CN116149875A - Scheduling method and device of cloud terminal, electronic equipment, storage medium and product - Google Patents

Scheduling method and device of cloud terminal, electronic equipment, storage medium and product Download PDF

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Publication number
CN116149875A
CN116149875A CN202310092115.7A CN202310092115A CN116149875A CN 116149875 A CN116149875 A CN 116149875A CN 202310092115 A CN202310092115 A CN 202310092115A CN 116149875 A CN116149875 A CN 116149875A
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cloud
applications
cloud application
terminals
application set
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徐裕民
张纪金
黄勇
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Beijing Baidu Netcom Science and Technology Co Ltd
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Beijing Baidu Netcom Science and Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/54—Interprogram communication
    • G06F9/547—Remote procedure calls [RPC]; Web services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/60—Software deployment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The disclosure provides a scheduling method, a scheduling device, electronic equipment, a storage medium and a program product of a cloud terminal, relates to the technical field of computers, and particularly relates to the technical field of virtual terminals. The specific implementation scheme is as follows: predicting the user use quantity of the cloud applications in the cloud application set in a preset time period according to the historical operation data of the cloud applications in the cloud application set; determining the operation number of cloud terminals operated in a preset time period according to the use number of users; and pre-running the cloud terminals with the running number before the preset time period comes. According to the cloud terminal management method and device, the cloud terminals with the corresponding number are flexibly deployed according to the actual use demands of the users on the cloud terminals, so that the operation flexibility of the cloud terminals and the utilization rate of cloud terminal resources are improved.

Description

Scheduling method and device of cloud terminal, electronic equipment, storage medium and product
Technical Field
The disclosure relates to the technical field of computers, in particular to the technical field of virtual terminals, and particularly relates to a scheduling method, device, electronic equipment, storage medium and computer program product of a cloud terminal, which can be used in a cloud terminal scene.
Background
Based on the virtualization technology, the cloud mobile phone can be remotely controlled in real time by a user through a native mobile phone instance virtualized in the cloud, so that cloud operation of various applications is realized. Traditional cloud mobile phones require users to rent in units of months, but in practice users may not need to use the cloud mobile phones for a long time, but only use a certain cloud application in a short time. And the mode of renting the cloud mobile phone is fixed, so that the cloud mobile phone resources and the user renting cost are wasted.
Disclosure of Invention
The disclosure provides a scheduling method, device, electronic equipment, storage medium and computer program product of a cloud terminal.
According to a first aspect, there is provided a scheduling method of a cloud terminal, including: predicting the user use quantity of the cloud applications in the cloud application set in a preset time period according to the historical operation data of the cloud applications in the cloud application set; determining the operation number of cloud terminals operated in a preset time period according to the use number of users; and pre-running the cloud terminals with the running number before the preset time period comes.
According to a second aspect, there is provided a scheduling apparatus of a cloud terminal, including: the cloud application management system comprises a first prediction unit, a second prediction unit and a third prediction unit, wherein the first prediction unit is configured to predict the number of users of cloud applications in a cloud application set in a preset time period according to historical operation data of the cloud applications in the cloud application set; a first determining unit configured to determine, according to the number of users used, the number of operations of the cloud terminal that operates within a preset period of time; and the operation unit is configured to pre-operate the cloud terminals with the operation quantity before a preset time period comes.
According to a third aspect, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method as described in any one of the implementations of the first aspect.
According to a fourth aspect, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform a method as described in any implementation of the first aspect.
According to a fifth aspect, there is provided a computer program product comprising: a computer program which, when executed by a processor, implements a method as described in any of the implementations of the first aspect.
According to the technology disclosed by the invention, the scheduling method of the cloud terminals is provided, the running number of the cloud terminals is determined based on the predicted user use number of the cloud applications in the cloud application set, and the cloud terminals with the corresponding number are operated in advance, so that the users do not need to rent the cloud terminals based on a fixed renting mode, but flexibly deploy the cloud terminals with the corresponding number according to the actual use requirements of the users on the cloud terminals, and the running flexibility of the cloud terminals and the utilization rate of cloud terminal resources are improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an exemplary system architecture diagram to which an embodiment according to the present disclosure may be applied;
FIG. 2 is a flow chart of one embodiment of a scheduling method of a cloud terminal according to the present disclosure;
fig. 3 is a schematic diagram of a relationship between a cloud terminal and a user in the prior art according to the present embodiment;
fig. 4 is a schematic diagram of a relationship between a cloud terminal and a user according to the present embodiment;
fig. 5 is a schematic diagram of an application scenario of a scheduling method of a cloud terminal according to the present embodiment;
FIG. 6 is a flow chart of yet another embodiment of a scheduling method of a cloud terminal according to the present disclosure;
FIG. 7 is a block diagram of one embodiment of a scheduling apparatus of a cloud terminal according to the present disclosure;
FIG. 8 is a schematic diagram of a computer system suitable for use in implementing embodiments of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the technical scheme of the disclosure, the related processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the personal information of the user accord with the regulations of related laws and regulations, and the public order colloquial is not violated.
Fig. 1 illustrates an exemplary architecture 100 to which the scheduling method and apparatus of a cloud terminal of the present disclosure may be applied.
As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The communication connection between the terminal devices 101, 102, 103 constitutes a topology network, the network 104 being the medium for providing the communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The terminal devices 101, 102, 103 may be hardware devices or software supporting network connections for data interaction and data processing. When the terminal device 101, 102, 103 is hardware, it may be various electronic devices supporting network connection, information acquisition, interaction, display, processing, etc., including but not limited to smartphones, tablet computers, electronic book readers, laptop and desktop computers, etc. When the terminal devices 101, 102, 103 are software, they can be installed in the above-listed electronic devices. It may be implemented as a plurality of software or software modules, for example, for providing distributed services, or as a single software or software module. The present invention is not particularly limited herein.
The server 105 may be a server that provides various services, for example, a background processing server that provides cloud terminal services to users to which the terminal devices 101, 102, 103 belong. The server may determine the number of cloud terminals to run based on the predicted number of user uses of the cloud applications in the cloud application set, and pre-run a corresponding number of cloud terminals. As an example, the server 105 may be a cloud server.
The server may be hardware or software. When the server is hardware, the server may be implemented as a distributed server cluster formed by a plurality of servers, or may be implemented as a single server. When the server is software, it may be implemented as a plurality of software or software modules (e.g., software or software modules for providing distributed services), or as a single software or software module. The present invention is not particularly limited herein.
It should also be noted that, the scheduling method of the cloud terminal provided by the embodiment of the present disclosure may be executed by a server, may also be executed by a terminal device, and may also be executed by the server and the terminal device in cooperation with each other. Accordingly, each part (for example, each unit) included in the scheduling device of the cloud terminal may be all set in the server, may be all set in the terminal device, or may be respectively set in the server and the terminal device.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. When the electronic device on which the scheduling method of the cloud terminal operates does not need to perform data transmission with other electronic devices, the system architecture may include only the electronic device (e.g., a server or a terminal device) on which the scheduling method of the cloud terminal operates.
Referring to fig. 2, fig. 2 is a flowchart of a scheduling method of a cloud terminal according to an embodiment of the disclosure, where the flowchart 200 includes the following steps:
step 201, predicting the number of users of the cloud applications in the cloud application set in a preset time period according to the historical operation data of the cloud applications in the cloud application set.
In this embodiment, an execution body of the scheduling method of the cloud terminal (for example, the terminal device or the server in fig. 1) may acquire, from a remote location or from a local location, historical operation data of cloud applications in the cloud application set through a wired network connection manner or a wireless network connection manner, and predict, according to the historical operation data of the cloud applications in the cloud application set, the number of users using the cloud applications in the cloud application set in a preset period of time.
The cloud application set includes various cloud applications including, but not limited to, social cloud-like applications, information cloud-like applications, game cloud-like applications, online shopping cloud-like applications, tool cloud-like applications. The execution main body is based on a virtualization technology, cloud terminal services such as a cloud mobile phone, a cloud computer and the like can be provided for a user, and the user can deploy various cloud applications required by the user in the cloud terminal.
According to the time period of using each cloud application by the cloud terminal corresponding to each user in the historical operation data, the execution body can predict the change trend of the use quantity of each cloud application in the future, so that the use quantity of the cloud application in the cloud application set is predicted in a preset time period according to the change trend.
In order to further improve the accuracy of predicting the number of users, the executing body needs to further consider key factors that influence the number of users, such as whether the cloud application has been updated recently, whether the cloud application has preferential activities for the cloud application in a preset time period, whether the preset time period is on holidays, and the like, in the prediction process.
In some optional implementations of this embodiment, the executing body may execute the step 201 as follows: and predicting the number of users of the cloud applications in the cloud application set within a preset time period according to the historical operation data of the cloud applications in the cloud application set through a pre-trained prediction model.
The prediction model is used for representing the corresponding relation between the historical operation data of the cloud application and the user use quantity of the cloud application in a preset time period. The prediction model may be obtained by training a neural network model, for example, the prediction model may be a cyclic neural network model, or an LSTM (long short-term memory) model.
As an example, the predictive model may be trained as follows: first, a training sample set is acquired. The training samples in the training sample set comprise historical running data of the cloud application, key factor data which characterizes whether the application has updating recently, whether preferential activities aiming at the cloud application exist in a preset time period, whether the preset time period is in holidays and the like and influences the use quantity of users, and predictive labels which characterize the use data of the users of the cloud application in a future time period.
The future time period corresponding to the predictive tag may be a future time period relative to a historical time period corresponding to the historical operating data. Specifically, the execution body divides all the historical operation data of the cloud application which is cut off to the current state into two parts, wherein one part is used as the historical operation data in the training sample, and the other part is used as the prediction label. Wherein the time corresponding to the operation data as the predictive label is after the time corresponding to the historical operation data. As an example, for the cloud application a, the execution subject acquires the past 30 operation data, takes the operation data of the previous 25 days as the history operation data, and takes the number of user uses in the operation data of the subsequent 5 days as the predictive label.
And then, using a machine learning method, using historical operation data of the cloud application to represent whether the application has updating recently, whether the application has preferential activities for the cloud application in a preset time period, whether the preset time period is on holidays and the like, and key factor data influencing the use quantity of users, and using a prediction label corresponding to the input training data as expected output to train to obtain a prediction model.
In the implementation manner, the number of the users of the cloud applications in the cloud application set is predicted within a preset time period based on the trained prediction model, so that the prediction accuracy of the number of the users is improved.
Step 202, determining the operation number of the cloud terminals operated in a preset time period according to the user use number.
In this embodiment, the execution body may determine, according to the number of users used, the number of operations of the cloud terminal that operates in the preset period of time.
As an example, for each cloud application in the cloud application set, the number of users corresponding to the cloud application may be directly used as the number of operations of the cloud terminal that operates the cloud application in the preset period of time.
As yet another example, for each cloud application in the cloud application set, a product of the number of user uses corresponding to the cloud application and a preset proportion may be used as the number of operations of the cloud terminal that operates the cloud application in a preset period of time. The preset proportion corresponding to each cloud application may be specifically set according to actual situations, and the preset proportions corresponding to different cloud applications may be the same or different, which is not limited herein.
In some optional implementations of this embodiment, the executing body may execute the step 202 as follows:
first, determining the initial running number of cloud terminals for running the cloud applications in the cloud application set in a preset time period according to the using number of users of the cloud applications in the cloud application set.
As an example, for each cloud application in the cloud application set, the number of user uses corresponding to the cloud application may be directly used as the initial running number of cloud terminals running the cloud application in a preset period of time.
Secondly, determining the running number of cloud terminals for running the cloud applications in the cloud application set in a preset time period according to the initial running number and the attribute information of the cloud applications in the cloud application set.
The attribute information of the cloud application may be information of a storage space required for the cloud application, a required installation time, and the like.
Specifically, a plurality of attribute thresholds may be set in order from small to large, and for applications in different attribute ranges, different preset proportions are set with reference to the principle that the size of the attribute range is positively correlated with the size of the preset proportion. For each cloud application in the cloud application set, the product of the initial running number corresponding to the cloud application and the preset proportion can be used as the running number of cloud terminals running the cloud application in a preset time period.
Taking the storage space required by the cloud application as an example, a first storage threshold and a second storage threshold may be set. Wherein the first storage threshold is less than the second storage threshold. For cloud applications with storage space in a range less than a first storage threshold, setting a preset proportion to be 50%; for cloud applications with storage space between a first storage threshold and a second storage threshold, setting a preset proportion to be 75%; for cloud applications where the storage space is in a range greater than the second storage threshold, the preset proportion is set to 100%.
When the storage space of the cloud application is smaller, the cloud terminal can generally install the cloud application and start the cloud application based on less time, at this time, less cloud terminals can be prepared in advance, and even if the number of the prepared cloud terminals is insufficient, more cloud terminals can be installed and started in less time to run the cloud application; when the storage space of the cloud application is large, the cloud terminal generally installs the cloud application and starts the cloud application based on more time, and at this time, a sufficient number of cloud terminals need to be prepared in advance to avoid the problem of insufficient preparation, which causes long waiting time of users.
According to the cloud terminal operation method and device, the attribute information of the cloud application is further considered on the basis of considering the use quantity of users of the cloud application, so that the operation quantity of cloud terminals to be prepared is finally determined, the determined operation quantity of the cloud terminals is more attached to the actual operation condition of the cloud terminals, and the accuracy of the operation quantity and the flexibility of the operation of the cloud terminals are improved.
In some optional implementations of this embodiment, the executing body may execute the first step by: and determining the initial running number of cloud terminals for running the cloud applications in the cloud application group according to the user using number of the cloud applications in the cloud application set and the using correlation among different cloud applications in the cloud application set.
The cloud application group is determined based on the use relevance among different cloud applications in the cloud application set.
As an example, in the process of using the cloud terminal, the user deploys the game cloud application a and the friend-making cloud application B in the cloud terminal, and then considers that the game cloud application a and the friend-making cloud application B have a use association, and the game cloud application a and the friend-making cloud application B can form a cloud application group.
For cloud applications in the same cloud application group, the cloud applications are generally deployed in the same cloud terminal. In the implementation manner, for cloud applications in a cloud application group with use relevance, determining the initial running number of cloud terminals for running the cloud applications in the cloud application group by combining the user use number of each cloud application in the cloud application group.
As an example, the number of users corresponding to the game cloud application a is 500, the number of users corresponding to the friend-making cloud application B is 300, the number of users of the tool cloud application C is 300, and the number of users of the online shopping cloud application D is 200, and then the initial running number of cloud application groups formed by the game cloud application a, the friend-making cloud application B and the tool cloud application C is 300, and the initial running number of cloud application groups formed by the game cloud application a and the online shopping cloud application D is 200.
In the implementation manner, on the basis of considering the number of users using cloud applications, the use relevance among the applications is further considered, so that cloud terminals running cloud applications in the cloud application group are determined by taking the cloud application group formed by the cloud applications with the use relevance as a unit, and the accuracy of the determined initial running number is further improved.
In some optional implementations of this embodiment, the executing body may execute the second step by: and determining the running number of cloud terminals for running the cloud applications in the cloud application group in a preset time period according to the initial running number of the cloud terminals corresponding to the cloud application group and the attribute information of the cloud applications in the cloud application group for the cloud application group consisting of different cloud applications in the cloud application set.
As an example, for the maximum value in the attribute information of the cloud applications in the cloud application group, or the sum of the attribute information of the cloud applications in the cloud application group, a plurality of attribute thresholds are set in order from small to large, and for the cloud applications in different attribute ranges, different preset proportions are set with reference to the principle that the attribute range sizes and the preset proportion sizes are positively correlated. For each cloud application in the cloud application set, the product of the initial running number corresponding to the cloud application and the preset proportion can be used as the running number of cloud terminals running the cloud application in a preset time period.
In the implementation manner, for the cloud application group formed by the cloud applications with the use relevance, on the basis of considering the number of users of the cloud applications, attribute information of the cloud applications in the cloud application group is further considered to finally determine the number of operation of the cloud terminals to be prepared, so that the determined number of operation of the cloud terminals is more attached to the actual operation situation of the cloud terminals, and the accuracy of the number of operation is further improved.
Step 203, running the cloud terminals with the running number in advance before a preset time period comes.
In this embodiment, the execution body may run the cloud terminals with the running number in advance before a preset time period comes.
As an example, a time difference between the current time and a preset time period is determined, and when the time difference is smaller than a preset time difference threshold, the cloud terminal with the running number is pre-run, wherein the preset time period is considered to be forthcoming. The preset time difference threshold may be specifically set according to practical situations, for example, the preset time difference threshold is 5 minutes.
With continued reference to fig. 3, a prior art relationship diagram 300 between a cloud terminal and a user is shown. After renting the cloud terminal, the user binds with the cloud terminal in a fixed renting time period no matter whether the user uses the cloud terminal or not, and occupies the cloud terminal, so that the waste of cloud terminal resources in an idle state is caused.
With continued reference to fig. 4, a schematic diagram 400 of the relationship between a cloud terminal and a user in the present disclosure is shown. The user can be bound with the cloud terminal only in the process of using the cloud terminal, and occupies the cloud terminal. When the cloud terminal is not used, the cloud terminal is applied for use by other users, so that the cloud terminal can be flexibly distributed to users with actual use requirements, and the utilization rate of cloud terminal resources is improved.
With continued reference to fig. 5, fig. 5 is a schematic diagram 500 of an application scenario of the scheduling method of the cloud terminal according to the present embodiment. In the application scenario of fig. 5, a server 501 first obtains historical operating data 503 of cloud applications in a cloud application set from a database 502. Then, predicting the user use quantity 504 of the cloud applications in the cloud application set in a preset time period according to the historical operation data of the cloud applications in the cloud application set; then, according to the number of users 504, determining the number of cloud terminals operated in a preset time period 505; and finally, running the cloud terminals with the running number in advance before a preset time period comes.
In this embodiment, a scheduling method of cloud terminals is provided, based on the predicted number of users using cloud applications in a cloud application set, the running number of cloud terminals is determined, and cloud terminals with corresponding numbers are operated in advance, so that the users do not need to rent cloud terminals based on a fixed lease mode, but flexibly deploy cloud terminals with corresponding numbers according to actual use requirements of the users on the cloud terminals, and the running flexibility of the cloud terminals and the utilization rate of cloud terminal resources are improved.
In some optional implementations of this embodiment, the foregoing execution body may further perform the following operations: firstly, in the process that a target user uses a cloud terminal, predicting a target cloud application used next by the target user according to historical operation data of the target user when the target user stops; then, the target cloud application is preloaded.
As an example, the execution subject may predict, through a prediction model, a target cloud application that the target user uses next according to the historical operation data that the target user has stopped at. The prediction model may be a neural network model such as a recurrent neural network or an LSTM network.
The predictive model may be trained as follows: first, a training sample set is acquired. The training samples in the training sample set comprise historical operation data of the user and a prediction label for representing a target cloud application used next by the user. Then, using a machine learning method, taking the historical operation data of the user in the training sample as input, taking the prediction label corresponding to the input data as expected output, and training to obtain a prediction model.
According to the cloud application prediction method and device, based on prediction of the cloud application to be operated by the target user, the cloud application to be operated by the target user is preloaded, waiting time of the user can be reduced, and experience of the user is improved.
In some optional implementations of this embodiment, the foregoing execution body may further perform the following operations: firstly, determining the use time of a target user for using a cloud terminal; then, according to the use time, the cost information of the target user for using the cloud terminal is determined.
In the implementation mode, the determined using time is the actual using time of the cloud terminal used by the user, the cost information of the cloud terminal used by the user is determined based on the using time, the actual using situation of the cloud terminal by the user is more fitted, and the problem that the user wastes the using cost in a fixed renting mode is solved.
With continued reference to fig. 6, there is shown a schematic flow 600 of yet another embodiment of a scheduling method of a cloud terminal according to the present disclosure, comprising the steps of:
step 601, predicting the number of users of the cloud applications in the cloud application set in a preset time period according to the historical running data of the cloud applications in the cloud application set by using a pre-trained prediction model.
The prediction model is used for representing the corresponding relation between the historical operation data of the cloud application and the user use quantity of the cloud application in a preset time period
Step 602, determining the initial running number of cloud terminals for running cloud applications in a cloud application group according to the number of users of the cloud applications in the cloud application set and the use correlation between different cloud applications in the cloud application set.
The cloud application group is determined based on the use relevance among different cloud applications in the cloud application set.
Step 603, for a cloud application group formed by different cloud applications in the cloud application set, determining the running number of cloud terminals running the cloud applications in the cloud application group in a preset time period according to the initial running number of cloud terminals corresponding to the cloud application group and attribute information of the cloud applications in the cloud application group.
Step 604, running the cloud terminals with the running number in advance before a preset time period comes.
Step 605, in the process that the target user uses the cloud terminal, predicting the target cloud application used next by the target user according to the historical operation data of the target user.
Step 606, preloading the target cloud application.
In step 607, the use time of the target user using the cloud terminal is determined.
And step 608, determining the cost information of the target user for using the cloud terminal according to the using time.
As can be seen from this embodiment, compared with the embodiment corresponding to fig. 2, the flow 600 of the cloud terminal scheduling method in this embodiment specifically illustrates a process of determining the number of operations, a process of preloading the target cloud application, and a process of determining the cost information of using the cloud terminal by the target user, which further improves the operation flexibility of the cloud terminal, the utilization rate of the cloud terminal resources, and saves the use cost of the user.
With continued reference to fig. 7, as an implementation of the method shown in the foregoing figures, the present disclosure provides an embodiment of a scheduling apparatus for a cloud terminal, where an embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be specifically applied to various electronic devices.
As shown in fig. 7, the scheduling apparatus 700 of the cloud terminal includes: a first prediction unit 701 configured to predict, according to historical operation data of cloud applications in the cloud application set, the number of users of the cloud applications in the cloud application set within a preset period of time; a first determining unit 702 configured to determine, according to the number of users used, the number of operations of the cloud terminal that operates within a preset period of time; an operation unit 703 configured to previously operate the cloud terminals of the above-described operation number before a preset period of time expires.
In some optional implementations of the present embodiment, the first prediction unit 701 is further configured to: and predicting the number of the users of the cloud applications in the cloud application set in a preset time period according to the historical operation data of the cloud applications in the cloud application set through a pre-trained prediction model, wherein the prediction model is used for representing the corresponding relation between the historical operation data of the cloud applications and the number of the users of the cloud applications in the preset time period.
In some optional implementations of the present embodiment, the first determining unit 702 is further configured to: determining the initial running number of cloud terminals for running the cloud applications in the cloud application set in a preset time period according to the using number of users of the cloud applications in the cloud application set; and determining the running number of cloud terminals for running the cloud applications in the cloud application set in a preset time period according to the initial running number and the attribute information of the cloud applications in the cloud application set.
In some optional implementations of the present embodiment, the first determining unit 702 is further configured to: according to the number of users using cloud applications in a cloud application set and the use relevance among different cloud applications in the cloud application set, determining the initial running number of cloud terminals for running the cloud applications in a cloud application group, wherein the use relevance characterization is based on the relevance among different cloud applications in the cloud application set generated by the simultaneous deployment and use of the different cloud applications in the cloud application set in the cloud terminals by the users, and the cloud application group is determined based on the use relevance among the different cloud applications in the cloud application set.
In some optional implementations of the present embodiment, the first determining unit 702 is further configured to: and determining the running number of cloud terminals for running the cloud applications in the cloud application group in a preset time period according to the initial running number of the cloud terminals corresponding to the cloud application group and the attribute information of the cloud applications in the cloud application group for the cloud application group consisting of different cloud applications in the cloud application set.
In some optional implementations of this embodiment, the apparatus further includes: a second prediction unit (not shown in the figure) configured to predict a target cloud application used next by the target user according to the current historical operation data of the target user in the process of using the cloud terminal by the target user; a preloading unit (not shown in the figure) configured to preload the target cloud application.
In some optional implementations of this embodiment, the apparatus further includes: a second determination unit (not shown in the figure) configured to determine a use time of the cloud terminal by the target user; a third determining unit (not shown in the figure) configured to determine fee information of the target user using the cloud terminal according to the use time.
In this embodiment, a scheduling device for cloud terminals is provided, based on the predicted number of users using cloud applications in a cloud application set, the running number of cloud terminals is determined, and cloud terminals with corresponding numbers are operated in advance, so that the users do not need to rent cloud terminals based on a fixed lease mode, but flexibly deploy cloud terminals with corresponding numbers according to actual use requirements of the users on the cloud terminals, and the running flexibility of the cloud terminals and the utilization rate of cloud terminal resources are improved.
According to an embodiment of the present disclosure, the present disclosure further provides an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, so that the at least one processor can implement the cloud terminal scheduling method described in any of the above embodiments when executing the instructions.
According to an embodiment of the present disclosure, there is further provided a readable storage medium storing computer instructions for enabling a computer to implement the scheduling method of a cloud terminal described in any of the above embodiments when executed.
The disclosed embodiments provide a computer program product that, when executed by a processor, enables the scheduling method of a cloud terminal described in any of the above embodiments.
Fig. 8 illustrates a schematic block diagram of an example electronic device 800 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 8, the apparatus 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to the bus 804.
Various components in device 800 are connected to I/O interface 805, including: an input unit 806 such as a keyboard, mouse, etc.; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, etc.; and a communication unit 809, such as a network card, modem, wireless communication transceiver, or the like. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The computing unit 801 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 801 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 performs the respective methods and processes described above, for example, a scheduling method of a cloud terminal. For example, in some embodiments, the scheduling method of the cloud terminal may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 800 via ROM 802 and/or communication unit 809. When the computer program is loaded into the RAM803 and executed by the computing unit 801, one or more steps of the scheduling method of the cloud terminal described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the scheduling method of the cloud terminal by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called as a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of large management difficulty and weak service expansibility in the traditional physical host and virtual special server (VPS, virtual Private Server) service; or may be a server of a distributed system or a server incorporating a blockchain.
According to the technical scheme of the embodiment of the disclosure, the scheduling method of the cloud terminals is provided, the running number of the cloud terminals is determined based on the predicted user use number of the cloud applications in the cloud application set, the cloud terminals with the corresponding number are operated in advance, the users do not need to rent the cloud terminals based on a fixed renting mode, the cloud terminals with the corresponding number are flexibly deployed according to the actual use requirements of the users on the cloud terminals, and the running flexibility of the cloud terminals and the utilization rate of cloud terminal resources are improved.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions provided by the present disclosure are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims (17)

1. A scheduling method of cloud terminals comprises the following steps:
predicting the number of users of the cloud applications in the cloud application set within a preset time period according to historical operation data of the cloud applications in the cloud application set;
determining the operation number of cloud terminals operated in the preset time period according to the user use number;
and pre-operating the cloud terminals with the operation quantity before the preset time period comes.
2. The method of claim 1, wherein predicting the number of user uses of the cloud applications in the cloud application set for the preset period of time according to historical operating data of the cloud applications in the cloud application set comprises:
and predicting the number of users of the cloud applications in the cloud application set in the preset time period according to the historical operation data of the cloud applications in the cloud application set through a pre-trained prediction model, wherein the prediction model is used for representing the corresponding relation between the historical operation data of the cloud applications and the number of users of the cloud applications in the preset time period.
3. The method of claim 1, wherein the determining, according to the number of users used, the number of cloud terminals operating within the preset time period includes:
Determining the initial running number of cloud terminals running the cloud applications in the cloud application set in the preset time period according to the using number of users of the cloud applications in the cloud application set;
and determining the running number of cloud terminals running the cloud applications in the cloud application set in the preset time period according to the initial running number and the attribute information of the cloud applications in the cloud application set.
4. The method of claim 3, wherein the determining, according to the number of users using cloud applications in the cloud application set, an initial running number of cloud terminals running cloud applications in the cloud application set in the preset period of time includes:
according to the number of users using cloud applications in the cloud application set and the use correlation among different cloud applications in the cloud application set, determining the initial running number of cloud terminals for running cloud applications in a cloud application group, wherein the use correlation represents the correlation among different cloud applications generated based on the simultaneous deployment of the users in the cloud terminals and using different cloud applications in the cloud application set, and the cloud application group is determined based on the use correlation among different cloud applications in the cloud application set.
5. The method of claim 4, wherein the determining, according to the initial running number and the attribute information of the cloud applications in the cloud application set, the running number of cloud terminals running the cloud applications in the cloud application set in the preset period of time includes:
and determining the running number of cloud terminals running the cloud applications in the cloud application group in the preset time period according to the initial running number of the cloud terminals corresponding to the cloud application group and the attribute information of the cloud applications in the cloud application group for the cloud application group consisting of different cloud applications in the cloud application set.
6. The method of any of claims 1-5, further comprising:
in the process that a target user uses a cloud terminal, predicting a target cloud application used next by the target user according to historical operation data of the target user when the target user is cut off to the current;
and preloading the target cloud application.
7. The method of claim 6, further comprising:
determining the use time of the cloud terminal used by the target user;
and determining the cost information of the target user for using the cloud terminal according to the using time.
8. A scheduling apparatus of a cloud terminal, comprising:
the cloud application management system comprises a first prediction unit, a second prediction unit and a third prediction unit, wherein the first prediction unit is configured to predict the number of users of cloud applications in a cloud application set within a preset time period according to historical operation data of the cloud applications in the cloud application set;
a first determining unit configured to determine, according to the number of users used, the number of operations of the cloud terminal that operates in the preset period of time;
and the operation unit is configured to pre-operate the cloud terminals with the operation number before the preset time period comes.
9. The apparatus of claim 8, wherein the first prediction unit is further configured to:
and predicting the number of users of the cloud applications in the cloud application set in the preset time period according to the historical operation data of the cloud applications in the cloud application set through a pre-trained prediction model, wherein the prediction model is used for representing the corresponding relation between the historical operation data of the cloud applications and the number of users of the cloud applications in the preset time period.
10. The apparatus of claim 8, wherein the first determination unit is further configured to:
determining the initial running number of cloud terminals running the cloud applications in the cloud application set in the preset time period according to the using number of users of the cloud applications in the cloud application set; and determining the running number of cloud terminals running the cloud applications in the cloud application set in the preset time period according to the initial running number and the attribute information of the cloud applications in the cloud application set.
11. The apparatus of claim 10, wherein the first determination unit is further configured to:
according to the number of users using cloud applications in the cloud application set and the use correlation among different cloud applications in the cloud application set, determining the initial running number of cloud terminals for running cloud applications in a cloud application group, wherein the use correlation represents the correlation among different cloud applications generated based on the simultaneous deployment of the users in the cloud terminals and using different cloud applications in the cloud application set, and the cloud application group is determined based on the use correlation among different cloud applications in the cloud application set.
12. The apparatus of claim 11, wherein the first determination unit is further configured to:
and determining the running number of cloud terminals running the cloud applications in the cloud application group in the preset time period according to the initial running number of the cloud terminals corresponding to the cloud application group and the attribute information of the cloud applications in the cloud application group for the cloud application group consisting of different cloud applications in the cloud application set.
13. The apparatus of any of claims 8-12, further comprising:
The second prediction unit is configured to predict a target cloud application used next by a target user according to the current historical operation data of the target user when the target user uses the cloud terminal;
and the preloading unit is configured to preload the target cloud application.
14. The apparatus of claim 13, further comprising:
a second determining unit configured to determine a use time of the target user using the cloud terminal;
and a third determining unit configured to determine cost information of the target user using the cloud terminal according to the use time.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
16. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-7.
17. A computer program product comprising: computer program which, when executed by a processor, implements the method according to any of claims 1-7.
CN202310092115.7A 2023-01-18 2023-01-18 Scheduling method and device of cloud terminal, electronic equipment, storage medium and product Pending CN116149875A (en)

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