Entertainment equipment remote operation and maintenance system and method based on Internet of Things and SaaS platform

Abstract

The invention relates to the technical field of remote monitoring, in particular to an entertainment equipment remote operation and maintenance system and method based on the Internet of Things and an SaaS platform, and the system comprises a terminal access verification module, an operation load monitoring module, a cache state verification module, a task distribution mapping module and a cross-domain resource unified distribution module. According to the method, the device number, the port and the gateway information are subjected to correlation proofreading and duplicate removal in the access stage, the consistency and uniqueness of the access data can be controlled at the source, the CPU, memory and bandwidth indexes are continuously collected and compared with the resource standard item by item in the operation process, the resource load state can be subjected to instant analysis and trend judgment, and the method has the advantages of being high in practicability and high in reliability. The task segment identification and the data block version are matched before the task is executed, version updating is triggered when differences are mined, and task assignment is completed in combination with the real-time resource occupation condition after updating is completed, so that task distribution between cross-domain nodes is kept balanced, the risk of resource idleness and conflict backlog is reduced, and cooperative processing continuity in a multi-node environment is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of remote monitoring technology, and in particular to a remote operation and maintenance system and method for entertainment equipment based on the Internet of Things and SaaS platform. Background Technology

[0002] Remote monitoring technology falls under the category of integrated applications of automation control and information communication. Its core aspects include real-time acquisition, transmission, and control command issuance of information on the operating status, operation process, and environment of distributed terminal devices via communication networks. It encompasses technical elements such as communication hardware, embedded control systems, data acquisition devices, and cloud management platforms. The overall technology involves remote centralized management of field terminals from a central location using wired or wireless communication methods, and is widely applied in scenarios such as industrial equipment monitoring, public service facility management, and home and commercial terminal device management. Specifically, traditional entertainment equipment remote operation and maintenance systems refer to systems used in home or commercial entertainment scenarios to monitor the operating status, control playback, and handle faults of various audio and video playback devices, on-demand terminals, and interactive control devices via local area networks (LANs) or dedicated communication networks. These systems typically integrate embedded processing chips and storage units at the device end, and complete operation and maintenance management by issuing control commands and operating configurations to the device through local management software or a LAN control terminal.

[0003] Existing technologies lack comprehensive verification of device numbers and network parameters during device access, making it impossible to effectively eliminate duplicate or abnormal access terminals. Resource usage relies solely on local monitoring, making it difficult to detect potential bottlenecks in a timely manner. When task data cache versions differ across multiple nodes, there is a lack of a unified processing mechanism, which can easily lead to data inconsistency and response delays during task execution. Under cross-regional conditions, task allocation is not based on the real-time resource status of nodes, resulting in idle resources and uneven distribution of task load. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a remote operation and maintenance system and method for entertainment devices based on the Internet of Things and a SaaS platform. The technical solution is as follows: On the one hand, it provides a remote operation and maintenance system for entertainment equipment based on the Internet of Things and a SaaS platform. This system includes: The terminal access verification module obtains the terminal device number, access port and gateway MAC address, reads the license number, compares the number and analyzes the port and MAC correspondence, removes duplicates by number, and obtains a list of connected terminals. The load monitoring module collects CPU utilization, memory usage and bandwidth usage based on the list of connected terminals, compares the collected data with the resource configuration standard, analyzes resource usage and bottlenecks, and obtains a terminal operation status table. The cache status verification module, based on the terminal running status table, matches the task segment identifier with the data block version, analyzes the consistency, marks inconsistent devices as cache conflicts, and obtains a cache conflict list. Based on the cache conflict list, the task distribution mapping module filters conflict entries, compares the task fragment and data block versions with the current version, updates inconsistent versions to the current version, and then allocates the updated task fragments to idle nodes to obtain the task distribution mapping table. Based on the task allocation mapping table, the cross-domain resource allocation module obtains the CPU utilization, memory usage, and bandwidth usage of cross-domain nodes, analyzes resource availability, associates nodes with task fragment identifiers, and obtains a cross-domain task landing point table.

[0005] As a further embodiment of the present invention, the list of connected terminals includes device number, access port, and IoT gateway MAC address; the terminal running status table includes CPU utilization, memory usage, and network bandwidth usage; the cache conflict list includes device number, task fragment identifier, and cache conflict status; the task allocation mapping table includes task fragment identifier, data block version, and processing thread node; and the cross-domain task landing point table includes cross-domain data center node, task fragment identifier, and node resource availability.

[0006] As a further aspect of the present invention, the resource configuration standard refers to, during the load monitoring process, first analyzing the target range of CPU utilization, memory usage, network bandwidth usage, etc., collecting real-time usage data of terminals and nodes, and then comparing them sequentially with the target range to determine whether the resource usage is normal. The resource usage and bottlenecks refer to the process of collecting the CPU, memory, and bandwidth usage rates of each terminal, comparing the data item by item with the target range of the resource configuration standard, judging the usage ratio and trend of resources, and analyzing the links with high usage.

[0007] As a further aspect of the present invention, the conflict entry refers to comparing the task fragment identifier with the corresponding data block version item by item during cache status verification. When the versions are inconsistent, the corresponding device number and task fragment identifier are extracted and placed into the subsequent version update and task allocation processing flow. The cross-domain node CPU utilization rate refers to the process of first obtaining the number of used cores and the total number of cores of the target cross-domain data center node during the cross-domain resource allocation process, comparing the relationship, analyzing whether the node's computing resources meet the allocation conditions, and arranging task distribution when the resource status is within the executable range.

[0008] As a further aspect of the present invention, the terminal access verification module includes: The device number acquisition submodule obtains the device number, access port and IoT gateway MAC address of the entertainment terminal, associates the device number with the access port and MAC address, and obtains the port and gateway correspondence information. The information comparison submodule, based on the correspondence between the port and the gateway, reads the licensed device number entries from the SaaS tenant configuration table, compares the device number with the licensed device number, filters matching entries, and obtains matching device information. The access deduplication submodule, based on the matching device information, calls the device number of the matching entry, deduplicates the duplicate numbers, and obtains a list of connected terminals.

[0009] As a further aspect of the present invention, the load monitoring module includes: Based on the list of connected terminals, the data acquisition submodule obtains the CPU utilization, memory usage, and network bandwidth usage of each terminal. For the same terminal, the usage rate is sequenced according to the device number and access port order, and the current value is appended according to the collection time order to obtain the terminal usage rate sequence. The resource comparison submodule, based on the terminal occupancy rate sequence, compares the CPU utilization rate standard value, memory occupancy rate standard value, and bandwidth occupancy rate standard value in the resource configuration standard with the corresponding items in the sequence, calculates the CPU occupancy rate ratio, and appends the comparison results according to the terminal number to obtain the resource comparison table; Based on the resource comparison table, the resource usage analysis submodule analyzes the CPU, memory and bandwidth usage of the terminal, arranges the comparison ratio and device number into corresponding status entries, and associates them with the terminal list according to the access port order to obtain the terminal running status table.

[0010] As a further aspect of the present invention, the cache status verification module includes: Based on the terminal running status table, the task extraction submodule extracts the task segment identifier and data block version of the device, and obtains the task version corresponding information by matching the task segment identifier with the corresponding data block version. The version matching submodule analyzes whether the versions are consistent based on the task version corresponding information, the version-by-task fragment identifier and data block, calculates the distribution density of devices with inconsistent versions, and obtains the version abnormal distribution status. The conflict classification submodule filters out device information with inconsistent versions based on the abnormal distribution status of the versions, and obtains a cache conflict list by associating the corresponding device number and task segment identifier.

[0011] As a further aspect of the present invention, the task distribution mapping module includes: The conflict filtering submodule filters entries with cache conflicts based on the cache conflict list, extracts task fragment identifiers and data block versions, and matches the data with the device number of the entry to obtain conflict task information. Based on the conflict task information, the version update submodule obtains the task fragment identifier and data block version, compares them item by item with the current version record, and selects the current version data block to replace it when the versions are inconsistent, thereby obtaining the update task information. Based on the updated task information and the processing thread occupancy rate of the nodes, the task dispatch submodule filters out nodes that are in an idle state, and assigns the updated task fragments to the nodes to obtain a task allocation mapping table.

[0012] As a further aspect of the present invention, the cross-domain resource allocation module includes: Based on the task allocation mapping table, the resource acquisition submodule obtains the CPU utilization, memory usage, and network bandwidth usage of the target cross-domain data center node, and obtains the node resource information by matching each data item with the corresponding node identifier. The availability analysis submodule analyzes the CPU, memory and bandwidth usage of the nodes based on the node resource information, determines the resource availability status, analyzes the corresponding results and node identifiers, and obtains the node availability status. The task landing point association submodule associates available nodes with corresponding task fragment identifiers based on the node availability status to obtain a cross-domain task landing point table.

[0013] On the other hand, a remote operation and maintenance method for entertainment equipment based on the Internet of Things (IoT) and a SaaS platform, wherein the remote operation and maintenance method for entertainment equipment based on the IoT and SaaS platform is executed based on the aforementioned remote operation and maintenance system for entertainment equipment based on the IoT and SaaS platform, includes the following steps: S1: Obtain the device number, access port, and IoT gateway MAC address of the entertainment terminal; read the licensed device number entry from the SaaS tenant configuration table; compare the device number with the license number; analyze the correspondence between the access port and the gateway MAC address; remove duplicates by device number; and obtain a list of connected terminals. S2: Based on the list of connected terminals, obtain the CPU utilization, memory usage and network bandwidth usage of each terminal, compare the running data with the resource configuration standard, analyze the terminal's usage in CPU, memory and bandwidth, and obtain the terminal running status table; S3: Based on the terminal running status table, extract the task segment identifier and data block version for matching, analyze whether they are consistent, classify inconsistent devices as cache conflict items, and obtain a cache conflict list according to the device number and task segment identifier. S4: Based on the cache conflict list, filter conflict entries, obtain task fragment identifiers and data block versions, compare them with the current version record, update to the current version if the versions are inconsistent, assign task fragments to nodes with idle processing thread occupancy, and obtain a task allocation mapping table. S5: Based on the task allocation mapping table, obtain the CPU utilization, memory usage and network bandwidth usage of the target cross-domain data center node, analyze the node resource availability, associate the node with the task fragment identifier, and obtain the cross-domain task landing point table.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by associating and deduplicating device numbers, ports, and gateway information during the access phase, the consistency and uniqueness of access data can be controlled at the source. During operation, CPU, memory, and bandwidth indicators are continuously collected and compared with resource standards item by item, enabling real-time analysis and trend judgment of resource load status. Before task execution, task segment identifiers and data block versions are matched, and version updates are triggered when differences are discovered. After the update is completed, task assignment is completed based on real-time resource usage, ensuring a balanced distribution of tasks among cross-domain nodes, reducing the risk of resource idleness and conflict backlog, and ensuring the continuity of collaborative processing in a multi-node environment. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a system block diagram of the present invention; Figure 3 This is a flowchart of the terminal access verification module in this invention; Figure 4 This is a flowchart of the load monitoring module in this invention; Figure 5 This is a flowchart of the cache status verification module in this invention; Figure 6 This is a flowchart of the task distribution mapping module in this invention; Figure 7 This is a flowchart of the cross-domain resource allocation module in this invention; Figure 8 This is a flowchart of the method steps of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0019] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0020] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] This invention provides a remote operation and maintenance system for entertainment devices based on the Internet of Things and a SaaS platform, such as... Figure 1-2 The diagram shown illustrates a remote operation and maintenance system for entertainment equipment based on an IoT and SaaS platform. The system includes: The terminal access verification module obtains the device number, access port and MAC address of the IoT gateway of the entertainment terminal, reads the licensed device number entry according to the SaaS tenant configuration table, compares the device number with the tenant licensed device number, analyzes whether the access port and gateway MAC address correspond, and removes duplicates of the matching device entries according to the device number to obtain the list of connected terminals. The load monitoring module obtains the CPU utilization, memory usage, and network bandwidth usage of each terminal based on the list of connected terminals. It compares the data with the resource configuration standards, analyzes the resource usage of each terminal, and obtains a terminal running status table. The cache status verification module extracts the task fragment identifier and data block version of the device based on the terminal running status table and matches them. It analyzes the consistency between the task fragment identifier and the data block version, marks the mismatched devices as cache conflicts, and classifies them according to the device number and task fragment identifier to obtain a cache conflict list. The task distribution mapping module filters entries with cache conflicts based on the cache conflict list, obtains task fragment identifiers and data block versions, compares them with the current version records, and if the versions are inconsistent, selects the current version data block for updating, and assigns the updated task fragments to nodes where the processing thread occupancy rate is idle, thus obtaining the task allocation mapping table. The cross-domain resource allocation module obtains the CPU utilization, memory usage, and network bandwidth usage of the target cross-domain data center nodes based on the task allocation mapping table, analyzes the availability of node resources, associates the nodes with task fragment identifiers, and obtains the cross-domain task landing point table.

[0023] The list of connected terminals includes the device number, access port, and IoT gateway MAC address. The terminal operation status table includes CPU utilization, memory usage, and network bandwidth usage. The cache conflict list includes the device number, task fragment identifier, and cache conflict status. The task allocation mapping table includes the task fragment identifier, data block version, and processing thread node. The cross-domain task landing point table includes the cross-domain data center node, task fragment identifier, and node resource availability.

[0024] Please see Figure 2 and Figure 3 The terminal access verification module includes: The device number acquisition submodule obtains the device number, access port and IoT gateway MAC address of the entertainment terminal, associates the device number with the access port and MAC address, and obtains the port and gateway correspondence information. First, each entertainment terminal is connected to the data collection device. The device number can be directly extracted from the unique code reading interface of the device itself. The access port needs to be determined by the physical connection detection device to identify the corresponding interface number. For example, in a cabinet, the occupancy status of ports 1 to 16 is checked, and the occupied port number is matched with the unique device number. The MAC address of the IoT gateway is obtained through network connection information. The hardware address string of the gateway is read and formatted. Then, during the execution process, the obtained device number, access port number, and MAC address are associated in pairs. For example, the terminal with the number E1001 is matched with port 05 and MAC addresses A1:B2:C3:D4:E5:F6. This step requires determining the terminal number, access port number, and MAC address. To determine whether a port and MAC address belong to the same physical connection path, the network topology information table can be used for item-by-item comparison. If the number, port, and MAC information are found to belong to the same link in the topology table, the combination is confirmed as a valid match. All valid matches are confirmed as a many-to-one relationship according to the device number dimension. That is, a device number retains only its corresponding unique port and unique MAC address combination. For example, when E1002 detects signals on two different ports, it is necessary to compare the MAC address of the gateway connected to the port and filter out a data that matches the MAC address of the authorized gateway. Finally, all the filtered matching relationships are organized into a set of three items: device number, corresponding port, and corresponding MAC address, to obtain the port and gateway correspondence information.

[0025] The information comparison submodule, based on the port and gateway correspondence information, reads the licensed device number entries from the SaaS tenant configuration table, compares the device number with the licensed device number, filters matching entries, and obtains matching device information. First, the port and gateway correspondence information is retrieved line by line, and the device IDs are extracted. These are then compared one by one with the license ID list in the SaaS tenant configuration table. Before the comparison, the license ID list needs to be formatted correctly, such as removing spaces and converting to uppercase or lowercase to ensure consistency with the device ID format in the port and gateway correspondence information. During the comparison, each device ID is matched against the license ID, and successfully matched entries are temporarily stored. For example, the device IDs E2005, E2006, and E2008 in the port and gateway correspondence information are compared with E2006 and E2008 in the license ID list. Item by item, E2007 and E2008 were compared. Finally, E2006 and E2008 were successfully matched. For each successfully matched number, it is also necessary to associate its corresponding port number and gateway MAC address information to ensure that this information can be directly accessed in subsequent steps. At the same time, it is necessary to determine whether the same device number appears in multiple ports. If duplicates are found, the information that matches the gateway MAC address is retained, and other inconsistent data is discarded. All the results after comparison and filtering are uniformly included in a directly usable dataset. Each item in this dataset contains three items: device number, corresponding port number, and corresponding gateway MAC address, thus obtaining the matching device information.

[0026] The access deduplication submodule, based on the matching device information, calls the device number of the matching entry, removes duplicate numbers, and obtains a list of connected terminals. First, the device number of each record is retrieved. These numbers are read one by one and formed into a temporary list. During execution, it should be ensured that each number in the list is bound to its corresponding access port and gateway MAC address information so that the source entry can be accurately located during the deduplication operation. For example, if there are four numbers in the matching device information: E3001, E3002, E3001, and E3003, and E3001 appears twice with the same port and MAC address, it should be determined as a duplicate record. In the process of determining duplicates, the device number can be completely matched by string comparison. At the same time, it is checked whether its corresponding port number and MAC address field are completely identical. If all three pieces of information are completely identical, it is considered a duplicate, and only one record is retained in the final set. For cases where the ports or MAC addresses are different but the device numbers are the same, it is necessary to further determine whether the device number allows multiple access paths in the business rules. For example, if a device is allowed to access through two ports in the entertainment terminal management, the record will not be deleted. If not, the record with the port or MAC address that does not meet the requirements must be deleted. All the unique device numbers that have been screened and their corresponding port and MAC information are rearranged into a standardized record format. For example, the following records are ultimately retained: E3001-Port 07-MACA1:B2:C3:D4:E5:F6, E3002-Port 08-MACA2:B3:C4:D5:E6:F7, and E3003-Port 10-MACA3:B4:C5:D6:E7:F8, to obtain the list of connected terminals.

[0027] Please see Figure 2 and Figure 4 The load monitoring module includes: The data acquisition submodule obtains the CPU utilization, memory usage, and network bandwidth usage of each terminal based on the list of connected terminals. For the same terminal, the usage rate is sequenced according to the device number and access port order. The current value is appended in the order of collection time to obtain the terminal usage rate sequence. First, the device number and access port information of each record in the list are retrieved sequentially. Then, the current CPU utilization, memory usage, and network bandwidth usage are collected from the corresponding terminal using the running monitoring command. The acquisition of each usage rate must be associated with the real-time operating status of the terminal. For example, on the terminal with the device number T5001 and port 12, the collected CPU utilization is 42%, the memory usage is 61%, and the network bandwidth usage is 38%. These usage rate data must be kept synchronized in the same collection process to avoid numerical deviations caused by time asynchrony. Then, for the same terminal, the three usage rates collected are matched one-to-one according to the device number and access port order. For example, the three usage rates of T5001-port 12 are recorded first. Next, record the three utilization rates of T5002-port 15 to form an ordered data alignment relationship. Then, append the latest value to the end of the existing sequence in the order of collection time. If the CPU utilization rate of T5001 in the previous sequence was 40%, the memory utilization rate was 60%, and the network bandwidth utilization rate was 35%, then directly append the 42%, 61%, and 38% collected this time. This appending method must maintain the consistency of the three utilization rates for subsequent comparison and analysis. During the execution process, the length of the data before and after appending must also be checked to ensure that the number of utilization rate records for each terminal is equal. In this way, in the case of multiple terminals and multiple ports, the sequence can be stably expanded according to the predetermined number and port order to finally obtain the terminal utilization rate sequence.

[0028] The resource comparison submodule is based on the terminal occupancy rate sequence. According to the standard values ​​of CPU utilization rate, memory occupancy rate, and bandwidth occupancy rate in the resource configuration standard, it compares with the corresponding items in the sequence, calculates the CPU occupancy rate ratio, and appends the comparison results according to the terminal number to obtain the resource comparison table. The formula for calculating CPU utilization percentage specifically represents: ; in, Terminal number represents CPU utilization percentage Representative terminal Actual CPU utilization This represents the standard value for CPU utilization. Representative terminal Actual memory usage This represents the standard value for memory usage. This represents a fine-tuning item for differences in memory usage. This represents a minimal constant that avoids a denominator of zero. Representative terminal Actual bandwidth utilization This represents the standard value of bandwidth utilization. This represents the bias adjustment of the bandwidth ratio. Represents the base of the logarithmic function; The overall calculation logic of the formula is as follows: Calculate the absolute difference between the current actual value and the standard value of the CPU. Then, the difference in memory usage Add fine-tuning items Multiplication is performed, and the entire result is squared to avoid explosive interference from excessively large individual resources on the metric. Then, the sum of the standard CPU value and the smallest positive number is used as the denominator for normalization. Finally, a logarithmic function term representing the bandwidth utilization deviation is multiplied to map its exponential adjustment capability on the calculation result. The overall multiplication structure maintains the synergistic effect of three dimensions: the absolute value and the square root soften outliers, and the logarithmic term modulates the nonlinear expansion trend. The following are numbered The terminal's monitoring data acquisition and calculation steps within the sampling period are as follows: The sampling and monitoring data retrieves the current resource usage value of the terminal. It is calculated by reading the ratio of CPU user + system value to total number of cores every 10 seconds; This is obtained by comparing the ratio of used memory value to total memory value. Statistics are based on the ratio of real-time bandwidth traffic to the total limit; The baseline value recorded in the configuration standard table is: Calculated based on the first 30 days of stability; Acquired within the same period; : Calculate the average value of data from multiple terminals under normal operating conditions; Coefficient and threshold settings: : Refer to the average peak fluctuation of memory over the past 5 minutes; Fixed safety constants; : Lower limit protection item for bandwidth ratio; The standard base is 10 to facilitate the analysis of the calculation result range; Substitute the parameters one by one to perform the calculation: Calculate the difference: ; ; Root of product: ; Denominator normalization: ; Step 4, Logarithmic terms: ; ; ; Interpretation of results and numerical significance: This indicates that terminal number 2 has extremely low resource deviation in the current sampling period, and its load deviation is small compared to the configuration standard. The value will be recorded in the resource comparison table for comparison. If the value is in the lower range of the sample threshold 0.00–0.20, it means that the terminal's current resource usage is reasonable and there is no need to migrate or adjust it. Based on the result, the terminal's load balancing action can be skipped. Explanation of the innovative aspects of the formula: The advantage of the formula is that by introducing the square root of the product of the differences between CPU and memory, and combining it with the logarithmic function term of the bandwidth offset, it enables the differentiating resource dimensions to have coupling and nonlinear adjustment capabilities. It can simultaneously identify the offsets of multiple resource items and smooth out sudden peaks, thereby enhancing the overall resource scheduling system's ability to perceive the status of heterogeneous resources.

[0029] The resource usage analysis submodule analyzes the CPU, memory and bandwidth usage of the terminal based on the resource comparison table, arranges the comparison ratio and device number into corresponding status entries, and associates them with the terminal list according to the access port order to obtain the terminal running status table. First, read the device number and its corresponding CPU, memory, and bandwidth usage percentages from the lookup table. Associate these three percentages with the device number. During the analysis, CPU utilization needs to be judged based on pre-defined range standards. For example, 0% to 40% is considered low utilization, 41% to 75% is medium utilization, and 76% to 100% is high utilization. Memory and bandwidth utilization are similarly categorized according to corresponding ranges. For example, memory utilization of 0% to 50% is low utilization, 51% to 85% is medium utilization, and 86% to 100% is high utilization. Similarly, bandwidth utilization of 0% to 30% is low utilization, 31% to 70% is medium utilization, and 71% to 100% is high utilization. These range values ​​can be obtained by analyzing the resources of the entertainment terminal under different loads. The source performance is statistically analyzed. For example, if a device with the ID T8001 has a CPU utilization of 68%, a memory utilization of 77%, and a bandwidth utilization of 54%, then this device is classified as having medium CPU utilization, high memory utilization, and medium bandwidth utilization. The results of each classification are arranged according to the device ID to form corresponding status entries. At the same time, the order of the device IDs must be consistent with the order of the access ports. For example, if port 01 corresponds to T8001, port 02 corresponds to T8003, and port 03 corresponds to T8002, then the order of the status entries should be T8001, T8003, and T8002. This ensures that when associated with the list of connected terminals, the port order matches the order of the status entries, ultimately resulting in the terminal operation status table.

[0030] Please see Figure 2 and Figure 5 The cache status verification module includes: The task extraction submodule extracts the task fragment identifier and data block version of the device based on the terminal running status table. By matching the task fragment identifier with the corresponding data block version, the task version information is obtained. First, read the unique ID of each device in the status table and then sequentially retrieve its corresponding task fragment identifier field. This field is usually a sequence of letters and numbers used to mark the specific position of the task in the processing flow. Next, read the corresponding data block version information for that device. This version information is a version number in a fixed format, such as V1.2 or V3.5, used to identify the update batch of the data block. During the extraction process, it is necessary to ensure that the task fragment identifier and the data block version information come from the same record to avoid association errors caused by reading across records. For example, for device number D1001, its task fragment identifier is TPX-045 and its data block version is V2.1. Therefore, TPX-045 and V2.1 must be retained as a pair. This process requires... The process iterates through all device records, skipping or supplementing records with missing task fragment identifiers or data block versions to ensure data integrity. When multiple task fragment identifiers exist for the same device number, the task fragment with the earlier sequence number should be retained according to the access port order, and other entries with duplicate numbers should be discarded. This rule can be implemented by maintaining a port priority order table. For example, port 03 takes precedence over port 05. If the same device has records on both ports, the task fragment identifier and data block version pair of port 03 should be retained first. After the above matching and filtering, each task fragment identifier and its corresponding data block version are fixed to the corresponding device number in a one-to-one relationship, forming an association list indexed by device number, and finally obtaining the task version corresponding information.

[0031] The version matching submodule analyzes whether the versions are consistent based on the task version corresponding information, the version-by-task fragment identifier and data block, calculates the distribution density of devices with inconsistent versions, and obtains the version abnormal distribution status. The specific formula for calculating the distribution density of devices with inconsistent versions is as follows: ; in, Distribution density of devices with inconsistent versions This represents the data block version value corresponding to the i-th task fragment. This represents the standard version value in the task version correspondence information. This represents the number of devices corresponding to the i-th task segment. This represents the standard deviation of the time-series fluctuation of device resource utilization for the i-th task segment within the version monitoring period. This represents the average standard deviation of the time series fluctuation of device resource utilization across all task segments. The connectivity value of the device within the i-th task segment in the network topology is measured in terms of the number of connections. The maximum value representing the connectivity of a task segment device is expressed in terms of the number of connections. The total number of task segments is represented by the number of segments. Represents the index of a task fragment; Formula operation logic: First, calculate the absolute value of the difference between the actual version value and the standard version value of each task segment to keep the difference amount non-negative. Then, multiply the difference value by the number of devices corresponding to the task segment to reflect the weighting effect of device scale on the difference. Next, calculate the ratio of the standard deviation of the time series fluctuation of the device resource utilization rate of the task segment to the average standard deviation of the fluctuation of the entire segment and take the square root as the fluctuation smoothing factor introduced into the above product. Then, calculate the ratio of the average device connectivity of the task segment to the maximum connectivity of the entire segment and continue to multiply, so that the network structure characteristics participate in the difference measurement. After completing the above product calculation, sum the results of all task segments to obtain the total global weighted difference. Finally, divide the total by the total number of task segments for normalization to obtain the distribution density of devices with inconsistent versions. Version v1.2.3 corresponds to the value 1.23. The version numbers of the three task segments detected are v1.2.3 (1.23), v1.3.0 (1.30), and v1.2.0 (1.20). The current setting is v1.3.0, corresponding to the value 1.30; The first segment has 12 devices, the second segment has 10 devices, and the third segment has 15 devices. The system monitors CPU, memory, and bandwidth usage every 10 minutes for 24 hours and calculates the standard deviation. The first segment of monitoring showed that the standard deviation of the CPU utilization sample sequence was 4.2%. ; The second segment was 5.0%, and the third segment was 3.8%; The average of the standard deviations of the time series fluctuations in the resource utilization rate of equipment in a task segment; ; The average number of connections for the first segment is 8, for the second segment it is 9, and for the third segment it is 7. : Maximum value, i.e. . The current value is 3.

[0032] The absolute version difference of the calculation segment in the process of substituting numerical values ​​into the formula: Segment 1: ; Segment 2: ; Segment 3: ; Calculate the square root of the fluctuation ratio of the segment: Segment 1: ; Segment 2: ; Segment 3: ; Calculate the connectivity ratio of the segments: Segment 1: ; Segment 2: ; Segment 3: ; Calculation and summation part: Contribution value of segment 1: ; Segment 2 contribution value: ; Segment 3 contribution value: ; Accumulation: ; ; Interpretation of Results and Numerical Significance: Distribution Density of Devices with Inconsistent Versions Units / task segment. If the system baseline value is 0.50 units / task segment, the results indicate that the distribution density of inconsistent devices in the current version is higher than the baseline, which means that there is a certain degree of concentrated difference in version management. This corresponds to the "abnormal distribution status of version" in the step results, indicating that some task segments need to be adjusted for version consistency. Explanation of the innovative aspects of the formula: The advantage of the formula is that by introducing two parameters, namely the square root of the ratio of the standard deviation of the time series fluctuation of equipment resource utilization rate and the ratio of the network topology connectivity of equipment, they are combined with the version difference value and the number of equipment to participate in the product operation. In the calculation of version difference, the quantitative integration of the impact of equipment operation volatility and network structure is taken into account, so that the impact of the operating characteristics of the equipment group on the abnormal concentration of version can be reflected in the distribution density assessment.

[0033] The conflict classification submodule filters device information with inconsistent versions based on the version anomaly distribution status, and associates the corresponding device number and task fragment identifier to obtain a cache conflict list. First, all records in the distribution are read, and device numbers marked as inconsistent versions are retrieved sequentially. Each of these numbers is then cross-referenced with its corresponding task fragment identifier in the associated data table to ensure that the task fragment identifier and device number originate from the same source. For example, if device number D4502 is marked as inconsistent in the version anomaly distribution, its unique task fragment identifier TPJ-092 needs to be located in the task fragment record table and paired with the device number. During this step, each combination of device number and task fragment identifier needs to be compared for duplicates. If duplicate combinations are found, only the earliest registered record is retained to avoid data redundancy in subsequent processing. When the same device number is associated with multiple task fragment identifiers, priority should be determined according to the device access port order or storage address order. For example, task fragments on port 02 take precedence over task fragments on port 05. The selected combination will directly enter the cache conflict dataset. After confirming each combination, all matching device numbers and task fragment identifiers are paired into one-to-one entries. Each entry contains two key pieces of information: device number and task fragment identifier, arranged in the original input order, ultimately resulting in the cache conflict list.

[0034] Please see Figure 2 and Figure 6 The task distribution mapping module includes: The conflict filtering submodule filters entries with cache conflicts based on the cache conflict list, extracts task fragment identifiers and data block versions, and matches the data with the device number of the entry to obtain conflict task information. First, each record is read sequentially, and its conflict flag field value is checked for truth. Entries with true conflict flags are temporarily stored in a filter list. Then, the task fragment flag and data block version fields are extracted from the filter list one by one, and a positional correspondence is established between these two fields and the device number of the original record. During the process, the task fragment flag needs to be compared repeatedly. If multiple identical task fragment flags exist under the same device number, the record with the largest difference in data block version is selected and retained, while the others are discarded to avoid duplicate interference. Next, the device numbers of the retained records are sorted sequentially to ensure the stability of the subsequent data correspondence. Then, the task fragment flag and data block version are merged into a pairwise dataset according to the device number order. In the instantiation scenario, the case where device A102, task fragment T56, and data block version V3 have a true conflict flag in the conflict list can be referenced. At this time, it will be bound to device number A102 and stored in the dataset. Finally, the processing of all entries that meet the conditions is completed, and the conflict task information is obtained.

[0035] The version update submodule obtains the task fragment identifier and data block version based on the conflict task information, compares them item by item with the current version record, and selects the current version data block to replace it when the versions are inconsistent, thus obtaining the update task information; First, the task fragment identifier and corresponding data block version of each record in the conflict task data table are read. Using the task fragment identifier as a search condition, the corresponding current version number is located item by item in the version record table. The version field value is then used for precise character or numerical matching. If the comparison result is the same version, the original data block record remains unchanged. If the comparison result is different versions, a replacement operation is performed, that is, the version number and corresponding data block content in the current version record table are used to overwrite the old version record in the conflict task data table. During this process, it must be ensured that each replacement operation corresponds to a unique task fragment identifier and does not affect other non-version-related fields under the same identifier. For example, if task fragment T015 is recorded as version 3.2 in the conflict task information, but the current version record table shows version 3.5, then version 3.2 is extracted. The data block content corresponding to version 5 directly overwrites the original version 3.2 data block, while retaining other field information of task fragment T015 unchanged. If a single processing involves multiple task fragments, they must be processed sequentially according to their task fragment identifier numbers to ensure that no cross-reference errors occur during multiple replacements. An update mark is generated for the replaced records, and the replaced version number is registered in the internal cache for subsequent verification and to prevent duplicate replacements. For example, in a batch processing, if the versions of task fragments T021, T034, and T045 are replaced from 1.8, 2.0, and 2.4 to 1.9, 2.2, and 2.5 respectively, the update records retain the correspondence between the task fragment identifier and the new version number. After all processing is completed, the complete set of replaced records is re-aggregated to obtain the updated task information. The task dispatch submodule, based on updated task information and the processing thread occupancy rate of nodes, filters nodes that are in an idle state, and assigns the updated task fragments to the nodes to obtain a task allocation mapping table. First, the identifier, required resource type, and resource consumption value of each task segment are read from the task information table. This data is then compared with the current processing thread occupancy rate of each node in the node monitoring record. The processing thread occupancy rate is compared as a percentage with a set idle judgment benchmark value, which can be calculated by referring to 40% of the total number of processing threads. That is, when the current occupancy rate of a node is lower than 40%, it is marked as idle. For example, if the current occupancy rate of node N07 is 32%, it is marked as idle. Then, nodes are sequentially retrieved from the list of idle nodes, and each node is matched with its available resources according to the CPU, memory, and bandwidth requirements of the task segment. The matching process retains the binding relationship between the node and the task segment as long as all resource requirements are met. If a node does not have enough resources, it is skipped and the next node is selected. Among the matched nodes, the allocation order is arranged according to the priority order of the task segment identifier. The priority can be sorted by the task importance level or execution sequence number. For example, if the priority of task segment T305 is higher than that of T412, it will be allocated to the idle node that meets the condition. Finally, after completing the matching and priority allocation of all task segments and nodes, a task allocation mapping table is obtained.

[0036] Please see Figure 2 and Figure 7 The cross-domain resource allocation module includes: The resource acquisition submodule obtains the CPU utilization, memory usage, and network bandwidth usage of the target cross-domain data center node based on the task allocation mapping table, and obtains the node resource information by matching each data item with the corresponding node identifier. First, the target cross-domain data center node identifier corresponding to each task allocation in the mapping table is read. Each node identifier is used as an index to obtain the node's CPU utilization, memory usage, and network bandwidth usage from the cross-domain node monitoring records. CPU utilization is calculated by comparing the node's used cores with its total core count, and then expressed as a percentage. For example, if node A12 currently has 3 out of 8 cores in use, its CPU utilization is 37.5%. Memory usage is obtained by comparing the node's real-time memory usage with its total memory. For example, if node A12 has a total memory of 64GB and 24GB is used, its usage is 37.5%. Network bandwidth usage is calculated by checking the node's real-time bandwidth usage. The data is compared with the total bandwidth value for calculation. For example, if the total bandwidth of a node is 1Gbps and the current usage is 600Mbps, then the bandwidth usage rate is 60%. After obtaining the three data items, a one-to-one correspondence is established between each data item and the corresponding node identifier, and they are arranged into a unified structure according to the node order in the task allocation mapping table. For the batch data acquisition process of multiple nodes, it is necessary to traverse all node entries in the task allocation mapping table to ensure that the CPU utilization, memory usage, and bandwidth usage of all nodes are extracted and associated with their respective node identifiers. For example, if the mapping table contains nodes A12, B08, and C15, then the three resource usage rates of these three nodes are obtained and associated with their identifiers to finally obtain the node resource information.

[0037] The availability analysis submodule analyzes the CPU, memory and bandwidth usage of nodes based on node resource information, determines the resource availability status, analyzes the corresponding results and node identifiers, and obtains the node availability status. First, the CPU utilization, memory usage, and network bandwidth usage of each node are read. These three metrics are then compared one-to-one with pre-defined availability thresholds. These thresholds are set based on the stable operation requirements of the node's environment; for example, the CPU utilization threshold could be set to 80%, the memory usage threshold to 75%, and the bandwidth usage threshold to 70%. These thresholds are determined after a comprehensive evaluation of the node's hardware configuration and task load characteristics. The judgment process involves comparing whether CPU utilization is less than 80%, memory usage is less than 75%, and bandwidth usage is less than 70%. If any one of these exceeds the threshold, the resource is deemed unavailable; otherwise, the resource is deemed available. If a node is available, it is marked as an available node. If one or more nodes are unavailable, it is marked as an unavailable node. For example, if node X21 has a CPU utilization of 72%, a memory utilization of 68%, and a bandwidth utilization of 55%, all three values ​​are within the threshold range, so this node is determined to be available. However, if node Y09 has a CPU utilization of 85%, a memory utilization of 69%, and a bandwidth utilization of 63%, since its CPU utilization exceeds the threshold of 80%, this node is determined to be unavailable. After determining the availability of all nodes, the availability determination result of each node is output along with its node identifier, forming a pairwise data set of node identifier and availability status, and finally obtaining the node availability status.

[0038] The task landing point association submodule associates available nodes with corresponding task fragment identifiers based on the node availability status to obtain a cross-domain task landing point table. First, the set of node identifiers that have been determined to be available is read. Then, the task fragment identifier information corresponding to each available node is retrieved sequentially from the data table. The node identifier is used as an index parameter to locate the corresponding task fragment data. If a node has multiple task fragment identifiers, they are arranged according to the numerical order of the task fragment identifiers and form a one-to-one or one-to-many pairing relationship with the node identifiers. During this process, the task fragment identifiers of all nodes are cross-checked to ensure that there are no duplicate pairing records. For example, if node A13 corresponds to task fragments T001 and T003, node B07 corresponds to task fragment T002, and node C19 corresponds to task fragments T004 and T005, then the pairing... In the records, node A13 forms one associated record with T001 and another associated record with T003, and so on. When there are many nodes, they can be sorted first by the alphabetical sequence of the node identifiers, and then sorted within each node according to the size of the task fragment identifier number, so as to maintain the consistency of the order of the paired records. After the pairing is completed, all paired records are merged into a set of cross-domain task landing point records. Each record contains a direct correspondence between the node identifier and the corresponding task fragment identifier, such as forming grouped data like A13-T001, A13-T003, B07-T002, C19-T004, C19-T005, and finally the cross-domain task landing point table is obtained.

[0039] Please see Figure 8 The remote operation and maintenance method for entertainment equipment based on the Internet of Things and SaaS platform is executed based on the aforementioned remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform, and includes the following steps: S1: Obtain the device number, access port, and IoT gateway MAC address of the entertainment terminal; read the licensed device number entry from the SaaS tenant configuration table; compare the device number with the license number; analyze the correspondence between the access port and the gateway MAC address; remove duplicates by device number; and obtain a list of connected terminals. S2: Based on the list of connected terminals, obtain the CPU utilization, memory usage and network bandwidth usage of each terminal, compare the running data with the resource configuration standard, analyze the terminal's usage in CPU, memory and bandwidth, and obtain the terminal running status table; S3: Based on the terminal running status table, extract the task segment identifier and data block version for matching, analyze whether they are consistent, classify inconsistent devices as cache conflict items, and obtain a cache conflict list according to device number and task segment identifier. S4: Based on the cache conflict list, filter conflict entries, obtain task fragment identifiers and data block versions, compare them with the current version record, update to the current version if the versions are inconsistent, and assign task fragments to nodes with idle processing thread occupancy to obtain the task allocation mapping table. S5: Based on the task allocation mapping table, obtain the CPU utilization, memory usage and network bandwidth usage of the target cross-domain data center node, analyze the node resource availability, associate the node with the task fragment identifier, and obtain the cross-domain task landing point table.

[0040] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A remote operation and maintenance system for entertainment equipment based on the Internet of Things and a SaaS platform, characterized in that: The system includes: The terminal access verification module obtains the terminal device number, access port and gateway MAC address, reads the license number, compares the number and analyzes the port and MAC correspondence, removes duplicates by number, and obtains a list of connected terminals. The load monitoring module collects CPU utilization, memory usage and bandwidth usage based on the list of connected terminals, compares the collected data with the resource configuration standard, analyzes resource usage and bottlenecks, and obtains a terminal operation status table. The cache status verification module matches the task segment identifier and data block version based on the terminal running status table, analyzes the consistency, marks inconsistent devices as cache conflicts, and obtains a cache conflict list. Based on the cache conflict list, the task distribution mapping module filters conflict entries, compares the task fragment and data block versions with the current version, updates inconsistent versions to the current version, and then allocates the updated task fragments to idle nodes to obtain the task distribution mapping table. Based on the task allocation mapping table, the cross-domain resource allocation module obtains the CPU utilization, memory usage, and bandwidth usage of cross-domain nodes, analyzes resource availability, associates nodes with task fragment identifiers, and obtains a cross-domain task landing point table.

2. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that: The list of connected terminals includes device number, access port, and IoT gateway MAC address. The terminal operation status table includes CPU utilization, memory usage, and network bandwidth usage. The cache conflict list includes device number, task fragment identifier, and cache conflict status. The task allocation mapping table includes task fragment identifier, data block version, and processing thread node. The cross-domain task landing point table includes cross-domain data center node, task fragment identifier, and node resource availability.

3. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that, The resource configuration standard refers to the process of analyzing the target range of CPU utilization, memory usage, network bandwidth usage, etc. during the load monitoring process, collecting real-time usage data of terminals and nodes, and comparing them with the target range in turn to determine whether the resource usage is normal. The resource usage and bottlenecks refer to the process of collecting the CPU, memory, and bandwidth usage rates of each terminal, comparing the data item by item with the target range of the resource configuration standard, judging the usage ratio and trend of resources, and analyzing the links with high usage.

4. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that, The conflict entry refers to the process of comparing the task fragment identifier with the corresponding data block version item by item during cache status verification. When the versions are inconsistent, the corresponding device number and task fragment identifier are extracted and put into the subsequent version update and task allocation process. The cross-domain node CPU utilization rate refers to the process of first obtaining the number of used cores and the total number of cores of the target cross-domain data center node during the cross-domain resource allocation process, comparing the relationship, analyzing whether the node's computing resources meet the allocation conditions, and arranging task distribution when the resource status is within the executable range.

5. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that, The terminal access verification module includes: The device number acquisition submodule obtains the device number, access port and IoT gateway MAC address of the entertainment terminal, associates the device number with the access port and MAC address, and obtains the port and gateway correspondence information. The information comparison submodule, based on the port and gateway correspondence information, reads the licensed device number entries from the SaaS tenant configuration table, compares the device number with the licensed device number, filters matching entries, and obtains matching device information. The access deduplication submodule, based on the matching device information, calls the device number of the matching entry, deduplicates the duplicate numbers, and obtains a list of connected terminals.

6. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that, The load monitoring module includes: Based on the list of connected terminals, the data acquisition submodule obtains the CPU utilization, memory usage, and network bandwidth usage of each terminal. For the same terminal, the usage rate is sequenced according to the device number and access port order, and the current value is appended according to the collection time order to obtain the terminal usage rate sequence. The resource comparison submodule, based on the terminal occupancy rate sequence, compares the CPU utilization rate standard value, memory occupancy rate standard value, and bandwidth occupancy rate standard value in the resource configuration standard with the corresponding items in the sequence, calculates the CPU occupancy rate ratio, and appends the comparison results according to the terminal number to obtain the resource comparison table; Based on the resource comparison table, the resource usage analysis submodule analyzes the CPU, memory and bandwidth usage of the terminal, arranges the comparison ratio and device number into corresponding status entries, and associates them with the terminal list according to the access port order to obtain the terminal running status table.

7. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that, The cache status verification module includes: Based on the terminal running status table, the task extraction submodule extracts the task segment identifier and data block version of the device, and obtains the task version corresponding information by matching the task segment identifier with the corresponding data block version. The version matching submodule analyzes whether the versions are consistent based on the task version corresponding information, the version-by-task fragment identifier and data block, calculates the distribution density of devices with inconsistent versions, and obtains the version abnormal distribution status. The conflict classification submodule filters out device information with inconsistent versions based on the abnormal distribution status of the versions, and obtains a cache conflict list by associating the corresponding device number and task segment identifier.

8. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that, The task distribution mapping module includes: The conflict filtering submodule filters entries with cache conflicts based on the cache conflict list, extracts task fragment identifiers and data block versions, and matches the data with the device number of the entry to obtain conflict task information. Based on the conflict task information, the version update submodule obtains the task fragment identifier and data block version, compares them item by item with the current version record, and selects the current version data block to replace it when the versions are inconsistent, thereby obtaining the update task information. Based on the updated task information and the processing thread occupancy rate of the nodes, the task dispatch submodule filters out nodes that are in an idle state, and assigns the updated task fragments to the nodes to obtain a task allocation mapping table.

9. The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform according to claim 1, characterized in that, The cross-domain resource allocation module includes: Based on the task allocation mapping table, the resource acquisition submodule obtains the CPU utilization, memory usage, and network bandwidth usage of the target cross-domain data center node, and obtains the node resource information by matching each data item with the corresponding node identifier. The availability analysis submodule analyzes the CPU, memory and bandwidth usage of the nodes based on the node resource information, determines the resource availability status, analyzes the corresponding results and node identifiers, and obtains the node availability status. The task landing point association submodule associates available nodes with corresponding task fragment identifiers based on the node availability status to obtain a cross-domain task landing point table.

10. A method for remote operation and maintenance of entertainment equipment based on the Internet of Things and a SaaS platform, characterized in that, The remote operation and maintenance system for entertainment equipment based on the Internet of Things and SaaS platform as described in any one of claims 1-9 includes the following steps: S1: Obtain the device number, access port, and IoT gateway MAC address of the entertainment terminal; read the licensed device number entry from the SaaS tenant configuration table; compare the device number with the license number; analyze the correspondence between the access port and the gateway MAC address; remove duplicates by device number; and obtain a list of connected terminals. S2: Based on the list of connected terminals, obtain the CPU utilization, memory usage and network bandwidth usage of each terminal, compare the running data with the resource configuration standard, analyze the terminal's usage in CPU, memory and bandwidth, and obtain the terminal running status table; S3: Based on the terminal running status table, extract the task segment identifier and data block version for matching, analyze whether they are consistent, classify inconsistent devices as cache conflict items, and obtain a cache conflict list according to the device number and task segment identifier. S4: Based on the cache conflict list, filter conflict entries, obtain task fragment identifiers and data block versions, compare them with the current version record, update to the current version if the versions are inconsistent, assign task fragments to nodes with idle processing thread occupancy, and obtain a task allocation mapping table. S5: Based on the task allocation mapping table, obtain the CPU utilization, memory usage and network bandwidth usage of the target cross-domain data center node, analyze the node resource availability, associate the node with the task fragment identifier, and obtain the cross-domain task landing point table.

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