High-performance calculation user quota intelligent management system

Abstract

The invention relates to the field of quota management system design, in particular to a high-performance calculation user quota intelligent management system. A data acquisition module is arranged and used for acquiring operation data input by user sides and recording resource use data when game roles controlled by different user sides interact with modeling targets preset in a game scene; the quota analysis module is used for calculating resource demand characterization parameters for the modeling targets according to the resource use data corresponding to the plurality of modeling targets so as to divide resource demand degree categories of the modeling targets; and the resource allocation module is used for determining a pre-interaction modeling target according to the operation data of the user side and adaptively allocating resources to the user side in advance according to the resource demand degree category of the modeling target, so that the smoothness of game operation and the rationality of the resource quota are ensured, and the overall utilization efficiency of resources is improved.

Description

Technical Field

[0001] The invention relates to the field of quota management system design, and in particular to an intelligent quota management system for high-performance computing users. Background Art

[0002] With the development of information technology and the explosive growth of data volume, the rational allocation of resources has become an urgent problem that needs to be solved. Therefore, user quota management can further understand and meet user needs by monitoring and analyzing user-side resource usage, flexibly manage and allocate resources, and allocate quotas to users by optimizing resource allocation, thereby ensuring the rational use of resources and efficient operation of the system and improving the overall utilization of resources.

[0003] Chinese Patent Publication No.: CN111447577A, discloses a quota management method and device, the method comprising: receiving a quota allocation request carrying a target user identifier sent by a network element, inputting data usage information of the target user within a second preset time period into a set prediction model corresponding to the target user to obtain a target quota, the network element provides mobile data services to the target user according to the target quota, and by using the target quota obtained by the set prediction model, the target quota can be dynamically adjusted according to the actual situation of the user's recent data usage, so that the obtained target quota can accurately match the user's current data usage.

[0004] However, the following problems still exist in the prior art: when the user side controls the game character to interact with the NPC character in the game, the user side will issue intensive, continuous and rapid control instructions. At the same time, the NPC character itself will also issue actions according to the settings, which will result in a large amount of resource consumption. Due to the failure to allocate resources in advance in time, the current resources may not be able to guarantee the smoothness of the game operation, thereby reducing the overall resource utilization efficiency. Summary of the invention

[0005] To this end, the present invention provides a high-performance computing user quota intelligent management system to overcome the problem in the prior art that when a user controls a game character to interact with an NPC character in the game, the user terminal will issue intensive, continuous and rapid control instructions. At the same time, the NPC character itself will also issue actions according to the settings, which will result in a large amount of resource consumption. Due to the failure to allocate resources in advance in time, the current resources may not be able to guarantee the smoothness of the game operation, thereby reducing the overall utilization efficiency of resources.

[0006] To achieve the above object, the present invention provides a high performance computing user quota intelligent management system, which includes:

[0007] A data acquisition module, which is used to acquire operation data input by the user terminal and record resource usage data when the game characters controlled by different user terminals interact with the modeling targets preset in the game scene, wherein the operation data includes several instructions for the user terminal to control the game characters to generate actions;

[0008] A quota analysis module connected to the data acquisition module, for calculating a resource demand characterization parameter for a plurality of modeling targets based on resource usage data corresponding to the modeling targets, so as to classify the resource demand degree of the modeling targets, wherein the resource usage data corresponding to the plurality of modeling targets include a throughput of a user terminal and a number of instructions issued by the user terminal;

[0009] A resource allocation module, which is connected to the data acquisition module and the quota analysis module respectively, is used to determine the pre-interaction modeling target according to the operation data of the user terminal, and allocate resources to the user terminal according to the resource demand degree category of the modeling target, including:

[0010] According to the resource demand characterization parameter, the upper limit of the number of service nodes at the user end is adjusted, a time domain curve of the number of service nodes is constructed, the slope of the time domain curve segment at each moment is analyzed to determine whether it has entered a dense phase, and the response time of each service node at the user end in the dense phase is called to determine whether there is congestion, so as to correct the upper limit of the number of service nodes at the user end;

[0011] Or, determining operation stability characterization parameters according to system load characteristics to determine whether to adjust the upper limit of the number of user-side service nodes;

[0012] Among them, the system load characteristics include the average number of active processes on the user side and the data transmission volume.

[0013] Furthermore, the quota analysis module calculates the resource demand characterization parameter according to formula (1):

[0014]

[0015] In formula (1), R represents the parameter representing resource demand, P represents the throughput of the user end, P0 represents the throughput threshold, U represents the number of instructions issued by the user end, U0 represents the instruction number threshold, α represents the throughput weight coefficient, and β represents the instruction number weight coefficient.

[0016] Furthermore, the quota analysis module is used to classify the resource demand degree categories of the modeling target, including:

[0017] If the resource demand characterization parameter is greater than or equal to the resource demand characterization parameter threshold, the resource demand of the modeling target is determined to be a high degree category;

[0018] If the resource demand characterization parameter is less than the resource demand characterization parameter threshold, the resource demand of the modeling target is determined to be a low-level category.

[0019] Furthermore, the resource allocation module is used to allocate resources to the user terminal according to the resource demand level category of the modeling target, including:

[0020] If the resource demand of the modeling target is of a high degree category, the upper limit of the number of service nodes at the user end is adjusted according to the resource demand characterization parameter, a time domain curve of the number of service nodes is constructed, and the slope of the time domain curve segment at each moment is analyzed to determine whether it has entered the intensive stage, and the response time of each service node at the user end in the intensive stage is called to determine whether there is congestion, so as to correct the upper limit of the number of service nodes at the user end;

[0021] If the resource demand of the modeling target is of a low level category, the operation stability characterization parameter is determined according to the system load characteristics to determine whether to adjust the upper limit of the number of user-side service nodes.

[0022] Furthermore, the resource allocation module is used to adjust the upper limit of the number of user-side service nodes, including:

[0023] The upper limit of the number of service nodes at the user end is increased, and the increase in the upper limit of the number of service nodes is positively correlated with the resource demand characterization parameter.

[0024] Furthermore, the resource allocation module is used to construct the time domain curve of the number of service nodes and analyze the slope of the time domain curve at each moment, including:

[0025] A rectangular coordinate system is constructed with time as the horizontal axis and the number of service nodes as the vertical axis;

[0026] Marking coordinate points of the number of service nodes at each time in the rectangular coordinate system;

[0027] Connecting the coordinate points with a smooth curve to obtain the time domain curve;

[0028] If there is a time domain curve segment whose slope is greater than or equal to the slope threshold, it is determined to enter the intensive stage.

[0029] Furthermore, the resource allocation module is used to determine whether congestion exists, including:

[0030] If the response time of each service node of the user end in the intensive phase is greater than or equal to the response time threshold, it is determined that congestion exists.

[0031] Furthermore, the resource allocation module is used to modify the upper limit of the number of user-side service nodes, including:

[0032] If congestion exists, the upper limit of the number of user-side service nodes will be corrected.

[0033] Furthermore, the resource allocation module is used to determine the operational stability characterization parameters including:

[0034] to calculate a ratio of an average number of active processes within a predetermined time period to an average number of active processes of a preset threshold number of active processes within a predetermined time period;

[0035] for calculating a data transmission volume ratio of a data transmission volume within a predetermined time period to a data transmission volume threshold within a preset predetermined time period;

[0036] The operation stability characterization parameter is obtained by respectively assigning corresponding weight values ​​to the average ratio of the number of active processes and the ratio of the data transmission volume and summing them up.

[0037] Furthermore, the resource allocation module is used to determine whether to adjust the upper limit of the number of user-side service nodes, including:

[0038] If the operation stability characterization parameter is greater than or equal to the operation stability characterization parameter threshold, the upper limit of the number of client service nodes is adjusted.

[0039] Compared with the prior art, the present invention sets up a data acquisition module for acquiring the operation data input by the user terminal and recording the resource usage data when the game characters controlled by different user terminals interact with the modeling targets pre-set in the game scene; the quota analysis module is used to calculate the resource demand characterization parameters for the modeling targets according to the resource usage data corresponding to a number of modeling targets, so as to classify the resource demand degree categories of the modeling targets; the resource allocation module is used to determine the pre-interaction modeling targets according to the operation data of the user terminal, and adaptively allocate resources to the user terminal in advance according to the resource demand degree categories of the modeling targets, thereby ensuring the smoothness of the game operation and the rationality of the resource quota, and improving the overall resource utilization efficiency.

[0040] In particular, the present invention calculates resource demand characterization parameters for modeling targets through resource usage data corresponding to several modeling targets. During the game operation, the user terminal continuously issues operation instructions, which will generate a certain amount of resource consumption and data transmission. In particular, when the user terminal controls the game character to interact with the modeling target pre-set in the game scene, more resource consumption and data transmission will be generated. For example, when fighting with the NPC character that needs to be defeated in a high-difficulty task, the operation instructions issued by the user terminal to control the game character to attack are intensive, continuous and fast. Therefore, sufficient resources are required to ensure the smoothness of the user terminal's control of the game character operation and avoid freezes and the like. Therefore, the present application calculates the resource demand characterization parameters for the modeling target through the user terminal's throughput and the number of instructions issued to characterize the degree of resources required when the user terminal controls the game character to interact with the modeling target, provide data support for the subsequent division of the resource demand degree of the modeling target, determine the pre-interaction modeling target according to the user terminal's operation data, adaptively allocate resources to the user terminal in advance, and thus ensure the smoothness of the game operation and the rationality of the resource quota, and improve the overall resource utilization efficiency.

[0041] In particular, the present invention adjusts the upper limit of the number of service nodes on the user side in advance according to the resource demand characterization parameter under the category of high resource demand of the modeling target. According to the high resource level required by the modeling target for pre-interaction, the upper limit of the number of service nodes on the user side is increased in advance to ensure the smoothness of the game operation. During the continuous operation of the game, the number of service nodes used by the user side is detected, a time domain curve of the number of service nodes is constructed, and the slope of the time domain curve segment at each moment is analyzed. For example, if the slope of the time domain curve segment is greater than or equal to the slope of the time domain segment when the game is running stably, it is determined that the intensive stage has been entered, and the response time data of each service node on the user side in the intensive stage is called. In actual situations, when the data transmission is stable and the resources can meet the needs of the user side, each service node on the user side will respond to the operation request instruction in a timely manner. If the service node fails to respond in time, a longer waiting time for the response is required. In this case, it is determined that congestion exists, so as to correct the upper limit of the number of service nodes on the user side, ensure the timely response of each service node and the smoothness of data transmission, and avoid congestion.

[0042] In particular, the present invention determines the operation stability characterization parameters according to the system load characteristics under the low resource demand category of the modeling target, and predicts the resource demand according to the average number of active processes and the data transmission volume when the existing resources can meet the user-side needs. For example, a large number of active processes will generate high demand for resources, and a large amount of data transmission will increase the system load and the usage of memory resources, and will also use more network bandwidth, CPU and other resources. Therefore, the present application characterizes the user-side demand tendency for resources through the operation stability characterization parameters to determine whether to adjust the upper limit of the number of user-side service nodes, thereby ensuring the smoothness of game operation and the rationality of resource quotas, and improving the overall resource utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a functional module diagram of the high performance computing user quota intelligent management system according to an embodiment of the invention;

[0044] Figure 2 A logical decision diagram for classifying resource demand levels for embodiments of the invention;

[0045] Figure 3 A logic decision diagram for determining whether to enter the intensive phase for an embodiment of the invention;

[0046] Figure 4 A logical decision diagram for determining whether congestion exists according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0048] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0049] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0050] See also Figures 1 to 4 As shown, Figure 1 This is a functional module diagram of the high performance computing user quota intelligent management system according to an embodiment of the present invention. Figure 2 A logical decision diagram for classifying resource demand levels in an embodiment of the invention, Figure 3 A logic decision diagram for determining whether to enter the intensive phase for an embodiment of the invention, Figure 4 The logical decision diagram for determining whether there is congestion according to the embodiment of the invention is as follows: The intelligent management system for high performance computing user quotas according to the embodiment of the invention includes:

[0051] A data acquisition module, which is used to acquire operation data input by the user terminal and record resource usage data when the game characters controlled by different user terminals interact with the modeling targets preset in the game scene, wherein the operation data includes several instructions for the user terminal to control the game characters to generate actions;

[0052] A quota analysis module connected to the data acquisition module, for calculating a resource demand characterization parameter for a plurality of modeling targets based on resource usage data corresponding to the modeling targets, so as to classify the resource demand degree of the modeling targets, wherein the resource usage data corresponding to the plurality of modeling targets include a throughput of a user terminal and a number of instructions issued by the user terminal;

[0053] A resource allocation module, which is connected to the data acquisition module and the quota analysis module respectively, is used to determine the pre-interaction modeling target according to the operation data of the user terminal, and allocate resources to the user terminal according to the resource demand degree category of the modeling target, including:

[0054] According to the resource demand characterization parameter, the upper limit of the number of service nodes at the user end is adjusted, a time domain curve of the number of service nodes is constructed, the slope of the time domain curve segment at each moment is analyzed to determine whether it has entered a dense phase, and the response time of each service node at the user end in the dense phase is called to determine whether there is congestion, so as to correct the upper limit of the number of service nodes at the user end;

[0055] Or, determining operation stability characterization parameters according to system load characteristics to determine whether to adjust the upper limit of the number of user-side service nodes;

[0056] Among them, the system load characteristics include the average number of active processes on the user side and the data transmission volume.

[0057] Specifically, the operation data input by the user terminal includes operation instructions such as instructions for controlling the movement of the game character and instructions for controlling the game character to use skills.

[0058] It can be understood that the modeling targets pre-set in the game scene include NPC characters in the game and character models such as bosses that need to be defeated in tasks of different difficulty. At the same time, controlling the game characters to interact with them can be a conversation with the NPC characters, or a number of actions generated by fighting against the bosses that need to be defeated in the task. The relevant data can be obtained by calling the background running data, which will not be elaborated here.

[0059] Specifically, there is no limitation on the specific structures of the data acquisition module, quota analysis module and resource allocation module, which themselves or each unit therein can be composed of logic components or a combination of logic components, and the logic components include field programmable processors, computers or microprocessors in computers.

[0060] Specifically, the quota analysis module calculates the resource demand characterization parameter according to formula (1):

[0061]

[0062] In formula (1), R represents the parameter representing resource demand, P represents the throughput of the user end, P0 represents the throughput threshold, U represents the number of instructions issued by the user end, U0 represents the instruction number threshold, α represents the throughput weight coefficient, and β represents the instruction number weight coefficient.

[0063] In this example, the user-side throughput is the amount of data that the user-side device can receive and send per unit time in network communication.

[0064] The instruction quantity threshold U0 and throughput threshold P0 issued by the user end are pre-set. The instruction quantity and throughput within a predetermined time period recorded by the data acquisition module when different user ends interact with the corresponding modeling targets are obtained, and the mean instruction quantity ΔU and the mean throughput ΔP corresponding to each user end are solved. It is set that U0=r1×ΔU, P0=r2×ΔP, r1 is the first deviation coefficient, r2 is the second deviation coefficient, 1.05<r1<1.10, 1.1<r2<1.15, α is 0.55, and β is 0.45.

[0065] The predetermined time period is selected within the interval [0.3ΔT, 0.5ΔT], where ΔT is the average interaction duration when different user terminals interact with the modeling target.

[0066] The present invention calculates resource demand characterization parameters for modeling targets through resource usage data corresponding to several modeling targets. During the game operation, the user terminal continuously issues operation instructions, which will generate a certain amount of resource consumption and data transmission. In particular, when the user terminal controls the game character to interact with the modeling target pre-set in the game scene, more resource consumption and data transmission will be generated. For example, when fighting with the NPC character that needs to be defeated in a high-difficulty task, the operation instructions issued by the user terminal to control the game character to attack are intensive, continuous and fast. Therefore, sufficient resources are required to ensure the smoothness of the user terminal's control of the game character operation and avoid the occurrence of freezes and the like. Therefore, the present application calculates the resource demand characterization parameters for the modeling target through the throughput of the user terminal and the number of instructions issued to characterize the degree of resources required when the user terminal controls the game character to interact with the modeling target, and provides data support for the subsequent division of the resource demand degree of the modeling target. The pre-interaction modeling target is determined according to the operation data of the user terminal, and resources are adaptively allocated to the user terminal in advance, thereby ensuring the smoothness of the game operation and the rationality of the resource quota, and improving the overall resource utilization efficiency.

[0067] Specifically, the quota analysis module is used to classify the resource demand degree of the modeling target, including:

[0068] If the resource demand characterization parameter is greater than or equal to the resource demand characterization parameter threshold, the resource demand of the modeling target is determined to be a high degree category;

[0069] If the resource demand characterization parameter is less than the resource demand characterization parameter threshold, the resource demand of the modeling target is determined to be a low-level category.

[0070] The resource demand characterization parameter threshold R0 is selected in the interval [1.35, 1.47].

[0071] Specifically, the resource allocation module is used to allocate resources to the user terminal according to the resource demand level category of the modeling target, including:

[0072] If the resource demand of the modeling target is of a high degree category, the upper limit of the number of service nodes at the user end is adjusted according to the resource demand characterization parameter, a time domain curve of the number of service nodes is constructed, and the slope of the time domain curve segment at each moment is analyzed to determine whether it has entered the intensive stage, and the response time of each service node at the user end in the intensive stage is called to determine whether there is congestion, so as to correct the upper limit of the number of service nodes at the user end;

[0073] If the resource demand of the modeling target is of a low level category, the operation stability characterization parameter is determined according to the system load characteristics to determine whether to adjust the upper limit of the number of user-side service nodes.

[0074] Specifically, there is no limitation on the method of determining the pre-interaction modeling target. It can be to identify the modeling target corresponding to the jump position according to the jump position instruction issued by the user end, and determine the corresponding modeling target as the pre-interaction modeling target. This will not be repeated.

[0075] Specifically, the resource allocation module is used to adjust the upper limit of the number of user-side service nodes, including:

[0076] The upper limit of the number of service nodes at the user end is increased, and the increase in the upper limit of the number of service nodes is positively correlated with the resource demand characterization parameter.

[0077] In this embodiment, optionally,

[0078] The resource demand characterization parameter R is compared with the first resource demand characterization parameter comparison threshold R1 and the second resource demand characterization parameter comparison threshold R2,

[0079] If R>R2, the service node number upper limit increase amount is determined to be the first service node number upper limit increase amount c1, and c1=[0.45c0] is set;

[0080] If R1≤R≤R2, the service node number upper limit increase amount is determined to be the second service node number upper limit increase amount c2, and c2=[0.33c0] is set;

[0081] If R<R1, the service node number upper limit increase amount is determined to be the third service node number upper limit increase amount c3, and c3=[0.21c0] is set;

[0082] Wherein, c0 represents the upper limit of the initial service node, R1=1.2R0, R2=1.3R0.

[0083] Regarding the upper limit of the initial service node, those skilled in the art can determine it according to the scale, design, number of players and complexity of the server architecture of the game, which will not be elaborated here.

[0084] Specifically, the resource allocation module is used to construct the time domain curve of the number of service nodes and analyze the slope of the time domain curve at each moment, including:

[0085] A rectangular coordinate system is constructed with time as the horizontal axis and the number of service nodes as the vertical axis;

[0086] Marking coordinate points of the number of service nodes at each time in the rectangular coordinate system;

[0087] Connecting the coordinate points with a smooth curve to obtain the time domain curve;

[0088] If there is a time domain curve segment whose slope is greater than or equal to the slope threshold, it is determined to enter the intensive stage.

[0089] The slope threshold F0 is selected in the interval [0.24, 0.36].

[0090] Specifically, the resource allocation module is used to determine whether congestion exists, including:

[0091] If the response time of each service node of the user end in the intensive phase is greater than or equal to the response time threshold, it is determined that congestion exists.

[0092] In the intensive phase, if the response time of each service node of the user end is less than the response time threshold, it is determined that there is no congestion.

[0093] The response time threshold T0 is preset. The response time data of each service node during the game running on the user side is obtained, and the average response time ΔT is calculated. It is set that T0=k×ΔT, k is the offset coefficient, 1.15<r<1.3.

[0094] Specifically, the resource allocation module is used to modify the upper limit of the number of user-side service nodes, including:

[0095] If congestion exists, the upper limit of the number of user-side service nodes will be corrected.

[0096] It is understandable that if there is congestion, the upper limit of the number of user-side service nodes will be increased to ensure smooth data transmission and timely response of service nodes, avoid freezes and the like, and at the same time, meet the resource needs of the user side. The increase can be 0.1-0.3 times the current upper limit of the number of service nodes.

[0097] The present invention adjusts the upper limit of the number of service nodes on the user side in advance according to the resource demand characterization parameter under the category of high resource demand of the modeling target. According to the high resource demand required by the modeling target for pre-interaction, the upper limit of the number of service nodes on the user side is increased in advance to ensure the smoothness of the game operation. During the continuous operation of the game, the number of service nodes used by the user side is detected, a time domain curve of the number of service nodes is constructed, and the slope of the time domain curve segment at each moment is analyzed. For example, if the slope of the time domain curve segment is greater than or equal to the slope of the time domain segment when the game is running stably, it is determined that the intensive stage has been entered, and the response time data of each service node on the user side in the intensive stage is called. In actual situations, when the data transmission is stable and the resources can meet the needs of the user side, each service node on the user side will respond to the operation request instruction in a timely manner. If the service node fails to respond in time, a longer waiting time for the response is required. In this case, it is determined that congestion exists, so as to correct the upper limit of the number of service nodes on the user side, ensure the timely response of each service node and the smoothness of data transmission, and avoid congestion.

[0098] Specifically, the resource allocation module is used to determine the operational stability characterization parameters including:

[0099] to calculate a ratio of an average number of active processes within a predetermined time period to an average number of active processes of a preset threshold number of active processes within a predetermined time period;

[0100] for calculating a data transmission volume ratio of a data transmission volume within a predetermined time period to a data transmission volume threshold within a preset predetermined time period;

[0101] The operation stability characterization parameter is obtained by respectively assigning corresponding weight values ​​to the average ratio of the number of active processes and the ratio of the data transmission volume and summing them up.

[0102] In this embodiment, the operational stability characterization parameter D is calculated according to the following formula:

[0103]

[0104] In the formula, D represents the operation stability characterization parameter, H represents the mean number of active processes within a predetermined time period, H0 represents the threshold value of the number of active processes, J represents the data transmission volume within a predetermined time period, J0 represents the data transmission volume threshold, γ represents the weight coefficient of the ratio of the mean number of active processes, and δ represents the weight coefficient of the data transmission volume ratio.

[0105] The threshold value H0 for the number of active processes and the threshold value J0 for the amount of data transmitted are preset. The number of active processes and the amount of data transmitted within a predetermined time period recorded by the data acquisition module when different user terminals interact with the corresponding modeling targets are obtained. The mean number of active processes ΔH and the mean amount of data transmitted ΔJ corresponding to each user terminal are solved. It is set that H0 = q1 × ΔH, J0 = q2 × ΔJ, q1 is the first precision coefficient, q2 is the second precision coefficient, 1.07 < q1 < 1.14, 1.15 < q2 < 1.19, γ is 0.57, and δ is 0.43.

[0106] The predetermined time period is selected within the interval [0.3ΔT, 0.5ΔT], where ΔT is the average interaction duration when different user terminals interact with the modeling target.

[0107] Specifically, the resource allocation module is used to determine whether to adjust the upper limit of the number of user-side service nodes, including:

[0108] If the operation stability characterization parameter is greater than or equal to the operation stability characterization parameter threshold, the upper limit of the number of client service nodes is adjusted.

[0109] The upper limit of the number of service nodes will be increased by 0.1-0.3 times the initial upper limit of the number of service nodes.

[0110] The present invention determines the operation stability characterization parameters according to the system load characteristics under the low resource demand category of the modeling target, and predicts the resource demand according to the average number of active processes and the data transmission volume when the existing resources can meet the user-side demand. For example, a large number of active processes will generate high demand for resources, and a large amount of data transmission will increase the system load and the usage of memory resources, and will also use more network bandwidth, CPU and other resources. Therefore, the present application characterizes the user-side demand tendency for resources through the operation stability characterization parameters to determine whether to adjust the upper limit of the number of user-side service nodes, thereby ensuring the smoothness of game operation and the rationality of resource quotas, and improving the overall resource utilization efficiency.

[0111] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A high performance computing user quota intelligent management system, characterized in that: include: A data acquisition module, which is used to acquire operation data input by the user terminal and record resource usage data when the game characters controlled by different user terminals interact with the modeling targets preset in the game scene, wherein the operation data includes several instructions for the user terminal to control the game characters to generate actions; A quota analysis module connected to the data acquisition module, for calculating a resource demand characterization parameter for a plurality of modeling targets based on resource usage data corresponding to the modeling targets, so as to classify the resource demand degree of the modeling targets, wherein the resource usage data corresponding to the plurality of modeling targets include a throughput of a user terminal and a number of instructions issued by the user terminal; A resource allocation module, which is connected to the data acquisition module and the quota analysis module respectively, is used to determine the pre-interaction modeling target according to the operation data of the user terminal, and allocate resources to the user terminal according to the resource demand degree category of the modeling target, including: According to the resource demand characterization parameter, the upper limit of the number of service nodes at the user end is adjusted, a time domain curve of the number of service nodes is constructed, the slope of the time domain curve segment at each moment is analyzed to determine whether it has entered a dense phase, and the response time of each service node at the user end in the dense phase is called to determine whether there is congestion, so as to correct the upper limit of the number of service nodes at the user end; Or, determining operation stability characterization parameters according to system load characteristics to determine whether to adjust the upper limit of the number of user-side service nodes; Among them, the system load characteristics include the average number of active processes on the user side and the data transmission volume.

2. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The quota analysis module calculates the resource demand characterization parameter according to formula (1): In formula (1), R represents the parameter representing resource demand, P represents the throughput of the user end, P0 represents the throughput threshold, U represents the number of instructions issued by the user end, U0 represents the instruction number threshold, α represents the throughput weight coefficient, and β represents the instruction number weight coefficient.

3. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The quota analysis module is used to classify the resource demand degree of the modeling target, including: If the resource demand characterization parameter is greater than or equal to the resource demand characterization parameter threshold, the resource demand of the modeling target is determined to be a high degree category; If the resource demand characterization parameter is less than the resource demand characterization parameter threshold, the resource demand of the modeling target is determined to be a low-level category.

4. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The resource allocation module is used to allocate resources to the user end according to the resource demand level category of the modeling target, include, If the resource demand of the modeling target is of a high degree category, the upper limit of the number of service nodes at the user end is adjusted according to the resource demand characterization parameter, a time domain curve of the number of service nodes is constructed, and the slope of the time domain curve segment at each moment is analyzed to determine whether it has entered the intensive stage, and the response time of each service node at the user end in the intensive stage is called to determine whether there is congestion, so as to correct the upper limit of the number of service nodes at the user end; If the resource demand of the modeling target is of a low level category, the operation stability characterization parameter is determined according to the system load characteristics to determine whether to adjust the upper limit of the number of user-side service nodes.

5. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The resource allocation module is used to adjust the upper limit of the number of user-side service nodes, including: The upper limit of the number of service nodes at the user end is increased, and the increase in the upper limit of the number of service nodes is positively correlated with the resource demand characterization parameter.

6. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The resource allocation module is used to construct the time domain curve of the number of service nodes and analyze the slope of the time domain curve at each moment, including: A rectangular coordinate system is constructed with time as the horizontal axis and the number of service nodes as the vertical axis; Marking coordinate points of the number of service nodes at each time in the rectangular coordinate system; Connecting the coordinate points with a smooth curve to obtain the time domain curve; If there is a time domain curve segment whose slope is greater than or equal to the slope threshold, it is determined to enter the intensive stage.

7. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The resource allocation module is used to determine whether congestion exists, including: If the response time of each service node of the user end in the intensive phase is greater than or equal to the response time threshold, it is determined that congestion exists.

8. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The resource allocation module is used to modify the upper limit of the number of user-side service nodes, including: If congestion exists, the upper limit of the number of user-side service nodes will be corrected.

9. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The resource allocation module is used to determine the operational stability characterization parameters including: to calculate a ratio of an average number of active processes within a predetermined time period to an average number of active processes of a preset threshold number of active processes within a predetermined time period; for calculating a data transmission volume ratio of a data transmission volume within a predetermined time period to a data transmission volume threshold within a preset predetermined time period; The operation stability characterization parameter is obtained by respectively assigning corresponding weight values ​​to the average ratio of the number of active processes and the data transmission volume ratio and summing them up.

10. The high performance computing user quota intelligent management system according to claim 1, characterized in that: The resource allocation module is used to determine whether to adjust the upper limit of the number of user-side service nodes, including: If the operation stability characterization parameter is greater than or equal to the operation stability characterization parameter threshold, the upper limit of the number of client service nodes is adjusted.

Images