A data intelligent interaction method and system based on cross-platform data communication

Abstract

The present invention relates to a data intelligent interaction method and system based on cross-platform data communication, the method comprising: creating an interactive service pool, the interactive service pool comprising a plurality of interactive services, each interactive service being used to serve the data interaction request of a program; real-time monitoring of the density of the interactive service pool, when the density is greater than a first density threshold, adopting a first control method to perform density control, and judging whether the density decreases; if it decreases, performing continuous real-time monitoring; otherwise, adopting a second control method to adjust the interactive service pool. The present invention adaptively changes the interactive service control mode around the communication end or the program end as the main body of intelligent control, and can perform all-round and multi-level intelligent control under different interactive service states, thereby improving the efficiency of data interaction.

Description

Technical field

[0001] The present invention belongs to the technical field of data intelligent interaction, and in particular relates to a data intelligent interaction method and system based on cross-platform data communication. [Background Technology]

[0002] Cross-platform data communication refers to the ability to transmit and exchange data between disparate software, hardware, operating systems, networks, and devices. This communication method must overcome differences between platforms to ensure seamless, secure, and efficient data flow. Cross-platform data communication is crucial in modern information technology because it allows diverse systems and applications to collaborate and share data and resources. Computer applications running on one computing system often need to communicate with other computer applications running on other computing systems. One method for communication between these computer applications is to establish direct links between the computer systems. Communication between systems in business-to-business applications, web services, database mining, and other applications increasingly relies on XML technology to develop, disseminate, and exchange data and knowledge. With the advancement of communication mechanisms, existing systems also need to be able to communicate and exchange with web servers and systems that incorporate new communication protocols. A common key technology in cross-platform data communication is synchronous communication (synchronous / blocking calls). Interacting services communicate synchronously through HTTP requests, typically requiring the calling service to wait for the called service to process the request and return a response. This approach is simple to implement, using standard HTTP client libraries. However, if the service response is slow, the calling service's thread will be blocked, impacting performance. There's also asynchronous communication (asynchronous / non-blocking calls), which uses message queues (such as RabbitMQ, Kafka, and ActiveMQ) for asynchronous communication. One service sends messages to a message queue, and another service reads and processes them. When using message queues, client applications running on a computing system can send messages to a queue or a list of intended recipients, receive messages from a queue, and register to be notified of messages in the queue. This approach improves system responsiveness and scalability, as services don't directly block or wait for each other. However, its implementation is complex, requiring handling of message acknowledgments, retries, and failed message processing. Another approach is event-driven communication, in which services communicate through publishing and subscribing to events. When a significant event occurs in a service, it publishes the event to an event bus or message queue, and other services subscribe to and respond to these events. This approach allows for the construction of highly decoupled and scalable systems, allowing services to be scaled and deployed independently. However, its disadvantage is increased system complexity, requiring the management of issues such as event ordering, loss, and duplication. There's also Remote Procedure Call (RPC): Direct calls between services are made through RPC frameworks (such as gRPC). This is similar to local method calls, but the calls are executed on the remote service. Its advantage is that calls are simple and objects and methods can be used directly. Its disadvantage is that it increases coupling between services, and network delays or service failures can affect the performance of the calling service. There's also service mesh technology, which uses a service mesh to manage communication between services, providing capabilities such as service discovery, load balancing, fault recovery, metrics, and monitoring.It can reduce the complexity of service communication and provide consistent communication strategies and security mechanisms; however, it increases the complexity of the system and resource consumption.

[0003] In the era of big data and artificial intelligence, the importance of data intelligence applications continues to grow, as data and intelligent technologies are becoming key drivers of business and social development. Big data technology can process and analyze massive amounts of data, providing deep insights and trend analysis, helping businesses and organizations make more informed decisions. Real-time data analysis can help monitor business processes and system performance, quickly identifying and resolving problems. With technological advancements, the application of data intelligence will become more widespread and in-depth, becoming an indispensable part of modern society. Existing technologies fail to consider the inherent characteristics of the communication and programming terminals in intelligent analysis, and fail to utilize the big data information contained in historical operational data to discover these characteristics and guide the implementation of intelligent interactive services. Therefore, how to consider the inherent characteristics of the communication and programming terminals, discover the big data information contained in operational data, and guide intelligent interaction in cross-platform data communication is a technical problem to be solved. To address the problems in the existing technology, the present invention adaptively changes the interactive service control method around the communication terminal or programming terminal as the main body of intelligent control, enabling comprehensive and multi-level intelligent control under different interactive service states, thereby improving the efficiency of data interaction. [Summary of the invention]

[0004] In order to solve the above problems in the prior art, the present invention proposes a data intelligent interaction method and system based on cross-platform data communication, the method comprising:

[0005] Step S1: Create an interactive service pool, which contains N×T interactive services n，t , each interactive service is used to serve the data interaction request of a program; where: T is the time width of the interactive service pool, and N is the spatial size of the interactive service pool; after receiving a data interaction request, when there is an idle interactive service in the interactive server pool, an interactive service is assigned to the data interaction request based on the order of columns first and rows; each interactive service has two attributes, the first attribute a1 is the communication platform, communication mechanism or communication object type, and the second attribute a2 is the type of program served; correspondingly, the interactive service pool corresponds to two matrices, the first matrix MX1=[a1 n，t ] corresponds to the first attribute of the interactive service; each element in the second matrix corresponds to the second attribute of the interactive service MX2 = [a2 n，t ]; where: n = 1 to N, t = 1 to T; interactive services are implemented in the order from the head to the tail of the interactive service pool;

[0006] Step S2: Monitor the density of the interactive service pool in real time. If the density is greater than a first density threshold, use a first control method to control the density and determine whether the density is decreasing. If it is decreasing, return to step S2 for continuous real-time monitoring. Otherwise, use a second control method to adjust the interactive service pool. The density indicates the degree of congestion of interactive services in the interactive service pool.

[0007] The density control is performed by adopting the first control mode, specifically: setting the allocation mode of the interactive service to the first allocation mode; obtaining the first matrix MX1 of the interactive service pool = [a1 n，t ]; compare the first matrix and the first matrix sample to determine the first control object, and schedule the first control object to the head position of the interactive service pool; wherein: the first control object includes one or more interactive services;

[0008] The second control method is used to adjust the interactive service pool, specifically: setting the interactive service allocation method to the second allocation method; obtaining the second matrix MX2 of the interactive service pool = [a2 n，t ]; obtain second matrix samples of the same type and number as the second matrix as target second matrix samples; adjust the interactive service pool based on the target second matrix samples so that the second matrix corresponding to the adjusted interactive service pool contains submatrices that are the same as the target second matrix; the same type and number means that the two matrices have the same type of element values ​​and the same number of elements with the same element value, but the position distribution of these element values ​​in the matrix is ​​different;

[0009] The adjusting of the interactive service pool based on the target second matrix samples is specifically as follows: replacing the second matrix portion having the same type and number as the target second matrix samples to obtain an updated second matrix; and adjusting the position of the interactive service in the interactive service pool corresponding to the second matrix portion so that the adjusted second matrix of the interactive service pool is equal to the updated second matrix.

[0010] Furthermore, after receiving the data interaction request, when there is no idle interaction service in the interaction server pool, the data interaction request waits in a queue outside the interaction server pool.

[0011] Furthermore, the interactive service pool is managed in a circular queue manner.

[0012] Furthermore, the interactive service pool is managed by a circular data heap method.

[0013] Furthermore, by sliding the pointer, the interactive service allocated first is always at the head of the interactive service pool, and one interactive service is taken from the head of the interactive service pool each time for implementation.

[0014] Furthermore, after the interactive service pool is adjusted using the second control method, the density of the interactive service pool is continuously monitored in real time, and after the density is less than or equal to the second density threshold, the density control is switched to the first control method.

[0015] A data intelligent interaction system based on cross-platform data communication, wherein the data intelligent interaction system based on cross-platform data communication is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication.

[0016] A data intelligent interaction device based on cross-platform data communication, wherein the data intelligent interaction device based on cross-platform data communication is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication.

[0017] A data intelligent interaction platform based on cross-platform data communication, wherein the data intelligent interaction platform based on cross-platform data communication is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication.

[0018] A data intelligent interaction server based on cross-platform data communication, characterized in that the data intelligent interaction server based on cross-platform data communication is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication.

[0019] The beneficial effects of the present invention include:

[0020] (1) Adaptively change the interactive service control mode around the communication end or the program end as the main body of intelligent control, adopt two allocation modes and two corresponding control modes; set the allocation mode related to the busyness of the interactive service to correspond to it, one is conducive to introducing time information, and the other is conducive to discovering internal connections. Through the phased switching of the allocation mode, control mode, and attribute-based matrix, all-round intelligent control is achieved under different interactive service states, thereby improving the efficiency of data interaction;

[0021] (2) In view of the diverse impact of the diversity of communication terminals on the efficiency of interactive service implementation during cross-platform data communication, a density-based sensitive indicator is constructed to discover the first control object containing U interactive services with scale changes and prioritize their implementation. This can quickly improve the implementation speed of interactive services while being transparent to the real-time parameters of the communication terminals. It is suitable for interactive services in complex cross-platform data communications.

[0022] (3) When the program side is used as the subject of intelligent control, the influence of the service program type and the order of its request on the efficiency of interactive services is discovered through intelligent analysis. Through local adjustment of the interactive service pool, the regional distribution of the local interactive services in the interactive service pool in the matrix is ​​optimized, which potentially changes the influence of the inherent correlation between different types of programs on the efficiency of interactive services. Therefore, without changing the order of interactive service requests, the efficiency of interactive services is improved based on data intelligent analysis.

Brief Description of the Drawings

[0023] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application, but do not constitute an improper limitation of the present invention. In the drawings:

[0024] Figure 1 Schematic diagram of the data intelligent interaction method based on cross-platform data communication provided by the present invention. [Specific implementation method]

[0025] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The exemplary embodiments and descriptions are only used to explain the present invention but are not intended to limit the present invention.

[0026] The present invention proposes a data intelligent interaction method and system based on cross-platform data communication, as shown in the attached Figure 1 As shown, the method includes the following steps:

[0027] Step S1: Create an interactive service pool, which contains N×T interactive services n，t , each interactive service is used to serve the data interaction request of a program; where: T is the time width of the interactive service pool, and N is the spatial size of the interactive service pool; after receiving a data interaction request, when there is an idle interactive service in the interactive server pool, an interactive service is assigned to the data interaction request based on the order of column (time) first and row (space) second (that is, an interactive service unit is assigned in the interactive service pool); each interactive service has two attributes, the first attribute a1 is the communication platform, communication mechanism or communication object type (or identifier), and the second attribute a2 is the type of program served (the type of the interactive service request issuer); correspondingly, the interactive service pool corresponds to two matrices, the first matrix MX1=[a1 n，t ] corresponds to the first attribute of the interactive service; each element in the second matrix corresponds to the second attribute of the interactive service MX2 = [a2 n，t ]; where: n = 1 ~ N, t = 1 ~ T; in general, when implementing interactive services, from the head to the tail of the interactive service pool, that is, s1, 1, s 1，2 ,...,s N，TGet an interactive service from the interactive service pool in the order and use its communication mechanism to communicate;

[0028] Preferably: after receiving the data interaction request, when there is no idle interaction service in the interaction server pool, the data interaction request is queued outside the interaction server pool;

[0029] Preferably, the interactive service pool is managed in a circular queue manner. By means of a pointer sliding, the first interactive service allocated is always at the head of the interactive service pool. Each time, an interactive service is taken out from the head of the interactive service pool to implement an interactive service request; the taken interactive service is activated; the tail pointer of the interactive service pool points to the next interactive service of the last allocated interactive service (that is, the next idle interactive service to be allocated); obviously, when s 1，1 After being implemented, 1，2 Becoming the head means becoming the new s 1，1 ; N, T are preset values;

[0030] Preferred: N = 2 to 10; of course, the spatial size of the interactive service pool can be directly set to 1 to express one-dimensional interactive control, and the analysis of the matrix is ​​converted into the analysis of the sequence or vector;

[0031] The data interaction request is assigned an interactive service based on the order of column (time) first and row (space); specifically, two allocation modes are adopted; the first allocation mode is that when there is an idle interactive service in the interactive service pool, an interactive service is obtained from the end of the interactive service pool for allocation, and the interactive service pool is managed by time intervals. When a time interval passes, even if the interactive services in the time interval (the column) are not allocated, the time t at the end of the interactive service pool is set to t=t+1; that is, even if there is an unallocated interactive service at the end of the interactive service pool corresponding to the time interval t, it will be vacant and the next allocated interactive service will be s 1，t+1; The first matrix can better reflect the arrival time of data interaction requests, and contains time information; the second allocation mode is that when there is an idle interactive service in the interactive service pool, an interactive service is obtained from the tail of the interactive server pool for allocation; the time interval elapsed is not considered, that is, there is no dangling interactive service between the allocated interactive services; by default, the first mode is selected for allocation; it can be seen that no matter which allocation method is adopted, the communication resources themselves have not changed or been wasted, but the way the interactive service resources are used is different; two allocation modes correspond to two control methods, and the two allocation methods and the interactive service pool The idle or busy degree is related. Under the first allocation mode, the interactive service pool can be considered to be in a relatively idle state, and the embodiment of effective time information is also suitable for control using the first control mode. However, when the state of the interactive service pool changes, it is insufficient to solve the interaction problem only from the communication segment, and the importance of time information decreases. Therefore, switching to the second allocation mode is coordinated. On the basis of reducing the waste of interactive service pool resources, it is suitable for the deployment of the second control mode. In this way, all-round intelligent control is carried out from aspects such as allocation mode, control mode, and attribute usage. The communication end or program end is adaptively selected as the main body of intelligent control, thereby improving the efficiency of data interaction.

[0032] Preferably, each interactive service runs in its own process and interacts via a lightweight communication mechanism; for example, using an HTTP resource API, such as a RESTful API or gRPC.

[0033] Preferably, each interactive service is set in the program, and when the data interactive pool is idle, the interactive service set in the program is activated; at this time, the interactive service in the interactive service pool serves as an activation key to authorize the interactive service program placed in the program;

[0034] Preferably: the program is an application, process, thread, etc. that issues an interactive service request running entity;

[0035] Step S2: Monitor the density of the interactive service pool in real time. If the density is greater than a first density threshold, use the first control method to control the density and determine whether the density is decreasing. If it is decreasing (or decreases to less than or equal to the first density threshold within a preset time interval), return to step S2 for continuous real-time monitoring. Otherwise, use the second control method to adjust the interactive service pool.

[0036] Preferably: after the interactive service pool is adjusted using the second control method, the density of the interactive service pool is continuously monitored in real time, and after the density is less than or equal to the second density threshold, the density control is switched to the first control method;

[0037] Preferably, the first density threshold and the second density threshold are preset values;

[0038] Preferably: the first density threshold is set to be equal to the second density threshold;

[0039] Preferred: After changing to the second allocation method, the suspended interactive services in the interactive service pool are deleted, and the data interaction requests queued into the interactive service pool are entered in sequence and are assigned interactive services accordingly;

[0040] The real-time monitoring of the interactive service element density, specifically: the number of non-dangling elements in the interactive service pool divided by N × T as the element density; the interactive service pool is not assigned interactive services are set to dangling;

[0041] Alternatively: when the first control mode is adopted, the real-time monitoring of the density of interactive service elements is specifically as follows: obtaining the last non-dangling element s in the interactive service pool n，t The number (n, t) will As the element density; where: n1 is the non-dangling element s in the interactive service pool n，t The number of all non-dangling elements before;

[0042] The density control is performed by adopting the first control mode, specifically: setting the allocation mode of the interactive service to the first allocation mode; obtaining the first matrix MX1 of the interactive service pool = [a1 n，t ]; compare the first matrix with the first matrix sample to determine the first control object, and schedule the first control object to the head position of the interactive service pool to increase the priority of the first control object to be implemented; wherein: the first control object includes one or more interactive services; obviously, other interactive services that are not scheduled are shifted back in order to reduce the priority of implementation;

[0043] Preferably: the correspondence between the first matrix sample and the first control object is pre-acquired and saved; specifically: historical data (simulation data) is sorted according to the first allocation mode to obtain an interactive service sequence with a width of N (a time interval T is used as a restriction during the sorting process so that the interactive services with a width of N are all within a time interval T); a time window T is slid in the interactive service sequence, and each slide corresponds to an N×T historical first matrix HMX1; for the historical first matrix and its corresponding interactive service pool, if the control mode is to prioritize the implementation of the first control object containing U interactive services, so that the density of the interactive service pool decreases fastest after the implementation of the U interactive services, the corresponding historical first matrix is ​​used as the first matrix sample, and the correspondence between the first matrix sample and the first control object is saved; because the U value is different, each first matrix sample corresponds to one or more control objects; obviously, the historical data when the first allocation mode is adopted can be directly analyzed; and the historical data is operation log data or simulation data; when simulation data is used, the density decrease after the priority implementation of different control objects under different interactive service pools can be directly simulated;

[0044] Further: setting the U value to be equal to the average number of interactive service implementations in a current time interval; determining a first control object with a length of U corresponding to the first matrix sample;

[0045] The method for determining the density reduction is to calculate the density reduction value dr using the following formula (1); where: drb, dra are the densities before and after the control method is adopted; α1, α2, ... αU are the density adjustment coefficients corresponding to the communication platform, communication mechanism or communication object type of U interactive services;

[0046] dr=(drb-dra)×(α1+α2+,...αU) / U(1);

[0047] Preferably: α1, α2, ... αU are preset values; when the communication platform, communication mechanism or communication object type makes the interactive service implementation speed faster, the density adjustment coefficient value is larger, otherwise, it is smaller;

[0048] The first matrix is ​​compared with the first matrix sample to determine the first control object, specifically: calculating the first matrix MX1 = [a1 n，t ] and the first matrix sample HMX1 = [ha1 n，t ] similarity r1;

[0049] Preferably, the similarity r1 is calculated using the following formula (2):

[0050]

[0051] The second control method is used to adjust the interactive service pool, specifically: setting the interactive service allocation method to the second allocation method; obtaining the second matrix MX2 of the interactive service pool = [a2 n，t ]; obtaining second matrix samples that match the number of second matrix types as target second matrix samples; adjusting the interactive service pool based on the target second matrix samples so that the second matrix corresponding to the adjusted interactive service pool contains the same submatrix as the target second matrix;

[0052] Preferably: the second matrix sample size is less than or equal to the second matrix;

[0053] Preferably: the sub-matrix is ​​a true sub-matrix or a false sub-matrix;

[0054] The acquiring of the second matrix sample that matches the second matrix as the target second matrix sample specifically includes the following steps:

[0055] Step S2A1: Determine the current sample size CrSz = Nx × Tx; obtain a second matrix sample with a sample size equal to the current sample size as a second matrix sample to be processed;

[0056] Preferably: the initial value of the current sample size CrSz is N×T;

[0057] Step S2A2: Acquire an unprocessed second matrix sample to be processed, set the window size to be equal to the second matrix sample size, and slide the window in the second matrix. When the number of types of the second matrix portion within the window and the second matrix sample is the same, use the second matrix sample as the target second matrix sample. The same number of types means that the two matrices have the same element value types (for example, both matrices have only element values ​​of 1 and 2, and do not have other types of element values), and have the same number of elements with the same element value (the same number of elements with the value of 1 and the value of 2), while the position distribution of these element values ​​in the matrices is different. Obviously, when the number of types of the two matrices is the same, the two matrices are actually different. Repeat this step until there is no unprocessed second matrix sample to be processed or the target second matrix sample is found.

[0058] Step S2A3: If the current sample size is the minimum sample size, then end; otherwise, reduce the current sample size and return to step S2A1;

[0059] Preferably, the minimum sample size is a preset value; for example: 1×2, 2×1, 2×2;

[0060] The reducing the current sample size is specifically as follows: assuming that the current sample size CrSz=Nx×Tx, it is reduced to (Nx-1)×(Tx-1);

[0061] Alternatively, the current sample size is reduced, specifically, assuming that the current sample size CrSz = Nx × Tx, then the current sample size is reduced to (Nx) × (Tx-1) or (Nx-1) × (Tx);

[0062] Preferably: when there are multiple target second matrix samples, the sample with the smallest size is selected for adjustment;

[0063] Alternatively: when there are multiple samples of the target second matrix, select the sample with the largest size for adjustment;

[0064] The adjustment of the interactive service pool based on the target second matrix sample is specifically as follows: replacing the second matrix portion having the same number of types as the target second matrix sample with the target second matrix sample to obtain an updated second matrix; adjusting the position of the interactive service in the interactive service pool corresponding to the second matrix portion so that the adjusted second matrix of the interactive service pool is equal to the updated second matrix; through the adjustment of the interactive service pool, the interactive services are adaptively changed in order according to the different types of programs served, potentially changing the impact of the inherent correlation between different types of programs on the efficiency of the interactive services, thereby guiding the improvement of the efficiency of the interactive services based on data intelligent analysis without changing the order of interactive service requests;

[0065] Preferably, the second matrix sample is obtained by simulation; during the simulation, an interactive service pool and its corresponding second matrix are determined, and a sliding window of the interactive service pool is set according to the current sample size; the position of elements in the second matrix portion (and its corresponding interactive service pool) within the sliding window is randomly changed and the interactive service pool is adjusted accordingly, and the element value and position within the window with the shortest time for implementing all interactive services in the interactive service pool are determined as the candidate second matrix sample; for the same interactive service pool, the position of the window in the second matrix is ​​changed by sliding the window during the simulation, and the candidate second matrix sample is determined again; therefore, changing the window position once will obtain a candidate second matrix sample; after the sliding is completed, the number of occurrences of the repeated candidate second matrix samples is counted; the interactive service pool and its corresponding second matrix are replaced, and the above simulation process is repeated until the cutoff condition is met; the candidate second matrix sample with the largest number of occurrences is selected as the target second matrix sample;

[0066] Preferably: the cut-off condition is that the number of simulations reaches a preset value, or the count shows significance;

[0067] Alternatively: select the top 5-10% of the candidate second matrix samples as the target second matrix samples;

[0068] Based on the same inventive concept, the present invention also provides a data intelligent interaction system based on cross-platform data communication, which is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication;

[0069] Based on the same inventive concept, the present invention also provides a data intelligent interaction device based on cross-platform data communication, which is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication;

[0070] Based on the same inventive concept, the present invention also provides a data intelligent interaction platform based on cross-platform data communication, which is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication;

[0071] Based on the same inventive concept, the present invention also provides a data intelligent interaction server based on cross-platform data communication, and the server is used to implement the above-mentioned data intelligent interaction method based on cross-platform data communication.

[0072] A computer program (also referred to as a program, software, software application, script, or code) can be written in any form of programming language, including assembly or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program, or in multiple collaborative files (e.g., files storing one or more modules, subroutines, or code portions). A computer program can be deployed to execute on one computer or on multiple computers located at one site or distributed across multiple sites and interconnected by a communication network.

[0073] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0075] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A data intelligent interaction method based on cross-platform data communication, characterized in that: The method comprises: Step S1: Create an interactive service pool, which contains interactive services Each interactive service is used to serve the data interaction request of a program; wherein: is the time width of the interactive service pool, is the spatial size of the interactive service pool; after receiving a data interaction request, when there is an idle interactive service in the interactive service pool, an interactive service is assigned to the data interaction request based on the order of columns first and rows; each interactive service has two attributes, the first attribute Is the communication platform, communication mechanism or communication object type, the second attribute Is the type of program being served; correspondingly, the interactive service pool corresponds to two matrices, the first matrix Each element in the matrix corresponds to the first attribute of the interactive service; each element in the second matrix corresponds to the second attribute of the interactive service ;in: ; Implement interactive services in the order from the head to the tail of the interactive service pool; Step S2: Monitor the density of the interactive service pool in real time. If the density is greater than a first density threshold, use a first control method to control the density and determine whether the density is decreasing. If it is decreasing, return to step S2 for continuous real-time monitoring. Otherwise, use a second control method to adjust the interactive service pool. The density indicates the degree of congestion of interactive services in the interactive service pool. The density control is performed by adopting the first control mode, specifically: setting the allocation mode of the interactive service to the first allocation mode; obtaining the first matrix of the interactive service pool ; Compare the first matrix and the first matrix sample to determine the first control object, and schedule the first control object to the head position of the interactive service pool; wherein: the first control object includes one or more interactive services; The second control method is used to adjust the interactive service pool, specifically: setting the allocation method of the interactive service to the second allocation method; obtaining the second matrix of the interactive service pool ; Obtain second matrix samples of the same type and number as the second matrix as target second matrix samples; Adjust the interactive service pool based on the target second matrix samples so that the second matrix corresponding to the adjusted interactive service pool contains submatrices identical to the target second matrix; The same type and number means that the two matrices have the same element values ​​and the same number of elements with the same element values, but the position distribution of these element values ​​in the matrices is different; The adjusting of the interactive service pool based on the target second matrix samples is specifically as follows: replacing the second matrix portion having the same type and number as the target second matrix samples to obtain an updated second matrix; and adjusting the position of the interactive service in the interactive service pool corresponding to the second matrix portion so that the adjusted second matrix of the interactive service pool is equal to the updated second matrix.

2. The data intelligent interaction method based on cross-platform data communication according to claim 1, characterized in that: After receiving the data interaction request, when there is no idle interaction service in the interaction service pool, the data interaction request waits in a queue outside the interaction service pool.

3. The data intelligent interaction method based on cross-platform data communication according to claim 2, characterized in that: The interactive service pool is managed in a circular queue manner.

4. The data intelligent interaction method based on cross-platform data communication according to claim 3 is characterized in that: The interactive service pool is managed by a circular data heap.

5. The data intelligent interaction method based on cross-platform data communication according to claim 4 is characterized in that: By sliding the pointer, the interactive service allocated first is always at the head of the interactive service pool, and one interactive service is taken from the head of the interactive service pool for implementation each time.

6. The data intelligent interaction method based on cross-platform data communication according to claim 5, characterized in that: After the interactive service pool is adjusted using the second control method, the density of the interactive service pool is continuously monitored in real time, and after the density is less than or equal to the second density threshold, the density control is switched to the first control method.

7. A data intelligent interaction system based on cross-platform data communication, characterized in that: The data intelligent interaction system based on cross-platform data communication is used to implement the data intelligent interaction method based on cross-platform data communication described in any one of claims 1 to 6.

8. A data intelligent interaction device based on cross-platform data communication, characterized in that: The data intelligent interaction device based on cross-platform data communication is used to implement the data intelligent interaction method based on cross-platform data communication described in any one of claims 1 to 6.

9. A data intelligent interaction platform based on cross-platform data communication, characterized in that: The data intelligent interaction platform based on cross-platform data communication is used to implement the data intelligent interaction method based on cross-platform data communication described in any one of claims 1 to 6.

10. A data intelligent interactive server based on cross-platform data communication, characterized in that: The data intelligent interaction server based on cross-platform data communication is used to implement the data intelligent interaction method based on cross-platform data communication described in any one of claims 1 to 6.

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