A distributed information processing method and device for simulation environment

Abstract

The present invention discloses a distributed information processing method and device for simulation environment. The method is implemented by using a master simulation node and a slave node. The master simulation node is used to receive user information sent by each slave node to construct a game simulation environment; the slave node is used to receive user information and send the user information to the master simulation node; the master simulation node and the slave node are connected through a plurality of routers; all routers constitute a router network; the router includes a port; the port includes a transmission channel and a buffer queue set; the buffer queue set includes a plurality of buffer queues; the method includes: using each slave node, according to a preset sampling time interval T, obtaining its user information set; for any slave node, preprocessing the obtained user information set to obtain its preprocessed user information set; for any slave node, using a transmission link processing model to process the preprocessed user information set to obtain a corresponding optimal routing path; based on the optimal routing path of each slave node, sending the preprocessed user information set of the slave node to the master simulation node.

Description

Technical Field

[0001] The present invention relates to the field of computer simulation, and in particular to a distributed information processing method and device oriented to a simulation environment. Background Art

[0002] At present, virtual simulation and simulation technology are widely used in simulation scenarios of game confrontation. In the simulation process of multi-party game, the information of each participant needs to be input into the simulation system. At the same time, as the simulation program runs, it needs to be able to receive the input information of the participants in real time and reflect the information in the game confrontation process without affecting the normal operation of the game confrontation process.

[0003] How to receive and process the input information of each participant in real time while realizing the operation of game simulation, and add the input information to the game simulation process without affecting the normal operation of game simulation, is an urgent problem to be solved in the current simulation computing field. Summary of the invention

[0004] The present invention mainly solves the problem of how to receive and process input information of each participant in real time while realizing the operation of game simulation, and add the input information to the operation process of game simulation without affecting the normal operation of game simulation. The present invention discloses a distributed information processing method and device for simulation environment.

[0005] In a first aspect of the embodiment of the present application, a distributed information processing method for a simulation environment is disclosed, which is implemented by using a master simulation node and a slave node, wherein the master simulation node is used to receive user information sent by each slave node to construct a game simulation environment; the slave node is used to receive user information and send the user information to the master simulation node; the master simulation node and the slave node are connected through a plurality of routers; all routers constitute a router network; the router includes a port; the port includes a transmission channel and a buffer queue set; the buffer queue set includes a plurality of buffer queues; the method includes:

[0006] S1, using each slave node, according to the preset sampling time interval T, obtain its user information set;

[0007] S2, for any slave node, preprocessing the acquired user information set to obtain its preprocessed user information set;

[0008] S3, for any slave node, use the transmission link processing model to process the pre-processed user information set to obtain the corresponding optimal routing path;

[0009] S4, based on the optimal routing path of each slave node, sending the pre-processed user information set of the slave node to the master simulation node.

[0010] The preprocessing of the acquired user information set to obtain the preprocessed user information set includes:

[0011] S21, performing outlier elimination processing on the user information set to obtain a first data set;

[0012] S22, performing boundary check processing on the first data set to obtain a first information set;

[0013] S23, taking the slave node IP address as the source address and the master simulation node IP address as the target address, adding the source address and the target address to the first information set to obtain a preprocessed user information set; the preprocessed user information set includes several pieces of user information.

[0014] The performing boundary check processing on the first data set to obtain a first information set includes:

[0015] S221, for each type of data attribute of the first data set, using the data collection information of the data as an independent variable and the data value of the data as a dependent variable, perform autoregression-sliding average modeling to obtain regression models of the data attributes of the class; using the regression model, perform calculation processing on the independent variable to obtain regression data values; determine whether the absolute value of the difference between the regression data value and the corresponding dependent variable value is greater than a set first regression discrimination threshold; if it is greater than the first regression discrimination threshold, delete the data from the first data set; if it is less than the first regression discrimination threshold, do not process the data;

[0016] S222, after completing S221 for data of all data attributes, a first information set is obtained.

[0017] The sampling time interval T is calculated according to the node bandwidth allocation value R0, the link rate B0, and the flow data frame length F0, and its calculation expression is:

[0018] T=F0 / [B0sin(R0 / B0)],

[0019] Where T is the sampling time interval.

[0020] The method of processing the pre-processed user information set using the transmission link processing model for any slave node to obtain a corresponding optimal routing path includes:

[0021] S31, according to the source address in the pre-processed user information set of the slave node, determine the router closest to the source address as the source router; according to the target address in the pre-processed user information set, determine the router closest to the target address as the target router; determine the user information with the information sequence number 1 in the pre-processed user information set as the current user information;

[0022] S32, initializing a first measurement value;

[0023] S33, determining whether the target router address of the current user information is equal to the source router address plus 1, and obtaining a first determination result. If the first determination result is yes, the first measurement value is increased by 1; if the first determination result is no, no operation is performed on the first measurement value;

[0024] S34, determining whether the first measurement value is equal to a preset zeroing threshold value a1, and obtaining a second determination result; if the second determination result is yes, setting the first measurement value to 0, determining the next user information of the current user information in the pre-processed user information set as the current user information, and executing S33; if the second determination result is no, executing S35;

[0025] S35, determining whether the first measurement value is greater than a preset first threshold value β, and obtaining a third determination result; if the third determination result is yes, using the path optimization model to obtain an optimal path from the source router to the target router;

[0026] If the third judgment result is no, determine whether the judgment process described in S33 is completed for all user information in the user information set to obtain the fourth judgment result;

[0027] If the fourth judgment result is no, determine the next user information of the current user information in the pre-processed user information set as the current user information, and execute S33; if the fourth judgment result is yes, execute S36;

[0028] S36, obtaining the occupancy q of the transmission channel of the source router on the shortest path from the source router to the target router vc_m The occupancy of the transmission channel refers to the ratio of the number of transmission channels full of data to the total number of transmission channels of the router port;

[0029] S37, obtaining the occupancy q of the buffer queue of the router port in the shortest path m , and the occupancy of the buffer queue of the router port of the second shortest path q nm; The occupancy of the buffer queue refers to the ratio of the number of buffer queues full of data to the total number of buffer queues of the router port; using the parameter update model, the first threshold value β is updated; using the path optimization model, the optimal path from the source router to the target router is obtained.

[0030] The first threshold value β is calculated according to the parameters of the router network, and its calculation expression is:

[0031] β=a / (ah+1)×a1,

[0032] Wherein, a1 is a zeroing threshold value; the router network includes several groups; each group includes a routers; each router is connected to h slave nodes.

[0033] The path optimization model includes:

[0034] Among all intermediate groups of source routers and target routers in the router network, randomly select a group and determine the first router in the group as an intermediate node;

[0035] Taking the intermediate node as the demarcation point, obtaining the connection relationship of all routers between the demarcation point and the source router from the router network structure information, taking all routers between the demarcation point and the source router as points and the corresponding connection relationship as edges, constructing a first graph data structure set; the router network structure information includes the address of each router in the router network and the routers connected to it;

[0036] Taking the corresponding point of the source router as the starting point and the demarcation point as the end point; using the shortest path algorithm to solve the first graph data structure set, obtain the shortest path between the starting point and the end point, and determine the shortest path as the first path;

[0037] Taking the intermediate node as the demarcation point, obtaining the connection relationship of all routers between the demarcation point and the target router from the router network structure information, taking all routers between the demarcation point and the target router as points and the corresponding connection relationship as edges, constructing a second graph data structure set;

[0038] Taking the point corresponding to the target router as the end point and the demarcation point as the starting point; using the shortest path algorithm to solve the second graph data structure set, obtain the shortest path between the starting point and the end point, and determine that the shortest path is the second path;

[0039] The first path and the second path are concatenated to obtain an optimal path from the source router to the target router.

[0040] In a second aspect of the embodiment of the present application, a distributed information processing device for a simulation environment is disclosed, the device comprising:

[0041] A memory storing executable program code;

[0042] a processor coupled to the memory;

[0043] The processor calls the executable program code stored in the memory to execute the distributed information processing method oriented to the simulation environment.

[0044] In a third aspect of the embodiments of the present application, a computer storable medium is disclosed, wherein the computer storable medium stores computer instructions, and when the computer instructions are called, they are used to execute the distributed information processing method for the simulation environment.

[0045] In a fourth aspect of the embodiments of the present application, an information data processing terminal is disclosed, and the information data processing terminal is used to implement the distributed information processing method for the simulation environment.

[0046] The beneficial effects of the present invention are:

[0047] In the computer simulation system, the present invention receives and processes input information of each participant in real time while realizing the operation of game simulation, and adds the input information to the game simulation operation process without affecting the normal operation of the game simulation.

[0048] The present invention realizes real-time and efficient transmission of multi-channel user information by comprehensively considering the transmission channels and buffer queues of multiple routers in a computer network, thereby improving the efficiency and accuracy of information transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a flow chart for implementing the method of the present invention. DETAILED DESCRIPTION

[0050] In order to better understand the content of the present invention, an embodiment is given here.

[0051] Figure 1 It is a flow chart for implementing the method of the present invention.

[0052] In a first aspect of the embodiment of the present application, a distributed information processing method for a simulation environment is disclosed, which is implemented by using a master simulation node and a slave node, wherein the master simulation node is used to receive user information sent by each slave node to construct a game simulation environment; the slave node is used to receive user information and send the user information to the master simulation node; the master simulation node and the slave node are connected through a plurality of routers; all routers constitute a router network; the router includes a port; the port includes a transmission channel and a buffer queue set; the buffer queue set includes a plurality of buffer queues; the method includes:

[0053] S1, using each slave node, according to the preset sampling time interval T, obtain its user information set;

[0054] S2, for any slave node, preprocessing the acquired user information set to obtain its preprocessed user information set;

[0055] S3, for any slave node, use the transmission link processing model to process the pre-processed user information set to obtain the corresponding optimal routing path;

[0056] S4, based on the optimal routing path of each slave node, sending the pre-processed user information set of the slave node to the master simulation node.

[0057] The preprocessing of the acquired user information set to obtain the preprocessed user information set includes:

[0058] S21, performing outlier elimination processing on the user information set to obtain a first data set;

[0059] S22, performing boundary check processing on the first data set to obtain a first information set;

[0060] S23, taking the slave node IP address as the source address and the master simulation node IP address as the target address, adding the source address and the target address to the first information set to obtain a preprocessed user information set; the preprocessed user information set includes several pieces of user information.

[0061] The performing boundary check processing on the first data set to obtain a first information set includes:

[0062] S2201, for each type of data attribute of the first data set, using the data collection information of the data as an independent variable and the data value of the data as a dependent variable, perform autoregression-sliding average modeling to obtain regression models of the data attributes of the class; using the regression model, perform calculation processing on the independent variable to obtain regression data values; determine whether the absolute value of the difference between the regression data value and the corresponding dependent variable value is greater than a set first regression discrimination threshold; if it is greater than the first regression discrimination threshold, delete the data from the first data set; if it is less than the first regression discrimination threshold, do not process the data;

[0063] S2202: After completing S2201 for data of all data attributes, a first information set is obtained.

[0064] The sampling time interval T is calculated according to the node bandwidth allocation value R0, the link rate B0, and the flow data frame length F0, and its calculation expression is:

[0065] T=F0 / [B0sin(R0 / B0)],

[0066] Where T is the sampling time interval.

[0067] The transmission link processing model includes:

[0068] S31, according to the source address in the pre-processed user information set, determine the router closest to the source address as the source router; according to the target address in the pre-processed user information set, determine the router closest to the target address as the target router; determine the user information with information sequence number 1 in the pre-processed user information set as the current user information;

[0069] S32, initializing a first measurement value;

[0070] S33, determining whether the target router address of the current user information is equal to the source router address plus 1, and obtaining a first determination result. If the first determination result is yes, the first measurement value is increased by 1; if the first determination result is no, no operation is performed on the first measurement value;

[0071] S34, determining whether the first measurement value is equal to a preset zeroing threshold value a1, and obtaining a second determination result; if the second determination result is yes, setting the first measurement value to 0, determining the next user information of the current user information in the pre-processed user information set as the current user information, and executing S33; if the second determination result is no, executing S35;

[0072] S35, determining whether the first measurement value is greater than a preset first threshold value β, and obtaining a third determination result; if the third determination result is yes, using the path optimization model to obtain an optimal path from the source router to the target router;

[0073] If the third judgment result is no, determine whether the judgment processing process described in S33 is completed for all user information in the user information set to obtain the fourth judgment result; if the fourth judgment result is no, determine that the next user information of the current user information in the pre-processed user information set is the current user information, and execute S33; if the fourth judgment result is yes, execute S36;

[0074] S36, obtaining the occupancy q of the transmission channel of the source router on the shortest path from the source router to the target router vc_m The occupancy of the transmission channel refers to the ratio of the number of transmission channels full of data to the total number of transmission channels of the router port;

[0075] S37, obtaining the occupancy q of the buffer queue of the router port in the shortest path m , and the occupancy of the buffer queue of the router port of the second shortest path q nm ; The occupancy of the buffer queue refers to the ratio of the number of buffer queues full of data to the total number of buffer queues of the router port; using the parameter update model, the first threshold value β is updated; using the path optimization model, the optimal path from the source router to the target router is obtained.

[0076] The first threshold value β is calculated according to the parameters of the router network, and its calculation expression is:

[0077] β=a / (ah+1)×a1;

[0078] Wherein, a1 is a zero threshold value; the router network includes several groups; each group includes a routers; each router is connected to h slave nodes;

[0079] The calculation expression of the parameter update model is:

[0080]

[0081] The path optimization model includes:

[0082] Among all intermediate groups between source routers and target routers in the router network, a group is randomly selected, and the first router in the group is determined as an intermediate node; the intermediate group is a group between the source router and the target router in the router network; the first router in the group is a router with the smallest IP address in the group.

[0083] Taking the intermediate node as the demarcation point, obtaining the connection relationship of all routers between the demarcation point and the source router from the router network structure information, taking all routers between the demarcation point and the source router as points, and taking the corresponding connection relationship as edges, constructing a first graph data structure set; taking the corresponding point of the source router as the starting point, and taking the demarcation point as the end point; using the shortest path algorithm, solving the first graph data structure set, obtaining the shortest path between the starting point and the end point, and determining the shortest path as the first path; the router network structure information includes the address of each router in the router network and the routers connected to it;

[0084] Taking the intermediate node as the demarcation point, obtaining the connection relationship of all routers between the demarcation point and the target router from the router network structure information, taking all routers between the demarcation point and the target router as points, and taking the corresponding connection relationship as edges, constructing a second graph data structure set; taking the corresponding point of the target router as the end point, and taking the demarcation point as the starting point; using the shortest path algorithm, solving the second graph data structure set, obtaining the shortest path between the starting point and the end point, and determining the shortest path as the second path;

[0085] The first path and the second path are concatenated to obtain an optimal path from the source router to the target router.

[0086] The user information is the smallest unit of information sent from the slave node to the master simulation node. In the process of sending information from the slave node to the master simulation node, only one user information is sent each time the information is sent.

[0087] The autoregressive-moving average modeling can be implemented using the ARMA method;

[0088] The performing boundary check processing on the first data set to obtain a first information set includes:

[0089] S221, for each data attribute of the first data set, preset a corresponding value range; the value range includes an upper limit value of the value range and a lower limit value of the value range;

[0090] S222, for each data of each data attribute of the first data set, judging whether the value of the data is within the value range according to the value range of the data attribute; if the data is within the value range, not processing the data; if the data is not within the value range, setting the value of the data to the upper limit value or the lower limit value of the value range that is closest to the data;

[0091] S223, after completing S222 for the data of all data attributes, a first information set is obtained.

[0092] The shortest path is the path from the source router to the target router in the router network that passes through the least routers. The lengths of all possible connected paths from the source router to the target router can be calculated through the router network structure information, and the path with the smallest length is taken as the shortest path. Similarly, the second shortest path is the path from the source router to the target router in the router network that passes through the second fewest routers. The lengths of all possible connected paths from the source router to the target router can be calculated through the router network structure information, and the path with the second smallest length is taken as the second shortest path. The value of the zeroing threshold a1 can be 1000.

[0093] The shortest path algorithm may be one of Floyd, Bellman-Ford, SPFA, and Dijkstra;

[0094] All intermediate groups between the source router and the target router in the router network refer to all groups between the group where the source router is located and the group where the target router is located.

[0095] The first router in the group is the router with the smallest IP address in the group.

[0096] The optimal path from the source router to the target router is used to indicate the optimal transmission path of the message information from the source router to the target router.

[0097] The buffer queue is used to store data received in the router port but not yet sent out; the transmission channel is a channel for data transmission between the router and multiple downstream routers, which can store data;

[0098] The buffer queue is used to store information to be sent;

[0099] The user information includes user drawing instructions, color lighting and material instructions, rendering instructions, scene information and user behavior information

[0100] The constructed game simulation environment can be based on OpenGL, and according to the received user drawing instructions, image object information can be drawn; according to the received color lighting and material instructions, scene information can be drawn; according to the received rendering instructions and user behavior information, the image object information and scene information are rendered to obtain the game simulation environment;

[0101] The drawing obtains the image object information by calling the drawing instructions in the OpenGL API, and the drawing instructions include glBegin, glCullFace, etc.;

[0102] The drawing obtains scene information by calling the color, lighting and material instructions in the OpenGL API, and the color, lighting and material instructions include glcolor, glColorMask, glCullFace and the like.

[0103] The rendering process of the image object information and the scene information is implemented by calling the rendering instructions in the OpenGL API, and the rendering instructions include glArrayElement, glDrawArrays, glBlendFunc, etc.

[0104] How to ensure that the master simulation node can accurately and without omission receive the user information sent by each slave node during the simulation operation is the key to solving the problem of receiving and processing the input information of each participant in real time while realizing the operation of the game simulation, adding the input information to the game simulation operation process, and not affecting the normal operation of the game simulation. The present invention introduces a parallel data transmission and buffering mechanism between each slave node to ensure the accurate transmission of each user information.

[0105] In a second aspect of the embodiment of the present application, a distributed information processing device for a simulation environment is disclosed, the device comprising:

[0106] A memory storing executable program code;

[0107] a processor coupled to the memory;

[0108] The processor calls the executable program code stored in the memory to execute the distributed information processing method oriented to the simulation environment.

[0109] In a third aspect of the embodiments of the present application, a computer storable medium is disclosed, wherein the computer storable medium stores computer instructions, and when the computer instructions are called, they are used to execute the distributed information processing method for the simulation environment.

[0110] In a fourth aspect of the embodiments of the present application, an information data processing terminal is disclosed, and the information data processing terminal is used to implement the distributed information processing method for the simulation environment.

[0111] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A distributed information processing method for a simulation environment, characterized in that: The game is realized by using a master simulation node and a slave node. The master simulation node is used to receive user information sent by each slave node to construct a game simulation environment; the slave node is used to receive user information and send the user information to the master simulation node. The master simulation node and the slave nodes are connected via a plurality of routers; All routers constitute a router network; the routers include ports; the ports include transmission channels and buffer queue sets; The buffer queue set includes a plurality of buffer queues; the method includes: S1, using each slave node, according to the preset sampling time interval T, obtain its user information set; S2, for any slave node, preprocessing the acquired user information set to obtain its preprocessed user information set; S3, for any slave node, use the transmission link processing model to process the pre-processed user information set to obtain the corresponding optimal routing path; S4, based on the optimal routing path of each slave node, sending the pre-processed user information set of the slave node to the master simulation node.

2. The distributed information processing method for simulation environment according to claim 1, characterized in that: The preprocessing of the acquired user information set to obtain the preprocessed user information set includes: S21, performing outlier elimination processing on the user information set to obtain a first data set; S22, performing boundary check processing on the first data set to obtain a first information set; S23, taking the slave node IP address as the source address and the master simulation node IP address as the target address, adding the source address and the target address to the first information set to obtain a preprocessed user information set; the preprocessed user information set includes several pieces of user information.

3. The distributed information processing method for simulation environment as claimed in claim 2, characterized in that: The performing boundary check processing on the first data set to obtain a first information set includes: S221, for each type of data attribute of the first data set, using the data collection information of the data as an independent variable and the data value of the data as a dependent variable, perform autoregression-sliding average modeling to obtain regression models of the data attributes of the class; using the regression model, perform calculation processing on the independent variable to obtain regression data values; determine whether the absolute value of the difference between the regression data value and the corresponding dependent variable value is greater than a set first regression discrimination threshold; if it is greater than the first regression discrimination threshold, delete the data from the first data set; if it is less than the first regression discrimination threshold, do not process the data; S222, after completing S221 for data of all data attributes, a first information set is obtained.

4. The distributed information processing method for simulation environment according to claim 1, characterized in that: The sampling time interval T is calculated according to the node bandwidth allocation value R0, the link rate B0, and the flow data frame length F0, and its calculation expression is: T=F0 / [B0sin(R0 / B0)], Where T is the sampling time interval.

5. The distributed information processing method for simulation environment as claimed in claim 1, characterized in that: The method of processing the pre-processed user information set using the transmission link processing model for any slave node to obtain a corresponding optimal routing path includes: S31, according to the source address in the pre-processed user information set of the slave node, determine the router closest to the source address as the source router; according to the target address in the pre-processed user information set, determine the router closest to the target address as the target router; determine the user information with the information sequence number 1 in the pre-processed user information set as the current user information; S32, initializing a first measurement value; S33, determining whether the target router address of the current user information is equal to the source router address plus 1, and obtaining a first determination result. If the first determination result is yes, the first measurement value is increased by 1; if the first determination result is no, no operation is performed on the first measurement value; S34, determining whether the first measurement value is equal to a preset zeroing threshold value a1, and obtaining a second determination result; if the second determination result is yes, setting the first measurement value to 0, determining the next user information of the current user information in the pre-processed user information set as the current user information, and executing S33; if the second determination result is no, executing S35; S35, determining whether the first measurement value is greater than a preset first threshold value β, and obtaining a third determination result; if the third determination result is yes, using the path optimization model to obtain an optimal path from the source router to the target router; If the third judgment result is no, determine whether the judgment process described in S33 is completed for all user information in the user information set to obtain the fourth judgment result; If the fourth judgment result is no, determine the next user information of the current user information in the pre-processed user information set as the current user information, and execute S33; if the fourth judgment result is yes, execute S36; S36, obtaining the occupancy q of the transmission channel of the source router on the shortest path from the source router to the target router vc_m The occupancy of the transmission channel refers to the ratio of the number of transmission channels full of data to the total number of transmission channels of the router port; S37, obtaining the occupancy q of the buffer queue of the router port in the shortest path m , and the occupancy of the buffer queue of the router port of the second shortest path q nm ; The occupancy of the buffer queue refers to the ratio of the number of buffer queues full of data to the total number of buffer queues of the router port; using the parameter update model, the first threshold value β is updated; using the path optimization model, the optimal path from the source router to the target router is obtained.

6. The distributed information processing method for simulation environment as claimed in claim 5, characterized in that: The first threshold value β is calculated according to the parameters of the router network, and its calculation expression is: β=a / (ah+1)×a1, Wherein, a1 is a zeroing threshold value; the router network includes several groups; each group includes a routers; each router is connected to h slave nodes.

7. The distributed information processing method for simulation environment as claimed in claim 5, characterized in that: The path optimization model includes: Among all intermediate groups of source routers and target routers in the router network, randomly select a group and determine the first router in the group as an intermediate node; Taking the intermediate node as the demarcation point, obtaining the connection relationship of all routers between the demarcation point and the source router from the router network structure information, taking all routers between the demarcation point and the source router as points and the corresponding connection relationship as edges, constructing a first graph data structure set; the router network structure information includes the address of each router in the router network and the routers connected to it; Taking the corresponding point of the source router as the starting point and the demarcation point as the end point; using the shortest path algorithm to solve the first graph data structure set, obtain the shortest path between the starting point and the end point, and determine the shortest path as the first path; Taking the intermediate node as the demarcation point, obtaining the connection relationship of all routers between the demarcation point and the target router from the router network structure information, taking all routers between the demarcation point and the target router as points and the corresponding connection relationship as edges, constructing a second graph data structure set; Taking the point corresponding to the target router as the end point and the demarcation point as the starting point; using the shortest path algorithm to solve the second graph data structure set, obtain the shortest path between the starting point and the end point, and determine that the shortest path is the second path; The first path and the second path are concatenated to obtain an optimal path from the source router to the target router.

8. A distributed information processing device for a simulation environment, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the distributed information processing method for a simulation environment as described in any one of claims 1 to 7.

9. A computer storable medium, characterized in that: The computer storable medium stores computer instructions, and when the computer instructions are called, they are used to execute the distributed information processing method for simulation environment according to any one of claims 1 to 7.

10. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the distributed information processing method for simulation environment as described in any one of claims 1 to 7.

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