A PC-based BMC data IPMI remote management method and system

Abstract

The present invention relates to the technical field of remote data management, and discloses a BMC data IPMI remote management method based on a PC, including: splitting a total data acquisition task to obtain a data acquisition subtask set, determining a subtask processing flow, constructing a data acquisition flow diagram according to the subtask processing flow, obtaining an IP address set, connecting corresponding devices based on the IP address set, obtaining a response device set, accessing the response devices in sequence according to a processing flow matrix, obtaining response data, storing the response data in sequence in a distributed storage system, generating a storage address set, and performing device-data address linkage storage according to the storage address set and the IP address set. The present invention can solve the problems of large management complexity and an imperfect management system in the current remote management of BMC data.

Description

Technical Field

[0001] The present invention relates to a PC-based BMC data IPMI remote management method and system, belonging to the technical field of data remote management. Background Art

[0002] BMC (Baseboard Management Controller) is a dedicated controller used to monitor and manage servers. It can access the server's hardware status and configuration information even when the server operating system is down or shut down. IPMI (Intelligent Platform Management Interface) provides a unified interface and protocol for server management, such as how to monitor the system's hardware, sensors, control system components, and retrieve system event logs, so that administrators can remotely manage and control servers through standardized interfaces.

[0003] With the rapid development of information technology, the number of servers in data centers has increased dramatically, and efficient management and maintenance of servers has become an urgent problem to be solved. The PC-side management method based on the BMC mode and IPMI function fully utilizes the hardware management capabilities of the BMC and the standardized interface of the IPMI, providing an efficient solution for the remote management of servers. However, the current PC-side management method based on the BMC mode and IPMI function does not perform a process-based and systematic classification and splitting of BMC data, which leads to certain difficulties in tracing the source of abnormal data. In addition, there is no systematic system for the storage of abnormal data. Therefore, the current remote management of BMC data has the problems of high management complexity and an imperfect management system. Summary of the invention

[0004] The present invention provides a PC-based BMC data IPMI remote management method, device and computer-readable storage medium, the main purpose of which is to improve the precision of user portrait portrayal and solve the problems of large management complexity and imperfect management system in the current remote management of BMC data.

[0005] To achieve the above object, the present invention provides a PC-based BMC data IPMI remote management method, comprising:

[0006] Receiving a data acquisition instruction initiated by the PC, parsing the data acquisition instruction using a pre-built data management system to obtain a data acquisition overall task, splitting the data acquisition overall task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask;

[0007] Determine the subtask processing flow of the data acquisition subtask set, and construct a data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow;

[0008] Acquire an IP address set related to the data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set;

[0009] Access the corresponding response devices in the response device set in sequence according to the processing flow matrix to obtain the response data returned by the response devices;

[0010] The response data is stored in the pre-built distributed storage system in sequence. When the storage is successful, a storage address set is generated, and the device-data address linkage storage is performed based on the storage address set and the IP address set to complete the BMC data IPMI remote management based on the PC.

[0011] Optionally, the splitting of the data acquisition task to obtain a data acquisition subtask set includes:

[0012] Confirming all pending data related to the overall data acquisition task, wherein the acquisition logic of each set of pending data is predefined in the data management system;

[0013] According to different acquisition logics, all the data to be processed are classified to obtain multiple groups of logical data, wherein the logical data belonging to the same group have the same acquisition logic;

[0014] According to the corresponding relationship between the acquisition logic and the logical data, a data acquisition subtask set is constructed.

[0015] Optionally, the subtask processing flow of determining the data acquisition subtask set includes:

[0016] Prioritize the execution of each data acquisition subtask in the data acquisition subtask set to obtain a task processing ranking table;

[0017] Traversing the data streams appearing in each data acquisition subtask to obtain the subtask data stream, wherein the subtask data stream has a one-to-one correspondence with the data acquisition subtask;

[0018] According to the subtask data flow and the task processing sorting table, the subtask processing flow is constructed, where the structure of the subtask processing flow is:

[0019]

[0020] s i =(d 1 ,d 2 ,…,dj ,…,d n )

[0021] in, Represents the subtask processing flow, s i Indicates the i-th data acquisition subtask to be processed in the subtask processing flow, and processes s i-1 The priority is greater than or equal to s i , d j represents the jth subtask data stream generated when processing the i-th data acquisition subtask, m represents the total number of data acquisition subtasks in the subtask processing flow, and n represents the total number of subtask data streams generated when processing the i-th data acquisition subtask.

[0022] Optionally, constructing a data acquisition flow graph of the overall data acquisition task according to the subtask processing flow includes:

[0023] From the subtask data stream of the subtask processing flow, select the data that meets the requirements of the data acquisition instruction to obtain the target data stream set, where the structure of the target data stream set is:

[0024]

[0025] in, represents the target data stream set, represents the jth target data stream in the target data stream set, and u represents the total number of target data streams included in the target data stream set;

[0026] According to the overlapping subtask data flows between each data acquisition subtask in the subtask processing flow, a processing flow matrix is ​​constructed;

[0027] The processing flow matrix and the target data flow set are combined to obtain the data acquisition flow graph.

[0028] Optionally, the obtaining of overlapping subtask data flows between subtasks according to each data in the subtask processing flow to construct a processing flow matrix includes:

[0029] Extract two data acquisition subtasks from the subtask processing flow in sequence;

[0030] Determine whether there are overlapping subtask data streams in the two data acquisition subtasks;

[0031] If there is no overlapping subtask data stream, the relationship between the two data acquisition subtasks is marked as 0;

[0032] If there are overlapping subtask data streams, determine the number of overlaps of the overlapping subtask data streams, and mark the relationship between the two data acquisition subtasks according to the number of overlaps;

[0033] According to the relationship between the data acquisition subtasks, a processing flow matrix is ​​constructed.

[0034] Optionally, the structure of the processing flow matrix is:

[0035]

[0036] Where M represents the processing matrix, e i,1 represents the relationship between the ith data acquisition subtask and the first data acquisition subtask, and e i,i =0.

[0037] Optionally, the structure of the data acquisition flow graph is:

[0038]

[0039] Among them, G represents the data acquisition flow diagram, represents the target data flow set, and M represents the processing flow matrix.

[0040] Optionally, the step of sequentially accessing corresponding response devices in the response device set according to the processing flow matrix to obtain response data returned by the response devices includes:

[0041] A directed process matrix is ​​constructed according to the processing process matrix, wherein the structure of the directed process matrix is:

[0042]

[0043] in, represents a directed process matrix, → represents a directed symbol, e i→1 represents the directed relationship between the ith data acquisition subtask and the first data acquisition subtask, and e i→i =0;

[0044] Extracting non-zero directed relationship degrees in the directed process matrix in sequence, and judging whether the non-zero directed relationship degrees are positive relationship degrees according to the subtask processing process, wherein the non-zero directed relationship degrees refer to directed relationship degrees that are not 0;

[0045] If the non-zero directed relationship degree is a positive relationship degree, the non-zero directed relationship degree is used as a target relationship degree;

[0046] If the non-zero directed relationship degree is not a positive relationship degree, performing directed index inversion on the non-zero directed relationship degree to obtain a target relationship degree;

[0047] Summarize all target relationship degrees to obtain the target relationship degree set;

[0048] Constructing a target relationship degree sequence according to the target relationship degree set, and determining a device access sequence according to the target relationship degree sequence;

[0049] The device access sequence is used to access the responding device set, and the response data returned by the responding device is obtained.

[0050] Optionally, judging whether the non-zero directed relationship degree is a positive relationship degree according to the subtask processing flow includes:

[0051] Extracting a directed index sequence from the non-zero directed relationship degree;

[0052] Determining whether the directed index sequence conforms to the subtask processing flow;

[0053] If the directed index sequence does not conform to the subtask processing flow, the directed relationship degree is not a positive relationship degree;

[0054] If the directed index sequence conforms to the subtask processing flow, the directed relationship degree is a positive relationship degree.

[0055] To achieve the above object, the present invention also provides a PC-based BMC data IPMI remote management system, comprising:

[0056] The data acquisition task splitting module is used to receive the data acquisition instruction initiated by the PC, parse the data acquisition instruction using the pre-built data management system to obtain the data acquisition task, and split the data acquisition task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask;

[0057] A data acquisition flow diagram construction module is used to determine the subtask processing flow of the data acquisition subtask set, and construct a data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow;

[0058] A response data return module is used to obtain an IP address set related to the data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set; access corresponding response devices in the response device set in turn according to the processing flow matrix, and obtain response data returned by the response device;

[0059] The address linkage storage module is used to store the response data in sequence in a pre-built distributed storage system. When the storage is successful, a storage address set is generated, and device-data address linkage storage is performed based on the storage address set and the IP address set.

[0060] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0061] at least one processor; and,

[0062] a memory communicatively connected to the at least one processor; wherein,

[0063] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to implement the above-mentioned PC-based BMC data IPMI remote management method.

[0064] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned PC-based BMC data IPMI remote management method.

[0065] Compared with the problem described in the background technology, the present invention first receives a data acquisition instruction initiated by the PC, and then uses a pre-built data management system to parse the data acquisition instruction to obtain a total data acquisition task. Since the total data acquisition task is composed of one or more data acquisition subtasks, the total data acquisition task can be split to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask. Furthermore, since there is a certain subtask processing flow relationship between the data acquisition subtasks, the subtask processing flow of the data acquisition subtask set can be determined, and a data acquisition flow diagram of the total data acquisition task can be constructed according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow. Since each data acquisition subtask in the data acquisition subtask set needs to monitor and extract data from the device, in order to obtain data related to the data, According to the response data of the corresponding device related to the acquisition subtask, it is first necessary to obtain the IP address set related to the overall data acquisition task, and then connect the corresponding device based on the IP address set to obtain the response device set. At this time, the corresponding response devices in the response device set can be accessed in turn according to the processing flow matrix to obtain the response data sent back by the response device. Since each response device in the response device set is determined according to the IP address, the response data can be stored in an addressable manner. Since the response data is a very large amount of data, it can be stored in a distributed manner. First, the response data is stored in turn in a pre-built distributed storage system. When the storage is successful, a storage address set is generated. Since the storage address set is associated with the IP address set, the device-data address linkage storage can be performed according to the storage address set and the IP address set to complete the BMC data IPMI remote management based on the PC. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 A flowchart of a PC-based BMC data IPMI remote management method provided by an embodiment of the present invention;

[0067] Figure 2 A functional module diagram of a PC-based BMC data IPMI remote management system provided by an embodiment of the present invention;

[0068] Figure 3 A schematic diagram of the structure of an electronic device for implementing the PC-based BMC data IPMI remote management method provided by an embodiment of the present invention.

[0069] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0070] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0071] The embodiment of the present application provides a BMC data IPMI remote management method based on a PC. The execution subject of the BMC data IPMI remote management method based on a PC includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the BMC data IPMI remote management method based on a PC can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0072] Embodiment 1:

[0073] Reference Figure 1 FIG. 1 is a flow chart of a BMC data IPMI remote management method based on a PC according to an embodiment of the present invention. In this embodiment, the BMC data IPMI remote management method based on a PC includes:

[0074] S1. Receive a data acquisition instruction initiated by a PC, use a pre-built data management system to parse the data acquisition instruction to obtain a total data acquisition task, split the total data acquisition task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask.

[0075] It should be explained that the PC terminal is generally operated by the user, and the data acquisition instruction is also initiated according to the user's needs. For example, Xiao Zhang is a network security developer of the company, and Xiao Zhang's company has currently developed a data management system, which stores the storage records of data A, data B, data C, and data D, where the storage records are: data A is stored in the first memory, data B and data C are stored in the second memory, and data D is stored in the third memory. In the data management system, it is defined that data A, data B, data C, and data D have different acquisition logics. Now Xiao Zhang plans to test whether the data management system has data acquisition capabilities, so he uses the PC terminal to initiate a data acquisition instruction.

[0076] Furthermore, the data acquisition instruction includes Xiao Zhang's request, that is, the data acquisition task described in the embodiment of the present invention. Exemplarily, Xiao Zhang's data acquisition task is to access data A, data B, data C, and data D. However, since data A, data B, data C, and data D have different acquisition logics, if you want to access data A, data B, data C, and data D at the same time, you need to confirm the corresponding data acquisition subtasks according to the acquisition logic. In detail, the data acquisition subtask set obtained by splitting the data acquisition task includes:

[0077] Confirming all pending data related to the overall data acquisition task, wherein the acquisition logic of each set of pending data is predefined in the data management system;

[0078] According to different acquisition logics, all the data to be processed are classified to obtain multiple groups of logical data, wherein the logical data belonging to the same group have the same acquisition logic;

[0079] According to the corresponding relationship between the acquisition logic and the logical data, a data acquisition subtask set is constructed.

[0080] Exemplarily, assume that the above-mentioned data A, data B, data C and data D are the data that Xiao Zhang wants to obtain, and when data A, data B, data C are obtained, a lot of intermediate data will be generated, such as PC-side verification data, verification passed data, etc., so these data are collectively referred to as the data to be processed, but because different acquisition logics for data A, data B, data C and data D are defined in the data management system, if data B needs to be obtained first when obtaining data A, and PC-side verification data needs to be obtained first when obtaining data B, and data B can only be obtained after verification is passed, and data A needs to be obtained first to obtain data C and data D, then it is obvious that data A belongs to one acquisition logic, data B, PC-side verification data and verification passed data belong to one acquisition logic, and data C and data D belong to the same acquisition logic. Therefore, data A, data B, data C and data D are classified to obtain 3 groups of logical data, among which the first group of logical data is data A, the second group is data B, PC-side verification data and verification passed data, and the third group is data C and data D.

[0081] Furthermore, for example, the subtasks of the first set of logical data are: data Bv data A, the subtasks of the second set of logical data are: PC-side verification data→verification passed data→data B, and the subtasks of the third set of logical data are: data A→data C and data D.

[0082] S2. Determine the subtask processing flow of the data acquisition subtask set, and construct a data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow.

[0083] In detail, the subtask processing flow of determining the data acquisition subtask set includes:

[0084] Prioritize the execution of each data acquisition subtask in the data acquisition subtask set to obtain a task processing ranking table;

[0085] Traversing the data streams appearing in each data acquisition subtask to obtain the subtask data stream, wherein the subtask data stream has a one-to-one correspondence with the data acquisition subtask;

[0086] According to the subtask data flow and the task processing sorting table, the subtask processing flow is constructed, where the structure of the subtask processing flow is:

[0087]

[0088] s i =(d 1 ,d 2 ,…,d j ,…,d n )

[0089] in, Represents the subtask processing flow, s i Indicates the i-th data acquisition subtask to be processed in the subtask processing flow, and processes s i-1 The priority is greater than or equal to s i , d j represents the jth subtask data stream generated when processing the i-th data acquisition subtask, m represents the total number of data acquisition subtasks in the subtask processing flow, and n represents the total number of subtask data streams generated when processing the i-th data acquisition subtask.

[0090] For example, the first group of data acquisition subtasks is: data B → data A, the second group of data acquisition subtasks is: PC end verification data → verification data → data B, and the third group of data acquisition subtasks is: data A → data C and data D. Therefore, the corresponding task processing sequence table is: the second group of data acquisition subtasks → the first group of data acquisition subtasks → the third group of data acquisition subtasks. Therefore, the corresponding subtask processing flow is:

[0091] It can be further known that the first group of data acquisition subtasks has two subtask data streams, namely data B and data A, and the second group of data acquisition subtasks has three subtask data streams, namely PC-side verification data, verification data, and data B. The three data types are filled into s accordingly. 2 In the 2 =(d 1 ,d 2 ,d 3 ).

[0092] Furthermore, the data acquisition flow diagram of the overall data acquisition task is constructed according to the subtask processing flow, including:

[0093] From the subtask data stream of the subtask processing flow, select the data that meets the requirements of the data acquisition instruction to obtain the target data stream set, where the structure of the target data stream set is:

[0094]

[0095] in, represents the target data stream set, represents the jth target data stream in the target data stream set, and u represents the total number of target data streams included in the target data stream set;

[0096] According to the overlapping subtask data flows between each data acquisition subtask in the subtask processing flow, a processing flow matrix is ​​constructed;

[0097] The processing flow matrix and the target data flow set are combined to obtain the data acquisition flow graph.

[0098] Exemplarily, the above data A, data B, data C and data D are the data that Xiao Zhang wants to obtain, then data A, data B, data C and data D are the target data streams, and obviously, the target data streams belong to the subtask data streams. In other words, the total number of target data streams should be less than or equal to the total number of subtask data streams generated by all data acquisition subtasks in the subtask processing flow, that is, the total number u of target data streams included in the target data stream set should satisfy the following formula:

[0099]

[0100] Among them, num(s i ) represents the total number of subtask data flows generated when processing the i-th data acquisition subtask, and m represents the total number of data acquisition subtasks in the subtask processing flow.

[0101] For example, Xiao Zhang wants to obtain data A, data B, data C and data D, and according to the above acquisition logic, data A belongs to one logical data group, data B belongs to the second logical data group, and data C and data D belong to the third logical data group. Then the total number of target data streams u=3. In addition, when acquiring data B, other subtask data streams will be generated, including PC-side verification data and verification pass data. It can be seen that The total number of visible target data flows is less than

[0102] Furthermore, the subtask data flows that overlap between subtasks are obtained according to each data in the subtask processing flow, and a processing flow matrix is ​​constructed, including:

[0103] Extract two data acquisition subtasks from the subtask processing flow in sequence;

[0104] Determine whether there are overlapping subtask data streams in the two data acquisition subtasks;

[0105] If there is no overlapping subtask data stream, the relationship between the two data acquisition subtasks is marked as 0;

[0106] If there are overlapping subtask data streams, determine the number of overlaps of the overlapping subtask data streams, and mark the relationship between the two data acquisition subtasks according to the number of overlaps;

[0107] According to the relationship between the data acquisition subtasks, a processing flow matrix is ​​constructed.

[0108] For example, assuming that the subtask data streams of the first data acquisition subtask are data B and data A, and the subtask data streams of the second data acquisition subtask are PC-side verification data, verification pass data, and data B, then obviously, the relationship between the first data acquisition subtask and the second data acquisition subtask is 1, because the overlap number is 1. If the subtask data streams of the third data acquisition subtask are data A, data C, and data D, then there are no overlapping subtask data streams between the third data acquisition subtask and the second data acquisition subtask, that is, the relationship degree is 0.

[0109] In detail, the structure of the processing flow matrix is:

[0110]

[0111] Where M represents the processing matrix, e i,1 represents the relationship between the ith data acquisition subtask and the first data acquisition subtask, and e i,i =0.

[0112] For example, assuming that there are three data acquisition subtasks, the structure of the corresponding processing flow matrix is:

[0113]

[0114] And the diagonals of the process matrix are all 0, that is, e 1,1 =e 2,2 =e 3,3 =0.

[0115] Furthermore, the structure of the data acquisition flow graph is:

[0116]

[0117] Among them, G represents the data acquisition flow diagram, represents the target data flow set, and M represents the processing flow matrix.

[0118] S3. Acquire an IP address set related to the overall data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set.

[0119] According to the above description, the data management system stores storage records of data A, data B, data C, and data D, wherein the storage records are: data A is stored in the first storage, data B and data C are stored in the second storage, and data D is stored in the third storage. Then the first storage, the second storage, and the third storage are the response device set, and the IP addresses of the first storage, the second storage, and the third storage are the IP address set.

[0120] S4. Access corresponding response devices in the response device set in sequence according to the processing flow matrix to obtain response data returned by the response devices.

[0121] In detail, the step of sequentially accessing corresponding response devices in the response device set according to the processing flow matrix to obtain response data returned by the response devices includes:

[0122] A directed process matrix is ​​constructed according to the processing process matrix, wherein the structure of the directed process matrix is:

[0123]

[0124] in, represents a directed process matrix, → represents a directed symbol, e i→1 represents the directed relationship between the ith data acquisition subtask and the first data acquisition subtask, and e i→i =0;

[0125] Extracting non-zero directed relationship degrees in the directed process matrix in sequence, and judging whether the non-zero directed relationship degrees are positive relationship degrees according to the subtask processing process, wherein the non-zero directed relationship degrees refer to directed relationship degrees that are not 0;

[0126] If the non-zero directed relationship degree is a positive relationship degree, the non-zero directed relationship degree is used as a target relationship degree;

[0127] If the non-zero directed relationship degree is not a positive relationship degree, performing directed index inversion on the non-zero directed relationship degree to obtain a target relationship degree;

[0128] Summarize all target relationship degrees to obtain the target relationship degree set;

[0129] Constructing a target relationship degree sequence according to the target relationship degree set, and determining a device access sequence according to the target relationship degree sequence;

[0130] The device access sequence is used to access the responding device set, and the response data returned by the responding device is obtained.

[0131] Explainably, the positive relationship refers to the non-zero directed relationship in which the directed row index and the directed column index conform to the non-zero directed relationship of the subtask processing flow, the directed row index refers to the row index in the directed relationship, and the directed column index refers to the column index in the directed relationship, for example: i→1 The directed row index is i, e i→1 The directed column index of is 1.

[0132] For example, assuming that there are three data acquisition subtasks, the structure of the corresponding directed process matrix is:

[0133]

[0134] Among them, the diagonals of the directed process matrix are all 0, that is, e 1→1 =e 2→2 =e 3→3 =0.

[0135] Further, judging whether the non-zero directed relationship degree is a positive relationship degree according to the subtask processing flow includes:

[0136] Extracting a directed index sequence from the non-zero directed relationship degree;

[0137] Determining whether the directed index sequence conforms to the subtask processing flow;

[0138] If the directed index sequence does not conform to the subtask processing flow, the directed relationship degree is not a positive relationship degree;

[0139] If the directed index sequence conforms to the subtask processing flow, the directed relationship degree is a positive relationship degree.

[0140] Furthermore, the first group of data acquisition subtasks is: data B → data A, the second group of data acquisition subtasks is: PC end verification data → verification passed data → data B, the third group of data acquisition subtasks is: data A → data C and data D, and the corresponding task processing order table is: second group of data acquisition subtasks → first group of data acquisition subtasks → third group of data acquisition subtasks (i.e. 2 → 1 → 3), then e 1→2 (Directed index order is 1→2) does not conform to the subtask processing flow, e 1→3 It complies with the subtask processing flow, which is a positive relationship, e 2→1 It complies with the subtask processing flow, which is a positive relationship, e 2→3 It complies with the subtask processing flow and is a positive relationship.

[0141] Furthermore, the directed index inversion refers to inverting the directed row index and the directed column index of the directed relationship degree. For example, the directed relationship degree is e i→1 , then the degree of the directed relationship after the directed index inversion is e 1→i .

[0142] It can be explained that the target relationship degree sequence refers to a non-zero directed relationship degree sequence whose directed index sequence conforms to the subtask processing flow and has a connection relationship.

[0143] It can be understood that the step of constructing a target relationship degree sequence according to the target relationship degree set includes:

[0144] Extracting a directed index connection relationship degree set from the target relationship degree set;

[0145] The target relationship degree sequence is constructed according to the directed index connection relationship degree set.

[0146] Explainably, the directed index connection relationship set refers to a target relationship set in which the directed column index of one target relationship is the same as the directed row index of another target relationship, for example: 2→1 With e 1→3 Belongs to the directed index connection relationship set; e 1→3 With e 2→3 Does not belong to the directed index connection relationship set; e 2→1 With e 2→3 Finally, the target relationship degree sequence is obtained by connecting the directed index connection relationship degrees in the directed index connection relationship degree set according to the connection relationship of the directed index sequence.

[0147] Further, after obtaining the target relationship degree sequence, the device access sequence can be determined according to the target relationship degree sequence. For example, the first group of data acquisition subtasks is: data B→data A, the second group of data acquisition subtasks is: PC end verification data→verification passed data→data B, the third group of data acquisition subtasks is: data A→data C and data D, and the corresponding task processing sorting table is: second group of data acquisition subtasks→first group of data acquisition subtasks→third group of data acquisition subtasks (i.e., 2→1→3), and data A is stored in the first memory, data B and data C are stored in the second memory, and data D is stored in the third memory. When the target relationship degree sequence is e 2→1 With e 1→3 When , the second memory is accessed first (execute the second set of data acquisition subtasks to extract data B), then the first memory is accessed (execute the first set of data acquisition subtasks to extract data A), and finally the second memory and the third memory are accessed (execute the third set of data acquisition subtasks to extract data C and data D).

[0148] It is understandable that when accessing the second memory, the response data may be data B, response time, etc., when accessing the first memory, the response data may be data A, response time, etc., and finally when accessing the second memory and the third memory, the response data may be data C, data D, response time, response duration, etc. When the user needs to extract data A, the second memory is accessed first to obtain data B, and then the first memory is accessed to obtain data A.

[0149] S5. Store the response data in a pre-built distributed storage system in sequence. When the storage is successful, generate a storage address set, and perform device-data address linkage storage based on the storage address set and the IP address set to complete the BMC data IPMI remote management based on the PC.

[0150] It can be explained that the distributed storage system refers to a network storage architecture with multiple storage nodes. The device-data address linkage storage refers to the process of storing the storage address of the response data in association with the IP address of the response device associated with the response data. When a response data is obtained, if the response data is abnormal, the storage address of the response data can be extracted first, and then the associated one or more IP addresses can be identified based on the storage address, and finally the corresponding one or more response devices can be identified based on the associated one or more IP addresses, so that the cause of the data abnormality of the corresponding response device can be checked.

[0151] For example, when the abnormal response data is data D, the process of obtaining data D is (PC-side verification data → verification passed data → data B) second memory → (data A) first memory → (data D) third memory, then the abnormal data may also be data B and data A, so it is necessary to check for abnormalities in data B and data A.

[0152] Compared with the problem described in the background technology, the present invention first receives a data acquisition instruction initiated by the PC, and then uses a pre-built data management system to parse the data acquisition instruction to obtain a total data acquisition task. Since the total data acquisition task is composed of one or more data acquisition subtasks, the total data acquisition task can be split to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask. Furthermore, since there is a certain subtask processing flow relationship between the data acquisition subtasks, the subtask processing flow of the data acquisition subtask set can be determined, and a data acquisition flow diagram of the total data acquisition task can be constructed according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow. Since each data acquisition subtask in the data acquisition subtask set needs to monitor and extract data from the device, in order to obtain data related to the data, According to the response data of the corresponding device related to the acquisition subtask, it is first necessary to obtain the IP address set related to the overall data acquisition task, and then connect the corresponding device based on the IP address set to obtain the response device set. At this time, the corresponding response devices in the response device set can be accessed in turn according to the processing flow matrix to obtain the response data sent back by the response device. Since each response device in the response device set is determined according to the IP address, the response data can be stored in an addressable manner. Since the response data is a very large amount of data, it can be stored in a distributed manner. First, the response data is stored in turn in a pre-built distributed storage system. When the storage is successful, a storage address set is generated. Since the storage address set is associated with the IP address set, the device-data address linkage storage can be performed according to the storage address set and the IP address set to complete the BMC data IPMI remote management based on the PC.

[0153] Therefore, the present invention proposes a PC-based BMC data IPMI remote management method and system, the main purpose of which is to solve the current problems of large management complexity and imperfect management system in remote management of BMC data.

[0154] Embodiment 2:

[0155] like Figure 2 , which is a functional module diagram of a PC-based BMC data IPMI remote management system provided by an embodiment of the present invention.

[0156] The BMC data IPMI remote management system 100 based on the PC side of the present invention can be installed in an electronic device. According to the functions to be implemented, the BMC data IPMI remote management system 100 based on the PC side can include a data acquisition general task splitting module 101, a data acquisition flow diagram construction module 102, a response data return module 103 and an address linkage storage module 104. The module described in the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0157] The data acquisition overall task splitting module 101 is used to receive a data acquisition instruction initiated by the PC, parse the data acquisition instruction using a pre-built data management system to obtain a data acquisition overall task, and split the data acquisition overall task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask;

[0158] The data acquisition flow diagram construction module 102 is used to determine the subtask processing flow of the data acquisition subtask set, and construct the data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow;

[0159] The response data return module 103 is used to obtain an IP address set related to the data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set; access corresponding response devices in the response device set in turn according to the processing flow matrix to obtain response data returned by the response device;

[0160] The address linkage storage module 104 is used to store the response data in sequence into a pre-built distributed storage system, generate a storage address set when the storage is successful, and perform device-data address linkage storage based on the storage address set and the IP address set.

[0161] In detail, each module in the PC-based BMC data IPMI remote management system 100 in the embodiment of the present invention adopts the same method as above when used. Figure 1 The same technical means as the PC-based BMC data IPMI remote management method described in the previous section can produce the same technical effects, which will not be repeated here.

[0162] Embodiment 3:

[0163] like Figure 3 , which is a schematic diagram of the structure of an electronic device for implementing a PC-based BMC data IPMI remote management method provided by an embodiment of the present invention.

[0164] The electronic device 1 may include a processor 10, a memory 11, a bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a PC-based BMC data IPMI remote management program.

[0165] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. The memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), etc. equipped on the electronic device 1. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 may not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the BMC data IPMI remote management program based on the PC, but also be used to temporarily store data that has been output or is to be output.

[0166] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips, etc. The processor 10 is the control core (Control Unit) of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes or executes programs or modules stored in the memory 11 (such as BMC data IPMI remote management programs based on PC terminals, etc.), and calls data stored in the memory 11 to execute various functions of the electronic device 1 and process data.

[0167] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0168] Figure 3 Only an electronic device with components is shown, and those skilled in the art will understand that Figure 2 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0169] For example, although not shown, the electronic device 1 may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include any components such as one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, etc. The electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0170] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0171] Optionally, the electronic device 1 may further include a user interface, which may be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch device, etc. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0172] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0173] The PC-based BMC data IPMI remote management program stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0174] Receiving a data acquisition instruction initiated by the PC, parsing the data acquisition instruction using a pre-built data management system to obtain a data acquisition overall task, splitting the data acquisition overall task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask;

[0175] Determine the subtask processing flow of the data acquisition subtask set, and construct a data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow;

[0176] Acquire an IP address set related to the data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set;

[0177] Access the corresponding response devices in the response device set in sequence according to the processing flow matrix to obtain the response data returned by the response devices;

[0178] The response data is stored in the pre-built distributed storage system in sequence. When the storage is successful, a storage address set is generated, and the device-data address linkage storage is performed based on the storage address set and the IP address set to complete the BMC data IPMI remote management based on the PC.

[0179] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figure 1 to Figure 2 The description of the relevant steps in the corresponding embodiments will not be repeated here.

[0180] Furthermore, if the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0181] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0182] Receiving a data acquisition instruction initiated by the PC, parsing the data acquisition instruction using a pre-built data management system to obtain a data acquisition overall task, splitting the data acquisition overall task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask;

[0183] Determine the subtask processing flow of the data acquisition subtask set, and construct a data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow;

[0184] Acquire an IP address set related to the data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set;

[0185] Access the corresponding response devices in the response device set in sequence according to the processing flow matrix to obtain the response data returned by the response devices;

[0186] The response data is stored in the pre-built distributed storage system in sequence. When the storage is successful, a storage address set is generated, and the device-data address linkage storage is performed based on the storage address set and the IP address set to complete the BMC data IPMI remote management based on the PC.

[0187] The modules described as separate components may or may not be physically separated, and the components shown as modules 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 modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0188] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0189] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0190] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution 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 solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A BMC data IPMI remote management method based on PC, characterized in that: The method comprises: Receiving a data acquisition instruction initiated by the PC, parsing the data acquisition instruction using a pre-built data management system to obtain a data acquisition overall task, splitting the data acquisition overall task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask; Determine the subtask processing flow of the data acquisition subtask set, and construct a data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow; Acquire an IP address set related to the data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set; Access the corresponding response devices in the response device set in sequence according to the processing flow matrix to obtain the response data returned by the response devices; The response data is stored in a pre-built distributed storage system in sequence. When the storage is successful, a storage address set is generated, and the device-data address linkage storage is performed based on the storage address set and the IP address set to complete the BMC data IPMI remote management based on the PC side; The step of sequentially accessing corresponding response devices in the response device set according to the processing flow matrix to obtain response data returned by the response devices includes: A directed process matrix is ​​constructed according to the processing process matrix, wherein the structure of the directed process matrix is: in, represents a directed process matrix, → represents a directed symbol, e i→1 represents the directed relationship between the ith data acquisition subtask and the first data acquisition subtask, and e i→i =0; Extracting non-zero directed relationship degrees in the directed process matrix in sequence, and judging whether the non-zero directed relationship degrees are positive relationship degrees according to the subtask processing process, wherein the non-zero directed relationship degrees refer to directed relationship degrees that are not 0; If the non-zero directed relationship degree is a positive relationship degree, the non-zero directed relationship degree is used as a target relationship degree; If the non-zero directed relationship degree is not a positive relationship degree, performing directed index inversion on the non-zero directed relationship degree to obtain a target relationship degree; Summarize all target relationship degrees to obtain the target relationship degree set; Constructing a target relationship degree sequence according to the target relationship degree set, and determining a device access sequence according to the target relationship degree sequence; Performing device access on the responding device set according to the device access sequence to obtain response data returned by the responding device; The determining whether the non-zero directed relationship degree is a positive relationship degree according to the subtask processing flow includes: Extracting a directed index sequence from the non-zero directed relationship degree; Determining whether the directed index sequence conforms to the subtask processing flow; If the directed index sequence does not conform to the subtask processing flow, the directed relationship degree is not a positive relationship degree; If the directed index sequence conforms to the subtask processing flow, the directed relationship degree is a positive relationship degree.

2. The PC-based BMC data IPMI remote management method according to claim 1, characterized in that: The data acquisition task is split into a set of data acquisition subtasks, including: Confirming all pending data related to the overall data acquisition task, wherein the acquisition logic of each set of pending data is predefined in the data management system; According to different acquisition logics, all the data to be processed are classified to obtain multiple groups of logical data, wherein the logical data belonging to the same group have the same acquisition logic; According to the corresponding relationship between the acquisition logic and the logical data, a data acquisition subtask set is constructed.

3. The PC-based BMC data IPMI remote management method according to claim 2, characterized in that: The subtask processing flow of determining the data acquisition subtask set includes: Prioritize the execution of each data acquisition subtask in the data acquisition subtask set to obtain a task processing ranking table; Traversing the data streams appearing in each data acquisition subtask to obtain the subtask data stream, wherein the subtask data stream has a one-to-one correspondence with the data acquisition subtask; According to the subtask data flow and the task processing sorting table, the subtask processing flow is constructed, where the structure of the subtask processing flow is: s i =(d1,d2,...,d j ,...,d n ) in, Represents the subtask processing flow, s i Indicates the i-th data acquisition subtask to be processed in the subtask processing flow, and processes s i-1 The priority is greater than or equal to s i , d j represents the jth subtask data stream generated when processing the i-th data acquisition subtask, m represents the total number of data acquisition subtasks in the subtask processing flow, and n represents the total number of subtask data streams generated when processing the i-th data acquisition subtask.

4. The PC-based BMC data IPMI remote management method according to claim 3, characterized in that: The data acquisition flow diagram of the overall data acquisition task is constructed according to the subtask processing flow, including: From the subtask data stream of the subtask processing flow, select the data that meets the requirements of the data acquisition instruction to obtain the target data stream set, where the structure of the target data stream set is: in, represents the target data stream set, represents the jth target data flow in the target data flow set, and u represents the total number of target data flows included in the target data flow set; According to the overlapping subtask data flows between each data acquisition subtask in the subtask processing flow, a processing flow matrix is ​​constructed; The processing flow matrix and the target data flow set are combined to obtain the data acquisition flow graph.

5. The PC-based BMC data IPMI remote management method according to claim 4, characterized in that: The subtask data flows that overlap between subtasks are obtained according to each data in the subtask processing flow, and a processing flow matrix is ​​constructed, including: Extract two data acquisition subtasks from the subtask processing flow in sequence; Determine whether there are overlapping subtask data streams in the two data acquisition subtasks; If there is no overlapping subtask data stream, the relationship between the two data acquisition subtasks is marked as 0; If there are overlapping subtask data streams, determine the number of overlaps of the overlapping subtask data streams, and mark the relationship between the two data acquisition subtasks according to the number of overlaps; According to the relationship between the data acquisition subtasks, a processing flow matrix is ​​constructed.

6. The PC-based BMC data IPMI remote management method according to claim 5, characterized in that: The structure of the processing flow matrix is: Where M represents the processing matrix, e i,1 represents the relationship between the ith data acquisition subtask and the first data acquisition subtask, and e i,i =0.

7. The PC-based BMC data IPMI remote management method according to claim 6, characterized in that: The structure of the data acquisition flow diagram is: Among them, G represents the data acquisition flow diagram, represents the target data flow set, and M represents the processing flow matrix.

8. A PC-based BMC data IPMI remote management system using the method as claimed in claim 1, characterized in that: The system comprises: The data acquisition task splitting module is used to receive the data acquisition instruction initiated by the PC, parse the data acquisition instruction using the pre-built data management system to obtain the data acquisition task, and split the data acquisition task to obtain a data acquisition subtask set, wherein the data acquisition subtask set includes at least one data acquisition subtask; A data acquisition flow diagram construction module is used to determine the subtask processing flow of the data acquisition subtask set, and construct a data acquisition flow diagram of the data acquisition overall task according to the subtask processing flow, wherein the data acquisition flow diagram includes a processing flow matrix constructed by the subtask processing flow; A response data return module is used to obtain an IP address set related to the data acquisition task, connect corresponding devices based on the IP address set, and obtain a response device set; access corresponding response devices in the response device set in turn according to the processing flow matrix to obtain response data returned by the response device; The address linkage storage module is used to store the response data in sequence in a pre-built distributed storage system. When the storage is successful, a storage address set is generated, and device-data address linkage storage is performed based on the storage address set and the IP address set.

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