Multi-device offline restart management system and method
Through distributed monitoring and hierarchical restart management system, the fault detection lag and false restart problems of self-service terminal equipment clusters during network fluctuations or software crashes are solved, efficient and accurate fault handling and system stability are achieved, financial-level audit requirements, and system performance and user experience are improved.
Patent Information
- Application Number
- CN202510348593.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-24
- Publication Date
- 2025-08-05
AI Technical Summary
When existing self-service terminal equipment clusters fluctuate networks or software crashes, the central server responds late, resulting in lag in fault discovery, high resource occupancy, and increased operation and maintenance costs. Simple heartbeat detection cannot distinguish between instantaneous communication interruptions and substantial system failures, and frequent false triggering of restarts affects user experience.
The distributed health monitoring node array, abnormal behavior feature library, decision-making arbitration module and blockchain evidence storage unit are adopted, combined with edge computing and blockchain technology to realize real-time monitoring, dynamic hierarchical restart and tamper-free recording. Through LSTM neural network and Q-learning reinforcement learning, optimized restart strategy, combined with biometric verification and hierarchical restart strategy, to ensure the accuracy of fault detection and system stability.
It improves the accuracy of fault detection, shortens the average downtime, meets financial-level audit requirements, reduces the data loss rate under high-frequency restarts, improves system throughput and compliance review efficiency, and improves user experience.
Smart Images
Figure CN120429166A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of self-service terminals, and particularly to a multi-device disconnection and restart management system and method. Background Art
[0002] Existing self-service terminal device clusters generally adopt a centralized management architecture. When multiple devices simultaneously experience network fluctuations or software crashes, the central server is prone to response delays due to overloaded concurrent requests; Traditional restart mechanisms rely on manual inspections or are triggered at fixed time intervals, resulting in problems such as delayed fault discovery, high resource occupancy, and increased operation and maintenance costs; Some terminal devices adopt simple heartbeat detection schemes, which cannot distinguish between instantaneous communication interruptions and substantial system failures, and frequently mis-trigger restarts, affecting the user experience. Summary of the Invention
[0003] The purpose of the present invention is to provide a multi-device disconnection and restart management system and method for the above problems in the prior art, thereby solving all or one of the above problems existing in the prior art.
[0004] To solve the above technical problems, the specific technical solutions of the present invention are as follows: On the one hand, the present invention provides a multi-device disconnection and restart management system, including: A distributed health monitoring node array, deployed locally on each self-service terminal, for real-time collection of CPU load, memory occupancy rate, network latency, and disk I / O status parameters; An abnormal behavior feature library, for storing SVM classification model parameters and threshold matrices based on historical fault data; A decision arbitration module, for dynamically allocating restart priorities using a weighted round-robin algorithm; A cold start buffer pool, for pre-setting a lightweight operating system image and a snapshot of the business core process; A blockchain evidence storage unit, for making tamper-proof records of the triggering conditions, execution times, and operators of each restart operation.
[0005] As an improved solution, the health monitoring node array is implemented through an edge computing framework; The edge computing framework is used for: performing multi-dimensional correlation analysis on sensor data using a time series anomaly detection algorithm based on an LSTM neural network; a dynamic threshold adjustment mechanism, automatically correcting the alarm threshold in combination with the device usage period and the business load fluctuation coefficient.
[0006] As an improved solution, the decision arbitration module includes: A Q-learning-based reinforcement learning model is used to train the reward function R = αT_recovery + βC_resource; A multi-objective optimizer is used to balance restart timeliness and terminal service availability using the NSGA-II algorithm.
[0007] As an improved solution, the cold start buffer pool adopts a layered storage architecture; In the tiered storage architecture, the first-level cache stores hot data snapshots within the last 24 hours; the second-level cache uses erasure coding technology to protect key business data within three months.
[0008] As an improved solution, the blockchain evidence storage unit is equipped with a consortium chain architecture based on Hyperledger Fabric, with nodes including the operation and maintenance center, equipment manufacturers and third-party auditing agencies; The blockchain evidence storage unit is also equipped with a privacy protection mechanism that supports the national secret SM4 algorithm, which is used to desensitize sensitive operation logs.
[0009] On the other hand, the present invention also provides a method for managing multiple device offline restarts, comprising the following steps: Collect the real-time operating parameters of each terminal device through the Zigbee protocol; Input the parameters into the pre-trained random forest model to predict the fault probability and output the fault confidence P_f; When P_f > 0.8, the secondary verification process is triggered: the user is required to confirm the device status through biometrics; If the secondary verification fails, a hierarchical restart strategy is initiated: non-core subsystems are restarted first; After the restart is complete, the consistent hashing algorithm is used to verify the service integrity.
[0010] As an improved solution, the hierarchical restart strategy includes: Yellow warning level: only restart the current fault module; Orange warning level: Restart the relevant functional subsystem; Red alert level: The entire machine is cold restarted and rolled back to the last stable version.
[0011] As an improved solution, the biometric confirmation step includes: Multimodal fusion authentication: combining finger vein recognition and voiceprint recognition; Dynamic challenge response mechanism: Generates a unique voiceprint verification code for each verification.
[0012] As an improved solution, the service integrity verification includes: Compare the CRC32 checksums of key processes before and after restart; Detect whether the response time of each service port has recovered within the threshold T_response through heartbeat packets.
[0013] As an improved solution, the multi-device disconnection and restart management method further includes: Establish a device health index H(t) = ∑(w_i * S_i(t)), where S_i(t) is the standard score of the i-th indicator; when H(t) is lower than the preset threshold for 7 consecutive days, automatically trigger a preventive maintenance work order.
[0014] The beneficial effects of the technical solution of the present invention are: 1. The multi-device disconnection and restart management system described in the present invention can improve the accuracy of fault detection through the mutual cooperation of system modules; shorten the average downtime through a hierarchical restart strategy; the blockchain evidence storage mechanism meets financial-level audit requirements and improves the efficiency of compliance review; the cold start buffer pool design makes the data loss rate in high-frequency restart scenarios approach zero; the adaptive algorithm supports dynamic expansion, improves system throughput, makes up for the defects of the prior art, and has high application value.
[0015] 2. The multi-device disconnection and restart management method described in the present invention can orderly call system modules to implement the system logic of the multi-device disconnection and restart management system described in the present invention. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0017] Figure 1 is a schematic diagram of the architecture of the multi-device disconnection and restart management system described in Embodiment 1 of the present invention; Figure 2 is a schematic diagram of the process of the multi-device disconnection and restart management method described in Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0018] The following will elaborate on the preferred embodiments of the present invention in conjunction with the drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.
[0019] In the description of the present invention, it should be noted that the embodiments described in the present invention are some embodiments of the present invention, rather than all embodiments; based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.
[0020] The terms "first", "second", etc. in the description and claims of this article and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or equipment that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or equipment. Embodiment 1
[0021] This embodiment provides a multi-device disconnection and restart management system, as Figure 1 shown, including: A distributed health monitoring node array, deployed locally at each self-service terminal, for real-time collection of CPU load, memory occupancy rate, network latency, and disk I / O status parameters; An abnormal behavior feature library, for storing SVM classification model parameters and threshold matrices based on historical failure data; A decision arbitration module, for dynamically allocating restart priorities using a weighted round-robin algorithm; A cold start buffer pool, for pre-setting a lightweight operating system image and a snapshot of the business core process; A blockchain evidence storage unit, for making tamper-proof records of the trigger conditions, execution times, and operators of each restart operation.
[0022] As an improved solution, the health monitoring node array is implemented through an edge computing framework; The edge computing framework is used for: performing multi-dimensional correlation analysis on sensor data through a time series anomaly detection algorithm based on an LSTM neural network; a dynamic threshold adjustment mechanism, automatically correcting the alarm threshold in combination with the device usage period and the business load fluctuation coefficient.
[0023] As an improved solution, the decision arbitration module includes: A reinforcement learning model based on Q-learning, for training the reward function R = αT_recovery + βC_resource; A multi-objective optimizer is used to balance the restart timeliness and the availability of terminal services by using the NSGA-II algorithm.
[0024] As an improved solution, the cold start buffer pool adopts a hierarchical storage architecture; In the hierarchical storage architecture, the first-level cache stores the hot data snapshots within the last 24 hours; the second-level cache uses erasure coding technology to protect the key business data within three months.
[0025] As an improved solution, the blockchain evidence storage unit has a consortium chain architecture based on Hyperledger Fabric, and the nodes include an operation and maintenance center, equipment manufacturers, and third-party auditing agencies; The blockchain evidence storage unit also has a privacy protection mechanism that supports the national cipher SM4 algorithm for desensitizing sensitive operation logs.
[0026] It should be noted that the above examples are only for explaining the present invention and should not limit the protection scope of the present invention. Embodiment 2
[0027] Based on the same inventive concept as the multi-device disconnection and restart management system described in Embodiment 1, this embodiment provides a multi-device disconnection and restart management method, as Figure 2 shown, including the following steps: Collect the real-time operation parameters of each terminal device through the Zigbee protocol; Input the parameters into a pre-trained random forest model for fault probability prediction, and output the fault confidence level P_f; When P_f > 0.8, trigger a secondary verification process: require the user to confirm the device status through biometric identification; If the secondary verification fails, start a hierarchical restart strategy: preferentially restart non-core subsystems; After the restart is completed, use the consistent hashing algorithm to verify the service integrity.
[0028] As an improved solution, the hierarchical restart strategy includes: Yellow warning level: Only restart the current faulty module; Orange warning level: Restart the affiliated functional subsystem; Red warning level: Perform a cold start of the whole machine and roll back to the last stable version.
[0029] As an improved solution, the biometric identification confirmation step includes: Multi-modal fusion authentication: Combine finger vein recognition and voiceprint recognition; Dynamic challenge response mechanism: Generate a unique voiceprint verification code each time for verification.
[0030] As an improved solution, the service integrity verification includes: Comparing the CRC32 check values of key processes before and after restart; Detecting whether the response time of each service port has recovered within the threshold T_response through heartbeat packets.
[0031] As an improved solution, the multi-device disconnection and restart management method further includes: Establishing a device health index H(t) = ∑(w_i * S_i(t)), where S_i(t) is the standard score of the i-th indicator; when H(t) is lower than the preset threshold for 7 consecutive days, a preventive maintenance work order is automatically triggered.
[0032] It should be understood that in various embodiments of this article, the magnitudes of the serial numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of this article.
[0033] It should also be understood that in the embodiments of this article, the term "and / or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.
[0034] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described according to their functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this article.
[0035] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific logical process of the method described above can refer to the corresponding working processes of the system, device, and unit in the foregoing method embodiments, and will not be elaborated herein.
[0036] In several embodiments provided in this document, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Additionally, the displayed or discussed couplings or direct couplings or communication connections to each other can be indirect couplings or communication connections through some interfaces, devices, or units, and can also be in the form of electrical, mechanical, or other connections.
[0037] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiments in this document.
[0038] In addition, in each embodiment of this document, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.
[0039] If the above-mentioned integrated unit 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. Based on this understanding, the essence of the technical solution in this document, or the part that contributes to the prior art, or all or part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of this document. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.
[0040] The above are only the embodiments of the present invention and do not limit the patent scope of the present invention. All equivalent structural or equivalent process transformations made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, are equally included in the patent protection scope of the present invention.
Claims
1. A multi-device offline restart management system, characterized in that: include: A distributed health monitoring node array is deployed locally at each self-service terminal to collect real-time CPU load, memory usage, network latency, and disk I / O status parameters; Abnormal behavior feature library, used to store SVM classification model parameters and threshold matrix based on historical fault data; A decision arbitration module, which is used to dynamically assign restart priorities using a weighted round-robin algorithm; Cold start buffer pool, used to pre-set lightweight operating system images and business core process snapshots; The blockchain evidence storage unit is used to record the triggering conditions, execution time and operator of each restart operation in an unalterable manner.
2. The multi-device offline restart management system according to claim 1, characterized in that: The health monitoring node array is implemented through an edge computing framework; The edge computing framework is used to: perform multi-dimensional correlation analysis on sensor data based on the time series anomaly detection algorithm of the LSTM neural network; and a dynamic threshold adjustment mechanism to automatically correct the alarm threshold based on the device usage period and business load fluctuation coefficient.
3. The multi-device offline restart management system according to claim 1, characterized in that: The decision arbitration module includes: A Q-learning-based reinforcement learning model is used to train the reward function R = αT_recovery + βC_resource; A multi-objective optimizer is used to balance restart timeliness and terminal service availability using the NSGA-II algorithm.
4. The multi-device offline restart management system according to claim 1, characterized in that: The cold start buffer pool adopts a layered storage architecture; In the tiered storage architecture, the first-level cache stores hot data snapshots within the last 24 hours; the second-level cache uses erasure coding technology to protect key business data within three months.
5. The multi-device offline restart management system according to claim 1, characterized in that: The blockchain evidence storage unit is equipped with a consortium chain architecture based on Hyperledger Fabric, with nodes including the operation and maintenance center, equipment manufacturers and third-party audit institutions; The blockchain evidence storage unit is also equipped with a privacy protection mechanism that supports the national secret SM4 algorithm, which is used to desensitize sensitive operation logs.
6. A method for managing the offline restart of multiple devices, characterized in that: The following steps are involved: Collect the real-time operating parameters of each terminal device through the Zigbee protocol; Input the parameters into the pre-trained random forest model to predict the fault probability and output the fault confidence P_f; When P_f > 0.8, the secondary verification process is triggered: the user is required to confirm the device status through biometrics; If the secondary verification fails, a hierarchical restart strategy is initiated: non-core subsystems are restarted first; After the restart is complete, the consistent hashing algorithm is used to verify the service integrity.
7. The method for managing multiple device offline restarts according to claim 6, wherein: The hierarchical restart strategy includes: Yellow warning level: only restart the current fault module; Orange warning level: Restart the relevant functional subsystem; Red alert level: The entire machine is cold restarted and rolled back to the last stable version.
8. The method for managing multiple device offline restarts according to claim 6, wherein: The biometric confirmation step includes: Multimodal fusion authentication: combining finger vein recognition and voiceprint recognition; Dynamic challenge response mechanism: Generates a unique voiceprint verification code for each verification.
9. The method for managing multiple device offline restarts according to claim 6, wherein: The service integrity verification includes: Compare the CRC32 checksums of key processes before and after restart; Use heartbeat packets to detect whether the response time of each service port has returned to within the threshold T_response.
10. The method for managing multiple device offline restarts according to claim 6, wherein: The multi-device offline restart management method further includes: Establish the equipment health index H(t) = ∑(w_i * S_i(t)), where S_i(t) is the standard score of the i-th indicator; when H(t) is lower than the preset threshold for 7 consecutive days, a preventive maintenance work order is automatically triggered.