CN113332707B - Data processing method for game handle and game host - Google Patents
Data processing method for game handle and game host Download PDFInfo
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Classifications
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/20—Input arrangements for video game devices
- A63F13/24—Constructional details thereof, e.g. game controllers with detachable joystick handles
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/30—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers
- A63F13/32—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers using local area network [LAN] connections
- A63F13/327—Interconnection arrangements between game servers and game devices; Interconnection arrangements between game devices; Interconnection arrangements between game servers using local area network [LAN] connections using wireless networks, e.g. Wi-Fi or piconet
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/40—Processing input control signals of video game devices, e.g. signals generated by the player or derived from the environment
- A63F13/44—Processing input control signals of video game devices, e.g. signals generated by the player or derived from the environment involving timing of operations, e.g. performing an action within a time slot
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F13/00—Video games, i.e. games using an electronically generated display having two or more dimensions
- A63F13/55—Controlling game characters or game objects based on the game progress
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63F—CARD, BOARD, OR ROULETTE GAMES; INDOOR GAMES USING SMALL MOVING PLAYING BODIES; VIDEO GAMES; GAMES NOT OTHERWISE PROVIDED FOR
- A63F2300/00—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game
- A63F2300/40—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterised by details of platform network
- A63F2300/404—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterised by details of platform network characterized by a local network connection
- A63F2300/405—Features of games using an electronically generated display having two or more dimensions, e.g. on a television screen, showing representations related to the game characterised by details of platform network characterized by a local network connection being a wireless ad hoc network, e.g. Bluetooth, Wi-Fi, Pico net
Abstract
The application provides a data processing method for a game handle and a game host, which comprises the following steps: the game handle captures operation information of a player and generates a first control instruction; the game handle acquires a plurality of prediction models, inputs a first control instruction into the plurality of prediction models, and outputs a corresponding prediction instruction; the game handle determines at least one second control instruction from the plurality of predicted instructions and calculates at least one second priority information; after receiving the second control instruction and the second priority information, the game host searches second game data corresponding to the second control instruction and stores the second game data in a memory corresponding to the second priority information; and if the game host receives the control instruction which is the same as the second control instruction, the second game data is read from the corresponding memory and processed. According to the method and the device, the game host can rapidly execute the instruction from the game handle under the WiFi network, and the instruction processing efficiency is improved.
Description
Technical Field
The invention relates to the field of gamepads, in particular to a data processing method for a gamepad and a game host.
Background
In the field of games, with the continuous development of game development technologies, the requirements for the transmission rate and processing rate of game information become larger and larger, and improvement of response rate is an urgent need.
The interaction between the game console and the game pad can be realized by adopting a wired or wireless communication technology, for wireless communication, as the evolution of the communication technology and the improvement of the infrastructure, the speed of the wireless fidelity WiFi technology will be faster and faster in the visible future, for example, the speed of the 6 th generation WiFi is as high as 1228.8 MB/s. The use of WiFi technology for communication between a game pad and a game host becomes a possible trend, and in the case that the data transmission rate of wireless communication is faster and faster, how to increase the data processing rate of the game host becomes a problem to be solved.
Disclosure of Invention
The data processing method for the game handle and the game host can realize timely response of the game host under the WiFi network with a high communication rate.
In one aspect, the present application proposes a data processing method for a game console and a game host, where the game host and the game console perform data interaction through a WIFI network, the method including:
the game handle captures operation information of a player, generates a first control instruction based on the operation information, and sends the first control instruction to the game host;
the game handle acquires a plurality of prediction models, inputs the first control instruction into the plurality of prediction models respectively, and outputs a prediction instruction corresponding to each prediction model;
the game handle determines at least one second control instruction from a plurality of prediction instructions, and calculates at least one second priority information corresponding to the at least one second control instruction; the second control instruction is an instruction meeting a specified number of conditions in the plurality of prediction instructions, and the second priority information represents the probability of the second control instruction and the first control instruction occurring concomitantly in a first time interval;
the game handle sends the second control instruction and the second priority information to the game host after sending the first control instruction to the game host;
after receiving a second control instruction and second priority information, the game host searches second game data corresponding to the second control instruction and stores the second game data in a memory corresponding to the second priority information; wherein, the larger the probability value corresponding to the second priority information is, the higher the performance of the memory corresponding to the second priority information is;
after the game host computer executes the first control instruction, if the game host computer receives the control instruction which is the same as the second control instruction from the game handle, the second game data is read and processed from the memory corresponding to the second priority information.
In one possible implementation, the game host includes a first memory and a second memory, the first memory having a performance greater than that of the second memory, the first memory or the second memory including one of a register, a cache, a main RAM, and a virtual memory;
the storing the second game data in the memory corresponding to the second priority information includes: if the second priority information is larger than a second threshold value and smaller than the first threshold value, storing the second game data in a second memory; and if the second priority information exceeds a first threshold value, storing the second game data in a first memory.
Further, in the second time interval when the first instruction is received, if the control instruction which is the same as the second control instruction and is from the game handle is not received, the game data corresponding to the second instruction is stored in the hard disk with lower performance, so that the space of the high-performance memory is saved. If the control instruction which is the same as the second control instruction and is received from the game handle is not received within the second time interval of receiving the first instruction, the second control instruction is not the instruction to be sent next by the player, and the instruction prediction result of this time is wrong, at this time, game data of the instruction are stored in a memory with lower performance, so that the storage space of the high-performance memory can be saved. In one possible implementation, if the second game data is stored in the first memory, and in a second time interval when the first command is received, if the same control command as the second control command is not received from the game pad, the second game data is transferred to the second memory or is transferred to a nonvolatile memory such as a hard disk, a Flash, or the like. If the second game data is stored in the second memory, and the control instruction which is the same as the second control instruction is not received from the game handle in the second time interval of receiving the first instruction, the second game data is transferred to the nonvolatile memory such as the hard disk, the Flash and the like.
In one possible implementation, the plurality of prediction models includes a plurality of back propagation neural network models, kalman filter prediction models, time series prediction models, random forest models, softmax logistic regression models, and proximity algorithm models;
alternatively, the plurality of predictive models includes a plurality of the following models: the system comprises a plurality of back propagation neural network models with different parameters, a Kalman filtering prediction model with different parameters, a time sequence prediction model with different parameters, a random forest model with different parameters, a softmax logistic regression model with different parameters and a proximity algorithm model with different parameters.
The game handle determines at least one second control instruction from a plurality of prediction instructions, calculates at least one second priority information corresponding to the at least one second control instruction, and comprises the following steps: the game handle takes the instruction with the largest number of the plurality of predicted instructions as the second control instruction, and calculates the second priority information according to the proportion of the number of the second control instruction in the plurality of predicted instructions.
In one possible implementation manner, the at least one second control instruction includes a third instruction and a fourth instruction, the at least one second priority information includes third priority information and fourth priority information, the second game data corresponding to the at least one second control instruction includes third game data corresponding to the third instruction and fourth game data corresponding to the fourth instruction, the game handle determines the at least one second control instruction from a plurality of prediction instructions, and calculates the at least one second priority information corresponding to the at least one second control instruction, including: the game handle takes the instruction with the largest number of the plurality of predicted instructions as the third control instruction, and calculates the third priority information according to the proportion of the number of the third control instruction in the plurality of predicted instructions; taking an instruction with a second number of the plurality of predicted instructions as the fourth control instruction, and calculating fourth priority information according to the proportion of the fourth control instruction in the plurality of predicted instructions; the storing the second game data in the memory corresponding to the second priority information includes: storing the third game data in a first memory and the fourth game data in a second memory; and if the control instruction which is the same as the second control instruction and is received from the game handle, reading and processing the second game data from the memory corresponding to the second priority information, wherein the method comprises the following steps: if a control instruction which is the same as a third control instruction is received from the game handle, reading and processing the third game data from the first memory; and if the control command which is the same as the fourth control command is received from the game handle, reading and processing the fourth game data from the second memory.
Before the gamepad obtains the plurality of prediction models, the method further comprises: acquiring a historical instruction, training a plurality of prediction models through the historical instruction, and storing the trained plurality of prediction models; the gamepad obtains a plurality of predictive models, including: a stored trained plurality of predictive models is obtained.
In one possible implementation, the plurality of predictive models are associated with a first player identification, and before the gamepad obtains the plurality of predictive models, further comprising: acquiring the identity of a player; determining whether the identity is matched with the first player identification; the gamepad obtains a plurality of predictive models, including: and acquiring a plurality of prediction models associated with the first player identifier under the condition that the identity identifier is matched with the first player identifier.
Further, by associating the instruction of the game handle with the player identification, the operation habit of each player can be identified, and the priority information between the control instructions corresponding to each player can be acquired in a targeted manner, so that the rate of identifying the associated instruction can be increased, and the game data can be obtained more quickly.
According to the scheme, the identity of the player can be identified, the operation habit data (such as a plurality of control instructions) of the player can be matched according to the identity of the player, the control instructions possibly sent by the player through the game handle can be predicted according to the operation habit data of the player, the game data corresponding to the control instructions are pre-extracted into memories with different performance levels, so that the processor can quickly acquire the game data when executing the next game handle instructions, the instructions from the game handle can be quickly executed under the WiFi network, and the game experience of the player can be improved. Meanwhile, the method adopts various prediction models and multiple groups of parameters to conduct instruction prediction, so that the prediction accuracy can be improved, the method is more widely suitable for different scenes, and the robustness of a prediction result is improved.
Drawings
In order to more clearly describe the technical solutions in the embodiments or the background of the present application, the following description will describe the drawings that are required to be used in the embodiments or the background of the present application.
FIG. 1 is a schematic illustration of interaction of a gamepad and a game host as set forth in the present application;
FIG. 2 is a schematic diagram of a data processing method for a gamepad and a game host set forth in the present application;
fig. 3 is a schematic structural view of a game device according to the present application.
Detailed Description
The terms first, second and the like in the description and in the claims of the present application and in the above-described figures, are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, or apparatus.
Fig. 1 is a schematic interaction diagram of a game console and a game host according to the present application, where a game console 101 interacts with a game host 102 using a wireless communication WiFi network, and the game host and the game console may be respectively coupled with a router 103. The game console comprises a WiFi signal receiving and processing module, and the game host comprises a WiFi signal receiving and processing module, and the communication of the WiFi signal receiving and processing module and the game host can adopt various WiFi protocols, such as 802.11a protocols or 802.11ax protocols. After the game host receives the signals of the game handle through the WiFi network, game data are loaded and displayed according to game instructions, so that the aim of real-time interaction is fulfilled. In addition, the gamepad and the game host each include basic components such as a memory, a processor, and a bus.
When the game host computer processes the instruction of the game handle in real time, relevant game data need to be loaded and processed, and a game picture is rendered. In a WiFi network with a larger transmission rate, the network capacity is generally excessive, and how to use the good network capacity and improve the response speed of the game host is an important problem.
For a general host, the operation speed of the processor is far greater than the access speed of a memory such as a hard disk, that is, the access speed of the memory is the biggest factor limiting the speed of processing instructions by the game host. The method adopts a data multistage preloading mode to maximize the data reading rate, which essentially aims at solving the problem of unbalanced memory performance and processor performance in the game host at the cost of partial calculation power and partial network capacity of the processor consuming the game handle, thereby improving the response speed of the game host. Such a cost is obviously acceptable today where network capacity and processor power are rich.
The gamepad controls the game console via instructions, and the player typically presents a concomitant relationship in part or in whole between the plurality of game instructions. Taking a shooting-type game as an example, a player may be used to control turning on a scope after controlling a game piece to squat or to control starting shooting after controlling a game piece to jump. By researching the concomitance among game instructions, the game progress can be optimized, and the instruction processing rate can be improved.
Fig. 2 is a schematic diagram of a data processing method for a game console and a game host, which are proposed in the present application, and the game host and the game console perform data interaction through a WIFI network.
201. The game handle captures operation information of a player, generates a first control instruction based on the operation information, and sends the first control instruction to the game host. The game handle can receive operation information of a player through virtual or physical keys, a gyroscope, an acceleration sensor and the like, and generates control instructions according to the operation information, wherein the control instructions are used for controlling movement of game characters, loading of game pictures and setting of games.
202. The game handle acquires a plurality of prediction models, inputs the first control instruction into the plurality of prediction models respectively, and outputs the prediction instruction corresponding to each prediction model.
The plurality of prediction models are used for predicting instructions that the game host may receive (i.e., instructions subsequent to the first control instruction) in a first time interval after receiving the first control instruction, i.e., predicting what operation the player will perform next and what control instruction to send. The output multiple prediction instructions are preliminary prediction results.
In one possible implementation, the plurality of prediction models includes a plurality of back propagation neural network models, kalman filter prediction models, time series prediction models, random forest models, softmax logistic regression models, and proximity algorithm models.
For example, the game pad may train the above 6 models in advance and store the trained 6 models. After the first control command is obtained, the first control command is input into the trained 6 prediction models, and the 6 prediction models are output to correspond to the prediction commands. Because the various models have differences, prediction precision and the best applicable scene are different, and the output 6 prediction instructions may have differences. The following table is an exemplary output result. Table 1:
| input of a prior instruction | Predicted following instructions | Predictive model employed |
| Control instruction 1 | Control instruction 2 | Counter-propagationNeural network |
| Control instruction 1 | Control instruction 2 | Kalman filtering |
| Control instruction 1 | Control instruction 2 | Time series |
| Control instruction 1 | Control instruction 4 | Random forest |
| Control instruction 1 | Control instruction 3 | Logistic regression of softmax |
| Control instruction 1 | Control instruction 2 | Proximity algorithm |
As can be seen from the above exemplary table, when the control instruction 1 is input, the predicted instructions output by each model are a control instruction 2, a control instruction 3 and a control instruction 4, wherein the control instruction 2 occupies the largest proportion and is the instruction most likely to accompany the control instruction 1.
In one possible implementation, the plurality of predictive models may include a plurality of the following models: the system comprises a plurality of back propagation neural network models with different parameters, a Kalman filtering prediction model with different parameters, a time sequence prediction model with different parameters, a random forest model with different parameters, a softmax logistic regression model with different parameters and a proximity algorithm model with different parameters. Wherein, for the same model, if model parameters are different, the prediction effect may be different. Taking a back propagation neural network model as an example, the weight matrix between the input layer and the hidden layer is [ w1, w2; w3, w4]; taking the error as a constraint condition, and obtaining the weight matrix value as [ w1, w2 ] under the condition of error convergence after gradient descent training; w3, w4] = [0.15,0.20;0.25,0.30]. Properly adjusting training data, and obtaining a weight matrix value [ w1, w2 again; w3, w4] = [0.16,0.20;0.27,0.29]. After two sets of weight matrixes are obtained, the two sets of weight matrixes are respectively used as parameters of a back propagation neural network model, and through testing, the neural network model with the two sets of parameters can generate more accurate prediction results. The back propagation neural network model with two different parameters is obtained through the process. Other models may also be processed with reference to this process. The following table is an exemplary output result. Table 2:
as can be seen from the above exemplary table, when the control instruction 1 is input, the prediction instructions output by the respective models are control instruction 2, control instruction 3, and control instruction 4, wherein the control instruction 2 occupies the largest proportion.
The instruction prediction is performed by adopting a plurality of prediction models and a plurality of groups of parameters, so that the prediction precision can be improved, meanwhile, the method is more widely suitable for different scenes, and the robustness of a prediction result is improved.
203. The game handle determines at least one second control instruction from a plurality of prediction instructions, and calculates at least one second priority information corresponding to the at least one second control instruction; the second control instruction is an instruction meeting a specified number of conditions in the plurality of prediction instructions, and the second priority information indicates the probability that the second control instruction and the first control instruction appear concomitantly in a first time interval.
The plurality of prediction models respectively generate prediction instructions, and at this time, the more the number of the same type of prediction instructions is, the closer the prediction instructions are to the actual result, namely, the more likely the prediction instructions are sent to the game host by the player in a preset time after the first control instruction.
In one possible implementation, the game handle uses the instruction with the largest number of the plurality of predicted instructions as the second control instruction, and calculates the second priority information according to the proportion of the number of the second control instruction in the plurality of predicted instructions. The most number of the plurality of predicted instructions and the first control instruction are most likely to occur, i.e. after the game host receives the first control instruction, the game host has a high probability of continuously receiving the same instruction as the second control instruction.
Taking table 1 as an example, if the number of control instructions 2 is the largest, the control instruction 2 is a second control instruction, and the corresponding second priority information is the specific gravity occupied by the control instruction 2, that is, 66.7%.
It should be noted that the second control instruction is only a predictive instruction and is not an immediately executed instruction, and the second control instruction is used to instruct the game host to pre-fetch the game data corresponding to the control instruction that may be sent by the player into the memory with a specified performance level in advance, so that when the same instruction as the second control instruction is received, the game data can be quickly read from the corresponding memory. Further, when the game handle sends the second control instruction to the game host, prompt information indicating that the second control instruction belongs to a predictive instruction and is not an instruction executed immediately can be sent to the host at the same time, so as to instruct the game host to pre-fetch game data corresponding to the second control instruction into a designated memory in advance and not execute the second control instruction immediately.
204. After the game handle sends the first control instruction to the game host, the game handle sends the second control instruction and the second priority information to the game host; after receiving a second control instruction and second priority information, the game host searches second game data corresponding to the second control instruction and stores the second game data in a memory corresponding to the second priority information; wherein, the larger the probability value corresponding to the second priority information, the higher the performance of the memory corresponding to the second priority information.
The game host comprises a first memory and a second memory, wherein the performance of the first memory is larger than that of the second memory, and the first memory or the second memory comprises one of a register, a cache, a main memory RAM and a virtual memory. If the second priority information is larger than a second threshold value and smaller than the first threshold value, storing the second game data in a second memory; and if the second priority information exceeds a first threshold value, storing the second game data in a first memory.
In one possible implementation, the first memory is a cache and the second memory is a main memory RAM. Alternatively, the first memory is a register and the second memory is a cache. Alternatively, the first memory is a main memory RAM, and the second memory is a virtual memory or a nonvolatile memory. The nonvolatile memory comprises a mechanical hard disk, a solid state disk, a Flash memory or the like. The access rates of the register, the cache, the RAM and the nonvolatile memory are sequentially reduced, namely the register or the cache is a scarce memory with high performance, and the nonvolatile memory is a memory with large capacity and poor performance.
Taking table 1 as an example, assuming that the first threshold value is 50%, the second threshold value is 33%, and the control command 2 occupies 50%, and the probability value corresponding to the second priority information is 50%, when the first threshold value is satisfied, game data corresponding to the control command 2 can be fetched into the first memory (e.g., cache). And if the second priority information is more than 33% and less than 50%, the game data corresponding to the control instruction 2 may be fetched to a second memory (e.g., RAM), and if the priority information is less than 33%, no additional processing operation is performed.
In one possible implementation manner, the at least one second control instruction includes a third instruction and a fourth instruction, the at least one second priority information includes third priority information and fourth priority information, the second game data corresponding to the at least one second control instruction includes third game data corresponding to the third instruction and fourth game data corresponding to the fourth instruction, the game handle determines the at least one second control instruction from a plurality of prediction instructions, and calculates the at least one second priority information corresponding to the at least one second control instruction, including: the game handle takes the instruction with the largest number of the plurality of predicted instructions as the third control instruction, and calculates the third priority information according to the proportion of the number of the third control instruction in the plurality of predicted instructions; taking an instruction with a second number of the plurality of predicted instructions as the fourth control instruction, and calculating fourth priority information according to the proportion of the fourth control instruction in the plurality of predicted instructions; the storing the second game data in the memory corresponding to the second priority information includes: and storing the third game data in a first memory, and storing the fourth game data in a second memory.
The operations of identifying the third control command, extracting the third game data to the first memory, and identifying the fourth control command, extracting the fourth game data to the second memory are performed simultaneously (for example, may be performed in parallel), so as to achieve the purpose of multi-stage pre-storage.
Taking table 2 as an example, after the prediction of 8 prediction models, 8 prediction instructions are obtained, wherein the number of control instructions 2 is the largest, and the value of the corresponding third priority information is 50% as a third control instruction; the second number of control commands 3 corresponds to a value of 38% of the fourth priority information as the fourth control command. The game host extracts the third game data corresponding to the third control instruction, stores the third game data in the first memory (e.g., cache), extracts the fourth game data corresponding to the fourth control instruction, and stores the fourth game data in the second memory (e.g., RAM).
In addition, if the third game data is originally stored in the first memory, the game host does not need to execute the third game data to be stored in the first memory; if the fourth game data is originally stored in the second memory, the game host does not need to execute the fourth game data transfer to the second memory.
In the present application, the third priority information of the third control instruction largely indicates that there is a high probability that the game pad generates the third control instruction in a subsequent period of time after receiving the first control instruction, which is closely associated with the operation habit of the user. Because the probability of occurrence of the third control instruction is high, the game data of the third control instruction is extracted into the first memory (for example, the cache) with high access speed in advance. The fourth control command has a lower probability of accompanying occurrence than the third control command, but still reaches a certain value, and the game data of the third control command is extracted into a second memory (e.g. RAM) with access speed slightly lower than that of the first memory in advance. The most scarce and highest performance memory is used for storing game data which appears most probable, the less scarce and second highest performance memory is used for storing game data which appears next most probable, the game data is prefetched, and multilevel management is adopted, so that the processing mode can maximally balance the relation between the rarity of the high performance memory and the large storage capacity of the game data and the high speed of the game handle transmission instruction.
205. After the game host computer executes the first control instruction, if the game host computer receives the control instruction which is the same as the second control instruction from the game handle, the second game data is read and processed from the memory corresponding to the second priority information.
After the game host prestores the second game data in the corresponding memory, if the second game data receives the same control instruction as the second control instruction, the second game data is directly extracted and processed from the corresponding memory, so that the extraction speed of the second game data is greatly increased, and the speed of the game host responding to the client request is increased.
Further, in the second time interval when the first instruction is received, if the control instruction which is the same as the second control instruction and is from the game handle is not received, the game data corresponding to the second instruction is stored in the hard disk with lower performance, so that the space of the high-performance memory is saved. If the control instruction which is the same as the second control instruction and is received from the game handle is not received within the second time interval of receiving the first instruction, the second control instruction is not the instruction to be sent next by the player, and the instruction prediction result of this time is wrong, at this time, the instruction is stored in a memory with lower performance, so that the storage space of the high-performance memory can be saved. For example, if the second game data is stored in the first memory, during the second time interval when the first command is received, if the same control command as the second control command is not received from the game pad, the second game data is transferred to the second memory or to the nonvolatile memory such as the hard disk, flash, etc.
It should be noted that the second control instruction is only a predictive instruction and is not an immediately executed instruction, and the second control instruction is used to instruct the game host to pre-fetch the game data possibly sent by the player into the designated memory in advance, so that the game data can be quickly read from the corresponding memory when the same instruction as the second control instruction is received. Further, when the game handle sends the second control instruction to the game host, the game host needs to send prompt information indicating that the second control instruction belongs to a predictive instruction and is not an instruction executed immediately, so as to instruct the game host to pre-fetch game data corresponding to the second control instruction into a designated memory in advance and not execute the second control instruction immediately. The instruction which is received by the game host and is the same as the second control instruction is an instruction which is executed immediately, and the game host immediately starts to execute the appointed operation of the player after receiving the instruction.
The game data comprise at least one of game images to be rendered, configuration information and rendering instructions associated with the game images, wherein the game images comprise static images and dynamic images, the configuration information comprises configuration information required by image rendering and man-machine interaction, and the rendering instructions associated with the game images comprise instructions corresponding to operations such as image compression, image filtering, image merging and image shading.
In one possible implementation, the at least one second control instruction includes a third instruction and a fourth instruction, the at least one second priority information includes a third priority information and a fourth priority information, and the second game data corresponding to the at least one second control instruction includes a third game data corresponding to the third instruction and a fourth game data corresponding to the fourth instruction. After the game data are pre-stored in the corresponding memory, if a control instruction which is the same as a third control instruction is received from the game handle, the third game data are read from the first memory and processed; and if the control command which is the same as the fourth control command is received from the game handle, reading and processing the fourth game data from the second memory.
Further, in order to save the high-performance memory, if the same control instruction as the third control instruction is not received within the second preset time, the third game data is stored in a memory with lower performance (for example, in the second memory or the nonvolatile memory). If the same control instruction as the fourth control instruction is not received within the second preset time, the fourth game data is stored in a memory with lower performance (for example, a nonvolatile memory).
206. Before a plurality of prediction models are acquired, a game handle acquires historical instructions, trains the plurality of prediction models through the historical instructions, and stores the trained plurality of prediction models; the game handle obtains a plurality of prediction models, including: a stored trained plurality of predictive models is obtained.
The historical instructions comprise control instructions which are triggered by a player, and the historical instructions can be used for training a prediction model to predict instructions which can occur within a preset time after the first control instructions occur. Wherein the historical instructions for training the model may occur in pairs, the time interval between each pair of historical instructions being less than the first time interval. Taking Table 3 as an example, table 3:
| prior history instructions | Post history instructions |
| Control instruction 1 | Control instruction 2 |
| Control instruction 1 | Control instruction 3 |
| Control instruction 2 | Control instruction 4 |
| ...... | ...... |
Table 3 is a set of instructions for training a predictive model in which the time interval between a prior historical instruction and a subsequent historical instruction is less than a preset time interval (e.g., 2 seconds), which may allow the trained model to predict the instructions that will be generated.
In one possible implementation, a plurality of predictive models are associated with a first player identification, the identity of the player being obtained before the gamepad obtains the plurality of predictive models; determining whether the identity is matched with the first player identification; the game handle obtains a plurality of prediction models, including: and acquiring a plurality of prediction models associated with the first player identifier under the condition that the identity identifier is matched with the first player identifier.
Further, a plurality of historical instructions may also be associated with the first player identification. Acquiring historical instructions, training a plurality of prediction models through the historical instructions, and storing the trained plurality of prediction models, wherein the method comprises the following steps of: and acquiring a historical instruction corresponding to the first player identifier, training a plurality of prediction models through the historical instruction corresponding to the first player identifier, and storing the trained plurality of prediction models in association with the first player identifier.
Identifying the identity of the player, associating the prediction model and the historical instructions for training the prediction model with the identity of the player can identify the operation habit of a specific player, predicting the control instructions possibly sent by the player through the game handle based on the operation habit of the player, and pre-extracting game data corresponding to the control instructions into memories with different performance levels, so that the processor can quickly read the game data from the memories with higher performance when executing the next control instructions, the whole performance optimization process is more targeted, and the data processing rate of a game host can be greatly improved.
In the process of sending interactive data through the WiFi network, the interactive data comprises a predicted instruction and priority information of the instruction, so that partial network capacity is required to be occupied; when the game handle predicts instructions, the processor computing power of the part is occupied, so that the network capacity of the part and the processor computing power of the game handle are essentially sacrificed, the problem of unbalanced memory performance and processor performance in the game host is solved, and the response speed of the game host is further improved. Such a cost is obviously acceptable today where network capacity and processor power are rich.
Fig. 3 is a schematic structural diagram of a game device provided in an embodiment of the present application. Wherein the gaming device may be a game console or a joystick. The apparatus includes: at least one processor 301, such as a central processing unit (central processing unit, CPU), at least one memory 302, and at least one bus 303.
The memory 302 may store program instructions and the processor 301 may be configured to invoke the program instructions to perform a data processing method for the gamepad and the game host. Those of ordinary skill in the art will appreciate that all or part of the steps of the various methods of the above embodiments may be implemented by hardware associated with a program that may be stored in a computer-readable storage medium, including Read Only Memory (ROM), random access memory (random access memory, RAM), programmable read only memory (programmable read only memory, PROM), erasable programmable read only memory (erasable programmable read only memory, EPROM), one-time programmable read only memory (OTPROM), electrically Erasable Programmable Read Only Memory (EEPROM), compact disc read only memory (compact disc read-only memory, CD-ROM), solid State Disk (SSD), or other optical disk memory, magnetic disk memory, tape memory, or any other medium that can be used to carry or store data that is readable by a computer.
Claims (10)
1. A data processing method for a game console and a game host, wherein the game host and the game console perform data interaction through a WIFI network, the data processing method is characterized by comprising the following steps:
the game handle captures operation information of a player and generates a first control instruction based on the operation information;
the game handle acquires a plurality of prediction models, inputs the first control instruction into the plurality of prediction models respectively, and outputs a prediction instruction corresponding to each prediction model;
the game handle determines at least one second control instruction from a plurality of prediction instructions, and calculates at least one second priority information corresponding to the at least one second control instruction; the second control instruction is an instruction meeting a specified number of conditions in the plurality of prediction instructions, and the second priority information represents the probability of the second control instruction and the first control instruction occurring concomitantly in a first time interval;
the game handle sends the second control instruction and the second priority information to the game host after sending the first control instruction to the game host;
after receiving a second control instruction and second priority information, the game host searches second game data corresponding to the second control instruction and stores the second game data in a memory corresponding to the second priority information; wherein, the larger the probability value corresponding to the second priority information is, the higher the performance of the memory corresponding to the second priority information is;
after the game host computer executes the first control instruction, if the game host computer receives the control instruction which is the same as the second control instruction from the game handle, the second game data is read and processed from the memory corresponding to the second priority information.
2. The method of claim 1, wherein the game host comprises a first memory and a second memory, the first memory having a performance greater than a performance of the second memory, the first memory or the second memory comprising one of a register, a cache, a main RAM, and a virtual memory;
the storing the second game data in the memory corresponding to the second priority information includes: if the second priority information is larger than a second threshold value and smaller than the first threshold value, storing the second game data in a second memory; and if the second priority information exceeds a first threshold value, storing the second game data in a first memory.
3. The method of claim 2, wherein the plurality of prediction models comprises a plurality of back propagation neural network models, kalman filter prediction models, time series prediction models, random forest models, softmax logistic regression models, and proximity algorithm models;
alternatively, the plurality of predictive models includes a plurality of the following models: the system comprises a plurality of back propagation neural network models with different parameters, a Kalman filtering prediction model with different parameters, a time sequence prediction model with different parameters, a random forest model with different parameters, a softmax logistic regression model with different parameters and a proximity algorithm model with different parameters.
4. The method of claim 3, wherein the game pad determining at least one second control command from a plurality of predicted commands and calculating at least one second priority information corresponding to the at least one second control command comprises:
the game handle takes the instruction with the largest number of the plurality of predicted instructions as the second control instruction, and calculates the second priority information according to the proportion of the number of the second control instruction in the plurality of predicted instructions.
5. A method according to claim 2 or 3, wherein the at least one second control instruction comprises a third instruction and a fourth instruction, the at least one second priority information comprises a third priority information and a fourth priority information, the second game data corresponding to the at least one second control instruction comprises a third game data corresponding to the third instruction and a fourth game data corresponding to the fourth instruction, the gamepad determines the at least one second control instruction from a plurality of predicted instructions and calculates the at least one second priority information corresponding to the at least one second control instruction, comprising:
the game handle takes the instruction with the largest number of the plurality of predicted instructions as a third control instruction, and calculates the third priority information according to the proportion of the number of the third control instruction in the plurality of predicted instructions; taking the second number of instructions in the plurality of predicted instructions as a fourth control instruction, and calculating fourth priority information according to the proportion of the fourth control instruction in the plurality of predicted instructions;
the storing the second game data in the memory corresponding to the second priority information includes: storing the third game data in a first memory and the fourth game data in a second memory;
and if the control instruction which is the same as the second control instruction and is received from the game handle, reading and processing the second game data from the memory corresponding to the second priority information, wherein the method comprises the following steps:
if a control instruction which is the same as a third control instruction is received from the game handle, reading and processing the third game data from the first memory;
and if the control command which is the same as the fourth control command is received from the game handle, reading and processing the fourth game data from the second memory.
6. The method of claim 3, further comprising, prior to the gamepad acquiring a plurality of predictive models:
the game handle acquires a historical instruction, trains a plurality of prediction models through the historical instruction, and stores the trained plurality of prediction models;
the gamepad obtains a plurality of predictive models, including: a stored trained plurality of predictive models is obtained.
7. The method of claim 6, wherein the plurality of predictive models are associated with a first player identification, and wherein prior to the gamepad obtaining the plurality of predictive models, further comprising: acquiring the identity of a player; determining whether the identity is matched with the first player identification;
the gamepad obtains a plurality of predictive models, including: and acquiring a plurality of prediction models associated with the first player identifier under the condition that the identity identifier is matched with the first player identifier.
8. The method of claim 7, wherein the plurality of historical instructions are associated with a first player identification, wherein the obtaining historical instructions, through which a plurality of predictive models are trained, stores the trained plurality of predictive models, comprises:
and acquiring a historical instruction corresponding to the first player identifier, training a plurality of prediction models through the historical instruction corresponding to the first player identifier, and storing the trained plurality of prediction models in association with the first player identifier.
9. A gaming system comprising a game console and a gamepad, the game console and the gamepad being data interactive under a WiFi network, the game console and the gamepad being configured to perform the method of any one of claims 1-8.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to implement the method of any one of claims 1 to 8.
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