A method for realizing network data flow perspective in cloud

Abstract

The invention relates to the technical field of digital communication and software development, and discloses a method for realizing network data flow perspective in a cloud. By allocating a unique index in the cloud and uniformly associating it with flow perspective data recorded on a network node, the network data flow can be clarified and the network transmission can be transparent. The flow direction data of the traffic can be easily obtained according to the flow perspective result, and the flow direction data can be expanded to realize the business data flow topology and provide means for troubleshooting personnel to assist in determining relevant network problems. By issuing perspective configuration, flow perspective is performed for specific traffic to meet differentiated and precise perspective requirements. Network nodes filter and extract information, and flow perspective is performed in a single message dimension, with finer analysis granularity. Network nodes update perspective information, and the function occupies less memory and transmission bandwidth, and only single perspective data is used for carrying or saving. A perspective diagram is generated, and the data flow perspective result can be infinitely long in theory and is not restricted by any transmission protocol.

Description

Technical Field

[0001] The present invention relates to the technical field of digital communication and software development, and in particular to a method for realizing intra-cloud network data flow perspective. Background Art

[0002] In order to meet the growing demand of enterprises for bandwidth resources, computing resources, storage resources and other resources, cloud network technology plays an important role. Therefore, in order to meet the various needs of enterprises, the creators of cloud networks will design the entire network system more complex. In the cloud network system, network forwarding is a very important component, but network forwarding often has some problems. Due to the complexity of the business, the data flow is also ever-changing. Generally, network failures are relatively simple to troubleshoot. They can be solved by checking a certain network node. However, for sudden or more complex failures, due to the limitations of troubleshooting and positioning methods, the problem cannot be solved quickly.

[0003] The cloud network data flow perspective function can perspective the network data flow based on the single packet dimension and display the perspective results. Through the perspective results, you can clearly see all the network nodes that the data message passes through, and then judge whether the flow direction and forwarding process are correct. And if the traffic is discarded, you can also easily locate the specific location where the data is discarded. And you can use the filtering function to perspective specific traffic to meet differentiated flow perspective requirements. The flow perspective function can not only perspective the current data flow of the network, but also troubleshoot based on this function. Improve the troubleshooting efficiency of operation and maintenance personnel and reduce troubleshooting time.

[0004] For example, a Chinese patent with publication number CN115757433A discloses a method for implementing a unique constraint on an AO table on an MPP database that meets ACID characteristics. The method includes creating a unique index on the AO table, updating existing data in the AO table with a unique index, and then deleting the existing data on the AO table; importing new data to the current AO table row by row, and sending each row of data to the corresponding data node according to the distribution strategy of the current AO table, and writing it into the independent buffer of the AO table; then constructing an index tuple with the newly added data row TID and index column of the current AO table, and inserting it into the shared cache area of ​​the current index. By creating a unique index, and importing new data to the AO table based on the unique index, and performing conflict judgment by constructing an index tuple, the current transaction is rolled back when a conflict occurs, thereby solving the unique constraint problem of the AO table on the basis of the solution to the unique constraint of the heap table, and does not bring negative impact to the unique constraint implementation of the heap table.

[0005] For example, a Chinese patent with the authorization announcement number CN115865802B discloses a traffic mirroring method, device, virtual machine platform and storage medium for a virtual instance, which relates to the field of communication technology. The method includes: obtaining the traffic to be mirrored of the virtual instance; mirroring the inbound and outbound traffic of the virtual instance at the computing node of the virtual instance to obtain the mirrored traffic; obtaining the constructed traffic flow table for the mirrored traffic, generating a mirrored traffic message according to the mirrored traffic and the traffic flow table; sending the mirrored traffic message to the destination terminal so that the destination terminal can distinguish the inbound and outbound mirrored traffic of the port according to the mirrored traffic message. By implementing the mirroring of the traffic to be mirrored and the generation of the mirrored traffic message at the computing node, the relevant information of the virtual instance mirrored traffic is designed into the message, and it is sent out from the computing node in the form of a message carrying, so as to realize the mirroring and mirrored sending of the traffic of the virtual instance while occupying the least data center, and realize the distinction of the mirrored traffic at the terminal node.

[0006] The above patents have the problem raised by this background technology: the business in the cloud is complex and diverse, and the business traffic usually has to pass through multiple network nodes to reach the end point. Each network node performs corresponding business processing. If there is a problem of packet loss or large delay in the intermediate transmission process, it is difficult to locate which node is causing the problem. In some business scenarios, the same traffic may enter and exit from a network node multiple times. Under complex traffic data processing business, it is more difficult to troubleshoot problems. To solve this problem, the present invention proposes a method for realizing the perspective of network data flow in the cloud. Summary of the invention

[0007] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0008] In view of the problems existing in the above-mentioned existing method for implementing intra-cloud network data flow perspective, the present invention is proposed.

[0009] Therefore, the object of the present invention is to provide a method for realizing intra-cloud network data flow perspective.

[0010] To solve the above technical problems, the present invention provides the following technical solutions: intra-cloud network data flow perspective includes intra-cloud unique index allocation, flow feature recording and flow perspective analysis;

[0011] The process of the network data flow perspective in the cloud includes sending perspective configuration, the network node filtering and extracting information, the network node updating perspective information and generating perspective diagram.

[0012] As a preferred solution of the implementation method of the intra-cloud network data flow perspective described in the present invention, wherein: the intra-cloud unique index allocation is to uniformly manage the network nodes in the resource pool and allocate independent network node serial numbers to the network nodes, and after the network node obtains the independent network node serial number, it generates a unique index within the cloud according to the rules.

[0013] As a preferred solution of the method for realizing intra-cloud network data flow perspective of the present invention, wherein: the intra-cloud unique index is composed of a plurality of fields, including a network node sequence number and a message sequence number;

[0014] The message sequence number is generated by the network node that processes the message.

[0015] As a preferred solution of the method for implementing the perspective of network data flow in a cloud described in the present invention, the flow feature record includes information on the last network node that processed the traffic and the unique index in the cloud.

[0016] As a preferred solution of the method for realizing the perspective of network data flow in the cloud described in the present invention, when the network node processes the network data, the unique index in the cloud is used as the key to record the info feature information carried by the message, and the data flow direction can be associated with the unique index in the cloud and the current network node;

[0017] The information carried by the message has a fixed size, and each message only carries the perspective information of the previous network node.

[0018] As a preferred solution of the method for realizing the perspective of network data flow in a cloud according to the present invention, the perspective analysis of the flow direction is performed by obtaining the perspective data of the flow direction recorded on the network node and performing unified association with the unique index in the cloud;

[0019] The association relationship is associated with the target network node through the information stored in the cloud-entering network node, and then associated with the next target network node through the information in the target network node, and finally associated with all network nodes, and a flow perspective is displayed based on the information.

[0020] As a preferred solution of the method for implementing the perspective of network data flow in a cloud described in the present invention, wherein: the perspective configuration sent down includes perspective filtering configuration and network node configuration;

[0021] The filtering and extraction processing of the network node includes matching selection configuration, applying for a unique index in the cloud, and saving the current perspective record;

[0022] The updating process of the network node includes extracting the unique index in the cloud and updating the perspective record of the unique index in the cloud.

[0023] As a preferred solution of the method for realizing the perspective view of network data flow in a cloud according to the present invention, the process of generating the perspective view is as follows:

[0024] First, the flow perspective data of the network node is extracted, then the flow perspective data is arranged in order according to the unique index in the cloud, and finally a perspective diagram is generated according to the unique index in the cloud.

[0025] A computer device includes a memory for storing instructions and a processor for executing the instructions, so that the device executes a method for realizing a perspective of network data flow in a cloud.

[0026] A computer-readable storage medium stores a computer program, which, when executed, implements a method for realizing the perspective of network data flow in a cloud.

[0027] Beneficial effects of the present invention: The present invention can clarify the flow of network data and make network transmission transparent by allocating a unique index within the cloud and uniformly associating it with the flow perspective data recorded on the network node. The flow data of the traffic can be easily obtained according to the flow perspective result, and can be expanded according to the flow data to realize the business data flow topology and provide means for troubleshooting personnel to assist in determining related network problems. At the same time, the flow perspective function provides a filtering function, which can filter specific traffic to complete the flow perspective, thereby meeting the differentiated and precise perspective requirements; by issuing the perspective configuration, the flow perspective is performed on specific traffic; the network node filters and extracts information, and the flow perspective is performed on a single message dimension with a finer analysis granularity; the network node updates the perspective information, and the function occupies less memory and transmission bandwidth, and only uses the carrying or storage of a single perspective data; the perspective diagram is generated, and the data flow perspective result can be infinitely long in theory and is not restricted by any transmission protocol. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0029] Figure 1 A unique index structure diagram in the cloud of a method for realizing intra-cloud network data flow perspective according to the present invention;

[0030] Figure 2 A flowchart of perspective information carrying described in a method for implementing perspective of network data flow in a cloud according to the present invention;

[0031] Figure 3The perspective information association diagram of the method for realizing the perspective of network data flow in a cloud according to the present invention;

[0032] Figure 4 The present invention provides a flowchart of intra-cloud network data flow perspective according to a method for implementing intra-cloud network data flow perspective. DETAILED DESCRIPTION

[0033] 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.

[0034] 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.

[0035] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0036] Secondly, the present invention is described in detail with reference to the schematic diagram. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0037] Example 1

[0038] In this embodiment, a method for realizing intra-cloud network data flow perspective includes:

[0039] The intra-cloud network data flow perspective includes the intra-cloud unique index allocation, flow feature recording, and flow perspective analysis;

[0040] The unique index allocation in the cloud is to uniformly manage the network nodes in the resource pool and allocate independent network node numbers to the network nodes. After the network nodes obtain the independent network node numbers, they generate unique indexes in the cloud according to the rules.

[0041] The unique index in the cloud is composed of multiple fields, including the network node number and the message number;

[0042] The message sequence number is generated by the network node that processes the message and is guaranteed to be unique in a single flow perspective. By ensuring the uniqueness of the network node sequence number and the message sequence number, the uniqueness of the index in a single flow perspective is jointly ensured. The unique index structure diagram in the cloud is shown in the figure below. Figure 1 As shown;

[0043] Only the entry node in the cloud allocates unique indexes. Since most network nodes in the cloud are deployed in a multi-active manner, multiple nodes may generate unique indexes at the same time. The problem of conflict in allocating unique indexes is solved by uniformly arranging the network nodes and assigning network node numbers. The unique index is composed of multiple fields, including the network node number and the message number in the network node. The message number in the network node is generated by the network node that processes the message. The message number in the network node is guaranteed to be unique during a single flow perspective.

[0044] The flow feature record includes information about the last network node that processed the traffic and the unique index in the cloud;

[0045] When a network node processes network data, it uses the unique index in the cloud as the key to record the info feature information carried by the message. The data flow direction can be associated through the unique index in the cloud and the current network node.

[0046] The information carried in the message is of fixed size, and each message only carries the perspective information of the previous network node;

[0047] The purpose of using a unique key is to ensure that only one valid message is recorded. In addition to storing the info feature information carried by the data, the message also records the target network node. The difference from the conventional flow perspective in terms of function is that it is to reduce the bandwidth occupation caused by the perspective function and the memory occupation inside the network node. After the perspective is completed, the flow perspective of this message can be associated by obtaining the information of this unique index on all network nodes;

[0048] Perspective information carrying flow chart as Figure 2 As shown, after the message enters network node 1, a unique index is generated inside network node 1 and info information is filled in, so as to carry the relevant information of network node 1; after the message enters network node 2_1, the information of network node 1 is recorded according to the unique index, and info information is updated; and it is sent to network node 3_3; after the message enters network node 3_3, the processing is the same as that of network node 2_2, and info information is recorded and updated, and finally transmitted to the server.

[0049] Flow perspective analysis obtains the flow perspective data recorded on the network nodes and associates them uniformly with the unique index in the cloud, so as to achieve the purpose of obtaining a complete flow perspective.

[0050] The association relationship is to associate the information stored in the cloud-entering network node with the target network node, and then associate the next target network node with the information in the target network node, and finally associate all network nodes at the location, and display the flow perspective diagram based on the information;

[0051] Perspective information association diagram Figure 3 As shown, the traffic message passes through network node 1, network node 2_1, and network node 3_3; network node 1 flow direction feature record information: unique index x, no previous network node information, that is, it does not pass through the network node; network node 2_1 flow direction feature record information: unique index x, network node 1 flow direction feature information; network node 3_3 flow direction feature record information: unique index x, network node 2_1 flow direction feature information; through correlation analysis of unique index x, the flow perspective of this message is: network node 1 to network node 2_1 and then to network node 3_3.

[0052] The process of cloud network data flow perspective includes issuing perspective configuration, filtering and extracting information from network nodes, updating perspective information from network nodes, and generating perspective diagrams. The process diagram of cloud network data flow perspective is as follows: Figure 4 As shown;

[0053] Sending perspective configuration includes perspective filtering configuration and network node configuration;

[0054] The filtering and extraction processing of network nodes includes matching selection configuration, applying for unique index in the cloud, and saving the current perspective record;

[0055] The update processing of the network node includes extracting the unique index in the cloud and updating the perspective record of the unique index in the cloud;

[0056] The process of generating a perspective view is as follows:

[0057] First, extract the flow perspective data of the network nodes, then arrange the flow perspective data in order according to the unique index in the cloud, and finally generate the perspective diagram according to the unique index in the cloud;

[0058] The current network model of the cloud network needs to support the flow perspective function in key network nodes, and filter and perspective specific traffic according to the flow perspective rules. Each network node will record the perspective information of the shoelaces of this message. Finally, after the transmission is completed, the flow perspective information of all network nodes will be associated to finally obtain the flow perspective result.

[0059] Example 2

[0060] In this embodiment, a computer device is provided, including a memory and a processor, the memory is used to store instructions, and the processor is used to execute the instructions, so that the computer device executes the steps of the above-mentioned method for implementing the perspective of network data flow in the cloud.

[0061] Example 3

[0062] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed, the steps of the above-mentioned method for realizing the perspective of network data flow in the cloud are implemented.

[0063] The computer-readable storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk, or an optical disk, etc., which can store program codes.

[0064] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for realizing intra-cloud network data flow perspective, characterized in that: include, The intra-cloud network data flow perspective includes the intra-cloud unique index allocation, flow feature recording, and flow perspective analysis; The unique index allocation in the cloud is to uniformly manage the network nodes in the resource pool and allocate independent network node serial numbers to the network nodes. After the network nodes obtain the independent network node serial numbers, they generate unique indexes in the cloud according to the rules. The process of the intra-cloud network data flow perspective includes issuing perspective configuration, filtering and extracting information by the network node, updating perspective information by the network node and generating perspective diagram; The flow feature record includes information about the last network node that processed the traffic and the unique index in the cloud; When the network node processes network data, it uses the unique index in the cloud as the key to record the info feature information carried by the message, and can associate the data flow direction through the unique index in the cloud and the current network node; The information carried by the message adopts a fixed size, and each message only carries the perspective information of the previous network node; The flow perspective analysis is performed by obtaining the flow perspective data recorded on the network node and performing unified association with the unique index in the cloud; The association relationship is associated with the target network node through the information stored in the cloud-entering network node, and then associated with the next target network node through the information in the target network node, and finally associated with all network nodes, and a flow perspective is displayed based on the information.

2. A method for realizing intra-cloud network data flow perspective according to claim 1, characterized in that: The unique index in the cloud is composed of multiple fields, including a network node number and a message number; The message sequence number is generated by the network node that processes the message.

3. A method for realizing intra-cloud network data flow perspective according to claim 2, characterized in that: The sending of perspective configuration includes perspective filtering configuration and network node configuration; The filtering and extraction processing of the network node includes matching selection configuration, applying for a unique index in the cloud, and saving the current perspective record; The updating process of the network node includes extracting the unique index in the cloud and updating the perspective record of the unique index in the cloud.

4. A method for realizing intra-cloud network data flow perspective according to claim 3, characterized in that: The process of generating the perspective diagram is as follows: First, the flow perspective data of the network node is extracted, then the flow perspective data is arranged in order according to the unique index in the cloud, and finally a perspective diagram is generated according to the unique index in the cloud.

5. A computer device, characterized in that: include, A memory for storing instructions; The processor is used to execute the instruction so that the device executes a method for realizing intra-cloud network data flow perspective as described in any one of claims 1-4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, a method for realizing intra-cloud network data flow perspective as described in any one of claims 1-4 is implemented.

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