Cloud application intelligent scheduling method and device

Abstract

The invention provides a cloud application intelligent scheduling method and device, and the method comprises the steps: determining to-be-selected Internet data center (IDC) machine rooms when a user applies for the use of a cloud application, obtaining the value of a key parameter affecting the instance scheduling for each to-be-selected IDC machine room if the number of the to-be-selected IDC machine room is greater than 1, and obtaining the value of the key parameter of each to-be-selected IDC machine room; key parameters are obtained, the score of the values of the key parameters is calculated, the score of the IDC machine room is calculated according to the score of the values of the key parameters, and the key parameters comprise at least two of the distance between the user and the IDC machine room, the regional matching degree between the user and the IDC machine room and the network performance parameter between the user and the IDC machine room; according to the embodiment of the invention, the target IDC machine room is selected from the to-be-selected IDC machine rooms according to the scores of the to-be-selected IDC machine rooms, and an idle instance is selected from the target IDC machine room to be allocated to the user to operate the cloud application, so that the instances in the IDC machine rooms can be effectively scheduled, and smooth cloud application service can be provided for the user.

Description

Technical Field

[0001] The present invention relates to the field of cloud applications, and in particular to a cloud application intelligent scheduling method and device. Background Art

[0002] With the rapid development of cloud computing and network technology, cloud applications (such as cloud games) have become one of the important trends in the application industry as a new application usage method. Cloud applications migrate all the complex computing and rendering tasks handled by user terminals in traditional applications to cloud servers, and transmit the computing results to user terminals in the form of video streams through efficient network transmission. This architecture significantly reduces the hardware requirements for user devices, allowing users to easily enjoy high-quality application experience through a variety of devices such as mobile phones, tablets, and smart TVs. For users, cloud applications eliminate the performance limitations of hardware devices. As long as network conditions permit, they can easily experience large-scale applications with high complexity and high performance requirements.

[0003] When a user applies to use a cloud application, the scheduling service of the cloud service system needs to schedule the user to an idle instance in the IDC (Internet Data Center) computer room of the cloud service provider and install and run the application on the instance. As the number of IDC computer rooms continues to increase, how to effectively schedule the instances in these IDC computer rooms to provide users with smooth cloud application services has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] In view of the technical problems existing in the prior art, the embodiments of the present application provide a cloud application intelligent scheduling method and device.

[0005] In a first aspect, an embodiment of the present application provides a cloud application intelligent scheduling method, including: When a user applies to use a cloud application, determine the Internet data center IDC room to be selected. If the number of IDC rooms to be selected is greater than 1, then for each IDC room to be selected, obtain the value of a key parameter that affects instance scheduling, and calculate the score of the key parameter value. Calculate the score of the IDC room according to the score of the key parameter value, wherein the key parameter includes: at least two of the three parameters: the distance between the user and the IDC room, the degree of regional matching between the user and the IDC room, and the network performance parameter between the user and the IDC room; A target IDC computer room is selected from each of the IDC computer rooms to be selected according to the scores of each of the IDC computer rooms to be selected, and an idle instance is selected from the target IDC computer room and allocated to the user to run the cloud application.

[0006] In a second aspect, the embodiment of the present application further provides a cloud application intelligent scheduling device, including: A calculation unit is used to determine an Internet data center IDC room to be selected when a user applies to use a cloud application. If the number of the IDC rooms to be selected is greater than 1, then for each IDC room to be selected, a value of a key parameter affecting instance scheduling is obtained, and a score of the value of the key parameter is calculated. The score of the IDC room is calculated according to the score of the value of the key parameter, wherein the key parameter includes at least two of the three parameters: a distance between the user and the IDC room, a degree of regional matching between the user and the IDC room, and a network performance parameter between the user and the IDC room; The scheduling unit is used to select a target IDC computer room from each candidate IDC computer room according to the scores of each candidate IDC computer room, and select an idle instance from the target IDC computer room to allocate to the user to run the cloud application.

[0007] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the cloud application intelligent scheduling method described in the first aspect are executed.

[0008] In a fourth aspect, an embodiment of the present application further provides an electronic device, comprising: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium through the bus, and the processor executes the machine-readable instructions to perform the steps of the cloud application intelligent scheduling method as described in the first aspect.

[0009] In summary, the cloud application intelligent scheduling method and device, electronic device and storage medium provided in the embodiments of the present application use the values ​​of key parameters that affect instance scheduling to score each IDC computer room to be selected, select a target IDC computer room from each candidate IDC computer room according to the score of each candidate IDC computer room, and allocate an idle instance in the target IDC computer room to the user to run the cloud application. In this way, the instances in the IDC computer room can be effectively scheduled, thereby providing users with smooth cloud application services. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flowchart of an embodiment of a cloud application intelligent scheduling method provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of an embodiment of a cloud application intelligent scheduling device provided in an embodiment of the present application; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0011] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0012] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0013] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0014] Reference Figure 1 As shown, an embodiment of the present application provides a flow chart of a cloud application intelligent scheduling method, the method comprising: S10. When a user applies to use a cloud application, determine an Internet data center IDC room to be selected. If the number of IDC rooms to be selected is greater than 1, then for each IDC room to be selected, obtain the value of a key parameter that affects instance scheduling, and calculate the score of the key parameter value. Calculate the score of the IDC room according to the score of the key parameter value, wherein the key parameter includes at least two of the three parameters: the distance between the user and the IDC room, the degree of regional matching between the user and the IDC room, and the network performance parameter between the user and the IDC room. In the embodiment of the present application, it should be noted that the IDC computer room to be selected can be all IDC computer rooms of the cloud service provider or part of all IDC computer rooms of the cloud service provider (for example, the IDC computer room whose service scope can cover the location of the user). Among the key parameters affecting instance scheduling, the distance between the user and the IDC computer room can be calculated by the latitude and longitude coordinates of the user and the latitude and longitude coordinates of the IDC computer room; the geographical matching degree between the user and the IDC computer room refers to the matching degree between the user's location and the location of the IDC computer room in terms of country, province, city, district / county, etc.; the network performance parameters between the user and the IDC computer room may include network delay and / or packet loss rate.

[0015] The key parameters that affect instance scheduling include: the distance between the user and the IDC computer room, the degree of geographical matching between the user and the IDC computer room, and at least two of the network performance parameters between the user and the IDC computer room. This can avoid the limitations of evaluating the IDC computer room through a single parameter in the future, thereby selecting the most suitable IDC computer room for the user.

[0016] S11. Select a target IDC computer room from among the IDC computer rooms to be selected according to the scores of the IDC computer rooms to be selected, and select an idle instance from the target IDC computer room to allocate to the user to run the cloud application.

[0017] In the embodiment of the present application, it should be noted that if the number of IDC computer rooms to be selected is equal to 1, then the IDC computer room to be selected is the target IDC computer room; and if the number of IDC computer rooms to be selected is greater than 1, then it is necessary to select one IDC computer room from the IDC computer rooms to be selected as the target IDC computer room.

[0018] The cloud application intelligent scheduling method provided in the embodiment of the present application uses the value of the key parameter that affects the instance scheduling to score each candidate IDC computer room, selects the target IDC computer room from each candidate IDC computer room according to the score of each candidate IDC computer room, and allocates an idle instance in the target IDC computer room to the user to run the cloud application. In this way, the instances in the IDC computer room can be effectively scheduled, thereby providing users with smooth cloud application services.

[0019] Based on the foregoing method embodiment, the step of calculating the score of the key parameter value may include: Determine the score of the distance between the user and the IDC room according to a preset correspondence between the distance between the user and the IDC room and the score; and / or Determine the score of the regional matching degree between the user and the IDC room according to the preset correspondence between the regional matching degree between the user and the IDC room and the score; and / or The score of the network performance parameter between the user and the IDC computer room is determined according to the preset correspondence between the network performance parameter and the score between the user and the IDC computer room.

[0020] In the embodiment of the present application, it should be noted that the correspondence between the key parameters affecting instance scheduling and the scores can be preset, and the correspondence can be shown in Table 1 below.

[0021] Table 1 The distance between the user and the IDC room <100km 100km~200km 200km~300km 300km~500km ≥500km Score 5 4 3 2 1 The degree of geographical matching between users and IDC data centers Same district / county Same city Same province Same country / Score 4 3 2 1 / Network performance parameters between users and IDC computer room Network delay <10ms Packet loss rate <0.1% Network delay 10ms~20ms Packet loss rate 0.1%~0.2% Network delay 20ms~30ms Packet loss rate 0.2%~0.3% Network delay 30ms~50ms Packet loss rate 0.3%~0.5% Network delay ≥50ms Packet loss rate ≥0.5% Score 5 4 3 2 1 In Table 1 above, the distance between the user and the IDC room is divided into five ranges: (-∞, 100km), [100km, 200km), [200km, 300km), [300km, 500km) and [500km, +∞), and the corresponding scores of these five ranges are 5, 4, 3, 2 and 1 respectively; the geographical matching degree between the user and the IDC room is divided into four levels: the same district / county, the same city, the same province and the same country, and the corresponding scores of these four levels are 4, 3, 2 and 1 respectively; the network delay between the user and the IDC room is divided into five ranges: (-∞, 10ms), [10ms, 20ms), [20ms, 30ms), [30ms, 50ms) and [50ms, +∞), and the packet loss rate between the user and the IDC room is divided into five ranges: The score for the interval range of network delay (-∞, 0.1%), [0.1%, 0.2%), [0.2%, 0.3%), [0.3%, 0.5%) and [0.5%, +∞) is 5, the score for the interval range of network delay (10ms, 20ms) and the interval range of packet loss rate (0.1%, 0.2%) is 4, the score for the interval range of network delay (20ms, 30ms) and the interval range of packet loss rate (0.2%, 0.3%) is 3, the score for the interval range of network delay (30ms, 50ms) and the interval range of packet loss rate (0.3%, 0.5%) is 2, and the score for the interval range of network delay (50ms, +∞) and the interval range of packet loss rate (0.5%, +∞) is 1.

[0022] The interval ranges and corresponding scores in Table 1 above are only examples. In specific implementation, they can be set to interval ranges / scores different from those in Table 1 as needed. In addition to the four divisions of country, province, city, and district / county, district / county can be further divided into small areas, and small areas can be further divided into streets. In addition to the same district / county, same city, same province, and same country, the regional matching degree between users and IDC rooms can also include the same small area and the same street.

[0023] Assuming that the distance between the user and the IDC data center is 400km, which is within the range of [300km, 500km), the score for the distance between the user and the IDC data center is 2 (i.e., the score corresponding to the range of [300km, 500km)). Assuming that the user is located in the province where the IDC data center is located, but not in the district / county where the IDC data center is located, the score for the degree of regional matching between the user and the IDC data center is 2 (i.e., the score corresponding to the same province). Assuming that the network delay between the user and the IDC data center is 12ms and the packet loss rate is 0.18%, because the network delay of 12ms is within the range of [10ms, 20ms) and the packet loss rate of 0.18% is within the range of [0.1%, 0.2%), the score for the network performance parameters between the user and the IDC data center is 4 (i.e., the score corresponding to the network delay range of [10ms, 20ms) and the packet loss rate range of [0.1%, 0.2%)).

[0024] Based on the aforementioned method embodiment, determining the score of the network performance parameter between the user and the IDC computer room according to the preset correspondence between the network performance parameter and the score between the user and the IDC computer room may include: For each parameter item in the network performance parameter between the user and the IDC computer room, determine the score of the parameter item according to the preset correspondence between the network performance parameter between the user and the IDC computer room and the score; The minimum value is selected from the scores of each parameter item as the score of the network performance parameter between the user and the IDC computer room.

[0025] In this embodiment, the corresponding relationship in Table 1 is still used as an example. Assuming that the network delay between the user and the IDC computer room is 12ms, and the packet loss rate is 0.28%, because the network delay of 12ms is in the range of [10ms, 20ms), the score of the network delay is 4 (i.e., the score corresponding to the network delay range of [10ms, 20ms)), and the score of the packet loss rate is 3 (i.e., the score corresponding to the packet loss rate range of [0.2%, 0.3%)). The minimum value of the score of the network delay and the score of the packet loss rate is 3, and the score of the network performance parameter between the user and the IDC computer room is 3 (i.e., the minimum value).

[0026] Based on the aforementioned method embodiment, the calculation process of the value of the network performance parameter between the user and the IDC room may include: Determine multiple target IP addresses, and use a dialing method to obtain the values ​​of various parameter items of network performance parameters between the user and the IDC computer room corresponding to each of the multiple target IP addresses, wherein the number of the multiple target IP addresses is an odd number, and the locations corresponding to the multiple target IP addresses and the location corresponding to the IP address of the terminal used by the user to apply for using the cloud application both belong to a preset location range; For each parameter item of the network performance parameter, the average value of the parameter item of the network performance parameter between the user corresponding to each target IP address and the IDC computer room is calculated, and the average value is used as the value of the parameter item of the network performance parameter between the user and the IDC computer room.

[0027] In this embodiment, it should be noted that the IP addresses of the terminals of multiple users who use the cloud application within a preset location range around the user can be determined based on the IP address of the terminal used by the user to apply for the cloud application, and the multiple IP addresses can be used as the candidate IP addresses, or the multiple IP addresses together with the IP address of the terminal used by the user to apply for the cloud application can be used as the candidate IP addresses, wherein the number of candidate IP addresses is an odd number. Afterwards, the dialing service deployed in the IDC room can be used to perform a dialing test to obtain the network delay (network delay is the delay of one-way data transmission between the user and the IDC room) and the packet loss rate between the user corresponding to each candidate IP address and the IDC room. If the number of packet loss rates whose median value of the obtained odd number of packet loss rates is greater than or equal to a preset threshold (for example, 100%) is less than (odd number + 1) / 2, the IP addresses of the terminals of multiple users who use the cloud application within the preset location range around the user are determined again, and the number of IP addresses determined this time is the number of packet loss rates whose median value of the odd number of packet loss rates is greater than or equal to the preset threshold. The IP addresses determined this time together with the IP addresses corresponding to the packet loss rates whose median value of the odd number of packet loss rates is less than the preset threshold are the target IP addresses; or if the number of packet loss rates whose median value of the odd number of packet loss rates is greater than or equal to the preset threshold is greater than or equal to (odd number + 1) / 2, the selected IP address is the target IP address.

[0028] For network delay, the average value of the network delay between the user corresponding to each target IP address and the IDC computer room can be calculated, and the average value of the network delay can be used as the value of the network delay between the user and the IDC computer room; for packet loss rate, the average value of the packet loss rate between the user corresponding to each target IP address and the IDC computer room can be calculated, and the average value of the packet loss rate can be used as the value of the packet loss rate between the user and the IDC computer room.

[0029] Based on the foregoing method embodiment, calculating the score of the IDC room according to the score of the value of the key parameter may include: The scores of the values ​​of the key parameters are input into a pre-trained deep learning model to obtain the score of the IDC computer room.

[0030] In this embodiment, it should be noted that the scores of multiple sets of key parameter values ​​and the scores of the IDC computer room can be used as training data to train the deep learning model in advance to obtain a pre-trained deep learning model. After calculating the scores of the key parameter values, the scores of the key parameter values ​​can be directly input into the pre-trained deep learning model, and the output of the model is the score of the corresponding IDC computer room.

[0031] Based on the foregoing method embodiment, the step of selecting a target IDC room from among the candidate IDC rooms according to the scores of the candidate IDC rooms may include: According to the order of scores of the candidate IDC computer rooms from high to low, an IDC computer room with idle instances is selected from the candidate IDC computer rooms as the target IDC computer room.

[0032] In this embodiment, it should be noted that after calculating the scores of each candidate IDC room, one IDC room can be selected from each candidate IDC room in descending order of the scores of each candidate IDC room until an IDC room with an idle instance is found or until all IDC rooms are traversed but no IDC room with an idle instance is found. If an IDC room with an idle instance is finally found, the IDC room can be selected as the target IDC room.

[0033] Reference Figure 2 FIG. 1 is a schematic diagram of a cloud application intelligent scheduling device provided in an embodiment of the present application, the device comprising: The calculation unit 20 is used to determine the Internet data center IDC room to be selected when the user applies to use the cloud application. If the number of the IDC rooms to be selected is greater than 1, then for each IDC room to be selected, the value of the key parameter affecting the instance scheduling is obtained, and the score of the value of the key parameter is calculated, and the score of the IDC room is calculated according to the score of the value of the key parameter, wherein the key parameter includes: at least two of the three parameters of the distance between the user and the IDC room, the degree of regional matching between the user and the IDC room, and the network performance parameter between the user and the IDC room; The scheduling unit 21 is used to select a target IDC room from each candidate IDC room according to the scores of each candidate IDC room, and select an idle instance from the target IDC room to allocate to the user to run the cloud application.

[0034] The cloud application intelligent scheduling device provided in the embodiment of the present application uses the value of the key parameter that affects the instance scheduling to score each candidate IDC computer room, selects the target IDC computer room from each candidate IDC computer room according to the score of each candidate IDC computer room, and allocates an idle instance in the target IDC computer room to the user to run the cloud application, so that the instances in the IDC computer room can be effectively scheduled, thereby providing users with smooth cloud application services.

[0035] Based on the above device embodiment, the computing unit may be used for: Determine the score of the distance between the user and the IDC room according to a preset correspondence between the distance between the user and the IDC room and the score; and / or Determine the score of the regional matching degree between the user and the IDC room according to the preset correspondence between the regional matching degree between the user and the IDC room and the score; and / or The score of the network performance parameter between the user and the IDC computer room is determined according to the preset correspondence between the network performance parameter and the score between the user and the IDC computer room.

[0036] Based on the above device embodiment, the computing unit may be used for: For each parameter item in the network performance parameter between the user and the IDC computer room, determine the score of the parameter item according to the preset correspondence between the network performance parameter between the user and the IDC computer room and the score; The minimum value is selected from the scores of each parameter item as the score of the network performance parameter between the user and the IDC computer room.

[0037] Based on the aforementioned device embodiment, the calculation process of the value of the network performance parameter between the user and the IDC room may include: Determine multiple target IP addresses, and use a dialing method to obtain the values ​​of various parameter items of network performance parameters between the user and the IDC computer room corresponding to each of the multiple target IP addresses, wherein the number of the multiple target IP addresses is an odd number, and the locations corresponding to the multiple target IP addresses and the location corresponding to the IP address of the terminal used by the user to apply for using the cloud application both belong to a preset location range; For each parameter item of the network performance parameter, the average value of the parameter item of the network performance parameter between the user corresponding to each target IP address and the IDC computer room is calculated, and the average value is used as the value of the parameter item of the network performance parameter between the user and the IDC computer room.

[0038] The cloud application intelligent scheduling device provided in the embodiment of the present application has an implementation process that is consistent with the cloud application intelligent scheduling method provided in the embodiment of the present application, and the effect that can be achieved is also the same as the cloud application intelligent scheduling method provided in the embodiment of the present application, and will not be repeated here.

[0039] like Figure 3 As shown, an electronic device provided by an embodiment of the present application includes: a processor 30, a memory 31 and a bus 32, wherein the memory 31 stores machine-readable instructions executable by the processor 30, and when the electronic device is running, the processor 30 communicates with the memory 31 through the bus 32, and the processor 30 executes the machine-readable instructions to perform the steps of the above-mentioned cloud application intelligent scheduling method.

[0040] Specifically, the above-mentioned memory 31 and processor 30 can be general-purpose memory and processor, which are not specifically limited here. When the processor 30 runs the computer program stored in the memory 31, it can execute the above-mentioned cloud application intelligent scheduling method.

[0041] Corresponding to the above-mentioned cloud application intelligent scheduling method, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned cloud application intelligent scheduling method are executed.

[0042] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A cloud application intelligent scheduling method, characterized in that: include: When a user applies to use a cloud application, determine the Internet data center IDC room to be selected. If the number of IDC rooms to be selected is greater than 1, then for each IDC room to be selected, obtain the value of a key parameter that affects instance scheduling, and calculate the score of the key parameter value. Calculate the score of the IDC room according to the score of the key parameter value, wherein the key parameter includes: at least two of the three parameters: the distance between the user and the IDC room, the degree of regional matching between the user and the IDC room, and the network performance parameter between the user and the IDC room; A target IDC computer room is selected from each of the IDC computer rooms to be selected according to the scores of each of the IDC computer rooms to be selected, and an idle instance is selected from the target IDC computer room and allocated to the user to run the cloud application.

2. The method according to claim 1, characterized in that The calculating the score of the value of the key parameter comprises: Determine the score of the distance between the user and the IDC room according to a preset correspondence between the distance between the user and the IDC room and the score; and / or Determine the score of the regional matching degree between the user and the IDC room according to the preset correspondence between the regional matching degree between the user and the IDC room and the score; and / or The score of the network performance parameter between the user and the IDC computer room is determined according to the preset correspondence between the network performance parameter and the score between the user and the IDC computer room.

3. The method according to claim 2, characterized in that The step of determining the score of the network performance parameter between the user and the IDC computer room according to the preset correspondence between the network performance parameter and the score between the user and the IDC computer room includes: For each parameter item in the network performance parameter between the user and the IDC computer room, determine the score of the parameter item according to the preset correspondence between the network performance parameter between the user and the IDC computer room and the score; The minimum value is selected from the scores of each parameter item as the score of the network performance parameter between the user and the IDC computer room.

4. The method according to any one of claims 1 to 3, characterized in that The calculation process of the network performance parameter value between the user and the IDC room includes: Determine multiple target IP addresses, and use a dialing method to obtain the values ​​of various parameter items of network performance parameters between the user and the IDC computer room corresponding to each of the multiple target IP addresses, wherein the number of the multiple target IP addresses is an odd number, and the locations corresponding to the multiple target IP addresses and the location corresponding to the IP address of the terminal used by the user to apply for using the cloud application both belong to a preset location range; For each parameter item of the network performance parameter, the average value of the parameter item of the network performance parameter between the user corresponding to each target IP address and the IDC computer room is calculated, and the average value is used as the value of the parameter item of the network performance parameter between the user and the IDC computer room.

5. The method according to claim 1, characterized in that Calculating the score of the IDC room according to the score of the value of the key parameter includes: The scores of the values ​​of the key parameters are input into a pre-trained deep learning model to obtain the score of the IDC computer room.

6. The method according to claim 1, characterized in that The step of selecting a target IDC computer room from among the IDC computer rooms to be selected according to the scores of the IDC computer rooms to be selected includes: According to the order of scores of the candidate IDC computer rooms from high to low, an IDC computer room with idle instances is selected from the candidate IDC computer rooms as the target IDC computer room.

7. A cloud application intelligent scheduling device, characterized in that: include: A calculation unit is used to determine an Internet data center IDC room to be selected when a user applies to use a cloud application. If the number of the IDC rooms to be selected is greater than 1, then for each IDC room to be selected, a value of a key parameter affecting instance scheduling is obtained, and a score of the value of the key parameter is calculated. The score of the IDC room is calculated according to the score of the value of the key parameter, wherein the key parameter includes at least two of the three parameters: a distance between the user and the IDC room, a degree of regional matching between the user and the IDC room, and a network performance parameter between the user and the IDC room; The scheduling unit is used to select a target IDC computer room from each candidate IDC computer room according to the scores of each candidate IDC computer room, and select an idle instance from the target IDC computer room to allocate to the user to run the cloud application.

8. The device according to claim 7, characterized in that The computing unit is used for: Determine the score of the distance between the user and the IDC room according to the preset correspondence between the distance between the user and the IDC room and the score; and / or Determine the score of the regional matching degree between the user and the IDC computer room according to the preset correspondence between the regional matching degree between the user and the IDC computer room and the score; and / or The score of the network performance parameter between the user and the IDC computer room is determined according to the preset correspondence between the network performance parameter and the score between the user and the IDC computer room.

9. The device according to claim 8, characterized in that The computing unit is used for: For each parameter item in the network performance parameter between the user and the IDC computer room, determine the score of the parameter item according to the preset correspondence between the network performance parameter between the user and the IDC computer room and the score; The minimum value is selected from the scores of each parameter item as the score of the network performance parameter between the user and the IDC computer room.

10. The device according to any one of claims 7 to 9, characterized in that The calculation process of the network performance parameter value between the user and the IDC room includes: Determine multiple target IP addresses, and use a dialing method to obtain the values ​​of various parameter items of network performance parameters between the user and the IDC computer room corresponding to each of the multiple target IP addresses, wherein the number of the multiple target IP addresses is an odd number, and the locations corresponding to the multiple target IP addresses and the location corresponding to the IP address of the terminal used by the user to apply for using the cloud application both belong to a preset location range; For each parameter item of the network performance parameter, the average value of the parameter item of the network performance parameter between the user corresponding to each target IP address and the IDC computer room is calculated, and the average value is used as the value of the parameter item of the network performance parameter between the user and the IDC computer room.

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