Session playback solution for IPMI (Intelligent Platform Management Interface) console

Abstract

The invention discloses a solution for IPMI console session playback, and relates to the technical field of computer system management. Comprising the following steps: S1, initializing a session: when an administrator starts an IPMI session, a system initializes an empty data structure D for storing session data; s2, capturing session data: monitoring an IPMI (Intelligent Platform Management Interface) interface in real time by a system, and capturing all input and output data streams; s3, data encryption and compression: encrypting the captured data by using an advanced encryption standard (AES) to ensure data security; a formula E = AES (D, K) is applied, K is a secret key, and E is encrypted data. According to the method, the captured data is encrypted by using an advanced encryption standard, so that the security of the data is ensured; the GZIP algorithm is adopted to compress the encrypted data, so that the consumption of a storage space is reduced; by introducing a machine learning algorithm and a deep learning algorithm, the fault prediction and event analysis capabilities are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of computer system management, and in particular to a solution for IPMI console session playback. Background Art

[0002] In today's data center and server management environment, administrators often need to remotely access the server's console for troubleshooting and maintenance. Due to network latency or connection issues, it can be difficult to monitor the console session content in real time.

[0003] After searching, the application scheme of Chinese patent application No. 202210579567.3 discloses a network equipment central control intelligent management system and method, which is characterized by including a central control module, which includes an anti-intrusion control unit, an asset management module, a network management module, an automatic task unit, and a distributed terminal control module. The central control module is used for the unified management entrance of multiple data centers. In this module, users can perform central control management of the status, energy consumption, resource usage, and various instructions of several data centers. The method in the above patent has the following deficiencies: the ability of fault prediction and event analysis is still insufficient and needs to be improved. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings in the prior art and to propose a solution for IPMI console session playback.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A solution for IPMI console session playback, including:

[0007] S1: Initialize the session:

[0008] When an administrator starts an IPMI session, the system initializes an empty data structure D to store session data;

[0009] S2: Capture session data:

[0010] The system monitors the IPMI interface in real time and captures all input and output data streams;

[0011] S3: Data encryption and compression:

[0012] The captured data is encrypted using the Advanced Encryption Standard (AES) to ensure data security; the formula E = AES (D, K) is applied, where K is the key and E is the encrypted data; the encrypted data is compressed using the GZIP algorithm to reduce storage space consumption;

[0013] S4: Data Storage:

[0014] Store the compressed data C in a persistent storage device;

[0015] S5: Session playback:

[0016] When the session needs to be replayed, the compressed data C is loaded from the storage device; the decompression algorithm formula D = GZIP^(-1)(C) is applied to obtain the original encrypted data E; the AES decryption algorithm formula D = AES^(-1)(E,K) is used to obtain the original session data;

[0017] S6: Data processing and playback:

[0018] Sort and format the received data to ensure the correct playback order; synchronize the playback speed using the timestamp information T to ensure that the playback speed is consistent with the original session;

[0019] S7: Performance optimization and intelligent algorithm application:

[0020] Implement a caching mechanism to reduce frequent disk read and write operations and improve data loading efficiency; use multi-threading technology to parallelize data decryption and decompression to optimize playback startup time; introduce machine learning algorithms to perform pattern recognition on session data, automatically classify and mark key events; use deep learning algorithms to analyze historical session data and predict potential system failures and maintenance needs;

[0021] S8: Data Insights and Reports:

[0022] Generate system usage and performance reports by analyzing playback data; apply natural language processing algorithms to extract keywords in conversations and generate operation log summaries.

[0023] Preferably: in S1, initializing the session specifically includes:

[0024] When an administrator initiates a remote session through IPMI, the system automatically generates a unique session ID;

[0025] Create an empty data structure D for the session ID to store session data;

[0026] Initializes the timestamp recorder to ensure that every event in the session can be accurately recorded.

[0027] Preferably: in S2, capturing session data specifically includes:

[0028] The system configures the network interface and monitors IPMI requests and responses in real time;

[0029] For each request and response, record the timestamp and store the session data and its metadata in data structure D;

[0030] Make sure the captured data includes the text command, execution results, and any error messages.

[0031] Preferably: in S3, data encryption and compression specifically include:

[0032] The captured data is encrypted using the AES encryption algorithm and the key K;

[0033] The formula E=AES(D,K) is applied, where E represents the encrypted data block;

[0034] Apply the GZIP compression algorithm to E to reduce the data size for easy storage and transmission.

[0035] Preferably: in S4, the data storage specifically includes:

[0036] Store the compressed data C in a persistent storage device;

[0037] Index each session ID and the corresponding data file for quick retrieval;

[0038] Back up stored data regularly to prevent data loss.

[0039] Preferably: in S5, the session playback specifically includes:

[0040] When a session needs to be replayed, the user selects a specific session ID through the interface;

[0041] Load the compressed data C from the storage device and apply the GZIP decompression algorithm formula D = GZIP^(-1)(C);

[0042] Use the AES decryption algorithm formula D = AES^(-1)(E,K) to obtain the original session data.

[0043] Preferably: in S6, data processing and playback specifically include:

[0044] Sort and format the received data and synchronize it according to the timestamp information T;

[0045] Ensure that data is played back in the actual order in which the session occurred;

[0046] Playback performance is calculated in real time to ensure lag-free playback.

[0047] Preferably: in S7, the data insight and report specifically include:

[0048] Generate system usage and performance reports by analyzing playback data;

[0049] Apply natural language processing algorithms to extract keywords from conversations and generate operation log summaries;

[0050] Provide visual data analysis results to help administrators better understand the system operation status;

[0051] Extract keywords based on TF-IDF. The specific formula is:

[0052]

[0053] in:

[0054] w is a word;

[0055] d is the document;

[0056] D is the set of all documents;

[0057] TF(w,d) is the frequency of word w in document d;

[0058] N is the total number of documents in the document collection;

[0059] |{d∈D:w∈d}| is the number of documents containing word w.

[0060] Preferably: in S7, the performance optimization and intelligent algorithm application are specifically:

[0061] Implement a cache mechanism to reduce frequent disk read and write operations and improve data loading efficiency;

[0062] Use multi-threading technology to parallelize data decryption and decompression, optimizing playback startup time;

[0063] Introducing machine learning algorithms to perform pattern recognition on conversation data, automatically classify and mark key events;

[0064] Analyze historical session data using deep learning algorithms to predict potential system failures and maintenance needs.

[0065] Preferably, in the performance optimization and intelligent algorithm application, when pattern recognition is performed, it is performed based on a support vector machine, specifically:

[0066]

[0067] in:

[0068] x is the input vector, i.e., the feature vector of the current session data;

[0069] x i is the feature vector of the i-th training data point;

[0070] y i is the category label of the i-th training data point;

[0071] a i is the Lagrange multiplier, obtained through training;

[0072] K(x i ,x) is the kernel function, which is used to calculate the similarity between two data points;

[0073] b is the bias term of the decision boundary;

[0074] n is the number of training samples.

[0075] The beneficial effects of the present invention are:

[0076] 1. The present invention ensures data security by encrypting captured data using the Advanced Encryption Standard; reduces storage space consumption by compressing encrypted data using the GZIP algorithm; and enhances fault prediction and event analysis capabilities by introducing machine learning algorithms and deep learning algorithms.

[0077] 2. The present invention improves data loading efficiency and playback startup time by implementing a cache mechanism and multi-threading technology; and generates a system usage and performance report by analyzing the playback data. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 The present invention is a flowchart of a solution for IPMI console session playback. DETAILED DESCRIPTION

[0079] The technical solution of the present invention is further described in detail below in conjunction with specific implementation methods.

[0080] Embodiment 1:

[0081] A solution for IPMI console session playback, including:

[0082] S1: Initialize the session:

[0083] When an administrator starts an IPMI session, the system initializes an empty data structure D to store session data;

[0084] S2: Capture session data:

[0085] The system monitors the IPMI interface in real time and captures all input and output data streams;

[0086] S3: Data encryption and compression:

[0087] The captured data is encrypted using the Advanced Encryption Standard (AES) to ensure data security; the formula E = AES (D, K) is applied, where K is the key and E is the encrypted data; the encrypted data is compressed using the GZIP algorithm to reduce storage space consumption;

[0088] S4: Data Storage:

[0089] Store the compressed data C in a persistent storage device, such as a hard disk or SSD;

[0090] S5: Session playback:

[0091] When the session needs to be replayed, the compressed data C is loaded from the storage device; the decompression algorithm formula D = GZIP^(-1)(C) is applied to obtain the original encrypted data E; the AES decryption algorithm formula D = AES^(-1)(E,K) is used to obtain the original session data;

[0092] S6: Data processing and playback:

[0093] Sort and format the received data to ensure the correct playback order; synchronize the playback speed using the timestamp information T to ensure that the playback speed is consistent with the original session;

[0094] S7: Data Insights and Reports:

[0095] Generate system usage and performance reports by analyzing playback data; apply natural language processing (NLP) algorithms to extract keywords in conversations and generate operation log summaries.

[0096] Among them, in S1, initializing the session specifically includes:

[0097] When an administrator initiates a remote session through IPMI, the system automatically generates a unique session ID;

[0098] Create an empty data structure D for the session ID to store session data;

[0099] Initializes the timestamp recorder to ensure that every event in the session can be accurately recorded.

[0100] Wherein, in S2, capturing session data specifically includes:

[0101] The system configures the network interface and monitors IPMI requests and responses in real time;

[0102] For each request and response, record the timestamp and store the session data and its metadata in data structure D;

[0103] Make sure the captured data includes the text command, execution results, and any error messages.

[0104] Among them, in S3, data encryption and compression specifically include:

[0105] The captured data is encrypted using the AES encryption algorithm and the key K;

[0106] The formula E=AES(D,K) is applied, where E represents the encrypted data block;

[0107] Apply the GZIP compression algorithm to E to reduce the data size for easy storage and transmission.

[0108] Among them, in said S4, data storage specifically includes:

[0109] Store the compressed data C in a persistent storage device, such as a hard disk or SSD;

[0110] Index each session ID and the corresponding data file for quick retrieval;

[0111] Back up stored data regularly to prevent data loss.

[0112] Among them, in S5, the session playback specifically includes:

[0113] When a session needs to be replayed, the user selects a specific session ID through the interface;

[0114] Load the compressed data C from the storage device and apply the GZIP decompression algorithm formula D = GZIP^(-1)(C);

[0115] Use the AES decryption algorithm formula D = AES^(-1)(E,K) to obtain the original session data.

[0116] Among them, in said S6, data processing and playback specifically include:

[0117] Sort and format the received data and synchronize it according to the timestamp information T;

[0118] Ensure that data is played back in the actual order in which the session occurred;

[0119] Playback performance is calculated in real time to ensure lag-free playback.

[0120] Among them, in S7, data insights and reports specifically include:

[0121] Generate system usage and performance reports by analyzing playback data;

[0122] Apply natural language processing algorithms to extract keywords from conversations and generate operation log summaries;

[0123] Provide visual data analysis results to help administrators better understand the system operation status;

[0124] Extract keywords based on TF-IDF. The specific formula is:

[0125]

[0126] in:

[0127] w is a word;

[0128] d is the document;

[0129] D is the set of all documents;

[0130] TF(w,d) is the frequency of word w in document d;

[0131] N is the total number of documents in the document collection;

[0132] |{d∈D:w∈d}| is the number of documents containing word w.

[0133] Embodiment 2:

[0134] A solution for IPMI console session playback, including:

[0135] S1: Initialize the session:

[0136] When an administrator starts an IPMI session, the system initializes an empty data structure D to store session data;

[0137] S2: Capture session data:

[0138] The system monitors the IPMI interface in real time and captures all input and output data streams;

[0139] S3: Data encryption and compression:

[0140] The captured data is encrypted using the Advanced Encryption Standard (AES) to ensure data security; the formula E = AES (D, K) is applied, where K is the key and E is the encrypted data; the encrypted data is compressed using the GZIP algorithm to reduce storage space consumption;

[0141] S4: Data Storage:

[0142] Store the compressed data C in a persistent storage device, such as a hard disk or SSD;

[0143] S5: Session playback:

[0144] When the session needs to be replayed, the compressed data C is loaded from the storage device; the decompression algorithm formula D = GZIP^(-1)(C) is applied to obtain the original encrypted data E; the AES decryption algorithm formula D = AES^(-1)(E,K) is used to obtain the original session data;

[0145] S6: Data processing and playback:

[0146] Sort and format the received data to ensure the correct playback order; synchronize the playback speed using the timestamp information T to ensure that the playback speed is consistent with the original session;

[0147] S7: Performance optimization and intelligent algorithm application:

[0148] Implement a caching mechanism to reduce frequent disk read and write operations and improve data loading efficiency; use multi-threading technology to parallelize data decryption and decompression to optimize playback startup time; introduce machine learning algorithms to perform pattern recognition on session data, automatically classify and mark key events, such as login failures and configuration changes; use deep learning algorithms to analyze historical session data and predict potential system failures and maintenance needs;

[0149] S8: Data Insights and Reports:

[0150] Generate system usage and performance reports by analyzing playback data; apply natural language processing (NLP) algorithms to extract keywords in conversations and generate operation log summaries.

[0151] Among them, in S7, the performance optimization and intelligent algorithm application are specifically:

[0152] Implement a cache mechanism to reduce frequent disk read and write operations and improve data loading efficiency;

[0153] Use multi-threading technology to parallelize data decryption and decompression, optimizing playback startup time;

[0154] Introducing machine learning algorithms to perform pattern recognition on session data, automatically classifying and marking key events, such as login failures and configuration changes;

[0155] Analyze historical session data using deep learning algorithms to predict potential system failures and maintenance needs.

[0156] Among them, when performing pattern recognition, it is based on support vector machines, for example, identifying key events such as login failures or configuration changes, specifically:

[0157]

[0158] in:

[0159] x is the input vector, i.e., the feature vector of the current session data;

[0160] x i is the feature vector of the i-th training data point;

[0161] y i is the category label of the i-th training data point;

[0162] a i is the Lagrange multiplier, obtained through training;

[0163] K(x i ,x) is the kernel function, which is used to calculate the similarity between two data points;

[0164] b is the bias term of the decision boundary;

[0165] n is the number of training samples.

[0166] Among them, when analyzing historical session data and predicting potential system failures and maintenance needs, it is implemented based on long short-term memory networks, as follows:

[0167] h t =LSTM(x t ,h t-1 ,c t-1 )

[0168] in:

[0169] x t is the input at time t;

[0170] h t is the hidden state at time t;

[0171] h t-1 is the hidden state at time t-1;

[0172] c t-1 is the state of the cell at time t-1.

[0173] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A solution for IPMI console session playback, characterized in that: include: S1: Initialize the session: When an administrator starts an IPMI session, the system initializes an empty data structure D to store session data; S2: Capture session data: The system monitors the IPMI interface in real time and captures all input and output data streams; S3: Data encryption and compression: The captured data is encrypted using the Advanced Encryption Standard (AES) to ensure data security; the formula E = AES (D, K) is applied, where K is the key and E is the encrypted data; the encrypted data is compressed using the GZIP algorithm to reduce storage space consumption; S4: Data Storage: Store the compressed data C in a persistent storage device; S5: Session replay: When the session needs to be replayed, the compressed data C is loaded from the storage device; the decompression algorithm formula D = GZIP^(-1)(C) is applied to obtain the original encrypted data E; the AES decryption algorithm formula D = AES^(-1)(E,K) is used to obtain the original session data; S6: Data processing and playback: Sort and format the received data to ensure the correct playback order; synchronize the playback speed using the timestamp information T to ensure that the playback speed is consistent with the original session; S7: Performance optimization and intelligent algorithm application: Implement a caching mechanism to reduce frequent disk read and write operations and improve data loading efficiency; use multi-threading technology to parallelize data decryption and decompression to optimize playback startup time; introduce machine learning algorithms to perform pattern recognition on session data, automatically classify and mark key events; use deep learning algorithms to analyze historical session data and predict potential system failures and maintenance needs; S8: Data Insights and Reports: Generate system usage and performance reports by analyzing playback data; apply natural language processing algorithms to extract keywords in conversations and generate operation log summaries.

2. A solution for IPMI console session playback according to claim 1, characterized in that: In S1, initializing the session specifically includes: When an administrator initiates a remote session through IPMI, the system automatically generates a unique session ID; Create an empty data structure D for the session ID to store session data; Initializes the timestamp recorder to ensure that every event in the session can be accurately recorded.

3. A solution for IPMI console session playback according to claim 1, characterized in that: In S2, capturing session data specifically includes: The system configures the network interface and monitors IPMI requests and responses in real time; For each request and response, record the timestamp and store the session data and its metadata in data structure D; Make sure the captured data includes the text command, execution results, and any error messages.

4. A solution for IPMI console session playback according to claim 1, characterized in that: In S3, data encryption and compression specifically include: The captured data is encrypted using the AES encryption algorithm and the key K; The formula E=AES(D,K) is applied, where E represents the encrypted data block; Apply the GZIP compression algorithm to E to reduce the data size for easy storage and transmission.

5. A solution for IPMI console session playback according to claim 1, characterized in that: In S4, data storage specifically includes: Store the compressed data C in a persistent storage device; Index each session ID and the corresponding data file for quick retrieval; Back up stored data regularly to prevent data loss.

6. A solution for IPMI console session playback according to claim 1, characterized in that: In S5, the session playback specifically includes: When a session needs to be replayed, the user selects a specific session ID through the interface; Load the compressed data C from the storage device and apply the GZIP decompression algorithm formula D = GZIP^(-1)(C); Use the AES decryption algorithm formula D = AES^(-1)(E,K) to obtain the original session data.

7. A solution for IPMI console session playback according to claim 1, characterized in that: In S6, data processing and playback specifically include: Sort and format the received data and synchronize it according to the timestamp information T; Ensure that data is played back in the actual order in which the session occurred; Playback performance is calculated in real time to ensure lag-free playback.

8. A solution for IPMI console session playback according to claim 1, characterized in that: In S7, data insights and reports specifically include: Generate system usage and performance reports by analyzing playback data; Apply natural language processing algorithms to extract keywords from conversations and generate operation log summaries; Provide visual data analysis results to help administrators better understand the system operation status; Extract keywords based on TF-IDF. The specific formula is: in: w is a word; d is the document; D is the set of all documents; TF(w,d) is the frequency of word w in document d; N is the total number of documents in the document collection; |{d∈D:w∈d}| is the number of documents containing word w.

9. A solution for IPMI console session playback according to claim 8, characterized in that: In S7, the performance optimization and intelligent algorithm application are specifically as follows: Implement a cache mechanism to reduce frequent disk read and write operations and improve data loading efficiency; Use multi-threading technology to parallelize data decryption and decompression, optimizing playback startup time; Introducing machine learning algorithms to perform pattern recognition on conversation data, automatically classify and mark key events; Analyze historical session data using deep learning algorithms to predict potential system failures and maintenance needs.

10. A solution for IPMI console session playback according to claim 9, characterized in that: In the performance optimization and intelligent algorithm application, when pattern recognition is performed, it is performed based on a support vector machine, specifically: in: x is the input vector, i.e., the feature vector of the current session data; x i is the feature vector of the i-th training data point; y i is the category label of the i-th training data point; a i is the Lagrange multiplier, obtained through training; K(x i ,x) is the kernel function used to calculate the similarity between two data points; b is the bias term of the decision boundary; n is the number of training samples.

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