Distributed synchronization time method and system based on hybrid network

Abstract

The present invention relates to the field of signal control technology, and is a distributed synchronization time synchronization method and system based on a hybrid network. The specific method includes: drawing a topological relationship diagram of a hybrid network, and dividing the topological relationship diagram of the hybrid network into multiple data centers; collecting network response status data of each data center area, and calculating the network response anomaly coefficient in the evaluation strategy; collecting single node working status data of each data center area, and calculating the working status anomaly coefficient; evaluating the time synchronization anomaly rate of each data center area; according to the time synchronization anomaly rate, adaptively selecting a regional self-recovery strategy, and synchronizing the self-recovery records of each data center area to the hybrid network time synchronization log. The present invention solves the problems of low efficiency of structural management and maintenance in a complex network environment and poor stability and low reliability of network synchronization in the prior art.

Description

Technical Field

[0001] The invention relates to the technical field of signal control, and is a distributed synchronous timing method and system based on a hybrid network. Background Art

[0002] In modern computer networks, ensuring time synchronization between nodes is one of the key issues to ensure the normal operation of the network and the reliability of data communication. Traditional network synchronization methods, such as synchronization technology based on the Network Time Protocol (NTP), are usually limited by network delays and clock drift, and are difficult to meet application scenarios that require high-precision synchronization, such as financial transactions and industrial automation. In addition, when facing large-scale distributed networks, traditional synchronization methods also face challenges such as complex network topology, a large number of nodes, and increased communication load. These factors may lead to reduced synchronization accuracy and affect system stability.

[0003] In the existing disclosed invention technology, for example, the patent with publication number CN104184828A discloses a hybrid network system, a communication method and a network node. The hybrid network system includes a combined network architecture of a point-to-point network and a broadcast network. The point-to-point network has multiple point-to-point channels, and each network node can send messages to the corresponding network node or receive messages from the corresponding network node via the point-to-point channel; the broadcast network has multiple broadcast channels, and each broadcast channel can have at most one sender at the same time, but can have multiple receivers; at least some network nodes have the ability to send messages to be broadcast, and at least some network nodes have the ability to receive broadcast messages, and at least some network nodes are configured to select a broadcast network or a point-to-point network to complete the communication task to be performed at least according to the communication task to be performed by themselves. Preferably, each network node has the ability to send and receive broadcast messages.

[0004] Although the hybrid network of the above patent integrates multiple communication methods and optimization strategies, network load and delay are still key factors affecting synchronization accuracy, especially during periods of intensive communication or high load, data transmission delays or conflicts may occur, affecting the timeliness and accuracy of synchronization data. Summary of the invention

[0005] The technical problem to be solved by the present invention is to address the problems of low efficiency of structure management and maintenance in complex network environments and poor stability and low reliability of network synchronization in the prior art, and propose a distributed synchronization method and system based on a hybrid network.

[0006] In order to achieve the above object, the technical solution of the distributed synchronization method based on the hybrid network of the present invention includes the following steps:

[0007] S1: extract the topological relationship between each node of the hybrid network, draw a topological relationship diagram of the hybrid network, and divide the topological relationship diagram of the hybrid network into multiple data centers;

[0008] S2: Collecting network response status data of each data center area, and importing the network response status data into a network response status evaluation strategy to calculate a network response anomaly coefficient;

[0009] S3: Collecting the working status data of a single node in each data center area, and importing the working status data of the single node into the node working status evaluation strategy to calculate the working status abnormality coefficient;

[0010] S4: extracting the network response abnormality coefficient and the working status abnormality coefficient, and evaluating the time synchronization abnormality rate of each data center area;

[0011] S5: Adaptively select the regional self-recovery strategy based on the time synchronization anomaly rate, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log.

[0012] Specifically, S1 includes the following specific steps:

[0013] S11: extract n nodes of the hybrid network to form a node data set S = (s1, s2...s n-1 ), where s n-1 is the characteristic relationship between the n-1th node and the nth node;

[0014] S12: Calculate the fuzzy membership matrix L of the node data set, L = [l ij ], initialize the fuzzy membership matrix and calculate the fuzzy cluster center matrix, specifically:

[0015]

[0016] S13: Establish a clustering function, and import the fuzzy membership matrix L of the node data set into the clustering function, the clustering function is:

[0017] m is the number of data center regions obtained after fuzzy clustering of the hybrid network;

[0018] is the Manhattan distance between the i-th cluster node and the j-th data center area in the node data set S;

[0019] S14: extract the minimum value of the clustering function, and compare the minimum value of the clustering function with a preset fuzzy clustering threshold. When the difference between the minimum value of the clustering function and the fuzzy clustering threshold is the smallest, complete the regional division processing of the topological relationship diagram of the hybrid network and obtain m data center areas.

[0020] Specifically, S2 includes the following specific steps:

[0021] S21: extract the m data center areas obtained by the division in S1, and collect the bandwidth utilization rate of each data center area and the node load rate of each node in the data center area in real time through the network traffic monitor;

[0022] S22: The bandwidth utilization rate and node load rate of each data center area are introduced into the effective response probability value calculation strategy to calculate the effective response probability value of each data center area of ​​the hybrid network. The effective response probability value calculation strategy is specifically:

[0023]

[0024] Among them, e 1，m is the effective response probability value of the mth data center area;

[0025] h m is a subscript, indicating the hth node in the mth data center area; H m is the total number of nodes in the mth data center area;

[0026] h m The node load rate of the nodes and the average node load rate of the mth data center area;

[0027] DK m , are the bandwidth utilization of the mth data center area and the average bandwidth utilization of the hybrid network;

[0028] S23: The node packet loss rate of each node in each data center area is collected in real time through a network traffic monitor, and the node packet loss rate is introduced into a response error value calculation strategy to calculate the response error value of each data center area of ​​the hybrid network. The response error value calculation strategy is specifically as follows:

[0029]

[0030] Among them, e 2，m is the response error value of the mth data center area;

[0031] DB middle h mThe node packet loss rate of nodes and the closest one in the mth data center area The node packet loss rate.

[0032] Specifically, S3 includes the following specific steps:

[0033] S31: Record the clock drift data and clock deviation data of each node in the m data center areas to form a clock drift curve and clock skew curve in, is the function of the clock drift of the hth node in the mth data center area over time; is the function of the clock offset of the hth node in the mth data center area over time;

[0034] S32: Import the clock drift curve and the clock offset curve into the node working state evaluation strategy to calculate the working state abnormality coefficient r. The node working state evaluation strategy is specifically:

[0035]

[0036] Wherein, t is a unit evaluation period; ε1 and ε2 are the node working status evaluation ratios of clock drift and clock offset, respectively, ε1+ε2=0.8.

[0037] Specifically, in S4, the evaluation strategy for evaluating the time synchronization anomaly rate of each data center area is as follows:

[0038] Φ m =α1×φ1+α2×φ2;

[0039] Among them, Φ m is the time synchronization anomaly rate of the mth data center area;

[0040] φ1 and φ2 are the impact values ​​of abnormal network response and abnormal node working status on the hybrid network respectively;

[0041] α1 and α2 are the time synchronization anomaly influence ratios of the network response anomaly coefficient and the working state anomaly coefficient respectively; α1>α2.

[0042] Specifically, S5 includes the following specific steps:

[0043] S51: extracting the time synchronization anomaly rate data of each data center and performing abnormal area screening. When the time synchronization anomaly rate of the data center area is greater than the preset anomaly screening threshold in three consecutive monitoring periods, the data center area is marked as a time synchronization anomaly area, and step S52 is executed;

[0044] Otherwise, return to step S2 to continue to evaluate the status of the hybrid network;

[0045] S52: extracting the time synchronization anomaly rate data of the time synchronization anomaly area, configuring the hybrid network self-recovery selection thresholds G1 and G2, and selecting a self-recovery strategy;

[0046] When φ1≥G1, φ2<G2, the self-recovery strategy is to dynamically adjust the load and reallocate network resources;

[0047] When φ1<G1, φ2≥G2, the self-recovery strategy is: restart the abnormal node through remote operation;

[0048] When φ1≥G1, φ2≥G2, the self-recovery strategy is: automatically switch to the backup path or node, and transfer the task to the backup node;

[0049] S53: Adaptively select a regional self-recovery strategy, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log.

[0050] In addition, the distributed synchronization system based on the hybrid network of the present invention includes the following modules:

[0051] The system includes the following modules:

[0052] Data area division module, network response status evaluation module, node working status evaluation module, time synchronization anomaly rate calculation module, adaptive time synchronization module;

[0053] The data area division module is used to extract the topological relationship between each node of the hybrid network, draw a topological relationship diagram of the hybrid network, and divide the topological relationship diagram of the hybrid network into multiple data centers;

[0054] The network response status evaluation module is used to collect network response status data of each data center area, and import the network response status data into the network response status evaluation strategy to calculate the network response anomaly coefficient;

[0055] The node working status evaluation module is used to collect the working status data of individual nodes in each data center area, and import the working status data of individual nodes into the node working status evaluation strategy to calculate the working status abnormality coefficient;

[0056] The time synchronization anomaly rate calculation module is used to extract the network response anomaly coefficient and the working state anomaly coefficient, and evaluate the time synchronization anomaly rate of each data center area;

[0057] The adaptive timing module adaptively selects a regional self-recovery strategy according to the time synchronization anomaly rate, and synchronizes the self-recovery records of each data center area to the hybrid network timing log.

[0058] Specifically, the adaptive timing module includes: a hybrid network timing log unit, a self-recovery strategy execution unit and a timing cycle optimization unit;

[0059] The hybrid network time synchronization log unit is used to extract the time synchronization anomaly rate of each data center area obtained by evaluation;

[0060] The self-recovery strategy execution unit is used to select and execute the self-recovery strategy of the adaptive selection area, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log unit;

[0061] The time synchronization cycle optimization unit is used to count the time intervals of the self-recovery records of each data center area, and dynamically adjust the time synchronization cycle of each data center area according to the time intervals.

[0062] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the distributed synchronization method based on a hybrid network.

[0063] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned distributed synchronization and timing method based on a hybrid network when executing the computer program.

[0064] Compared with the prior art, the technical effects of the present invention are as follows:

[0065] 1. The present invention simplifies the structure management in a complex network environment and improves the efficiency of network organization and maintenance by extracting and drawing the topological relationship of the hybrid network and dividing it into data centers.

[0066] 2. The present invention collects and analyzes network response status data and node working status data, calculates the abnormality coefficient, and realizes accurate monitoring of network status, and timely identifies and handles potential abnormal problems.

[0067] 3. The present invention ensures the stability and reliability of network synchronization by evaluating the time synchronization anomaly rate and adaptively selecting a recovery strategy based on this information. At the same time, the recovery record is synchronized to the log, thereby enhancing the system's fault handling capability and data tracking capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0069] in:

[0070] Figure 1 It is a flow chart of a distributed synchronization method based on a hybrid network of the present invention;

[0071] Figure 2 It is a structural schematic diagram of the distributed synchronization and timing system based on the hybrid network of the present invention. DETAILED DESCRIPTION

[0072] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0073] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0074] Embodiment 1:

[0075] like Figure 1 As shown, the distributed synchronization method based on the hybrid network of the embodiment of the present invention is as follows: Figure 1 As shown, the specific steps are as follows:

[0076] S1: extract the topological relationship between each node of the hybrid network, draw a topological relationship diagram of the hybrid network, and divide the topological relationship diagram of the hybrid network into multiple data centers;

[0077] S11: extract n nodes of the hybrid network to form a node data set S = (s1, s2, ..., s n-1 ), where s n-1 is the characteristic relationship between the n-1th node and the nth node;

[0078] Exemplarily, in this embodiment, a characteristic relationship between nodes is provided, wherein the characteristic relationship is the communication delay between nodes of the hybrid network obtained by real-time measurement using a delay measurement tool;

[0079] S12: Calculate the fuzzy membership matrix L of the node data set, L = [l ij], initialize the fuzzy membership matrix and calculate the fuzzy cluster center matrix, specifically:

[0080]

[0081] S13: Establish a clustering function, and import the fuzzy membership matrix L of the node data set into the clustering function, the clustering function is:

[0082] m is the number of data center regions obtained after fuzzy clustering of the hybrid network;

[0083] is the Manhattan distance between the i-th cluster node and the j-th data center area in the node data set S;

[0084] S14: extract the minimum value of the clustering function, and compare the minimum value of the clustering function with a preset fuzzy clustering threshold. When the difference between the minimum value of the clustering function and the fuzzy clustering threshold is the smallest, complete the regional division processing of the topological relationship diagram of the hybrid network and obtain m data center areas.

[0085] S2: Collecting network response status data of each data center area, and importing the network response status data into a network response status evaluation strategy to calculate a network response anomaly coefficient;

[0086] S21: extract the m data center areas obtained by the division in S1, and collect the bandwidth utilization rate of each data center area and the node load rate of each node in the data center area in real time through the network traffic monitor;

[0087] S22: The bandwidth utilization rate and node load rate of each data center area are introduced into the effective response probability value calculation strategy to calculate the effective response probability value of each data center area of ​​the hybrid network. The effective response probability value calculation strategy is specifically:

[0088]

[0089] Among them, e 1，m is the effective response probability value of the mth data center area;

[0090] h m is a subscript, indicating the hth node in the mth data center area; H m is the total number of nodes in the mth data center area;

[0091] h m The node load rate of the nodes and the average node load rate of the mth data center area;

[0092] DKm , are the bandwidth utilization of the mth data center area and the average bandwidth utilization of the hybrid network;

[0093] S23: The node packet loss rate of each node in each data center area is collected in real time through a network traffic monitor, and the node packet loss rate is introduced into a response error value calculation strategy to calculate the response error value of each data center area of ​​the hybrid network. The response error value calculation strategy is specifically as follows:

[0094]

[0095] Among them, e 2，m is the response error value of the mth data center area;

[0096] DB middle h m The node packet loss rate of nodes and the closest one in the mth data center area The node packet loss rate.

[0097] S3: Collecting the working status data of a single node in each data center area, and importing the working status data of the single node into the node working status evaluation strategy to calculate the working status abnormality coefficient;

[0098] S31: Record the clock drift data and clock deviation data of each node in the m data center areas to form a clock drift curve and clock skew curve in, is the function of the clock drift of the hth node in the mth data center area over time; is the function of the clock offset of the hth node in the mth data center area over time;

[0099] S32: Import the clock drift curve and the clock offset curve into the node working state evaluation strategy to calculate the working state abnormality coefficient r. The node working state evaluation strategy is specifically:

[0100]

[0101] Wherein, t is a unit evaluation period; ε1 and ε2 are the node working status evaluation ratios of clock drift and clock offset, respectively, ε1+ε2=0.8.

[0102] S4: extracting the network response abnormality coefficient and the working status abnormality coefficient, and evaluating the time synchronization abnormality rate of each data center area;

[0103] In S4, the evaluation strategy for evaluating the time synchronization anomaly rate of each data center area is specifically as follows:

[0104] Φ m =α1×φ1+α2×φ2;

[0105] Among them, Φ m is the time synchronization anomaly rate of the mth data center area;

[0106] φ1 and φ2 are the impact values ​​of abnormal network response and abnormal node working status on the hybrid network respectively;

[0107] α1 and α2 are the time synchronization anomaly influence ratios of the network response anomaly coefficient and the working state anomaly coefficient respectively; α1>α2.

[0108] S5: Adaptively select the regional self-recovery strategy based on the time synchronization anomaly rate, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log.

[0109] S51: extracting the time synchronization anomaly rate data of each data center and performing abnormal area screening. When the time synchronization anomaly rate of the data center area is greater than the preset anomaly screening threshold in three consecutive monitoring periods, the data center area is marked as a time synchronization anomaly area, and step S52 is executed;

[0110] Otherwise, return to step S2 to continue to evaluate the status of the hybrid network;

[0111] S52: extracting the time synchronization anomaly rate data of the time synchronization anomaly area, configuring the hybrid network self-recovery selection thresholds G1 and G2, and selecting a self-recovery strategy;

[0112] When φ1≥G1, φ2<G2, the self-recovery strategy is to dynamically adjust the load and reallocate network resources;

[0113] When φ1<G1, φ2≥G2, the self-recovery strategy is: restart the abnormal node through remote operation;

[0114] When φ1≥G1, φ2≥G2, the self-recovery strategy is: automatically switch to the backup path or node, and transfer the task to the backup node;

[0115] S53: Adaptively select a regional self-recovery strategy, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log.

[0116] Embodiment 2:

[0117] like Figure 2As shown, the distributed synchronization system based on the hybrid network of the embodiment of the present invention includes the following modules:

[0118] Data area division module, network response status evaluation module, node working status evaluation module, time synchronization anomaly rate calculation module, adaptive time synchronization module;

[0119] The data area division module is used to extract the topological relationship between each node of the hybrid network, draw a topological relationship diagram of the hybrid network, and divide the topological relationship diagram of the hybrid network into multiple data centers;

[0120] The network response status evaluation module is used to collect network response status data of each data center area, and import the network response status data into the network response status evaluation strategy to calculate the network response anomaly coefficient;

[0121] The node working status evaluation module is used to collect the working status data of individual nodes in each data center area, and import the working status data of individual nodes into the node working status evaluation strategy to calculate the working status abnormality coefficient;

[0122] The time synchronization anomaly rate calculation module is used to extract the network response anomaly coefficient and the working state anomaly coefficient, and evaluate the time synchronization anomaly rate of each data center area;

[0123] The adaptive timing module adaptively selects a regional self-recovery strategy according to the time synchronization anomaly rate, and synchronizes the self-recovery records of each data center area to the hybrid network timing log.

[0124] The adaptive timing module includes: a hybrid network timing log unit, a self-recovery strategy execution unit and a timing cycle optimization unit;

[0125] The hybrid network time synchronization log unit is used to extract the time synchronization anomaly rate of each data center area obtained by evaluation;

[0126] The self-recovery strategy execution unit is used to select and execute the self-recovery strategy of the adaptive selection area, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log unit;

[0127] The time synchronization cycle optimization unit is used to count the time intervals of the self-recovery records of each data center area, and dynamically adjust the time synchronization cycle of each data center area according to the time intervals.

[0128] Exemplarily, in this embodiment, a method for dynamically adjusting the time synchronization period of each data center area according to the time interval is provided, and the method is specifically as follows: first, the time intervals are arranged from small to large, and then the time synchronization period lengths of each data center area are orderly allocated according to the time intervals; when the time interval is less than or equal to the time synchronization time interval threshold, the time synchronization period length of the data center area is shortened; otherwise, the time synchronization period length of the data center area is extended.

[0129] Embodiment three:

[0130] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0131] The processor executes the above-mentioned distributed synchronization and timing method based on the hybrid network by calling the computer program stored in the memory.

[0132] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement the distributed synchronization method and system based on a hybrid network provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0133] Embodiment 4:

[0134] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0135] When the computer program runs on a computer device, the computer device is enabled to execute the above-mentioned distributed synchronization method based on a hybrid network.

[0136] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0137] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0138] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0139] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0140] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0141] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0142] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0143] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0144] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0145] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0146] In summary, compared with the prior art, the technical effects of the present invention are as follows:

[0147] 1. The present invention simplifies the structure management in a complex network environment and improves the efficiency of network organization and maintenance by extracting and drawing the topological relationship of the hybrid network and dividing it into data centers.

[0148] 2. The present invention collects and analyzes network response status data and node working status data, calculates the abnormality coefficient, and realizes accurate monitoring of network status, and timely identifies and handles potential abnormal problems.

[0149] 3. The present invention ensures the stability and reliability of network synchronization by evaluating the time synchronization anomaly rate and adaptively selecting a recovery strategy based on this information. At the same time, the recovery record is synchronized to the log, thereby enhancing the system's fault handling capability and data tracking capability.

[0150] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. Distributed synchronization method based on hybrid network, Features: The method comprises the following specific steps: S1: extract the topological relationship between each node of the hybrid network, draw a topological relationship diagram of the hybrid network, and divide the topological relationship diagram of the hybrid network into multiple data centers; S2: Collecting network response status data of each data center area, and importing the network response status data into a network response status evaluation strategy to calculate a network response anomaly coefficient; S3: Collecting the working status data of a single node in each data center area, and importing the working status data of the single node into the node working status evaluation strategy to calculate the working status abnormality coefficient; S4: extracting the network response abnormality coefficient and the working status abnormality coefficient, and evaluating the time synchronization abnormality rate of each data center area; S5: Adaptively select the regional self-recovery strategy based on the time synchronization anomaly rate, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log; S1 includes the following specific steps: S11: extract n nodes of the hybrid network to form a node data set S = (s 1 ,s 2 ,...,s n-1 ), where s n-1 is the characteristic relationship between the n-1th node and the nth node; S12: Calculate the fuzzy membership matrix L of the node data set, L = [l ij ], initialize the fuzzy membership matrix and calculate the fuzzy cluster center matrix, specifically: S13: Establish a clustering function, and import the fuzzy membership matrix L of the node data set into the clustering function, the clustering function is: m is the number of data center regions obtained after fuzzy clustering of the hybrid network; is the Manhattan distance between the i-th cluster node and the j-th data center area in the node data set S; S14: extract the minimum value of the clustering function, and compare the minimum value of the clustering function with a preset fuzzy clustering threshold. When the difference between the minimum value of the clustering function and the fuzzy clustering threshold is the smallest, complete the regional division processing of the topological relationship diagram of the hybrid network and obtain m data center areas.

2. The distributed synchronization method based on a hybrid network according to claim 1, It is characterized in that S2 includes the following specific steps: S21: extract the m data center areas obtained by the division in S1, and collect the bandwidth utilization rate of each data center area and the node load rate of each node in the data center area in real time through the network traffic monitor; S22: The bandwidth utilization rate and node load rate of each data center area are introduced into the effective response probability value calculation strategy to calculate the effective response probability value of each data center area of ​​the hybrid network. The effective response probability value calculation strategy is specifically: Among them, e 1,m is the effective response probability value of the mth data center area; h m is a subscript, indicating the hth node in the mth data center area; H m is the total number of nodes in the mth data center area; h m The node load rate of the nodes and the average node load rate of the mth data center area; DK m , are the bandwidth utilization of the mth data center area and the average bandwidth utilization of the hybrid network; S23: The node packet loss rate of each node in each data center area is collected in real time through a network traffic monitor, and the node packet loss rate is introduced into a response error value calculation strategy to calculate the response error value of each data center area of ​​the hybrid network. The response error value calculation strategy is specifically as follows: Among them, e 2,m is the response error value of the mth data center area; DB middle h m The node packet loss rate of nodes and the closest one in the mth data center area The node packet loss rate.

3. The distributed synchronization method based on a hybrid network according to claim 2, It is characterized in that S3 includes the following specific steps: S31: Record the clock drift data and clock deviation data of each node in the m data center areas to form a clock drift curve and clock skew curve in, is the function of the clock drift of the hth node in the mth data center area over time; is the function of the clock offset of the hth node in the mth data center area over time; S32: Import the clock drift curve and the clock offset curve into the node working state evaluation strategy to calculate the working state abnormality coefficient r. The node working state evaluation strategy is specifically: Where t is a unit evaluation period; ε 1 ,ε 2 are the node working status evaluation ratios of clock drift and clock offset, respectively, 1 +ε 2 =0.

8.

4. The distributed synchronization method based on a hybrid network according to claim 3, It is characterized in that In S4, the evaluation strategy for evaluating the time synchronization anomaly rate of each data center area is specifically as follows: F m =a 1 ×φ 1 +a 2 ×φ 2 ; Among them, Φ m is the time synchronization anomaly rate of the mth data center area; φ 1 ,φ 2 They are the impact values ​​of abnormal network response and abnormal node working status on the hybrid network; α 1 ,α 2 are the time synchronization anomaly impact ratios of the network response anomaly coefficient and the working status anomaly coefficient respectively; α 1 >α 2 .

5. The distributed synchronization method based on a hybrid network according to claim 4, It is characterized in that S5 includes the following specific steps: S51: extracting the time synchronization anomaly rate data of each data center and performing abnormal area screening. When the time synchronization anomaly rate of the data center area is greater than the preset anomaly screening threshold in three consecutive monitoring periods, the data center area is marked as a time synchronization anomaly area, and step S52 is executed; Otherwise, return to step S2 to continue to evaluate the status of the hybrid network; S52: Extract the time synchronization anomaly rate data of the time synchronization anomaly area and configure the hybrid network self-recovery selection threshold G 1 ,G 2 , and select a self-recovery strategy; When φ 1 ≥G 1 ,φ 2 <G 2 When the network is running, the self-recovery strategy is to dynamically adjust the load and reallocate network resources; When φ 1 <G 1 ,φ 2 ≥G 2 When the self-recovery strategy is implemented, the abnormal node is restarted through remote operation; When φ 1 ≥G 1 ,φ 2 ≥G 2 When the system is running, the self-recovery strategy is to automatically switch to the backup path or node and transfer the task to the backup node; S53: Adaptively select a regional self-recovery strategy, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log.

6. A distributed synchronization time system based on a hybrid network, which is used to implement the distributed synchronization time method based on a hybrid network as described in any one of claims 1 to 5, It is characterized in that The system includes the following modules: Data area division module, network response status evaluation module, node working status evaluation module, time synchronization anomaly rate calculation module, adaptive time synchronization module; The data area division module is used to extract the topological relationship between each node of the hybrid network, draw a topological relationship diagram of the hybrid network, and divide the topological relationship diagram of the hybrid network into multiple data centers; The network response status evaluation module is used to collect network response status data of each data center area, and import the network response status data into the network response status evaluation strategy to calculate the network response anomaly coefficient; The node working status evaluation module is used to collect the working status data of individual nodes in each data center area, and import the working status data of individual nodes into the node working status evaluation strategy to calculate the working status abnormality coefficient; The time synchronization anomaly rate calculation module is used to extract the network response anomaly coefficient and the working state anomaly coefficient, and evaluate the time synchronization anomaly rate of each data center area; The adaptive timing module adaptively selects a regional self-recovery strategy according to the time synchronization anomaly rate, and synchronizes the self-recovery records of each data center area to the hybrid network timing log.

7. The distributed synchronization system based on hybrid network according to claim 6, It is characterized in that The adaptive timing module includes: a hybrid network timing log unit, a self-recovery strategy execution unit and a timing cycle optimization unit; The hybrid network time synchronization log unit is used to extract the time synchronization anomaly rate of each data center area obtained by evaluation; The self-recovery strategy execution unit is used to select and execute the self-recovery strategy of the adaptive selection area, and synchronize the self-recovery records of each data center area to the hybrid network time synchronization log unit; The time synchronization cycle optimization unit is used to count the time intervals of the self-recovery records of each data center area, and dynamically adjust the time synchronization cycle of each data center area according to the time intervals.

8. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the distributed synchronization method based on a hybrid network as described in any one of claims 1 to 5 is implemented.

9. An electronic device, It is characterized in that include: A memory for storing instructions; A processor is used to execute the instruction so that the device performs the operation of implementing the distributed synchronization method based on a hybrid network as described in any one of claims 1-5.

Images