A distributed partition storage security method and system for carbon data of new energy trucks

Abstract

The application discloses a new energy truck carbon data distributed partition storage security method and system, belongs to the technical field of data storage, and comprises the following steps: partitioning new energy truck carbon data; monitoring access indexes of each partition and reporting to a central management node; intelligently analyzing based on a global view, determining hot data and triggering a dynamic cache mechanism when it is found that the access frequency of the partition exceeds a first access frequency threshold and the access source is concentrated in a first geographic area, automatically positioning a main storage node, obtaining a copy and caching the copy to one or more target edge nodes in the first geographic area; and automatically cleaning up the cached copy in the region when the access frequency of the partition falls to a second access frequency threshold and lasts for a cooling time. The application effectively solves the delay problem of cross-region access carbon data, realizes dynamic optimization and intelligent load balancing of network bandwidth, and improves the system resource utilization efficiency.

Description

Technical Field

[0001] This invention belongs to the field of data storage technology, specifically a distributed partitioned storage security method and system for carbon data of new energy freight vehicles. Background Technology

[0002] With the widespread adoption of new energy freight vehicles, the amount of carbon data generated during their operation has surged. This data is crucial for environmental regulation, carbon trading, and fleet management. Currently, centralized cloud storage or simple distributed storage solutions are commonly used. However, the former suffers from high latency and bandwidth costs when dealing with cross-regional data access; the latter lacks intelligent data scheduling capabilities and cannot dynamically optimize data layout based on access patterns, resulting in high access pressure and slow response in hotspot areas, while storage resources in non-hotspot areas remain idle. Therefore, there is an urgent need for a storage method that can intelligently sense access hotspots and dynamically adjust data distribution to achieve low latency, high throughput, and efficient resource utilization. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention proposes a distributed partitioned storage security method and system for carbon data of new energy freight vehicles. The method involves partitioning the carbon data of new energy freight vehicles; monitoring access indicators of each partition and reporting them to a central management node; and performing intelligent analysis based on a global view. When the access frequency of a partition exceeds a first access frequency threshold and the access sources are concentrated in a first geographical region, it is identified as hot data, triggering a dynamic caching mechanism. This automatically locates the main storage node, obtains a copy, and caches it to one or more target edge nodes within the first geographical region. When the access frequency of the partition drops to a second access frequency threshold and remains in a cooling-off period, the cached copies within the region are automatically cleared. This invention effectively solves the latency problem of cross-regional access to carbon data, achieves dynamic optimization of network bandwidth and intelligent load balancing, and improves system resource utilization efficiency.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A distributed partitioned storage security method for carbon data of new energy freight vehicles includes:

[0006] Carbon data of new energy trucks is partitioned according to preset rules and distributed across multiple edge nodes. Access indicators of each carbon data partition are monitored and reported to the central management node. The access indicators include access frequency and geographical location of the access source.

[0007] When the access frequency of the target carbon data partition exceeds a preset first access frequency threshold, and the geographical location of the access source is concentrated in a first geographical region, the target carbon data partition is determined to be hot data, and a dynamic caching mechanism is triggered.

[0008] After the dynamic caching mechanism is triggered, the central management node locates the current storage node of the hot data, obtains a data copy of the target carbon data partition, and caches it to one or more target edge nodes located in the first geographical region.

[0009] The central management node continuously monitors the access status of the cached target carbon data partition. When the access frequency of the target carbon data partition drops to a preset second access frequency threshold and continues for a preset cooling time, the cached copy of the target carbon data partition located in the first geographical area is deleted.

[0010] Specifically, the partitioning according to preset rules includes:

[0011] A composite partition key is constructed based on the vehicle identification number and latitude and longitude coordinates of the driving route of new energy trucks;

[0012] Input the composite partition key into the consistent hash ring to generate multiple virtual nodes;

[0013] Based on the mapping relationship between virtual nodes and edge nodes, carbon data of new energy trucks are allocated to the corresponding edge nodes to form multiple carbon data partitions;

[0014] The composite partition key is constructed by concatenating the string form of the vehicle identification code with the decimal values ​​converted from the latitude and longitude coordinates of the starting and ending points of the driving route, and then performing hash processing using the SHA-256 algorithm to obtain a composite partition key of fixed length.

[0015] Specifically, the distributed storage includes:

[0016] Generate a metadata block containing timestamps and partition identifiers for each carbon data partition;

[0017] The metadata block is split into segments using a threshold secret sharing algorithm. m Each subkey is distributed to m One edge node;

[0018] Set minimum recovery threshold k When accessing metadata, at least collect k Only one subkey is needed to reconstruct the complete metadata.

[0019] Specifically, the monitoring of access metrics for each carbon data partition and reporting them to the central management node includes:

[0020] Each access request to the locally stored carbon data partition is captured in real time by an access monitoring agent deployed at each edge node, and a structured access log is generated. The key fields of the structured access log include the access timestamp, the partition number of the requested data, the IP address of the access source, the access request type, and the access duration.

[0021] The access monitoring agent aggregates and analyzes the generated access logs according to a preset fixed time window, counts the access frequency of each carbon data partition, and calls the embedded IP geographic information database to parse the access source IP address and obtain its corresponding access source geographic location.

[0022] The access monitoring agent encapsulates the access frequency and access source geographic location of each carbon data partition obtained within the statistical period into a monitoring report data packet, and reports it to the central management node periodically through a secure communication channel established based on the TLS protocol.

[0023] The central management node receives and parses monitoring report data packets from all edge nodes, summarizes the access indicator data in the data packets, stores them in a time-series database, and generates a global access view.

[0024] Specifically, when the access frequency of the target carbon data partition exceeds a preset first access frequency threshold, and the geographical locations of the access sources are concentrated in a first geographical region, the target carbon data partition is determined to be hot data, triggering a dynamic caching mechanism, including:

[0025] The central management node scans each carbon data partition based on a global access view, applying a preset first access frequency threshold and a geographic concentration threshold.

[0026] When the access frequency of any target carbon data partition exceeds the first access frequency threshold, and the access request sources exceed the geographical concentration threshold and originate from the same provincial administrative region, the central management node determines the corresponding region as the first geographical region, marks the corresponding target carbon data partition as hot data, and generates a hot data marking event.

[0027] In response to the hot data marking event, the central management node generates a corresponding hot data caching instruction, adds the hot data caching instruction to a caching task queue, and triggers the caching scheduler to retrieve the hot data caching instruction from the caching task queue to perform the caching operation; the hot data caching instruction at least includes the target carbon data partition number and the first geographic region code.

[0028] Specifically, the central management node locates the current storage node for the hot data, including:

[0029] The cache scheduler retrieves the hot data cache instructions to be processed from the cache task queue and parses out the target carbon data partition number.

[0030] The central management node queries its maintained partition-node mapping table, retrieves the network address of the primary edge node storing the hot data copy based on the target carbon data partition number, generates a data copy retrieval request containing authentication information, and sends it to the primary edge node through a secure communication link; the data copy retrieval request includes the target carbon data partition number and authentication information.

[0031] Specifically, obtaining a data copy of the target carbon data partition and caching it to one or more target edge nodes located within the first geographical region includes:

[0032] After verifying the legitimacy of the data copy retrieval request, the primary edge node reads the complete data of the target carbon data partition from local storage, compresses and encrypts it to generate a data copy package;

[0033] The primary edge node transmits the data replica packet to the temporary storage area designated by the central management node and sends a replica ready notification to the central management node.

[0034] After receiving the replica ready notification and verifying the data integrity, the central management node parses the first geographic region code recorded in the hot data caching instruction, queries the edge node registry based on the first geographic region code, filters out edge nodes located in the first geographic region that have current computing and network loads below a preset load threshold, and determines them as target edge nodes.

[0035] The central management node distributes data copy packets in the temporary storage area to one or more selected target edge nodes for caching via the content delivery network. After distribution, the central management node updates the partition cache mapping table to record the new cache relationship between the target carbon data partition and the target edge node.

[0036] Specifically, the central management node continuously monitors the access status of the cached target carbon data partition. When the access frequency of the target carbon data partition drops to a preset second access frequency threshold and remains there for a preset cooling time, the cached copy of the target carbon data partition located in the first geographical area is deleted, including:

[0037] Once the target carbon data partition is successfully cached to the target edge node within the first geographic region, the central management node creates a partition cache monitoring instance for the target carbon data partition. The partition cache monitoring instance receives access statistics about the target carbon data partition from the target edge node within the first geographic region. At the same time, the central management node sets a second access frequency threshold and a cooldown time for the partition cache monitoring instance, wherein the second access frequency threshold is less than the first access frequency threshold when caching is triggered.

[0038] The partition cache monitoring instance calculates the average access frequency of the target carbon data partition within a sliding time window in real time based on the received access statistics. The partition cache monitoring instance continuously determines whether the average access frequency has fallen below the second access frequency threshold. Once the average access frequency is detected to be below the second access frequency threshold, the partition cache monitoring instance starts a cooling timer. If the average access frequency remains below the second access frequency threshold for a continuous cooling period, it is determined that the target carbon data partition has changed from hot data to cold data, and a cache reclamation trigger event is generated.

[0039] In response to the cache reclamation trigger event, the central management node sends a cache copy deletion instruction to all target edge nodes of cache copies in the first geographic region according to the partition cache mapping table. After verifying the legality of the instruction, each target edge node deletes its local cache copy and sends a deletion confirmation message to the central management node.

[0040] After receiving deletion confirmation messages from all target edge nodes, the central management node updates the partition cache mapping table and removes the cache association between the corresponding target carbon data partition and the target edge node.

[0041] Specifically, before deleting the cache copy, a data consistency verification step is also included: the central management node compares the hash value of the cache copy with the hash value of the data currently stored on the main edge node; when the hash values ​​are inconsistent, the updated data is synchronized to all cache nodes first before deletion is performed.

[0042] A distributed partitioned storage security system for carbon data of new energy freight vehicles includes: a data partitioning module, an access monitoring module, a cache decision module, a cache distribution module, and a cache management module;

[0043] The data partitioning module is used to perform partitioning and manage the distributed storage of carbon data for new energy trucks in the edge node cluster.

[0044] The access monitoring module is used to collect access behavior data of each carbon data partition in real time and aggregate it to the central management node.

[0045] The cache decision module is used to analyze access behavior data, identify hot data, and trigger a dynamic caching mechanism from the global perspective of the central management node.

[0046] The cache distribution module is used to perform cache distribution tasks and push hot data copies to target edge nodes;

[0047] The cache management module is used to continuously monitor cached hot data copies and manage their lifecycle, including cooling judgment and resource reclamation.

[0048] Compared with the prior art, the beneficial effects of the present invention are:

[0049] This invention proposes a distributed partitioned storage security system for carbon data of new energy freight vehicles, and optimizes and improves its architecture, operation steps and processes. The system has the advantages of simple process, low investment and operation costs and low production and working costs.

[0050] This invention proposes a distributed partitioned storage security method for carbon data of new energy freight vehicles. By introducing a hot data intelligent identification mechanism based on access frequency and geographical concentration, and combining it with geographic awareness dynamic caching technology, this invention can accurately predict and respond to regional data access hotspots. Its core beneficial effect is that it automatically and quickly migrates high-frequency access hot data to edge nodes within the geographical area where the access sources are concentrated, thereby reducing the transmission distance and network hops of data requests, effectively reducing data access latency, and improving user query response speed.

[0051] This invention proposes a distributed partitioned storage security method for carbon data of new energy freight vehicles. This invention realizes refined and automated lifecycle management of cached resources. The system continuously monitors the access status of cached data. When the data's popularity fades, the cache reclamation process is automatically triggered to release the storage resources of edge nodes in a timely manner. This on-demand caching and timely release mode avoids the resource waste caused by static caching strategies and realizes dynamic optimization and efficient utilization of network bandwidth and storage space, thereby improving the resource elasticity and scalability of the distributed storage system as a whole. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of a distributed partitioned storage security method for carbon data of new energy freight vehicles according to the present invention;

[0053] Figure 2 This is a flowchart illustrating the principle of a distributed partitioned storage security method for carbon data of new energy freight vehicles according to the present invention.

[0054] Figure 3 This is a diagram of a distributed partitioned storage security system architecture for carbon data of new energy freight vehicles according to the present invention. Detailed Implementation

[0055] Example 1:

[0056] Please see Figure 1 and Figure 2 The present invention provides an embodiment of a distributed partitioned storage security method for carbon data of new energy freight vehicles, the method comprising S1~S4, including the following steps:

[0057] S1: The carbon data of new energy trucks is partitioned according to preset rules and distributed across multiple edge nodes. The access indicators of each carbon data partition are monitored and reported to the central management node. The access indicators include access frequency and geographical location of the access source.

[0058] Furthermore, the monitoring of access metrics for each carbon data partition includes: deploying a lightweight monitoring agent on each edge node to collect access logs in real time; calculating the access frequency of each carbon data partition through a sliding time window; and using an IP geolocation database to parse the actual physical location of the access source.

[0059] S2: When the access frequency of the target carbon data partition exceeds the preset first access frequency threshold, and the geographical location of the access source is concentrated in the first geographical region, the target carbon data partition is determined to be hot data, and the dynamic caching mechanism is triggered.

[0060] S3: After the dynamic caching mechanism is triggered, the central management node locates the current storage node of the hot data, obtains a data copy of the target carbon data partition, and caches it to one or more target edge nodes located in the first geographical area;

[0061] S4: The central management node continuously monitors the access status of the cached target carbon data partition. When the access frequency of the target carbon data partition drops to a preset second access frequency threshold and continues for a preset cooling time, the cached copy of the target carbon data partition located in the first geographical area is deleted.

[0062] Before deleting a cache copy, a data consistency verification step is also included: the central management node compares the hash value of the cache copy with the hash value of the data currently stored on the main edge node; when the hash values ​​are inconsistent, the updated data is synchronized to all cache nodes first before deletion is performed.

[0063] The partitioning according to preset rules includes:

[0064] A1: Construct a composite partition key based on the vehicle identification code and latitude and longitude coordinates of the driving route of new energy freight vehicles;

[0065] The composite partition key is constructed as follows: the string form of the vehicle identification code is concatenated with the decimal values ​​of the latitude and longitude coordinates of the starting and ending points of the driving route, and then hashed using the SHA-256 algorithm to obtain a composite partition key of fixed length. The SHA-256 algorithm is existing technology in this field and is not an inventive solution of this application, so it will not be described in detail here.

[0066] Furthermore, composite partition keys are typically composed of multiple fields with business significance, such as the last four characters of a vehicle identification number combined with the month number of the data collection date. The system extracts the values ​​of predefined fields from the data records and concatenates these values ​​into a complete string according to a strictly agreed-upon order and delimiter. For example, for a record with a vehicle identification number ending in 5678 and data collected in December, its composite partition key is constructed as the string 5678-12. The string formed by this concatenation is the original input for hash calculation. At the same time, to ensure the uniformity of hash calculation, the key is sometimes pre-normalized, for example, by converting all characters to uniform uppercase and lowercase.

[0067] A2: Input the composite partition key into the consistent hash ring to generate multiple virtual nodes;

[0068] Furthermore, a consistent hash ring is an abstract circular space ranging from zero to 2^n. n The range from zero to 2 to the power of 64 minus 1 forms a closed loop.

[0069] Furthermore, the specific steps of A2 include:

[0070] (1) Apply SHA-256 to the string of the composite partition key. The SHA-256 hash function converts the variable-length input string into a binary sequence of fixed length, which is the main hash value corresponding to the composite partition key. At the same time, a derivation strategy is used to generate a set of related but different hash values. For example, an index number or counter is introduced. Specifically, the system derives multiple different identifiers for the same composite partition key. For example, the numerical index zero, index one, index two, and so on are appended to the original composite partition key string in sequence until index N minus one, where N is the number of virtual nodes to be generated for each physical partition. Then, for each derived new string, i.e. composite partition key plus index zero, composite partition key plus index one, the same hash function is applied independently to calculate, so as to obtain N different hash values ​​that originate from the same composite partition key.

[0071] (2) Map the generated set of hash values ​​onto a consistent hash ring, where each hash value is a very large number. The system maps this hash value to the total size of the consistent hash ring, i.e. The modulo operation is performed to obtain an integer value that falls at any position on the ring. This position point represents a virtual node. Each hash value derived from the composite partition key is assigned a unique and specific coordinate position on the ring after the modulo operation. Therefore, a composite partition key eventually occupies N such coordinate points on the consistent hash ring. These N points are the N virtual nodes representing the data partition.

[0072] A3: Based on the mapping relationship between virtual nodes and edge nodes, the carbon data of new energy trucks is allocated to the corresponding edge nodes to form multiple carbon data partitions.

[0073] Furthermore, the specific steps in A3 include:

[0074] (1) After locating the target virtual node, query the virtual node-physical edge node mapping table that the system has established and maintained in advance. Through the virtual node-physical edge node mapping table, find the target physical edge node that uniquely corresponds to the target virtual node. This target physical edge node is the final physical location where the data record is specified to be stored.

[0075] (2) The system encapsulates the complete carbon data record of new energy trucks into a data packet and routes it to the determined target physical edge node through the network. After receiving the data packet, the target physical edge node parses and verifies it, and finally writes the data record into the corresponding carbon data partition logical unit in the local storage according to its composite partition key.

[0076] (3) Iterative repetition is performed, and each complete carbon data record of new energy truck is precisely routed and stored in a specific carbon data partition on the designated target physical edge node according to its composite partition key. Multiple carbon data partitions with complete data record sets and clear logical boundaries are formed on each edge node, thereby completing the construction of the distributed data storage structure.

[0077] The distributed storage includes:

[0078] B1: Generate a metadata block containing timestamps and partition identifiers for each carbon data partition;

[0079] B2: Use a threshold secret sharing algorithm to split the metadata block into... m Each subkey is distributed to m The edge nodes, wherein the threshold secret sharing algorithm is existing technology in this field and is not an inventive solution of this application, and will not be described in detail here;

[0080] B3: Set the minimum recovery threshold k When access to metadata is required, at least collect k Only one subkey is needed to reconstruct the complete metadata.

[0081] The monitoring of access metrics for each carbon data partition and the reporting to the central management node includes:

[0082] C1: Capture every access request to the locally stored carbon data partition in real time by deploying an access monitoring agent at each edge node, and generate a structured access log; the key fields of the structured access log include access timestamp, partition number of the requested data, IP address of the access source, access request type, and access duration;

[0083] C2: The access monitoring agent aggregates and analyzes the generated access logs according to a preset fixed time window, counts the access frequency of each carbon data partition, and calls the embedded IP geographic information database to parse the access source IP address and obtain its corresponding access source geographic location.

[0084] Furthermore, the fixed time window duration is 1-5 minutes, and it supports dynamic adjustment based on the access request volume of edge nodes; the greater the access request volume, the shorter the time window duration.

[0085] Furthermore, the specific steps of C2 include:

[0086] (1) The access monitoring agent runs continuously, and stores the details of each access request received as a raw record in the buffer. When the preset fixed time window ends, the access monitoring agent immediately locks the current buffer, marks its contents as a complete batch of logs to be processed, and at the same time enables a new empty buffer to accept subsequent requests, ensuring uninterrupted monitoring.

[0087] Furthermore, a buffer can be understood as a list arranged in chronological order.

[0088] (2) The access monitoring agent scans each record in the batch of logs to be processed, sorts and classifies them according to the carbon data partition number contained in the record, and reorganizes the messy original log stream into multiple independent partition access record sets based on partitions. Each set contains all access records of the same partition within the time window.

[0089] (3) The access monitoring agent processes each partition access record set one by one. By counting the total number of access records contained in a specific set, the partition access frequency in the current time window is directly calculated. This frequency is the total number of times the partition is accessed in this time period.

[0090] (4) For the same set of access records in a partition, the access monitoring agent extracts the access source IP address one by one. For each extracted IP address, the access monitoring agent calls the embedded IP geographic information database to query and parse the corresponding provincial administrative level geographic location information. Then, the access monitoring agent counts the geographic location parsing results of all access records in the set, identifies the geographic location that appears most often, and determines it as the main access source geographic location of the partition.

[0091] C3: The access monitoring agent encapsulates the access frequency and access source geographical location of each carbon data partition obtained within the statistical period into a monitoring report data packet, and reports it to the central management node on a regular basis through a secure communication channel established based on the TLS protocol.

[0092] Furthermore, the specific steps of C3 include:

[0093] (1) The access monitoring agent converts the access frequency and main access source geographical location information of each carbon data partition obtained within the statistical period from the data structure in memory into a standardized format suitable for network transmission. This process is serialization, and the data block obtained after serialization is the serialized report data.

[0094] (2) The access monitoring agent uses a hash algorithm to calculate the obtained serialized report data and generate a data integrity check code. Then, the serialized report data and the data integrity check code are combined, and a packet header containing information such as version number, edge node identifier, and timestamp is added to its header to construct a complete monitoring report data packet.

[0095] (3) Before sending the monitoring report data packet, the access monitoring agent and the central management node perform two-way identity authentication based on certificates. After the authentication is successful, the two parties negotiate to generate a temporary session key and establish an encrypted secure communication channel based on the transport layer security protocol.

[0096] (4) The access monitoring agent sends the monitoring report data packet to the central management node through the established secure communication channel. The access monitoring agent waits for and receives the delivery confirmation signal returned by the central management node. If the delivery confirmation signal is received, the reporting is considered successful; if it is not received within the time limit, the retransmission mechanism is triggered.

[0097] (5) After successfully receiving the delivery confirmation signal, the access monitoring agent determines that the reporting task is completed. Subsequently, the access monitoring agent cleans up the original data of the reported monitoring reports corresponding to this statistical period and related temporary cache stored locally, releases system resources, and prepares for the monitoring work of the next statistical period.

[0098] C4: The central management node receives and parses monitoring report data packets from all edge nodes, summarizes the access indicator data in the data packets, stores them in the time series database, and generates a global access view.

[0099] Furthermore, the specific steps of C4 include:

[0100] (1) The central management node continuously listens to the network port and waits for connections from various edge nodes. When the access monitoring agent initiates a connection and transmits data, the central management node receives the monitoring report data packet from the edge node and immediately performs a preliminary verification, including verifying the compliance of the basic format of the data packet and the legitimacy of the sending node's identity. Data packets that pass the verification are confirmed as data packets to be processed.

[0101] (2) The central management node decrypts the data packets to be processed to restore the original binary or text data. Then, the central management node parses the decrypted data according to the predefined structure and separates the data packet header information, serialized report content and additional original check code from it.

[0102] (3) The central management node uses the agreed hash algorithm to independently calculate the parsed serialized report content and generate a local check code. This local check code is compared with the parsed original check code. If the two are consistent, the data is determined to be complete and the serialized report content is regarded as valid report data.

[0103] (4) The central management node performs deserialization on the valid report data, converts it into an internal data structure, and extracts the core access indicator data such as the partition identifier, partition access frequency and the geographical location of the main access source for each carbon data partition from the internal data structure.

[0104] (5) The central management node will write all the access indicator data extracted in step four, along with the corresponding timestamp information, into the time series database for persistent storage in batches.

[0105] (6) Based on the latest time window, the central management node aggregates the access indicator data reported by all edge nodes from the time series database, summarizes and analyzes the data by partition identifier, generates a global access heat and geographical distribution profile for each partition, and finally synthesizes a unified global access view that reflects the overall access status of the system in real time.

[0106] When the access frequency of the target carbon data partition exceeds a preset first access frequency threshold, and the geographical locations of the access sources are concentrated in a first geographical region, the target carbon data partition is determined to be hot data, triggering a dynamic caching mechanism, including:

[0107] S2.1: The central management node scans each carbon data partition based on the global access view, applying a preset first access frequency threshold and geographic concentration threshold.

[0108] S2.2: When the access frequency of any target carbon data partition exceeds the first access frequency threshold, and the access request sources exceed the geographical concentration threshold and originate from the same provincial administrative region, the central management node determines the corresponding region as the first geographical region, marks the corresponding target carbon data partition as hot data, and generates a hot data marking event.

[0109] Furthermore, the geographical concentration threshold ranges from 60% to 80%, and can be customized based on the access distribution characteristics of carbon data in actual application scenarios.

[0110] Furthermore, the specific steps of S2.2 include:

[0111] (1) The central management node loads the preset judgment thresholds, including the first access frequency threshold for judging the access frequency and the geographical concentration threshold for judging the geographical concentration. After the judgment thresholds are loaded, the central management node starts the scanning process and reads the access status record of each carbon data partition from the newly generated global access view in turn, in preparation for condition judgment.

[0112] (2) For the target carbon data partition currently being scanned, the central management node compares the access frequency value recorded in its record with the first access frequency threshold loaded in the first step. If the access frequency value of the target carbon data partition is less than or equal to the first access frequency threshold, it is determined that it does not meet the access frequency condition. The central management node will stop the current scan of the target carbon data partition and continue to scan the next target carbon data partition in the global access view. Only when the access frequency value of the target carbon data partition is confirmed to be greater than the first access frequency threshold will the first condition be met, and the scanning process will enter the next judgment stage.

[0113] (3) After confirming that the target carbon data partition meets the access frequency conditions, the central management node begins to analyze the geographical distribution of its access sources. The central management node reads the geographical location information of the main access sources in the target carbon data partition record and counts the proportion of all access requests from the geographical location to the total access requests of the target carbon data partition. Then, the node compares this calculated actual proportion with the geographical concentration threshold loaded in the first step.

[0114] (4) If the calculated actual ratio is greater than or equal to the geographic concentration threshold, it is determined that the access source of the target carbon data partition is highly concentrated in a provincial administrative region. At this time, the central management node officially determines the provincial administrative region as the first geographic region corresponding to this hot data, and the node marks the status of the target carbon data partition as hot data.

[0115] (5) After completing the hot data determination and confirming the first geographic region, the central management node transforms this determination result into an internal system event. The central management node generates a structured hot data tagging event object, which explicitly contains three core pieces of information: the unique identifier of the target carbon data partition that is tagged as hot data, the code of the determined first geographic region, and the timestamp of the event trigger. The generation of this hot data tagging event marks the completion of the determination logic;

[0116] (6) The generated hot data tag event is immediately distributed to the system’s internal event bus or message queue. This distribution action formally announces to the entire system that a new hot data has been identified. The cache scheduler component, which is specifically responsible for handling cache logic, will continuously listen for such events. Once it receives this hot data tag event, it will immediately start dynamic caching.

[0117] S2.3: In response to the hot data marking event, the central management node generates a corresponding hot data caching instruction, adds the hot data caching instruction to a caching task queue, and immediately triggers the caching scheduler to retrieve the hot data caching instruction from the caching task queue to perform the caching operation; the hot data caching instruction at least includes the target carbon data partition number and the first geographic region code.

[0118] Furthermore, the cache task queue adopts a priority sorting mechanism. The higher the proportion of hot data access frequency exceeding the first access frequency threshold, the higher the priority of the corresponding hot data cache instruction.

[0119] Furthermore, the specific steps in S2.3 include:

[0120] (1) The first input received by the component responsible for handling events inside the central management node is the hot data tag event. The component will parse this event object and extract the core judgment result information from it, mainly including the unique number of the target carbon data partition that is judged as hot data, and the code of the first geographical area where the access requests are highly concentrated.

[0121] (2) Based on the parsed target carbon data partition number and first geographic region code, the central management node starts to create a new hot data cache instruction. This hot data cache instruction not only contains the target carbon data partition number and first geographic region code, but also automatically adds some management information, such as the unique serial number generated by the instruction, the timestamp, and the initial state identifier. This hot data cache instruction fully defines the specific cache task to be executed next.

[0122] (3) The system sends the hot data caching instruction to a dedicated cache task queue. The cache task queue sorts and buffers the structured hot data caching instructions according to the first-in-first-out principle. The operation of adding the hot data caching instruction to the cache task queue means that the cache task has been officially accepted by the system and is waiting to be scheduled for execution.

[0123] (4) After the hot data caching instruction is successfully added to the cache task queue, the system needs to notify the component responsible for executing the task to pick up the task. At this time, the system sends a wake-up or notification signal to the dedicated cache scheduler component. The purpose of this wake-up or notification signal is to inform the cache scheduler, which has been in a standby state, that there is a new task waiting to be processed in the cache task queue.

[0124] (5) Once triggered, the cache scheduler starts working. It first accesses the cache task queue and requests the next task to be processed from the cache task queue. The cache task queue retrieves the earliest added hot data cache instruction according to the sorting rules and delivers it to the cache scheduler.

[0125] (6) The cache scheduler starts a complete cache operation execution process based on the target carbon data partition number and the first geographic region code contained in the obtained hot data cache instruction.

[0126] The central management node locates the current storage node for hot data, including:

[0127] D1: The cache scheduler retrieves the hot data cache instructions to be processed from the cache task queue and parses out the target carbon data partition number;

[0128] Furthermore, the specific steps of D1 include:

[0129] (1) After the cache scheduler is triggered, it sends a request to the system's cache task queue to retrieve a task;

[0130] (2) The cache task queue responds to this request by returning the next hot data cache instruction to be processed in the cache task queue to the cache scheduler. The cache scheduler successfully receives the hot data cache instruction object.

[0131] (3) The cache scheduler parses the structure of the received hot data cache instruction object. According to the predefined instruction format, the cache scheduler locates and reads the specific field in the instruction that stores the target carbon data partition number, thereby obtaining the value of the number.

[0132] (4) After extracting the target carbon data partition number, the cache scheduler continues to parse the same hot data cache instruction object, locates and reads the field storing the first geographic region code in the instruction, and thus obtains the identifier value of the geographic region.

[0133] (5) The cache scheduler outputs the target carbon data partition number and the first geographic region code as core parameters. These two parameters are the final results of the instruction parsing step.

[0134] D2: The central management node queries the partition-node mapping table it maintains, retrieves the network address of the main edge node storing the hot data copy based on the target carbon data partition number, generates a data copy retrieval request containing authentication information, and sends it to the main edge node through a secure communication link; the data copy retrieval request includes the target carbon data partition number and authentication information.

[0135] Furthermore, the specific steps of D2 include:

[0136] (1) The central management node uses the target carbon data partition number as the query key to retrieve the partition-node mapping table it maintains. Through this query, the network address of the main edge node storing the data copy of the partition is obtained.

[0137] (2) The central management node creates a data replica to obtain the data structure of the request. The core fields of the data structure include the target carbon data partition number and the authentication information used to verify the legitimacy of the requester.

[0138] (3) The central management node uses the network address of the main edge node to initiate and complete an encrypted session negotiation based on certificate two-way authentication, and establishes a secure communication link to the main edge node.

[0139] (4) The central management node sends the generated data copy acquisition request to the main edge node through the established secure communication link and waits for the other party to receive the confirmation.

[0140] The step of obtaining a data copy of the target carbon data partition and caching it to one or more target edge nodes located within the first geographic region includes:

[0141] E1: After verifying the validity of the data replica acquisition request, the primary edge node reads the complete data of the target carbon data partition from local storage, compresses and encrypts it to generate a data replica package;

[0142] Furthermore, the compression process uses the LZ4 compression algorithm, the encryption process uses the AES-256 encryption algorithm, and the integrity of the data copy packet is guaranteed by SHA-512 hash verification. The LZ4 compression algorithm, AES-256 encryption algorithm, and SHA-512 hash algorithm are existing technologies in this field and are not inventive solutions of this application, and will not be described in detail here.

[0143] E2: The primary edge node transmits the data replica packet to the temporary storage area designated by the central management node and sends a replica ready notification to the central management node;

[0144] Furthermore, the specific steps of E2 include:

[0145] (1) The main edge node establishes a data transmission connection with the temporary storage area specified by the central management node according to the received instructions. After the connection is established, the main edge node uploads the locally generated data copy packets to the temporary storage area through the connection.

[0146] (2) After the data replica package is uploaded, the main edge node calculates the check value of the data replica package in the temporary storage area and compares it with the original check value of the local data replica package. After verification, it is confirmed that the data has been uploaded completely.

[0147] (3) After confirming that the data has been uploaded completely, the primary edge node generates a replica ready notification. The replica ready notification includes the target carbon data partition number and the access path of the data replica package in the temporary storage area. The primary edge node sends this notification to the central management node.

[0148] E3: After receiving the replica ready notification and verifying the data integrity, the central management node parses the first geographic region code recorded in the hot data cache instruction, queries the edge node registry based on the first geographic region code, filters out edge nodes located in the first geographic region whose current computing and network load is lower than the preset load threshold, and determines them as target edge nodes.

[0149] Furthermore, the preset load threshold is 70% of the maximum computing load and 60% of the maximum network load of the edge node. When either the computing load or the network load of the edge node reaches the load threshold, it will not be listed as a target edge node.

[0150] Furthermore, the specific steps of E3 include:

[0151] (1) After confirming that the data is ready, the central management node parses the hot data caching instruction that triggers this caching task and extracts the code of the first geographic region from it;

[0152] (2) The central management node uses the edge node registry it maintains as the query target, and uses the first geographic region code extracted in the first step as the key query condition to filter out all edge nodes located in the geographic region and form an initial node set.

[0153] (3) The central management node initiates a status query to each edge node in the initial node set to collect its current real-time load indicators, including the usage of computing resources and network resources;

[0154] (4) The central management node compares the real-time load indicators of each node with the preset load threshold and filters out nodes whose load indicators are all lower than the load threshold. These nodes constitute a qualified node set.

[0155] (5) The central management node summarizes the node identifiers in the qualified node set and generates the final target edge node list.

[0156] E4: The central management node distributes data copy packets in the temporary storage area to one or more selected target edge nodes for caching through the content delivery network. After the distribution is completed, the central management node updates the partition cache mapping table and records the new cache relationship between the target carbon data partition and the target edge node.

[0157] Furthermore, the specific steps of E4 include:

[0158] (1) The central management node submits a distribution instruction to the content delivery network. The distribution instruction includes the path of the data replica package in the temporary storage area and the list of target edge nodes. The content delivery network distributes the data replica package in parallel to all target edge nodes in the list of target edge nodes according to the distribution instruction.

[0159] (2) After the content delivery network completes the data distribution to all target edge nodes in the target edge node list, it returns a distribution success confirmation signal to the central management node;

[0160] (3) After receiving the distribution success confirmation signal, the central management node creates or updates a cache record for the target carbon data partition in the partition cache mapping table it maintains. The cache record clearly records the mapping relationship between the partition and the target edge node list that successfully cached it this time.

[0161] (4) After confirming that the partition cache mapping table has been successfully updated, the central management node instructs the temporary storage area to delete the distributed data copy packets and release storage resources.

[0162] The central management node continuously monitors the access status of the cached target carbon data partition. When the access frequency of the target carbon data partition drops to a preset second access frequency threshold and continues for a preset cooling time, the cached copy of the target carbon data partition located in the first geographical area is deleted, including:

[0163] S4.1: After the target carbon data partition is successfully cached to the target edge node in the first geographic region, the central management node creates a dedicated partition cache monitoring instance for the target carbon data partition. The partition cache monitoring instance receives access statistics about the target carbon data partition from the target edge node in the first geographic region. At the same time, the central management node sets a second access frequency threshold and a cooldown time for the partition cache monitoring instance, wherein the second access frequency threshold is less than the first access frequency threshold when caching is triggered.

[0164] Furthermore, the cooling time ranges from 30 minutes to 2 hours and can be dynamically adjusted according to the continuous periodic characteristics of the thermal data of carbon data.

[0165] Furthermore, the specific steps of S4.1 include:

[0166] (1) Once it is confirmed that the target carbon data partition has been successfully cached to the target edge node in the first geographic region, the central management node will dynamically create a dedicated partition cache monitoring instance for the partition.

[0167] Furthermore, the sole responsibility of a partition cache monitoring instance is to monitor access behavior of the partition in cached state. After the partition cache monitoring instance is created, the system strongly binds the partition cache monitoring instance to the unique identifier of the target carbon data partition to ensure that all monitoring data can be correctly routed to this partition cache monitoring instance for processing.

[0168] (2) The central management node publishes a routing rule to all edge nodes in the first geographic region. This routing rule instructs any access statistics report on this specific target carbon data partition to be sent to the newly created partition cache monitoring instance in addition to the global aggregator of the central management node when reporting.

[0169] (3) The central management node sets monitoring parameters for the newly created partition cache monitoring instance, including the second access frequency threshold and the cooldown time, wherein the second access frequency threshold is less than the first access frequency threshold used when the cache is triggered;

[0170] (4) The central management node is configured with data routing so that all access statistics information about the target carbon data partition reported by all edge nodes in the first geographic area are directed to the cache monitoring instance of that partition;

[0171] (5) After completing the parameter settings and data channel configuration, the central management node activates the partition cache monitoring instance. The partition cache monitoring instance starts to continuously receive access statistics information and makes monitoring logic judgments based on the second access frequency threshold and cooldown time.

[0172] S4.2: Based on the received access statistics, the partition cache monitoring instance calculates the average access frequency of the target carbon data partition in real time within a sliding time window. The partition cache monitoring instance continuously determines whether the average access frequency has fallen below the second access frequency threshold. Once the average access frequency is detected to be lower than the second access frequency threshold, the partition cache monitoring instance starts a cooling timer. If the average access frequency remains below the second access frequency threshold during the continuous cooling time, it is determined that the target carbon data partition has changed from hot data to cold data, and a cache reclamation trigger event is generated.

[0173] Furthermore, the specific steps in S4.2 include:

[0174] (1) The partition cache monitoring instance calculates the average access frequency of the target carbon data partition in a sliding time window in real time based on the access statistics it continuously receives from edge nodes in the first geographic region;

[0175] (2) The partition cache monitoring instance continuously compares the calculated average access frequency with the preset second access frequency threshold to determine whether it has fallen below the threshold.

[0176] (3) When the average access frequency is detected to be lower than the second access frequency threshold for the first time, the partition cache monitoring instance immediately starts a cooling timer, the duration of which is set to a preset cooling time;

[0177] (4) During the entire cooling time when the cooling timer is running, the partition cache monitoring instance continues to calculate and compare the average access frequency;

[0178] If the average access frequency rises to or exceeds the second access frequency threshold at any time during this period, the cooldown timer will be immediately reset and the system will return to continuous monitoring status.

[0179] If the cooling timer continues to run until the cooling time is reached, and the average access frequency is always lower than the second access frequency threshold throughout the entire cooling time, then the partition is determined to have become cold data.

[0180] (5) Once the cooling conditions are met, the partition cache monitoring instance generates a cache recycling trigger event and sends the event to the central management node.

[0181] S4.3: In response to the cache reclamation trigger event, the central management node sends a secure cache copy deletion command to all target edge nodes of cache copies in the first geographical region according to the partition cache mapping table. After verifying the legality of the command, each target edge node deletes its local cache copy and sends a deletion confirmation message to the central management node.

[0182] Furthermore, the specific steps of S4.3 include:

[0183] (1) In response to the cache recycling trigger event, the central management node parses out the target carbon data partition number and queries the partition cache mapping table to obtain a list of all target edge nodes that have cached a copy of the partition in the first geographic region;

[0184] (2) For each node in the target edge node list, the central management node generates a secure deletion instruction containing the target carbon data partition number and digitally signed, and sends it to each target edge node through a secure channel;

[0185] (3) After receiving the security deletion instruction, the target edge node verifies the legality of its digital signature. After the verification is successful, the node locates and deletes the corresponding data cache copy stored locally according to the target carbon data partition number in the instruction.

[0186] (4) After successfully deleting the local cache copy, the target edge node sends a signed deletion confirmation message to the central management node;

[0187] (5) After receiving the deletion confirmation message from the target edge node, the central management node updates the cache record of the target carbon data partition in the partition cache mapping table and removes the node information that has returned the deletion confirmation message.

[0188] S4.4: After receiving the deletion confirmation messages from all target edge nodes, the central management node updates the partition cache mapping table and removes the cache association between the corresponding target carbon data partition and the target edge node.

[0189] Example 2:

[0190] Please see Figure 3 Another embodiment of the present invention provides: a distributed partitioned storage security system for carbon data of new energy freight vehicles, comprising:

[0191] Data partitioning module, access monitoring module, cache decision module, cache distribution module, cache management module;

[0192] The data partitioning module is used to partition data and manage the distributed storage of carbon data for new energy trucks in the edge node cluster.

[0193] The access monitoring module is used to collect access behavior data for each carbon data partition in real time and aggregate it to the central management node;

[0194] The caching decision module is used to analyze access behavior data, identify hot data, and trigger dynamic caching mechanisms from the global perspective of the central management node.

[0195] The cache distribution module is used to perform cache distribution tasks, efficiently and securely pushing hot data copies to the target edge nodes;

[0196] The cache management module is used to continuously monitor cached hot data copies and manage their lifecycle, including cooling judgment and resource reclamation.

[0197] The data partitioning module includes: a data partitioning unit, a node mapping management unit, and a storage engine unit;

[0198] Data partitioning unit, used to calculate and assign a unique partition number to all carbon data of new energy trucks;

[0199] The node mapping management unit is used to create and maintain a partition-node mapping table, recording the primary edge node and backup edge node of each carbon data partition, so as to achieve precise location of data storage.

[0200] The storage engine unit, deployed on each edge node, is responsible for persistently storing the carbon data partitions allocated to the node locally and handling local data read and write requests.

[0201] The cache decision module includes: a global view synthesis unit, a hot data determination unit, and a cache scheduler unit;

[0202] The global view synthesis unit is used to receive and integrate monitoring reports from all edge nodes to generate a global access view of carbon data partitions, comprehensively displaying the real-time access popularity and geographical distribution of each partition.

[0203] The hot data determination unit is used to load the preset first access frequency threshold and geographic concentration threshold, continuously scan the global access view, and generate a hot data tag event when the partition meets the hot data conditions.

[0204] The cache scheduler unit is used to generate a hot data cache instruction containing the target carbon data partition number and the first geographic region code in response to the hot data tagging event, and put it into the cache task queue.

[0205] The cache distribution module includes: a data replica preparation unit, a target node filtering unit, a content distribution unit, and a cache management unit;

[0206] The data copy preparation unit is responsible for interacting with the main edge node, verifying the request, reading, compressing, and encrypting the target carbon data partition data, generating a secure data copy package, and temporarily storing it in the temporary storage area.

[0207] The target node filtering unit is used to query the edge node registry based on the geographical region in the hot data caching instruction and filter the optimal list of target edge nodes based on the load.

[0208] The content distribution unit is used to efficiently and reliably distribute data replica packets to all edge nodes in the target edge node list through the content distribution network;

[0209] The cache management unit is used to update the partition cache mapping table after successful distribution, record the new cache relationship, and ensure that the system can perceive the latest location of the data.

[0210] The cache management module includes: a monitoring instance unit, a cooling-off determination unit, and a recycling execution unit;

[0211] The monitoring instance unit is used to create a partition cache monitoring instance for each cached target carbon data partition and continuously track its average access frequency within the target geographic area.

[0212] The cooling determination unit is used to load a preset second access frequency threshold and cooling time. When the partition cache monitoring instance detects that the average access frequency is continuously lower than the second access frequency threshold, it generates a cache reclamation trigger event.

[0213] The recycling execution unit is used to respond to the cache recycling trigger event, send a cache replica deletion instruction to the relevant edge nodes, confirm the copy deletion, and then notify the cache metadata management unit to update the partition cache mapping table to complete the resource release.

[0214] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments under the guidance of the present invention without departing from the spirit and scope of the present invention. All of these variations are within the protection scope of the present invention.

Claims

1. A distributed partition storage security method for new energy truck carbon data, characterized in that, The application comprises the following steps: The carbon data of new energy trucks is divided into partitions according to preset rules, and is stored in multiple edge nodes in a distributed manner. Access indicators of each carbon data partition are monitored and reported to a central management node. The access indicators include access frequency and access source geographical location. When the access frequency of a target carbon data partition exceeds a preset first access frequency threshold, and the access source geographical location is concentrated in a first geographical area, the target carbon data partition is determined to be hot data, and a dynamic caching mechanism is triggered. After the dynamic caching mechanism is triggered, the central management node locates the current storage node of the hot data, obtains a data copy of the target carbon data partition, and caches it to one or more target edge nodes located in the first geographical area. The central management node continuously monitors the access state of the cached target carbon data partition. When the access frequency of the target carbon data partition falls below a preset second access frequency threshold and lasts for a preset cooling time, the cached copy of the target carbon data partition located in the first geographical area is deleted. The determination of the target carbon data partition as hot data when the access frequency of the target carbon data partition exceeds the preset first access frequency threshold and the access source geographical location is concentrated in the first geographical area, and the triggering of the dynamic caching mechanism, comprises the following steps: The central management node applies a preset first access frequency threshold and a geographical concentration threshold to each carbon data partition based on a global access view. When the access frequency of any target carbon data partition exceeds the first access frequency threshold, and more than the geographical concentration threshold of the access request sources come from the same provincial administrative region, the central management node determines that the corresponding region is the first geographical area, and marks the corresponding target carbon data partition as hot data, generating a hot data marking event. For the hot data marking event, the central management node generates a corresponding hot data caching instruction, adds the hot data caching instruction to a caching task queue, and triggers a cache scheduler to obtain the hot data caching instruction from the caching task queue to perform caching operations. The hot data caching instruction at least contains the target carbon data partition number and the first geographical area code.

2. The distributed partitioned storage security method of new energy truck carbon data according to claim 1, characterized in that, The partitioning according to preset rules comprises the following steps: A composite partition key is constructed based on the vehicle identification code and the driving route latitude and longitude coordinates of the new energy truck. The composite partition key is input into a consistent hash ring to generate multiple virtual nodes. According to the mapping relationship between the virtual nodes and the edge nodes, the carbon data of the new energy truck is distributed to the corresponding edge nodes to form multiple carbon data partitions. The construction method of the composite partition key is to concatenate the string form of the vehicle identification code and the decimal value converted from the latitude and longitude coordinates of the driving route start and end points, and then perform hash processing through the SHA-256 algorithm to obtain a composite partition key with a fixed length.

3. The distributed partitioned storage security method of new energy truck carbon data according to claim 2, characterized in that, The distributed storage comprises the following steps: A metadata block containing a timestamp and a partition identifier is generated for each carbon data partition. The metadata block is split into sub-keys using a threshold secret sharing algorithm, and distributed to edge nodes. m m edge nodes.​ Setting a minimum recovery threshold k When accessing the metadata, at least the k sub-keys are collected to reconstruct the complete metadata.

4. The distributed partitioned storage security method of new energy truck carbon data according to claim 3, characterized in that, The monitoring of the access indicators of each carbon data partition and the reporting to the central management node comprises the following steps: Each access request to the locally stored carbon data partition is captured in real time by an access monitoring agent deployed at each edge node, and a structured access log is generated; the key fields of the structured access log include access timestamp, partition number of the requested data, IP address of the access source, access request type, and access duration; The access monitoring agent aggregates and analyzes the generated access log according to a preset fixed time window, counts the access frequency of each carbon data partition, and calls an embedded IP geographic information library to analyze the access source IP address to obtain the corresponding access source geographic location; The access monitoring agent encapsulates the access frequency and access source geographic location of each carbon data partition obtained within a statistical period into a monitoring report data packet, and reports it to the central management node in a timely manner through a secure communication channel established based on the TLS protocol; The central management node receives and analyzes the monitoring report data packet from all edge nodes, aggregates and stores the access indicator data in a time series database, and generates a global access view.

5. The distributed partitioned storage security method of new energy truck carbon data according to claim 4, characterized in that, The central management node locates the current storage node of the hot data, including: The cache scheduler takes out the hot data cache instruction to be processed from the cache task queue, and parses the target carbon data partition number therein; The central management node queries the partition-node mapping table it maintains, retrieves the network address of the primary edge node storing the hot data copy according to the target carbon data partition number, generates a data copy acquisition request containing authentication information, and sends it to the primary edge node through a secure communication link; the data copy acquisition request contains the target carbon data partition number and authentication information.

6. The distributed partitioned storage security method of new energy truck carbon data according to claim 5, characterized in that, The data copy of the target carbon data partition is obtained, and the data copy is cached to one or more target edge nodes located in the first geographic area, including: After verifying the legality of the data copy acquisition request, the primary edge node reads the complete data of the target carbon data partition from the local storage, generates a data copy packet after compression and encryption processing; The primary edge node transmits the data copy packet to the temporary storage area specified by the central management node, and sends a copy ready notification to the central management node; After receiving the copy ready notification and verifying the data integrity, the central management node parses the first geographic area code recorded in the hot data cache instruction, queries the edge node registration table based on the first geographic area code, filters out the edge nodes located in the first geographic area and currently having a lower load than the preset load threshold, and determines them as target edge nodes; The central management node distributes the data copy packet in the temporary storage area to the selected one or more target edge nodes for caching through the content distribution network, and after the distribution is completed, the central management node updates the partition cache mapping table to record the new cache relationship between the target carbon data partition and the target edge node.

7. The distributed partitioned storage security method of new energy truck carbon data according to claim 6, characterized in that, The central management node continuously monitors the access state of the cached target carbon data partition, and when the access frequency of the target carbon data partition falls below a preset second access frequency threshold and lasts for a preset cooling time, the cache copy of the target carbon data partition located in the first geographic area is deleted, including: When the target carbon data partition is successfully cached to the target edge node in the first geographic area, the central management node creates a partition cache monitoring instance for the target carbon data partition, the partition cache monitoring instance receives access statistics from the target edge node in the first geographic area about the target carbon data partition, and at the same time, the central management node sets a second access frequency threshold and a cooling time for the partition cache monitoring instance, wherein the second access frequency threshold is less than the first access frequency threshold when the cache is triggered; The partition cache monitoring instance calculates the average access frequency of the target carbon data partition in the sliding time window based on the received access statistics, and continuously judges whether the average access frequency has fallen below the second access frequency threshold, and once it is detected that the average access frequency is lower than the second access frequency threshold, the partition cache monitoring instance starts the cooling timer, and if the average access frequency always remains below the second access frequency threshold within the continuous cooling time, it is determined that the target carbon data partition has changed from hot data to cold data, and a cache recovery trigger event is generated; The central management node responds to the cache recovery trigger event and sends cache copy deletion instructions to all target edge nodes in the first geographic area according to the partition cache mapping table, and each target edge node deletes the local cache copy after verifying the legality of the instruction and sends a deletion confirmation message to the central management node; The central management node updates the partition cache mapping table after receiving the deletion confirmation messages from all target edge nodes, and removes the cache association of the corresponding target carbon data partition and the target edge node.

8. The distributed partitioned storage security method of new energy truck carbon data according to claim 7, characterized in that, Before deleting the cache copy, a data consistency verification step is further included: the central management node compares the hash values of the cache copy and the current stored data of the master edge node; when the hash values are inconsistent, the updated data is synchronized to all cache nodes before deletion.

9. A distributed partitioned storage security system for new energy truck carbon data, which is used to implement the distributed partitioned storage security method for new energy truck carbon data in any one of claims 1-8. Comprise: Data partition module, access monitoring module, cache decision module, cache distribution module, cache management module; The data partition module is used for partitioning and managing the distributed storage of new energy truck carbon data in the edge node cluster; The access monitoring module is used for collecting access behavior data of each carbon data partition in real time and converging to the central management node; The cache decision module is used for analyzing access behavior data and identifying hot data under the global perspective of the central management node to trigger a dynamic cache mechanism; The cache distribution module is used for executing cache distribution tasks and pushing hot data copies to target edge nodes; The cache management module is used for continuously monitoring the cached hot data copies, managing their life cycle, including cooling judgment and resource recovery.

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