps of setting the start time constraint mechanism for each subtask in S400 are: S401. Sort the execution order of subtasks by using the dependency relationship between subtasks in the directed acyclic graph. Let the scheduling sequence be , and set the conditions for the scheduling sequence as: ； The condition indicates that the order of any subtask from u to v belongs to a directed acyclic graph, where Indicates the position index of the u-th subtask in the scheduling sequence, Indicates the position index of the vth subtask in the scheduling sequence; S402, set the startup time constraint mechanism to: ； In the formula, t start (v v ) represents the start time of the vth subtask, t finish (v u ) represents the predecessor subtask v of the vth subtask u Completion time, t data_trans (v u →v v ) indicates the execution of subtask v u To execute subtask v v Data transmission time.

6. The method for networking communication devices based on microservice architecture according to claim 5, characterized in that: The specific steps of starting the rematching strategy when the task fails in S500 are: S501, real-time monitoring of the execution time of each subtask is ts, and the real-time execution time is judged. When ts k >t start (v k )+t calc (v k ), it is judged that the kth subtask fails to execute; where ts k Indicates the execution time of the kth subtask; the execution time of all subtasks is judged; S502. When it is determined that the subtask has failed to execute, a rematching strategy is initiated. The matching strategy is as follows: in the set of neighboring devices of the communication device whose subtask execution failed, all communication devices corresponding to the communication device whose subtask execution failed are removed, and the matching energy efficiency of the remaining communication devices and the subtasks whose execution failed is recalculated, and the maximum matching energy efficiency is selected for rematching.

7. The method for networking communication devices based on microservice architecture according to claim 6, characterized in that: The specific steps of aggregating the execution results of all subtasks in the scheduling sequence in S600 are: S601. When all subtasks in the directed acyclic graph are successfully executed, the first subtask in the scheduling sequence aggregates the execution results of all subtasks. The formula is: ； In the formula, Result T Indicates the final result of the calculation task T, output k represents the output result of the kth subtask, and g represents the aggregation function; After obtaining the result of the computing task execution, a resource release signal is issued to execute the next round of computing tasks.

8. A communication equipment networking system based on a microservice architecture, characterized by: The communication equipment networking system includes an equipment analysis module, a task decomposition module, a matching module, a scheduling sequence module, a rematching module and an aggregation module; The device analysis module is used to calculate the relative distance between communication devices, determine the neighbor set of each communication device based on the communication radius of the communication device; and register the microservice capability vector in each communication device; The task decomposition module is used to decompose the computing tasks in the communication device network into parallel subtasks, construct a directed acyclic graph using the dependency relationship between subtasks, and define the structure of each subtask; The matching module is used to construct a matching energy efficiency function and constraint conditions, pair subtasks and communication devices, and assign each subtask to the optimal communication device for execution; The scheduling sequence module is used to formulate the scheduling sequence of subtasks using the dependency relationship in the directed acyclic graph and set the start time constraint mechanism for each subtask; The rematching module is used to monitor the execution time of the real-time subtask; Analyze the startup time to determine whether the subtask has failed. If the task fails, initiate a rematch strategy. The aggregation module is used to aggregate the execution results of all subtasks in the scheduling sequence to obtain the execution result of the computing task, and then send a resource release signal to execute the next round of computing tasks.

9. The communication device networking system based on microservice architecture according to claim 8, characterized in that: The matching module includes a matching energy efficiency unit and a constraint condition unit; The matching energy efficiency unit is used to calculate the matching energy efficiency of each subtask and all communication devices; The constraint condition unit is used to compare and judge the microservice capabilities of the communication device and the required resources in the subtask.

10. The communication device networking system based on microservice architecture according to claim 8, characterized in that: The scheduling sequence module includes an execution sorting unit and a time constraint unit; The execution sorting unit is used to sort the execution order of all subtasks according to the dependency relationship of each subtask; The time constraint unit is used to constrain the start time of each subtask.

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