Resource scheduling method and device applied to game numerical value test

Abstract

The invention relates to the technical field of game testing, and discloses a resource scheduling method and device applied to a game numerical value test, the method is applied to a numerical value test scheduling engine, and the method comprises the following steps: after the numerical value test scheduling engine completes initialization, loading configuration information of the numerical value test scheduling engine, obtaining a current test task in the test task queue; the current test task comprises multiple rounds of tests; determining a test resource demand corresponding to the current test task according to the configuration information and the current test task; determining a resource scheduling strategy of the current test task according to the test resource demand; and after the resource connection is established, allocating required test task resources to the current test task from the distributed resource pool based on a resource scheduling strategy. Therefore, the resource scheduling method and the resource scheduling device can flexibly schedule required resources from the distributed resource pool for the current test task in a targeted manner, so that the resource scheduling efficiency and reliability of the game test are improved, and the game test efficiency and stability are improved.

Description

Technical Field

[0001] The present invention relates to the field of game testing technology, and in particular to a resource scheduling method and device applied to game numerical testing. Background Art

[0002] In the existing game development process, game testing can be used to discover and fix loopholes and defects in the game, and to evaluate the game balance and stability, so as to optimize the game design and improve the user's gaming experience. It can be seen that game testing is a key part of the game development process.

[0003] However, in practice, it is found that if a large number of highly complex and computationally intensive game matches need to be tested, it may be difficult to efficiently and timely schedule test resources, resulting in performance bottlenecks, which may lead to inefficient game testing or inaccurate test results, affecting the efficiency of subsequent game optimization based on the test results.

[0004] Therefore, it is particularly important to propose a technical solution that can improve the resource scheduling efficiency and reliability of game testing, thereby improving the efficiency and stability of game testing. Summary of the invention

[0005] The present invention provides a resource scheduling method and device applied to game numerical testing, which can improve the resource scheduling efficiency and reliability of game testing, thereby improving the efficiency and stability of game testing.

[0006] In order to solve the above technical problems, the first aspect of the present invention discloses a resource scheduling method applied to a game numerical test, the method is applied to a numerical test scheduling engine, and the method comprises:

[0007] After detecting that the numerical test scheduling engine has completed initialization, loading the configuration information of the numerical test scheduling engine, and obtaining the current test task in the test task queue; the test task queue includes at least one test task; the current test task includes multiple rounds of testing;

[0008] Determine the test resource requirement corresponding to the current test task according to the configuration information and the current test task;

[0009] Determine the resource scheduling strategy for the current test task according to the test resource demand;

[0010] After establishing a resource connection with the distributed resource pool, required test task resources are allocated to the current test task from the distributed resource pool based on the resource scheduling policy.

[0011] As an optional implementation, in the first aspect of the present invention, the configuration information includes a combination of one or more of a game item, a game mode, a game resource address, and an initial scheduling strategy;

[0012] The step of determining the test resource requirement corresponding to the current test task according to the configuration information and the current test task includes:

[0013] Analyze the current test task to obtain test information corresponding to the current test task; the test information includes test game parameters and / or test environment parameters; the test game parameters include one or more combinations of test times, test objects and game operation modes; the test objects include one or more combinations of test levels, test gameplay, test characters, test lineups, test difficulty and test value types; the test environment parameters include environmental configuration parameters of the test environment;

[0014] Determine the test resource sub-demands corresponding to each round of the test in the current test task and the cluster resource demand corresponding to the current test task according to the configuration information and the test information; the test resource sub-demands corresponding to each round of the test include at least one test resource type required for the test and the resource quantity of each test resource type required for the test;

[0015] The test resource requirement corresponding to the current test task includes the test resource sub-requirements corresponding to each round of the test and the cluster resource requirement corresponding to the current test task.

[0016] As an optional implementation manner, in the first aspect of the present invention, determining the test resource sub-requirements corresponding to each round of the test in the current test task according to the configuration information and the test information includes:

[0017] Determine at least one resource type required for the current test task according to the configuration information;

[0018] Determine at least one test resource type required for each round of the test from all the resource types according to the test information;

[0019] Analyze the computational complexity of each round of the test in the current test task according to the test information;

[0020] Based on the computational complexity corresponding to each round of the test, the quantity of resources of each test resource type required for each round of the test is determined.

[0021] As an optional implementation, in the first aspect of the present invention, the multiple rounds of tests included in the current test task are arranged in time sequence;

[0022] Wherein, determining the resource scheduling strategy of the current test task according to the test resource demand includes:

[0023] Based on a preset expansion algorithm, determine the target comparison test corresponding to each round of the test; when the expansion algorithm is a discrete expansion algorithm, the target comparison test corresponding to each round of the test includes a combination of one or more of the first test in the timing, the last test in the timing, and the test that is adjacent to the test timing; when the expansion algorithm is a non-discrete expansion algorithm, the target comparison test corresponding to each round of the test includes a first adjacent test that is adjacent to the test timing and a second adjacent test that is adjacent to the first adjacent test timing;

[0024] For each round of the test, determining a resource comparison result corresponding to the test based on the test and the target comparison test corresponding to the test;

[0025] According to the resource comparison results corresponding to each round of the test, a resource scheduling strategy for the current test task is generated.

[0026] As an optional implementation, in the first aspect of the present invention, when the expansion algorithm is the non-discrete expansion algorithm, for each round of the test, the test is compared with the target corresponding to the test to determine the resource comparison result corresponding to the test, including:

[0027] Calculating a resource quantity ratio between a test resource sub-requirement of a second adjacent test corresponding to the test and a test resource sub-requirement of a first adjacent test corresponding to the test; wherein the resource comparison result corresponding to the test includes the resource quantity ratio;

[0028] And, when the expansion algorithm is the non-discrete expansion algorithm, generating the resource scheduling strategy of the current test task according to the resource comparison result corresponding to each round of the test includes:

[0029] For each round of the test, the resource quantity ratio in the resource comparison result corresponding to the test is determined as the resource expansion ratio of the test;

[0030] A resource scheduling strategy for the current test task is generated according to the resource expansion ratio of each round of the test.

[0031] As an optional implementation manner, in the first aspect of the present invention, allocating required test task resources for the current test task from the distributed resource pool based on the resource scheduling strategy includes:

[0032] When the resource scheduling type corresponding to the resource scheduling strategy is a dynamic scheduling type, determining the target resource unit corresponding to each round of the test in the distributed resource pool; wherein the target resource unit corresponding to each round of the test is the resource unit with the least number of connections determined when executing the test;

[0033] For each round of the test, based on the resource scheduling strategy, the required test resources are allocated to the test from the target resource units corresponding to the test;

[0034] The test task resources include the test resources required for each round of the test.

[0035] As an optional implementation manner, in the first aspect of the present invention, after allocating required test task resources for the current test task from the distributed resource pool based on the resource scheduling policy, the method further includes:

[0036] During the execution of the current test task, monitoring resource usage of each round of the test;

[0037] Determine the resource utilization rate of each round of the test according to the test resources required for each round of the test and the resource usage of each round of the test;

[0038] According to the resource utilization and a preset dynamic adjustment mechanism, the resource scheduling strategy is optimized to obtain an optimized scheduling strategy; the dynamic adjustment mechanism includes an elastic container mechanism and / or a load dynamic expansion mechanism.

[0039] A second aspect of the present invention discloses a resource scheduling device applied to a game numerical test, the device being applied to a numerical test scheduling engine, the device comprising:

[0040] An acquisition module, configured to load the configuration information of the numerical test scheduling engine and acquire the current test task in the test task queue after detecting that the numerical test scheduling engine has completed initialization; the test task queue includes at least one test task; the current test task includes multiple rounds of testing;

[0041] A determination module, used to determine the test resource requirements corresponding to the current test task according to the configuration information and the current test task;

[0042] The determination module is further used to determine the resource scheduling strategy of the current test task according to the test resource demand;

[0043] The allocation module is used to allocate the required test task resources for the current test task from the distributed resource pool based on the resource scheduling strategy after establishing a resource connection with the distributed resource pool.

[0044] As an optional implementation, in the second aspect of the present invention, the configuration information includes a combination of one or more of a game item, a game mode, a game resource address, and an initial scheduling strategy;

[0045] The specific manner in which the determination module determines the test resource requirement corresponding to the current test task according to the configuration information and the current test task includes:

[0046] Analyze the current test task to obtain test information corresponding to the current test task; the test information includes test game parameters and / or test environment parameters; the test game parameters include one or more combinations of test times, test objects and game operation modes; the test objects include one or more combinations of test levels, test gameplay, test characters, test lineups, test difficulty and test value types; the test environment parameters include environmental configuration parameters of the test environment;

[0047] Determine the test resource sub-demands corresponding to each round of the test in the current test task and the cluster resource demand corresponding to the current test task according to the configuration information and the test information; the test resource sub-demands corresponding to each round of the test include at least one test resource type required for the test and the resource quantity of each test resource type required for the test;

[0048] The test resource requirement corresponding to the current test task includes the test resource sub-requirements corresponding to each round of the test and the cluster resource requirement corresponding to the current test task.

[0049] As an optional implementation, in the second aspect of the present invention, the specific manner in which the determination module determines the test resource sub-requirements corresponding to each round of the test in the current test task according to the configuration information and the test information includes:

[0050] Determine at least one resource type required for the current test task according to the configuration information;

[0051] Determine at least one test resource type required for each round of the test from all the resource types according to the test information;

[0052] Analyze the computational complexity of each round of the test in the current test task according to the test information;

[0053] Based on the computational complexity corresponding to each round of the test, the quantity of resources of each test resource type required for each round of the test is determined.

[0054] As an optional implementation, in the second aspect of the present invention, the multiple rounds of tests included in the current test task are arranged in time sequence;

[0055] The specific manner in which the determination module determines the resource scheduling strategy of the current test task according to the test resource demand includes:

[0056] Based on a preset expansion algorithm, determine the target comparison test corresponding to each round of the test; when the expansion algorithm is a discrete expansion algorithm, the target comparison test corresponding to each round of the test includes a combination of one or more of the first test in the timing, the last test in the timing, and the test that is adjacent to the test timing; when the expansion algorithm is a non-discrete expansion algorithm, the target comparison test corresponding to each round of the test includes a first adjacent test that is adjacent to the test timing and a second adjacent test that is adjacent to the first adjacent test timing;

[0057] For each round of the test, determining a resource comparison result corresponding to the test based on the test and the target comparison test corresponding to the test;

[0058] According to the resource comparison results corresponding to each round of the test, a resource scheduling strategy for the current test task is generated.

[0059] As an optional implementation, in the second aspect of the present invention, when the capacity expansion algorithm is the non-discrete capacity expansion algorithm, for each round of the test, the test is compared with the target corresponding to the test to determine the resource comparison result corresponding to the test, including:

[0060] Calculating a resource quantity ratio between a test resource sub-requirement of a second adjacent test corresponding to the test and a test resource sub-requirement of a first adjacent test corresponding to the test; wherein the resource comparison result corresponding to the test includes the resource quantity ratio;

[0061] And, when the expansion algorithm is the non-discrete expansion algorithm, generating the resource scheduling strategy of the current test task according to the resource comparison result corresponding to each round of the test includes:

[0062] For each round of the test, the resource quantity ratio in the resource comparison result corresponding to the test is determined as the resource expansion ratio of the test;

[0063] A resource scheduling strategy for the current test task is generated according to the resource expansion ratio of each round of the test.

[0064] As an optional implementation, in the second aspect of the present invention, the specific manner in which the allocation module allocates the required test task resources from the distributed resource pool to the current test task based on the resource scheduling strategy includes:

[0065] When the resource scheduling type corresponding to the resource scheduling strategy is a dynamic scheduling type, determining the target resource unit corresponding to each round of the test in the distributed resource pool; wherein the target resource unit corresponding to each round of the test is the resource unit with the least number of connections determined when executing the test;

[0066] For each round of the test, based on the resource scheduling strategy, the required test resources are allocated to the test from the target resource units corresponding to the test;

[0067] The test task resources include the test resources required for each round of the test.

[0068] As an optional implementation, in the second aspect of the present invention, the device further includes:

[0069] A monitoring module, configured to monitor resource usage of each round of the test during the execution of the current test task after the allocation module allocates the required test task resources to the current test task from the distributed resource pool based on the resource scheduling strategy;

[0070] The determination module is further used to determine the resource utilization rate of each round of the test according to the test resources required for each round of the test and the resource usage of each round of the test;

[0071] The optimization module is used to optimize the resource scheduling strategy according to the resource utilization and a pre-set dynamic adjustment mechanism to obtain an optimized scheduling strategy; the dynamic adjustment mechanism includes an elastic container mechanism and / or a load dynamic expansion mechanism.

[0072] The third aspect of the present invention discloses another resource scheduling device for game numerical testing, the device comprising:

[0073] A memory storing executable program code;

[0074] a processor coupled to the memory;

[0075] The processor calls the executable program code stored in the memory to execute part or all of the steps of the resource scheduling method applied to game numerical testing disclosed in the first aspect of the present invention.

[0076] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute part or all of the steps of the resource scheduling method for game numerical testing disclosed in the first aspect of the present invention.

[0077] Compared with the prior art, the present invention has the following beneficial effects:

[0078] In the present invention, after detecting that the numerical test scheduling engine has completed initialization, the configuration information of the numerical test scheduling engine is loaded, and the current test task in the test task queue is obtained; the test task queue includes at least one test task; the current test task includes multiple rounds of testing; based on the configuration information and the current test task, the test resource demand corresponding to the current test task is determined; based on the test resource demand, the resource scheduling strategy of the current test task is determined; after establishing a resource connection with a distributed resource pool, based on the resource scheduling strategy, the required test task resources are allocated to the current test task from the distributed resource pool. It can be seen that the implementation of the present invention can load the corresponding configuration information and obtain the current test task after the numerical test scheduling engine is initialized, and then determine the test resource requirements corresponding to the current test task based on the configuration information and the current test task, and then determine the corresponding resource scheduling strategy based on the test resource requirements, and after establishing the resource connection, allocate the required test task resources for the current test task from the distributed resource pool based on the resource scheduling strategy, and can flexibly adjust the required scheduling resources from the distributed resource pool for the current game numerical test task and flexibly schedule the resources required for the task, thereby improving the flexibility and accuracy of determining the test resource requirements of the game test, and flexibly allocating test task resources through the distributed resource pool, so as to improve the efficiency, accuracy and reliability of the resource scheduling of the game test, thereby improving the efficiency and stability of the game test, which is beneficial to improving the accuracy and reliability of the game test results, and further beneficial to the efficiency and accuracy of subsequent game optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0080] Figure 1 It is a flow chart of a resource scheduling method applied to game numerical testing disclosed in an embodiment of the present invention;

[0081] Figure 2 It is a flow chart of another resource scheduling method applied to game numerical testing disclosed in an embodiment of the present invention;

[0082] Figure 3 It is a structural schematic diagram of a resource scheduling device applied to game numerical testing disclosed in an embodiment of the present invention;

[0083] Figure 4It is a structural schematic diagram of another resource scheduling device for game numerical testing disclosed in an embodiment of the present invention;

[0084] Figure 5 It is a structural schematic diagram of another resource scheduling device applied to game numerical testing disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0085] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0086] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0087] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0088] The present invention discloses a resource scheduling method and device for game numerical testing, which can load corresponding configuration information and obtain the current test task after completing the initialization of the numerical test scheduling engine, and then determine the test resource requirements corresponding to the current test task according to the configuration information and the current test task, and then determine the corresponding resource scheduling strategy according to the test resource requirements, and after establishing the resource connection, allocate the required test task resources for the current test task from the distributed resource pool based on the resource scheduling strategy, and can flexibly adjust the required scheduling resources from the distributed resource pool for the current game numerical test task and flexibly schedule the resources required for the task, improve the determination flexibility and accuracy of the test resource requirements of the game test, and flexibly allocate the test task resources through the distributed resource pool, so as to improve the efficiency, accuracy and reliability of the resource scheduling of the game test, thereby improving the efficiency and stability of the game test, which is conducive to improving the accuracy and reliability of the game test results, and is conducive to the subsequent game optimization efficiency and accuracy. The following are detailed descriptions.

[0089] Embodiment 1

[0090] See also Figure 1 , Figure 1 1 is a flow chart of a resource scheduling method for game numerical testing disclosed in an embodiment of the present invention. Figure 1 The resource scheduling method for game numerical testing described above can be applied to a resource scheduling device, which may include a resource scheduling device, a resource scheduling terminal, a resource scheduling system, and a server, wherein the server may be a local server or a cloud server, which is not limited in the embodiments of the present invention; the method can also be applied to a numerical test scheduling engine, and further, the numerical test scheduling engine can be applied to game numerical testing. Exemplarily, the game numerical testing can be specifically a game balance test, which is not limited in the embodiments of the present invention. Figure 1 As shown, the resource scheduling method applied to game numerical testing may include the following operations:

[0091] 101. After detecting that the numerical test scheduling engine has completed initialization, load the configuration information of the numerical test scheduling engine, and obtain the current test task in the test task queue.

[0092] In the embodiment of the present invention, the test task queue may include at least one test task; wherein the current test task is one of the test tasks, and the current test task may include multiple rounds of testing.

[0093] In an embodiment of the present invention, optionally, the configuration information of the numerical test scheduling engine may include a combination of one or more of game items, game modes, game resource addresses, and initial scheduling strategies, which are not limited in the embodiment of the present invention; wherein, exemplarily, the game mode may include PVP (Player Versus Player) mode and / or PVE (Player Versus Environment) mode, and may also include other game modes, which are not limited in the embodiment of the present invention; wherein, optionally, the initial scheduling strategy may be a resource scheduling strategy preset by the test scheduling engine, or may be a historical resource scheduling strategy executed by the test scheduling engine for the same type of tasks as the current test task, which is not limited in the embodiment of the present invention, and further optionally, the historical resource scheduling strategy may be a resource scheduling strategy after iterative optimization, which is not limited in the embodiment of the present invention. Further optionally, the configuration information of the numerical test scheduling engine may be stored in a configuration file of the numerical test scheduling engine, which is not limited in the embodiment of the present invention.

[0094] 102. Determine the test resource requirements corresponding to the current test task based on the configuration information and the current test task.

[0095] In the embodiment of the present invention, the test resource requirement corresponding to the current test task may include the test resource sub-requirements corresponding to each round of testing.

[0096] 103. Determine the resource scheduling strategy for the current test task based on the test resource requirements.

[0097] In an embodiment of the present invention, optionally, the resource scheduling strategy may include a combination of one or more of resource scheduling type, resource scheduling algorithm, scheduling resource address, resource size, resource quantity, resource scheduling time, resource scheduling frequency, and resource release time, which is not limited in the embodiment of the present invention.

[0098] 104. After establishing a resource connection with the distributed resource pool, based on the resource scheduling strategy, the required test task resources are allocated to the current test task from the distributed resource pool.

[0099] In the embodiment of the present invention, optionally, the test task resources may include a combination of one or more of CPU (Central Processing Unit) resources, memory resources, and storage resources, which is not limited in the embodiment of the present invention.

[0100] In the embodiment of the present invention, illustratively, based on the numerical test scheduling engine and according to the resource scheduling strategy, required test task resources can be allocated to the current test task from the distributed resource pool.

[0101] It can be seen that the method described in the embodiment of the present invention can load the corresponding configuration information and obtain the current test task after completing the initialization of the numerical test scheduling engine, and then determine the test resource requirements corresponding to the current test task based on the configuration information and the current test task, and then determine the corresponding resource scheduling strategy based on the test resource requirements. After establishing the resource connection, based on the resource scheduling strategy, the required test task resources are allocated to the current test task from the distributed resource pool, and the required resources for the current game numerical test task can be flexibly adjusted from the distributed resource pool and the resources required for the task can be flexibly scheduled, thereby improving the flexibility and accuracy of determining the test resource requirements for game testing, and flexibly allocating test task resources through the distributed resource pool, thereby improving the efficiency, accuracy and reliability of resource scheduling for game testing, thereby improving the efficiency and stability of game testing, which is beneficial to improving the accuracy and reliability of game testing results, and thereby facilitating the efficiency and accuracy of subsequent game optimization.

[0102] In an optional embodiment, before obtaining the current test task in the test task queue, the method may further include:

[0103] Based on containerization technology, each test task in the test task queue is encapsulated in the task container corresponding to the test task;

[0104] Configure the resource limit parameters of the task container corresponding to each test task.

[0105] Among them, illustratively, the containerization technology can be one of Docker, Kubernetes and other types of containerization technologies, which is not limited in the embodiments of the present invention.

[0106] Among them, the resource limitation parameters may include limited resource types and / or limited resource quantities, which are not limited in the embodiments of the present invention. Among them, the limited resource types may include resource types that can be scheduled by the test task (for example: CPU resources, memory resources), and the limited resource quantities may be the quantity threshold that can be scheduled by the test task for each limited resource type, which is not limited in the embodiments of the present invention.

[0107] It can be seen that this optional embodiment can encapsulate the test tasks in the container through containerization technology, and can also configure the resource restrictions of each container, which is conducive to realizing dynamic scheduling and resource isolation of resources, thereby facilitating improving the flexibility of resource scheduling.

[0108] In an optional embodiment, the numerical test scheduling engine may include an abstraction layer, and the numerical test scheduling engine may be configured as an adapter mode.

[0109] Among them, the above-mentioned numerical test scheduling engine can be used by calling the above-mentioned abstract layer; by configuring the above-mentioned adapter mode for the numerical test scheduling engine, the numerical test scheduling engine can be deployed in a variety of operating environments; exemplarily, the operating environment may include a combination of one or more of a local environment, a cloud environment, and a hybrid cloud environment, which is not limited in the embodiments of the present invention; wherein the local environment may include a combination of one or more of a mobile environment, a web environment, and a computer environment, which is not limited in the embodiments of the present invention.

[0110] It can be seen that this optional embodiment can configure the abstract layer and adapter mode, so that the numerical test scheduling engine can be compatible with different environments and run in different environments, which is conducive to realizing the above-mentioned resource scheduling method when conducting game numerical tests in different environments, and further helps to improve the applicability of the numerical test scheduling engine.

[0111] In an optional embodiment, allocating required test task resources for the current test task from a distributed resource pool based on a resource scheduling policy may include the following operations:

[0112] When the resource scheduling type corresponding to the resource scheduling strategy is a dynamic scheduling type, determining the target resource unit corresponding to each round of testing in the distributed resource pool; wherein the target resource unit corresponding to each round of testing is the resource unit with the least number of connections determined when executing the test;

[0113] For each round of testing, based on the resource scheduling strategy, the required test resources are allocated to the test from the target resource units corresponding to the test; wherein the test task resources include the test resources required for each round of testing.

[0114] The test resources required for each round of testing may include one or more combinations of CPU resources, memory resources, and storage resources, which are not limited in the embodiment of the present invention.

[0115] The distributed resource pool includes a plurality of deployable resource units, each resource unit has one or more resources required for the test, and the target resource unit is one of the resource units.

[0116] Optionally, the target resource unit corresponding to each round of testing may be specifically: a target resource unit with the least number of connections estimated in advance based on the connection status of each resource unit determined in advance; or it may be specifically: a target resource unit with the least number of connections determined in real time based on the real-time connection status of each resource unit during the execution of the current test task, and the embodiments of the present invention do not limit this.

[0117] It can be seen that this optional embodiment can determine the target resource unit corresponding to each round of testing in the distributed resource pool when the resource scheduling type is the dynamic scheduling type, and then allocate the required test resources for the test from the target resource unit corresponding to each round of testing based on the resource scheduling strategy, which can improve the flexibility of determining the target resource unit, and schedule resources from the target resource unit with the least number of connections, which can improve the scheduling efficiency and scheduling flexibility of resources required for each round of game testing, is conducive to achieving load balancing, and thus is conducive to further improving the efficiency and stability of game testing.

[0118] In this optional embodiment, optionally, the method may further include the following operations:

[0119] During the execution of the current test task, monitor the resource usage of each round of testing;

[0120] Determine the resource utilization rate of each round of testing based on the test resources required for each round of testing and the resource usage of each round of testing;

[0121] According to resource utilization and a pre-set dynamic adjustment mechanism, the resource scheduling strategy is optimized to obtain an optimized scheduling strategy; the dynamic adjustment mechanism includes an elastic container mechanism and / or a load dynamic expansion mechanism; or,

[0122] Determine whether the resource utilization rate of each round of testing is within the preset utilization rate range;

[0123] When it is determined that the resource utilization of any test is not within the preset utilization interval, the test whose resource utilization is not within the preset utilization interval is determined as the third target test;

[0124] According to the resource utilization rates of all third target tests and the preset utilization rate interval, the resource scheduling strategy is optimized to obtain an optimized scheduling strategy; wherein the optimized scheduling strategy is used as an initial scheduling strategy in the next test task.

[0125] The preset utilization interval includes at least one preset utilization threshold. Optionally, the preset utilization threshold may be a preset maximum utilization value or a preset minimum utilization value, which is not limited in the embodiment of the present invention.

[0126] It can be seen that this optional embodiment can also monitor the resource usage of each round of testing during the execution of the current test task, and determine the resource utilization of each round of testing based on the resource usage of each round of testing. If it is determined that the resource utilization of any test is not in the preset utilization range, the test whose resource utilization is not in the preset utilization range is determined as the third target test, and the resource scheduling strategy is optimized based on the resource utilization of all third target tests and the preset utilization range to obtain an optimized scheduling strategy, which can improve the timeliness and accuracy of monitoring resource usage during the game testing process, thereby helping to improve the determination efficiency and accuracy of tests with abnormal resource utilization, and further helping to improve the optimization accuracy of the resource scheduling strategy, and further helping to improve the determination efficiency and accuracy of the resource scheduling strategy in subsequent game testing tasks.

[0127] In this optional embodiment, optionally, the method may further include the following operations:

[0128] Based on the resource usage of each round of testing, detect whether there are resource anomalies in the execution of the current test task;

[0129] When it is detected that a resource anomaly exists during the execution of the current test task, it is determined that a fourth target test with the resource anomaly exists, and the fourth target test is re-executed based on a breakpoint retry mechanism.

[0130] It can be seen that this optional embodiment can also re-execute the fourth target test of resource anomalies based on the breakpoint retry mechanism when a resource anomaly is detected during the execution of the current test task, which can improve the timeliness and accuracy of detection of resource scheduling anomalies, thereby helping to ensure that the test task can be automatically restored when a resource anomaly occurs, and further helping to improve the stability and reliability of the game test execution process.

[0131] Embodiment 2

[0132] See also Figure 2 , Figure 2 1 is a flow chart of a resource scheduling method for game numerical testing disclosed in an embodiment of the present invention. Figure 2 The resource scheduling method for game numerical testing described above can be applied to a resource scheduling device, which may include a resource scheduling device, a resource scheduling terminal, a resource scheduling system, and a server, wherein the server may be a local server or a cloud server, which is not limited in the embodiments of the present invention; the method can also be applied to a numerical test scheduling engine, and further, the numerical test scheduling engine can be applied to game numerical testing. Exemplarily, the game numerical testing can be specifically a game balance test, which is not limited in the embodiments of the present invention. Figure 2As shown, the resource scheduling method applied to game numerical testing may include the following operations:

[0133] 201. After detecting that the numerical test scheduling engine has completed initialization, load the configuration information of the numerical test scheduling engine, and obtain the current test task in the test task queue.

[0134] In an embodiment of the present invention, the test task queue includes at least one test task; the current test task includes multiple rounds of testing; and the configuration information includes a combination of one or more of game items, game modes, game resource addresses, and initial scheduling strategies.

[0135] 202. Analyze the current test task and obtain the test information corresponding to the current test task.

[0136] In an embodiment of the present invention, the test information may include test game parameters and / or test environment parameters; optionally, the test game parameters include a combination of one or more of the test times, the test objects, and the game operation modes; wherein, exemplarily, the game operation modes may be a combination of one or more of the cloud mode, the local mode, and other operation modes, which is not limited in the embodiment of the present invention; optionally, the test objects include a combination of one or more of the test levels, the test gameplay, the test characters, the test lineups, the test difficulty, and the test numerical types; optionally, the test environment parameters include environmental configuration parameters of the test environment, which is not limited in the embodiment of the present invention.

[0137] 203. Determine the test resource sub-demands corresponding to each round of testing in the current test task and the cluster resource demand corresponding to the current test task according to the configuration information and the test information.

[0138] In the embodiment of the present invention, the test resource sub-requirements corresponding to each round of testing include at least one test resource type required for the test and the resource quantity of each test resource type required for the test.

[0139] 204. Determine the resource scheduling strategy for the current test task based on the test resource requirements.

[0140] In the embodiment of the present invention, the test resource requirement corresponding to the current test task includes the test resource sub-requirements corresponding to each round of testing and the cluster resource requirement corresponding to the current test task.

[0141] 205. After establishing a resource connection with the distributed resource pool, based on the resource scheduling strategy, the required test task resources are allocated to the current test task from the distributed resource pool.

[0142] In the embodiment of the present invention, for other detailed descriptions of step 201 and step 204-step 205, please refer to the detailed description of step 101 and step 103-step 104 in the first embodiment, and the embodiment of the present invention will not be repeated here.

[0143] It can be seen that the method described in the embodiment of the present invention can load the corresponding configuration information and obtain the current test task after completing the initialization of the numerical test scheduling engine, and then determine the test resource requirements corresponding to the current test task based on the configuration information and the current test task, and then determine the corresponding resource scheduling strategy based on the test resource requirements. After establishing the resource connection, based on the resource scheduling strategy, the required test task resources are allocated to the current test task from the distributed resource pool, and the required resources for the current game numerical test task can be flexibly adjusted from the distributed resource pool and the resources required for the task can be flexibly scheduled, thereby improving the flexibility and accuracy of determining the test resource requirements for game testing, and flexibly allocating test task resources through the distributed resource pool, thereby improving the efficiency, accuracy and reliability of resource scheduling for game testing, thereby improving the efficiency and stability of game testing, which is beneficial to improving the accuracy and reliability of game testing results, and thereby facilitating the efficiency and accuracy of subsequent game optimization. In addition, by analyzing the current test task, it is also possible to obtain the specific test game parameters and / or test environment parameters corresponding to the current test task, and determine the test resource types and corresponding resource quantities required for each round of testing based on the configuration information and the above test information. This can improve the accuracy and comprehensiveness of the analysis of the current test task, so as to obtain more comprehensive test information, which is conducive to further improving the accuracy of determining test resource requirements, and further conducive to improving the accuracy of resource scheduling for game testing.

[0144] In an optional embodiment, determining the test resource sub-requirements corresponding to each round of testing in the current test task according to the configuration information and the test information may include the following operations:

[0145] Determine at least one resource type required for the current test task according to the configuration information;

[0146] According to the test information, at least one test resource type required for each round of testing is determined from all resource types;

[0147] According to the test information, analyze the computational complexity corresponding to each round of testing in the current test task;

[0148] Based on the computational complexity corresponding to each round of testing, the number of resources of each test resource type required for each round of testing is determined.

[0149] The higher the computational complexity of each round of testing, the more resources are required to be called for that round of testing.

[0150] It can be seen that this optional embodiment can determine the resource type required for the current test task based on the configuration information, and then determine the test resource type required for each round of testing based on the test information, and then analyze the computational complexity corresponding to each round of testing based on the test information, and determine the number of resources of each test resource type required for each round of testing based on the computational complexity. This can improve the resource types required for each round of testing of the current test task, and improve the accuracy of determining the corresponding number of resources required for each round of testing based on the accurately determined test computational complexity, thereby helping to improve the accuracy of determining the test resource requirements of the current test task.

[0151] In another optional embodiment, the multiple rounds of tests included in the current test task are arranged in time sequence;

[0152] Among them, according to the test resource requirements, determining the resource scheduling strategy of the current test task may include the following operations:

[0153] Based on a pre-set expansion algorithm, determine the target comparison test corresponding to each round of testing; when the expansion algorithm is a discrete expansion algorithm, the target comparison test corresponding to each round of testing includes a combination of one or more of the tests that are sequentially first, sequentially last, and sequentially adjacent to the test; when the expansion algorithm is a non-discrete expansion algorithm, the target comparison test corresponding to each round of testing includes a first adjacent test that is sequentially adjacent to the test and a second adjacent test that is sequentially adjacent to the first adjacent test;

[0154] For each round of testing, determine the resource comparison result corresponding to the test based on the test and the target comparison test corresponding to the test;

[0155] According to the resource comparison results corresponding to each round of testing, a resource scheduling strategy for the current test task is generated.

[0156] It can be seen that this optional embodiment can select the corresponding target comparison test based on the preset expansion algorithm, determine the resource comparison results of each round of testing, and then generate a resource scheduling strategy based on this, which can improve the selection flexibility of the expansion algorithm, thereby improving the selection flexibility and selection accuracy of the target comparison test, and further help to improve the determination flexibility and determination accuracy of the resource scheduling strategy.

[0157] In this optional embodiment, optionally, when the expansion algorithm is a non-discrete expansion algorithm, for each round of testing, according to the test and the target comparison test corresponding to the test, determining the resource comparison result corresponding to the test includes:

[0158] Calculating a resource quantity ratio between a test resource sub-requirement of a second adjacent test corresponding to the test and a test resource sub-requirement of a first adjacent test corresponding to the test; wherein the resource comparison result corresponding to the test includes the resource quantity ratio;

[0159] Furthermore, when the expansion algorithm is a non-discrete expansion algorithm, a resource scheduling strategy for the current test task is generated according to the resource comparison result corresponding to each round of testing, including:

[0160] For each round of testing, the resource quantity ratio in the resource comparison result corresponding to the test is determined as the resource expansion ratio of the test;

[0161] Generate a resource scheduling strategy for the current test task based on the resource expansion ratio of each round of testing.

[0162] For example, assuming that the current test task has three rounds of tests A, B, and C, the ratio between the number of resources required for test A (e.g., 60) and the number of resources required for test B (e.g., 80) (80 / 60=4 / 3) can be used as the resource expansion ratio for test C, which is not limited in this embodiment of the present invention.

[0163] It can be seen that this optional embodiment can also calculate the difference between previous adjacent test resource requirements as the expansion ratio when a non-discrete expansion algorithm is selected, thereby generating a corresponding resource scheduling strategy, which can improve the calculation flexibility of the resource expansion ratio, thereby facilitating improving the adjustment flexibility of the resource scheduling strategy, and further facilitating improving the resource scheduling flexibility.

[0164] In this optional embodiment, optionally, when the expansion algorithm is a discrete expansion algorithm, for each round of testing, determining the resource comparison result corresponding to the test according to the test and the target comparison test corresponding to the test may include the following operations:

[0165] For each round of testing, the test resource sub-requirements corresponding to the test are compared with the test resource sub-requirements corresponding to the determined target comparison test to obtain the resource comparison result corresponding to the test; the target comparison test includes a combination of one or more of the first test in the sequence, the last test in the sequence, and the test that is adjacent to the test sequence;

[0166] Furthermore, when the expansion algorithm is a discrete expansion algorithm, a resource scheduling strategy for the current test task is generated according to the resource comparison result corresponding to each round of testing, which may include the following operations:

[0167] According to the resource comparison results corresponding to all tests, determine whether the current test task meets the pre-set dynamic scheduling conditions;

[0168] When it is determined that the current test task meets the dynamic scheduling condition, the resource scheduling type of the current test task is determined to be a dynamic scheduling type;

[0169] When it is determined that the current test task does not meet the dynamic scheduling condition, the resource scheduling type of the current test task is determined to be a static scheduling type;

[0170] The resource scheduling strategy for the current test task is generated according to the resource comparison results corresponding to each round of testing, the above resource scheduling type and the initial scheduling strategy.

[0171] Among them, the resource comparison results corresponding to each round of testing may include resource type differences and / or resource quantity differences corresponding to each test resource type; among them, the resource type differences may include the difference set between the test resource type required for this round of testing and the test resource type required for the corresponding target comparison test, which is not limited in the embodiments of the present invention.

[0172] It can be seen that this optional embodiment can judge whether the current test task meets the dynamic scheduling conditions based on the resource comparison results obtained by comparing the test resource sub-requirements corresponding to each round of testing with the test resource sub-requirements corresponding to the corresponding target comparison test. If satisfied, the resource scheduling type of the current test task is determined to be a dynamic scheduling type; otherwise, the resource scheduling type of the current test task is determined to be a static scheduling type. Then, based on the resource comparison results, the resource scheduling type and the initial scheduling strategy, the resource scheduling policy of the current test task is generated, which can improve the accuracy of the analysis of the test resource requirements, thereby facilitating the improvement of the accuracy of the determination of the resource scheduling type, and further facilitating the improvement of the accuracy of the generation of the resource scheduling policy, so as to improve the accuracy and efficiency of resource scheduling.

[0173] In this optional embodiment, optionally, generating a resource scheduling strategy for the current test task according to the resource comparison result corresponding to each round of testing, the resource scheduling type and the initial scheduling strategy may include the following operations:

[0174] Determine whether the resource scheduling type of the current test task is consistent with the initial resource scheduling type of the initial scheduling strategy;

[0175] When it is determined that the resource scheduling type is consistent with the initial resource scheduling type, the initial scheduling strategy is adjusted according to the resource comparison results corresponding to each round of testing to obtain the resource scheduling strategy for the current test task;

[0176] When it is determined that the resource scheduling type is inconsistent with the initial resource scheduling type, a resource scheduling strategy for the current test task is generated according to the resource comparison result and resource scheduling type corresponding to each round of testing.

[0177] It can be seen that this optional embodiment can also adjust the initial scheduling strategy according to the resource comparison result to obtain the resource scheduling strategy of the current test task if it is determined that the resource scheduling type is consistent with the initial resource scheduling type. Otherwise, the resource scheduling strategy of the current test task is generated according to the resource comparison result and resource scheduling type corresponding to each round of testing. This can improve the flexibility of generating resource scheduling strategies and improve the degree of adaptation of resource scheduling strategies to actual needs, thereby helping to further improve the accuracy of resource scheduling strategies.

[0178] In this optional embodiment, optionally, judging whether the current test task meets the preset dynamic scheduling condition according to the resource comparison results corresponding to all tests may include the following operations:

[0179] Determine the first target test and the second target test in the current test task, and count the first number of the first target test and the second number of the second target test; wherein the first target test is a test in which the resource type difference does not meet the preset type difference condition; the second target test is a test in which there is at least one test resource type corresponding to a resource quantity difference value greater than the preset quantity difference value corresponding to the test resource type;

[0180] Determine the resource scheduling distribution corresponding to the current test task according to all first target tests and all second target tests; the resource scheduling distribution includes the first timing distribution of all first target tests in the current test task and the second timing distribution of all second target tests in the current test task;

[0181] Determine whether the first quantity satisfies a first preset quantity condition, whether the second quantity satisfies a second preset quantity condition, and whether the resource scheduling distribution condition satisfies a preset resource scheduling distribution condition;

[0182] When it is determined that the first quantity satisfies the first preset quantity condition and the second quantity satisfies the second preset quantity condition and the resource scheduling distribution condition satisfies the resource scheduling distribution condition, determining that the current test task satisfies the preset dynamic scheduling condition;

[0183] When it is determined that the first quantity does not meet the first preset quantity condition or the second quantity does not meet the second preset quantity condition or the resource scheduling distribution does not meet the resource scheduling distribution condition, it is determined that the current test task does not meet the preset dynamic scheduling condition.

[0184] It can be seen that this optional embodiment can also determine the first target test that does not meet the preset type difference condition and the second target test that does not meet the preset quantity difference by analyzing the resource type difference and the resource quantity difference, and determine the timing distribution of the first target test and the second target test, and then determine whether the dynamic scheduling conditions are met according to the quantity and timing distribution of the first target test and the second target test. When the resource scheduling conditions between multiple rounds of tests differ too much, dynamic scheduling can be adopted. If the resource scheduling conditions in the test task are relatively stable, static scheduling can be adopted. This can further improve the comprehensiveness and accuracy of the analysis of the differences in resource scheduling requirements for each round of testing, thereby helping to further improve the accuracy of determining the resource scheduling type, and further help to further improve the accuracy of generating resource scheduling strategies.

[0185] In this optional embodiment, optionally, determining whether the first quantity satisfies a first preset quantity condition may specifically be:

[0186] Determine a first proportion of the first quantity in the total number of tests of the current test task;

[0187] Determine whether the first quantity is less than or equal to a first preset quantity and whether the first proportion is less than or equal to the first preset proportion;

[0188] When it is determined that the first quantity is less than or equal to the first preset quantity and the first proportion is less than or equal to the first preset proportion, it is determined that the first quantity meets the first preset quantity condition;

[0189] When it is determined that the first quantity is greater than the first preset quantity or the first proportion is greater than the first preset proportion, it is determined that the first quantity does not satisfy the first preset quantity condition.

[0190] Optionally, determining whether the second quantity satisfies a second preset quantity condition may specifically be:

[0191] Determine a second proportion of the second number in the total number of tests of the current test task;

[0192] Determine whether the second number is less than or equal to a second preset number and whether the second proportion is less than or equal to the second preset proportion;

[0193] When it is determined that the second quantity is less than or equal to the second preset quantity and the second proportion is less than or equal to the second preset proportion, determining that the second quantity meets the second preset quantity condition;

[0194] When it is determined that the second quantity is greater than the second preset quantity or the second proportion is greater than the second preset proportion, it is determined that the second quantity does not satisfy the second preset quantity condition.

[0195] It can be seen that this optional embodiment can also determine whether the number of first target tests / second target tests meets the corresponding quantity conditions by determining whether the number of first target tests / second target tests is less than or equal to the preset number and whether the corresponding proportion is less than or equal to the preset proportion, which can improve the flexibility and accuracy of determining whether the first quantity / second quantity meets the quantity conditions, thereby helping to further improve the accuracy of determining whether the current test task meets the dynamic scheduling conditions.

[0196] In this optional embodiment, optionally, judging whether the resource scheduling distribution condition satisfies a preset resource scheduling distribution condition may specifically be:

[0197] Determine whether the overlap degree between the first time series distribution situation and the second time series distribution situation is greater than or equal to a preset overlap degree and whether the first time series distribution situation and the second time series distribution situation are both concentratedly distributed;

[0198] When it is determined that the overlap degree between the first timing distribution situation and the second timing distribution situation is greater than or equal to the preset overlap degree and the first timing distribution situation and the second timing distribution situation are both concentratedly distributed, it is determined that the resource scheduling distribution situation meets the preset resource scheduling distribution condition;

[0199] When it is determined that the overlap between the first timing distribution and the second timing distribution is less than a preset overlap or one of the first timing distribution and the second timing distribution is a dispersed distribution, it is determined that the resource scheduling distribution does not meet the preset resource scheduling distribution condition.

[0200] It can be seen that this optional embodiment can also determine that the resource scheduling distribution situation meets the preset resource scheduling distribution conditions if it is determined that the degree of overlap between the first timing distribution situation and the second timing distribution situation is greater than or equal to the preset overlap degree and the first timing distribution situation and the second timing distribution situation are both concentratedly distributed. Otherwise, it is determined that the resource scheduling distribution situation does not meet the preset resource scheduling distribution conditions. This can improve the flexibility and accuracy of judging whether the resource scheduling distribution situation meets the resource scheduling distribution conditions, thereby facilitating further improving the accuracy of judging whether the current test task meets the dynamic scheduling conditions.

[0201] Embodiment 3

[0202] See also Figure 3 , Figure 3 1 is a schematic diagram of a resource scheduling device for game numerical testing disclosed in an embodiment of the present invention. Figure 3The resource scheduling device for game numerical testing described may include one of a resource scheduling device, a resource scheduling terminal, a resource scheduling system and a server, wherein the server may be a local server or a cloud server, which is not limited in the embodiments of the present invention; the device may be applied to a numerical test scheduling engine, and further, the numerical test scheduling engine may be applied to game numerical testing, and exemplarily, the game numerical testing may be specifically a game balance test, which is not limited in the embodiments of the present invention. Figure 3 As shown, the resource scheduling device applied to game numerical testing may include:

[0203] The acquisition module 301 is used to load the configuration information of the numerical test scheduling engine after detecting that the numerical test scheduling engine has completed initialization, and obtain the current test task in the test task queue; the test task queue includes at least one test task; the current test task includes multiple rounds of testing;

[0204] The determination module 302 is used to determine the test resource requirements corresponding to the current test task according to the configuration information and the current test task;

[0205] The determination module 302 is further used to determine the resource scheduling strategy of the current test task according to the test resource requirements;

[0206] The allocation module 303 is used to allocate required test task resources for the current test task from the distributed resource pool based on the resource scheduling policy after establishing a resource connection with the distributed resource pool.

[0207] It can be seen that the device described in the embodiment of the present invention can load the corresponding configuration information and obtain the current test task after completing the initialization of the numerical test scheduling engine, and then determine the test resource requirements corresponding to the current test task based on the configuration information and the current test task, and then determine the corresponding resource scheduling strategy based on the test resource requirements, and after establishing the resource connection, allocate the required test task resources for the current test task from the distributed resource pool based on the resource scheduling strategy, and can flexibly adjust the required scheduling resources from the distributed resource pool for the current game numerical test task and flexibly schedule the resources required for the task, thereby improving the flexibility and accuracy of determining the test resource requirements of the game test, and flexibly allocating test task resources through the distributed resource pool, so as to improve the efficiency, accuracy and reliability of the resource scheduling of the game test, thereby improving the efficiency and stability of the game test, which is beneficial to improving the accuracy and reliability of the game test results, and thereby facilitating the efficiency and accuracy of subsequent game optimization.

[0208] In an optional embodiment, the configuration information includes a combination of one or more of a game item, a game mode, a game resource address, and an initial scheduling strategy;

[0209] The specific manner in which the determination module 302 determines the test resource requirement corresponding to the current test task according to the configuration information and the current test task may include:

[0210] Analyze the current test task to obtain the test information corresponding to the current test task; the test information includes test game parameters and / or test environment parameters; the test game parameters include one or more combinations of test times, test objects and game operation modes; the test objects include one or more combinations of test levels, test gameplay, test roles, test lineups, test difficulty and test value types; the test environment parameters include environmental configuration parameters of the test environment;

[0211] Determine the test resource sub-requirements corresponding to each round of testing in the current test task and the cluster resource requirements corresponding to the current test task according to the configuration information and the test information; the test resource sub-requirements corresponding to each round of testing include at least one test resource type required for the test and the resource quantity of each test resource type required for the test;

[0212] The test resource requirements corresponding to the current test task include the test resource sub-requirements corresponding to each round of testing and the cluster resource requirements corresponding to the current test task.

[0213] It can be seen that the device described in the implementation of this optional embodiment can obtain the specific test game parameters and / or test environment parameters corresponding to the current test task by analyzing the current test task, and determine the test resource type and the corresponding resource quantity required for each round of testing based on the configuration information and the above test information. It can improve the accuracy and comprehensiveness of the analysis of the current test task to obtain more comprehensive test information, which is conducive to further improving the accuracy of determining test resource requirements, and further conducive to improving the accuracy of resource scheduling for game testing.

[0214] In this optional embodiment, optionally, the specific manner in which the determination module 302 determines the test resource sub-requirements corresponding to each round of testing in the current test task according to the configuration information and the test information may include:

[0215] Determine at least one resource type required for the current test task according to the configuration information;

[0216] According to the test information, at least one test resource type required for each round of testing is determined from all resource types;

[0217] According to the test information, analyze the computational complexity corresponding to each round of testing in the current test task;

[0218] Based on the computational complexity corresponding to each round of testing, the number of resources of each test resource type required for each round of testing is determined.

[0219] It can be seen that the device described in the implementation of this optional embodiment can also determine the resource type required for the current test task based on the configuration information, and then determine the test resource type required for each round of testing based on the test information, and then analyze the computational complexity corresponding to each round of testing based on the test information, and determine the resource quantity of each test resource type required for each round of testing based on the computational complexity, which can improve the resource type required for each round of testing of the current test task, and improve the accuracy of determining the corresponding resource quantity required for each round of testing based on the accurately determined test computational complexity, thereby helping to improve the accuracy of determining the test resource requirements of the current test task.

[0220] In this optional embodiment, optionally, the multiple rounds of tests included in the current test task are arranged in time sequence;

[0221] The specific manner in which the determination module 302 determines the resource scheduling strategy for the current test task according to the test resource demand may include:

[0222] Based on a pre-set expansion algorithm, determine the target comparison test corresponding to each round of testing; when the expansion algorithm is a discrete expansion algorithm, the target comparison test corresponding to each round of testing includes a combination of one or more of the tests that are sequentially first, sequentially last, and sequentially adjacent to the test; when the expansion algorithm is a non-discrete expansion algorithm, the target comparison test corresponding to each round of testing includes a first adjacent test that is sequentially adjacent to the test and a second adjacent test that is sequentially adjacent to the first adjacent test;

[0223] For each round of testing, determine the resource comparison result corresponding to the test based on the test and the target comparison test corresponding to the test;

[0224] According to the resource comparison results corresponding to each round of testing, a resource scheduling strategy for the current test task is generated.

[0225] It can be seen that the device described in the implementation of this optional embodiment can also select the corresponding target comparison test based on the preset expansion algorithm, and then determine the resource comparison results of each round of testing, and then generate a resource scheduling strategy based on this, which can improve the selection flexibility of the expansion algorithm, thereby improving the selection flexibility and selection accuracy of the target comparison test, and further help to improve the determination flexibility and determination accuracy of the resource scheduling strategy.

[0226] In this optional embodiment, optionally, when the expansion algorithm is a non-discrete expansion algorithm, for each round of testing, according to the test and the target comparison test corresponding to the test, determining the resource comparison result corresponding to the test includes:

[0227] Calculating a resource quantity ratio between a test resource sub-requirement of a second adjacent test corresponding to the test and a test resource sub-requirement of a first adjacent test corresponding to the test; wherein the resource comparison result corresponding to the test includes the resource quantity ratio;

[0228] Furthermore, when the expansion algorithm is a non-discrete expansion algorithm, a resource scheduling strategy for the current test task is generated according to the resource comparison result corresponding to each round of testing, including:

[0229] For each round of testing, the resource quantity ratio in the resource comparison result corresponding to the test is determined as the resource expansion ratio of the test;

[0230] Generate a resource scheduling strategy for the current test task based on the resource expansion ratio of each round of testing.

[0231] It can be seen that the device described in implementing this optional embodiment can also calculate the difference between previous adjacent test resource requirements as the expansion ratio when a non-discrete expansion algorithm is selected, thereby generating a corresponding resource scheduling strategy, which can improve the calculation flexibility of the resource expansion ratio, thereby facilitating improving the adjustment flexibility of the resource scheduling strategy, and further facilitating improving the resource scheduling flexibility.

[0232] In another optional embodiment, the specific manner in which the allocation module 303 allocates the required test task resources for the current test task from the distributed resource pool based on the resource scheduling policy may include:

[0233] When the resource scheduling type corresponding to the resource scheduling strategy is a dynamic scheduling type, determining the target resource unit corresponding to each round of testing in the distributed resource pool; wherein the target resource unit corresponding to each round of testing is the resource unit with the least number of connections determined when executing the test;

[0234] For each round of testing, based on the resource scheduling strategy, the required test resources are allocated to the test from the target resource units corresponding to the test;

[0235] Among them, the test task resources include the test resources required for each round of testing.

[0236] It can be seen that the device described in the implementation of this optional embodiment can determine the target resource unit corresponding to each round of testing in the distributed resource pool when the resource scheduling type is a dynamic scheduling type, and then allocate the required test resources to the test from the target resource unit corresponding to each round of testing based on the resource scheduling strategy, which can improve the flexibility of determining the target resource unit, and schedule resources from the target resource unit with the least number of connections, which can improve the scheduling efficiency and scheduling flexibility of resources required for each round of game testing, thereby helping to further improve the efficiency and stability of game testing.

[0237] In this optional embodiment, optionally, as Figure 4 As shown, the device may also include:

[0238] The monitoring module 304 is used to monitor the resource usage of each round of testing during the execution of the current test task after the allocation module 303 allocates the required test task resources to the current test task from the distributed resource pool based on the resource scheduling policy;

[0239] The determination module 302 is further used to determine the resource utilization rate of each round of testing according to the test resources required for each round of testing and the resource usage of each round of testing;

[0240] The optimization module 305 is used to optimize the resource scheduling strategy according to the resource utilization and a preset dynamic adjustment mechanism to obtain an optimized scheduling strategy; the dynamic adjustment mechanism includes an elastic container mechanism and / or a load dynamic expansion mechanism.

[0241] It can be seen that the device described in the implementation of this optional embodiment can also monitor the resource usage of each round of tests during the execution of the current test task, and determine the resource utilization of each round of tests based on the resource usage of each round of tests. If it is determined that the resource utilization of any test is not in the preset utilization range, the test whose resource utilization is not in the preset utilization range is determined as the third target test, and the resource scheduling strategy is optimized based on the resource utilization and the preset utilization range of all third target tests to obtain an optimized scheduling strategy, which can improve the timeliness and accuracy of monitoring resource usage during the game testing process, thereby helping to improve the determination efficiency and accuracy of tests with abnormal resource utilization, and further helping to improve the optimization accuracy of the resource scheduling strategy, and further helping to improve the determination efficiency and accuracy of the resource scheduling strategy in subsequent game testing tasks.

[0242] Embodiment 4

[0243] See also Figure 5 , Figure 5 FIG. 1 is a schematic diagram of another resource scheduling device for game numerical testing disclosed in an embodiment of the present invention. Figure 5 As shown, the resource scheduling device applied to game numerical testing may include:

[0244] A memory 401 storing executable program codes;

[0245] a processor 402 coupled to the memory 401;

[0246] The processor 402 calls the executable program code stored in the memory 401 to execute part or all of the steps in the resource scheduling method for game numerical testing described in the first embodiment of the present invention or the second embodiment of the present invention.

[0247] Embodiment 5

[0248] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the resource scheduling method applied to game numerical testing described in Embodiment 1 or Embodiment 2 of the present invention.

[0249] Embodiment 6

[0250] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute part or all of the steps in the resource scheduling method for game numerical testing described in Example 1 or Example 2.

[0251] The device embodiments described above are only illustrative, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, i.e., they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0252] Through the specific description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the above technical solution can be essentially or partly contributed to the prior art in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, and the storage medium includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable rewritable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0253] Finally, it should be noted that the resource scheduling method and device for game numerical testing disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, which are only used to illustrate the technical solution of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A resource scheduling method for game numerical testing, characterized in that: The method is applied to a numerical test scheduling engine, and the method comprises: After detecting that the numerical test scheduling engine has completed initialization, loading the configuration information of the numerical test scheduling engine, and obtaining the current test task in the test task queue; the test task queue includes at least one test task; the current test task includes multiple rounds of testing; Determine the test resource requirements corresponding to the current test task according to the configuration information and the current test task; Determine the resource scheduling strategy for the current test task according to the test resource demand; After establishing a resource connection with the distributed resource pool, required test task resources are allocated to the current test task from the distributed resource pool based on the resource scheduling policy.

2. The resource scheduling method for game numerical testing according to claim 1, characterized in that: The configuration information includes one or more combinations of game items, game modes, game resource addresses, and initial scheduling strategies; The step of determining the test resource requirement corresponding to the current test task according to the configuration information and the current test task includes: Analyze the current test task to obtain test information corresponding to the current test task; the test information includes test game parameters and / or test environment parameters; the test game parameters include one or more combinations of test times, test objects and game operation modes; the test objects include one or more combinations of test levels, test gameplay, test characters, test lineups, test difficulty and test value types; the test environment parameters include environmental configuration parameters of the test environment; Determine the test resource sub-demands corresponding to each round of the test in the current test task and the cluster resource demand corresponding to the current test task according to the configuration information and the test information; the test resource sub-demands corresponding to each round of the test include at least one test resource type required for the test and the resource quantity of each test resource type required for the test; The test resource requirement corresponding to the current test task includes the test resource sub-requirements corresponding to each round of the test and the cluster resource requirement corresponding to the current test task.

3. The resource scheduling method for game numerical testing according to claim 2, characterized in that: The determining, according to the configuration information and the test information, the test resource sub-requirements corresponding to each round of the test in the current test task includes: Determine at least one resource type required for the current test task according to the configuration information; Determine at least one test resource type required for each round of the test from all the resource types according to the test information; Analyze the computational complexity of each round of the test in the current test task according to the test information; Based on the computational complexity corresponding to each round of the test, the quantity of resources of each test resource type required for each round of the test is determined.

4. The resource scheduling method for game numerical testing according to claim 2 or 3, characterized in that: The multiple rounds of tests included in the current test task are arranged in time sequence; Wherein, determining the resource scheduling strategy of the current test task according to the test resource demand includes: Based on a preset expansion algorithm, determine the target comparison test corresponding to each round of the test; when the expansion algorithm is a discrete expansion algorithm, the target comparison test corresponding to each round of the test includes a combination of one or more of the first test in the timing, the last test in the timing, and the test that is adjacent to the test timing; when the expansion algorithm is a non-discrete expansion algorithm, the target comparison test corresponding to each round of the test includes a first adjacent test that is adjacent to the test timing and a second adjacent test that is adjacent to the first adjacent test timing; For each round of the test, determining a resource comparison result corresponding to the test based on the test and the target comparison test corresponding to the test; According to the resource comparison results corresponding to each round of the test, a resource scheduling strategy for the current test task is generated.

5. The resource scheduling method for game numerical testing according to claim 4, characterized in that: When the expansion algorithm is the non-discrete expansion algorithm, for each round of the test, the test is compared with a target corresponding to the test to determine a resource comparison result corresponding to the test, including: Calculating a resource quantity ratio between a test resource sub-requirement of a second adjacent test corresponding to the test and a test resource sub-requirement of a first adjacent test corresponding to the test; wherein the resource comparison result corresponding to the test includes the resource quantity ratio; And, when the expansion algorithm is the non-discrete expansion algorithm, generating the resource scheduling strategy of the current test task according to the resource comparison result corresponding to each round of the test includes: For each round of the test, the resource quantity ratio in the resource comparison result corresponding to the test is determined as the resource expansion ratio of the test; A resource scheduling strategy for the current test task is generated according to the resource expansion ratio of each round of the test.

6. The resource scheduling method for game numerical testing according to any one of claims 1, 2, 3 and 5, characterized in that: The allocating required test task resources for the current test task from the distributed resource pool based on the resource scheduling strategy includes: When the resource scheduling type corresponding to the resource scheduling strategy is a dynamic scheduling type, determining the target resource unit corresponding to each round of the test in the distributed resource pool; wherein the target resource unit corresponding to each round of the test is the resource unit with the least number of connections determined when executing the test; For each round of the test, based on the resource scheduling strategy, the required test resources are allocated to the test from the target resource units corresponding to the test; wherein the test task resources include the test resources required for each round of the test.

7. The resource scheduling method for game numerical testing according to claim 6, characterized in that: After allocating required test task resources to the current test task from the distributed resource pool based on the resource scheduling strategy, the method further includes: During the execution of the current test task, monitoring resource usage of each round of the test; Determine the resource utilization rate of each round of the test according to the test resources required for each round of the test and the resource usage of each round of the test; According to the resource utilization and a preset dynamic adjustment mechanism, the resource scheduling strategy is optimized to obtain an optimized scheduling strategy; the dynamic adjustment mechanism includes an elastic container mechanism and / or a load dynamic expansion mechanism.

8. A resource scheduling device for game numerical testing, characterized in that: The device is applied to a numerical test scheduling engine, and the device comprises: An acquisition module, configured to load the configuration information of the numerical test scheduling engine and acquire the current test task in the test task queue after detecting that the numerical test scheduling engine has completed initialization; the test task queue includes at least one test task; the current test task includes multiple rounds of testing; A determination module, used to determine the test resource requirements corresponding to the current test task according to the configuration information and the current test task; The determination module is further used to determine the resource scheduling strategy of the current test task according to the test resource demand; The allocation module is used to allocate the required test task resources for the current test task from the distributed resource pool based on the resource scheduling strategy after establishing a resource connection with the distributed resource pool.

9. A resource scheduling device for game numerical testing, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the resource scheduling method applied to game numerical testing as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, and when the computer instructions are called, they are used to execute the resource scheduling method applied to game numerical testing as described in any one of claims 1-7.

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