Method for automatically detecting and solving repeated IP address conflict in distributed cluster

Abstract

The invention provides a method for automatically detecting and solving repeated IP address conflicts in a distributed cluster, belongs to the technical field of computers, ensures the uniqueness of IP addresses in the distributed cluster through real-time monitoring and an automatic conflict detection mechanism, avoids network abnormity and faults caused by repeated IPs, and improves the reliability of the distributed cluster. Therefore, the stability and reliability of the whole network are improved. Through the efficient data structure, intelligent management and dynamic allocation of the IP addresses can be realized, resource waste is avoided, each IP address is ensured to be reasonably utilized, and the overall utilization rate of cluster resources is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular, to a method for automatically detecting and resolving duplicate IP address conflicts in a distributed cluster. Background Art

[0002] In today's era of cloud computing and big data, distributed clusters have become the infrastructure cornerstone for many enterprises and service providers. These clusters usually consist of thousands or even hundreds of thousands of nodes, including servers, storage devices, network devices, and edge computing nodes, etc. With such a large scale of nodes and the dynamic joining and leaving characteristics, the allocation and management of IP addresses face unprecedented complexity.

[0003] In a dynamically allocated scenario, cluster nodes may automatically join or leave the cluster according to various strategies such as load balancing, fault recovery, and elastic scaling. This means that IP addresses must be able to be flexibly allocated and recycled to adapt to the real-time changes of nodes. However, this flexibility also brings risks. Especially when a node joins, if there is no effective mechanism to verify whether the allocated IP address is already occupied, IP address conflicts are very likely to occur.

[0004] IP address conflicts can lead to a series of serious network problems. First, the conflicting nodes may overwrite each other's network traffic, resulting in packet loss or incorrect routing, affecting the normal operation of services. Second, conflicts may also cause network congestion because network devices try to resolve the duplicate addresses, consuming unnecessary bandwidth and processing power. Finally, the long-term conflict state will reduce the availability and reliability of the entire cluster, affecting the user experience and business continuity.

[0005] Traditional IP address management mainly relies on DHCP (Dynamic Host Configuration Protocol) and DNS (Domain Name System) services, but these methods expose obvious deficiencies in a large-scale cluster environment. On the one hand, the address pool of DHCP may not be sufficient to cope with the rapid growth of the number of nodes, especially in the absence of effective monitoring and automatic recycling mechanisms. On the other hand, the update and propagation delay of DNS means that even if the conflict is resolved, it takes some time to take effect throughout the network, affecting the immediacy and consistency of services.

[0006] Facing IP address conflicts, manual checking and repair is the most direct but also the most time-consuming and laborious method. Network administrators need to check network logs one by one, locate the source nodes of the conflicts, and then manually change the IP address settings and reconfigure network devices. This method is not only inefficient but also error-prone. Especially in a large-scale cluster, it is almost impossible to achieve comprehensive coverage through manual operations, nor can it guarantee the long-term network health status. Summary of the Invention

[0007] In view of the problem of duplicate IP address conflicts in large-scale distributed clusters, the present invention provides a method for automatically detecting and resolving duplicate IP address conflicts in a distributed cluster, which solves the key problem of IP address management in large-scale distributed clusters, especially the problem of automatically detecting and resolving duplicate IP address conflicts.

[0008] The technical solution of the present invention is as follows:

[0009] A method for automatically detecting and resolving duplicate IP address conflicts in a distributed cluster, comprising the following steps:

[0010] a) Use a hash table to store the mapping relationship between the IP address of each node and the node identifier;

[0011] b) Maintain the consistency of the hash table data among multiple IP address management service nodes through a distributed consensus algorithm;

[0012] c) When a new node joins the cluster, automatically allocate an unused IP address and update the hash table;

[0013] d) Periodically perform network probes to verify the uniqueness of IP addresses;

[0014] e) If a duplicate IP address is found, reallocate a new IP address through the IP address management service and notify the affected nodes to update.

[0015] Furthermore,

[0016] The distributed consensus algorithm is selected from Raft, Paxos or their variants. Implement a master node election mechanism, where the master node is responsible for managing the hash table, and the slave nodes periodically synchronize their states with the master node.

[0017] Furthermore,

[0018] The network probe includes using ping, ARP request or TCP connection test to detect the reachability of each IP address.

[0019] Perform in-depth analysis on the probe results to identify IP addresses with abnormal responses. If several nodes respond to the same IP address, it is regarded as a conflict.

[0020] When several responses to the same IP address are detected, trigger a conflict detection algorithm to confirm the conflicting nodes by comparing the records in the hash table with the probe results.

[0021] Perform secondary verification on the suspected conflicting IP addresses.

[0022] Furthermore,

[0023] When a node leaves the cluster, its IP address is automatically recycled and the hash table is updated; the updated status is synchronized to all management service nodes through a distributed consistency algorithm to ensure the consistency of the global view.

[0024] Furthermore,

[0025] The IP address management service includes one or more centralized service nodes for coordinating the allocation and recycling of IP addresses.

[0026] Furthermore,

[0027] It also includes implementing security access control to only allow authorized nodes and management services to access and modify the hash table. Logging operations for IP address allocation, recycling, conflict detection, and resolution to support auditing and troubleshooting.

[0028] Furthermore,

[0029] It also includes implementing dynamic load balancing and resource optimization to ensure the high availability and performance of the IP address management service.

[0030] The IP address management service adopts a dynamic load balancing strategy to automatically adjust traffic allocation according to the load conditions of current service instances.

[0031] Monitor the usage of system resources and dynamically adjust the number and configuration of service instances according to the resource usage.

[0032] Furthermore,

[0033] It also includes providing a graphical user interface and API interfaces to facilitate IP address management by administrators and automation tools.

[0034] It also includes implementing regular stress tests and performance tests to verify the stability and performance of the system.

[0035] The beneficial effects of the present invention are

[0036] 1. Improve network stability and reliability

[0037] Conflict prevention: The real-time monitoring and automatic detection mechanism can quickly identify and prevent the occurrence of IP address conflicts, avoid network anomalies and interruptions caused thereby, and improve network stability and reliability.

[0038] Quick response: The automated conflict resolution process can promptly correct duplicate IP problems, reduce network latency and packet loss, and ensure the coherence and accuracy of data transmission.

[0039] 2. Enhance operation and maintenance efficiency and automation level

[0040] Automated Management: From IP address allocation, recycling to conflict detection and resolution, the entire process is highly automated, significantly reducing the workload of network administrators and improving operation and maintenance efficiency.

[0041] Reduced Manual Intervention: Through automated tools and graphical interfaces, administrators can easily monitor and manage IP addresses, reducing human errors and achieving more refined network resource management.

[0042] 3. Improve Resource Utilization and Cost - effectiveness

[0043] Intelligent Allocation: Optimized IP address allocation strategies and hash table structures ensure the effective utilization of IP resources, avoiding resource waste and reducing network operation costs.

[0044] Dynamic Recycling: The automatic IP recycling mechanism when nodes leave can timely release unused resources, enabling IP addresses to be re - allocated to new nodes, improving the turnover rate and utilization rate of resources.

[0045] 4. Promote Service Quality and User Experience

[0046] Service Continuity: High - availability design and fast fault - recovery mechanisms ensure service continuity, reducing service interruption time and enhancing user satisfaction and business continuity.

[0047] Performance Optimization: Performance monitoring and tuning measures ensure the efficient operation of the system, providing stable network services even under high - load conditions and enhancing the user experience.

[0048] 5. Strengthen Security and Compliance

[0049] Access Control: Strict access control and permission management mechanisms protect the security of IP address information, preventing unauthorized access and operations.

[0050] Audit and Compliance: Complete logging and auditing functions ensure the transparency of IP address management, meeting industry standards and regulatory requirements, such as data protection laws and network management specifications.

[0051] 6. Support Scalability and Flexibility

[0052] Modular Design: Modular architecture and standardized API interfaces enable the system to flexibly adapt to future technological developments and changes in business requirements, being easy to expand and upgrade.

[0053] Multi - protocol Support: Support for both IPv4 and IPv6 ensures the compatibility of the solution and future scalability, meeting the requirements in different network environments.

[0054] 7. Promote Technological Innovation and Competitiveness

[0055] Technological innovation: By integrating advanced data structures, distributed algorithms, and automation technologies, it has promoted technological innovation in the field of network management, enhancing the technological competitiveness and market position of enterprises.

[0056] Industry influence: The application of this invention can set an industry benchmark, lead the development trend of distributed cluster management technologies, and promote the progress and innovation of the entire industry.

[0057] In summary, while solving the problem of duplicate IP address conflicts in large-scale distributed clusters, this invention also brings a series of beneficial effects. It not only improves the stability and operation and maintenance efficiency of the network, but also enhances resource utilization, service quality, and security, supporting the technological innovation and competitiveness improvement of enterprises. Brief Description of the Drawings

[0058] Figure 1 is a schematic diagram of the overall architecture of the present invention;

[0059] Figure 2 is a flowchart of IP recycling;

[0060] Figure 3 is a flowchart of IP generation. Detailed Embodiment

[0061] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0062] The present invention provides a method for automatically detecting and resolving duplicate IP address conflicts in a distributed cluster, which comprehensively applies advanced data structures, distributed consensus algorithms, network monitoring technologies, and automated repair processes, aiming to ensure the uniqueness of IP addresses and improve the stability and performance of the network. The following is a detailed description of the solution:

[0063] 1. Distributed IP Address Management Service Architecture

[0064] 1.1 IP Address Database (Implemented by Hash Table)

[0065] Data Structure Design: Use a hash table as the core data structure to store the mapping relationship between the IP address of each node and its identity identifier (such as MAC address, UUID, or custom node ID).

[0066] Optimized Storage and Access: The design of the hash table takes into account load balancing. It uses a hash function to efficiently disperse data, avoiding hot spot problems, and supports O(1)-level lookup and insertion operations, maintaining high performance even in large-scale clusters.

[0067] 1.2 Distributed Consistency Algorithms

[0068] Algorithm Selection and Implementation: Adopt mature consistency algorithms such as Raft or Paxos to ensure that information about the IP address allocation status is consistent among all IP address management service nodes.

[0069] Master-Slave Election and State Synchronization: Implement a master node election mechanism. The master node is responsible for managing the hash table, and the slave nodes regularly synchronize their states with the master node to ensure quick switching in case of master node failure and maintain service continuity.

[0070] 2. Dynamic IP Address Allocation and Recycling Mechanism

[0071] 2.1 New Node Joining and IP Allocation

[0072] Allocation Strategy: When a new node joins the cluster, it requests an IP address allocation from the centralized IP address management service. The server checks the hash table, finds an unallocated IP address, binds it to the node's identity identifier, and updates the hash table simultaneously.

[0073] Allocation Record: Each allocation records the allocation time and the information of the allocated node for subsequent auditing and tracking.

[0074] 2.2 Node Departure and IP Recycling

[0075] Recycling Mechanism: When a node leaves the cluster, the node actively or passively notifies the IP address management service. The server removes the IP address record of the node from the hash table, making it available again for allocation to subsequent nodes.

[0076] Garbage Collection: Design a timed task or event-driven mechanism to periodically clean up IP address records that have not been referenced for a long time to prevent the hash table from expanding.

[0077] 3. Real-time Network Monitoring and Conflict Detection

[0078] 3.1 Network Probing and Analysis

[0079] Regular Scanning: Design a network probing tool to perform network scans regularly, using ping, ARP requests, or TCP connection tests to detect the reachability of each IP address.

[0080] Packet Analysis: Deeply analyze the probing results to identify IP addresses with abnormal responses. For example, if multiple nodes respond to the same IP address, it is regarded as a conflict.

[0081] 3.2 Conflict Detection Algorithm

[0082] Conflict Identification Logic: When the network detection tool detects multiple responses for the same IP address, the conflict detection algorithm is triggered. By comparing the records in the hash table with the detection results, the conflicting nodes are confirmed.

[0083] Exception Handling: Design an exception handling process to conduct secondary verification on the suspected conflicting IP addresses to ensure the accuracy of the detection results.

[0084] 4. Automated Conflict Resolution Mechanism

[0085] 4.1 Conflict Reporting and Recording

[0086] Conflict Reporting: When an IP address conflict is detected, the conflict information is automatically reported to the IP address management service, including the conflicting IP address, the involved node information, and the detection time, etc.

[0087] Conflict Recording: The server records the conflict events, including the network status before the conflict, the status of the conflicting nodes, and the detailed steps of conflict handling, which is convenient for subsequent auditing and analysis.

[0088] 4.2 Intelligent Reallocation

[0089] Address Reallocation: The server selects an unallocated IP address from the hash table and reallocates it to one of the conflicting nodes, and updates the records in the hash table.

[0090] Allocation Strategy Adjustment: According to the frequency and pattern of conflicts, the IP address allocation strategy is intelligently adjusted. For example, preferentially allocate unused subnets to reduce the possibility of conflicts.

[0091] 4.3 Automatic Notification and Update

[0092] Node Notification: The affected nodes automatically receive the new IP address information, triggering the local configuration update process, including changes to the operating system network configuration and restarting the network service, etc.

[0093] Status Synchronization: The updated status is synchronized to all management service nodes through the distributed consistency algorithm to ensure the consistency of the global view.

[0094] 5. Security and Audit Functions

[0095] 5.1 Access Control and Permission Management

[0096] Authentication: Implement role-based access control, allowing only authorized management services and nodes to access the IP address allocation information.

[0097] Operation Log: Records all operations related to IP address allocation, recycling, conflict detection, and resolution, including operation time, operator, operation result, etc., facilitating auditing and troubleshooting.

[0098] 5.2 Security Auditing and Reporting

[0099] Regular Auditing: Regularly perform security audits to check the security of IP address allocation, including unauthorized access, potential security vulnerabilities, etc.

[0100] Compliance Check: Ensure that the IP address management solution complies with relevant network management standards and regulatory requirements, such as IPv4 / IPv6 address usage specifications, data protection laws, etc.

[0101] 6. Scalability and Compatibility Considerations

[0102] 6.1 Modular Design

[0103] Scalable Architecture: The technical solution adopts a modular design, and each component such as network detection tools, distributed consensus algorithms, etc. can be independently upgraded or replaced to adapt to future technological developments and changing requirements.

[0104] Interface Standardization: Design standardized API interfaces to ensure that the solution can be seamlessly integrated with other network management software or third-party services.

[0105] 6.2 Protocol Compatibility

[0106] Multi-Protocol Support: The solution design considers an IPv4 and IPv6 dual-stack environment, supports IP address management under both protocols, and ensures compatibility and future scalability.

[0107] Through the above detailed technical solution, the present invention aims to provide a comprehensive, automated, and highly available IP address management solution, effectively solving the problem of duplicate IP address conflicts in large-scale distributed clusters, improving network stability and performance, reducing operation and maintenance costs, and ensuring service quality and user experience.

[0108] 7. Fault Recovery and Fault Tolerance Mechanism

[0109] 7.1 High-Availability Design

[0110] Redundant Backup: The IP address management service is deployed with multiple instances, and each instance has a complete copy of the hash table to ensure that when any one instance fails, other instances can seamlessly take over the service.

[0111] Heartbeat Monitoring: Implement a heartbeat monitoring mechanism to regularly check the health status of each instance. Once a fault is detected in a certain instance, immediately trigger the failover process.

[0112] 7.2 Data Persistence and Backup

[0113] Data Persistence: Use a persistent storage system (such as a distributed file system or a database) to store hash table data, ensuring that the data will not be lost due to service restart or failure.

[0114] Regular Backup: Implement a regular data backup strategy to back up the hash table data to external storage to prevent catastrophic data loss.

[0115] 7.3 Automatic Fault Recovery

[0116] Automatic Detection and Recovery: The system has a built-in automatic fault detection mechanism. Once a fault is detected, it automatically starts the recovery process, such as reassigning the IP address of the faulty node and updating the hash table, etc.

[0117] Fault Isolation: When a node fault is detected, the system can automatically isolate the faulty node to prevent the spread of the fault, and at the same time attempt to recover or replace the functions of the faulty node.

[0118] 8. Performance Optimization and Resource Management

[0119] 8.1 Load Balancing

[0120] Dynamic Load Balancing: The IP address management service adopts a dynamic load balancing strategy, automatically adjusting the traffic distribution according to the current load situation of the service instances to ensure the response time and stability of the service.

[0121] Resource Optimization: Monitor the usage of system resources, such as CPU, memory, and network bandwidth, and dynamically adjust the number and configuration of service instances according to the resource usage to avoid resource waste.

[0122] 8.2 Performance Monitoring and Tuning

[0123] Performance Metric Monitoring: Implement performance monitoring, collect key performance indicators (KPIs), such as service response time, requests per second (RPS), CPU and memory usage, etc., for evaluating system performance.

[0124] Continuous Tuning: According to the performance monitoring data, continuously optimize system parameters, such as adjusting the size of the hash table and optimizing the parameters of the distributed consistency algorithm, to improve the overall performance of the system.

[0125] 9. User Interface and Management Tools

[0126] 9.1 Graphical Management Interface

[0127] Intuitive UI Design: Provide a graphical user interface that enables administrators to intuitively view and manage the status of IP address allocation, conflict detection, and resolution.

[0128] Interactive Operations: Allow administrators to perform critical operations through the interface, such as manually allocating or reclaiming IP addresses, viewing detailed conflict logs, etc.

[0129] 9.2 API Interfaces

[0130] RESTful API: Provide RESTful-style API interfaces that allow third-party applications or scripts to directly interact with the IP address management service to perform operations such as queries, allocations, and reclaims.

[0131] Automation Tool Integration: Support integration with automation operation and maintenance tools (such as Ansible, Puppet, or Chef) to achieve an automated workflow for IP address management.

[0132] 10. Testing and Verification

[0133] 10.1 Unit Testing and Integration Testing

[0134] Unit Testing: Conduct unit testing on each module and component in the system to ensure that its functions are correct.

[0135] Integration Testing: Conduct integration testing to verify the interaction and collaboration between components and ensure that the system can work properly as a whole.

[0136] 10.2 Stress Testing and Performance Testing

[0137] Stress Testing: Simulate high-concurrency scenarios to test the performance and stability of the system under extreme conditions.

[0138] Performance Testing: Evaluate the response time and resource consumption of the system under different loads to ensure that the system can maintain good performance in various situations.

[0139] 10.3 Security Testing

[0140] Penetration Testing: Conduct penetration testing, simulate attack scenarios, evaluate the security of the system, and ensure that there are no obvious security vulnerabilities.

[0141] Compliance Check: Check whether the system complies with industry standards and regulatory requirements, such as PCIDSS, GDPR, etc., to ensure the compliance of the system.

[0142] Through the above detailed technical solutions, the present invention not only solves the problem of duplicate IP address conflicts in large-scale distributed clusters but also provides a highly available, high-performance, easy-to-manage, and secure IP address management service, which is applicable to various distributed computing environments, such as data centers, cloud computing platforms, and Internet of Things systems. This will greatly improve the efficiency of network operation and maintenance, reduce operation and maintenance costs, and enhance the stability of services and user experience.

[0143] Improve network stability and reliability:

[0144] Through real-time monitoring and an automated conflict detection mechanism, the present invention ensures the uniqueness of IP addresses in a distributed cluster, avoiding network anomalies and failures caused by duplicate IPs, thereby improving the overall network stability and reliability.

[0145] Optimize resource allocation and utilization:

[0146] Through efficient data structures (such as hash tables) and algorithms (such as distributed consensus algorithms), the present invention can achieve intelligent management and dynamic allocation of IP addresses, avoid resource waste, ensure that each IP address is reasonably utilized, and improve the overall utilization rate of cluster resources.

[0147] Enhance automated operation and maintenance capabilities:

[0148] This includes reducing manual intervention and realizing the automation of IP address management. From conflict detection to problem solving, the whole process is automated as much as possible, reducing the workload of network administrators, improving operation and maintenance efficiency, and shortening the fault recovery time.

[0149] Improve system scalability and flexibility:

[0150] Facing the ever-changing number of nodes and distributed environments, the present invention aims to build a scalable IP address management system that can maintain good performance and management efficiency regardless of the growth of the cluster scale, and adapt to various complex network topologies and business requirements.

[0151] Promote service quality and user experience:

[0152] Ultimately, the present invention is committed to improving the quality of services and the user experience. By ensuring network continuity and response speed, reducing service interruptions or degradations caused by IP address conflicts, it improves user satisfaction and business continuity.

[0153] Strengthen security and compliance:

[0154] Proper IP address management helps to strengthen network security and avoid potential security vulnerabilities caused by IP address conflicts. At the same time, the present invention can help organizations comply with relevant network management regulations and standards, such as the usage specifications and best practices of IPv4 / IPv6.

[0155] The present invention not only solves the technical challenge of duplicate IP address conflicts in a distributed cluster, but also promotes the modernization of network operation and maintenance, supporting the high availability, high performance and intelligent operation and maintenance requirements in cloud computing and big data environments.

[0156] The above are only the preferred embodiments of the present invention, which are only used to illustrate the technical solutions of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are all included in the protection scope of the present invention.

Claims

1. A method for automatically detecting and resolving duplicate IP address conflicts in a distributed cluster, characterized in that: The following steps are involved: a) Use a hash table to store the mapping between each node’s IP address and node identifier; b) Maintain the consistency of hash table data among several IP address management service nodes through a distributed consistency algorithm; c) When a new node joins the cluster, it automatically assigns an unused IP address and updates the hash table; d) Perform network probing regularly to verify the uniqueness of IP addresses; e) If duplicate IP addresses are found, new IP addresses are reallocated through the IP address management service and the affected nodes are notified to update.

2. The method according to claim 1, characterized in that The distributed consensus algorithm is selected from Raft and Paxos; a master node election mechanism is implemented, the master node is responsible for managing the hash table, and the slave nodes periodically synchronize status with the master node.

3. The method according to claim 1, characterized in that The network detection uses ping, ARP request or TCP connection test to detect the reachability of each IP address; Conduct in-depth analysis of the detection results to identify IP addresses with abnormal responses. If several nodes respond to the same IP address, it is considered a conflict. When multiple responses are detected for the same IP address, the conflict detection algorithm is triggered to identify the conflicting nodes by comparing the records in the hash table with the detection results; Perform secondary verification on suspected conflicting IP addresses.

4. The method according to claim 1, characterized in that When a node leaves the cluster, its IP address is automatically reclaimed and the hash table is updated; the updated status is synchronized to all management service nodes through a distributed consistency algorithm to ensure the consistency of the global view.

5. The method according to claim 1, characterized in that The IP address management service includes one or more centralized service nodes for coordinating the allocation and recovery of IP addresses.

6. The method according to claim 1, characterized in that It also includes implementing secure access controls to allow only authorized nodes and management services to access and modify the hash table; Log IP address allocation, reclaiming, conflict detection, and resolution operations to support auditing and troubleshooting.

7. The method according to claim 1, characterized in that It also includes dynamic load balancing and resource optimization. The IP address management service adopts a dynamic load balancing strategy to automatically adjust traffic distribution according to the load of the current service instance; Monitor system resource usage and dynamically adjust the number and configuration of service instances based on resource usage.

8. The method according to claim 1, characterized in that It also includes providing a graphical user interface and API interface to facilitate administrators and automated tools to manage IP addresses.

9. The method according to claim 1, characterized in that: It also includes implementing regular stress testing and performance testing to verify the stability and performance of the system.

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