Scheduling methods, devices, equipment, and media applied to cloud service platforms

Abstract

This disclosure provides a scheduling method, apparatus, device, and medium for cloud service platforms, relating to the field of cloud computing technology, and particularly to the field of cloud service scheduling technology. The implementation scheme is as follows: In response to receiving a service request from a target user, based on the service partition configuration information of the target user, a plurality of first target partitions are determined from a plurality of first service partitions of the cloud service platform; based on the access latency of the plurality of first target partitions, the priority of each of the plurality of first target partitions is determined; and based on the priority of each first target partition, the service request is scheduled to the plurality of first target partitions, so that the processing devices included in the plurality of first target partitions can process the service request.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of cloud computing, in particular to the technical field of cloud service scheduling, and specifically to a scheduling method and device applied to a cloud service platform, an electronic device, a computer readable storage medium and a computer program product. BACKGROUND

[0002] Cloud computing refers to accessing elastic scalable shared physical or virtual resource pools through a network, the resources can include servers, operating systems, networks, software, applications and storage devices, etc., and the resources can be deployed and managed in a demand-driven and self-service manner. Through cloud computing technology, efficient and powerful data processing capabilities can be provided for artificial intelligence, blockchain and other technical applications and model training.

[0003] A cloud service platform includes multiple machine rooms distributed in various regions, and on this basis, the cloud service platform can be divided into multiple service partitions based on geographic regions. When one or more service partitions fail, the cloud services bound to the failed partitions will be interrupted, affecting the continuity of user business.

[0004] The methods described in this section are not necessarily the methods that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any of the methods described in this section qualify as prior art merely by virtue of their inclusion in this section. Similarly, issues mentioned in this section should not be interpreted as an admission that any of the issues are numerically art. SUMMARY

[0005] The present disclosure provides a scheduling method and device applied to a cloud service platform, an electronic device, a computer readable storage medium and a computer program product.

[0006] According to an aspect of the present disclosure, a scheduling method applied to a cloud service platform is provided, wherein the cloud service platform includes a plurality of first service partitions, and the method includes: in response to receiving a service request of a target user, determining a plurality of first target partitions from the plurality of first service partitions based on service partition configuration information of the target user; determining a priority of each first target partition in the plurality of first target partitions based on access latency of the plurality of first target partitions; and scheduling the service request to the plurality of first target partitions based on the priority of each first target partition, so that processing devices included in the plurality of first target partitions can process the service request.

[0007] According to another aspect of the present disclosure, a scheduling apparatus applied to a cloud service platform is provided, wherein the cloud service platform comprises a plurality of first service partitions, and the apparatus comprises: a first determining unit configured to, in response to receiving a service request of a target user, determine a plurality of first target partitions from the plurality of first service partitions based on service partition configuration information of the target user; a second determining unit configured to determine a priority of each first target partition in the plurality of first target partitions based on access latency of the plurality of first target partitions; and a scheduling unit configured to schedule the service request to the plurality of first target partitions based on the priority of each first target partition, so that processing apparatuses comprised in the plurality of first target partitions can process the service request.

[0008] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the above-mentioned scheduling method applied to a cloud service platform.

[0009] According to another aspect of the present disclosure, a non-transitory computer readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to perform the above-mentioned scheduling method applied to a cloud service platform.

[0010] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein the computer program can implement the above-mentioned scheduling method applied to a cloud service platform when executed by a processor.

[0011] According to one or more embodiments of the present disclosure, the reliability and service efficiency of a cloud service can be improved.

[0012] It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become apparent through the following description. BRIEF DESCRIPTION OF DRAWINGS

[0013] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments and together with the description serve to explain exemplary implementations of the application. The illustrated embodiments are exemplary only and not limiting of the scope of the claims. In all the drawings, like reference numerals refer to like parts throughout the several views.

[0014] Figure 1 schematic diagrams of exemplary systems in which the various methods described herein can be implemented in accordance with exemplary embodiments of the present disclosure are shown;

[0015] Figure 2 A flow chart of a scheduling method applied to a cloud service platform is shown according to an example embodiment of the present disclosure;

[0016] Figure 3 A structural schematic diagram of a cloud service platform is shown according to an example embodiment of the present disclosure;

[0017] Figure 4 A structural block diagram of a scheduling device applied to a cloud service platform is shown according to an example embodiment of the present disclosure;

[0018] Figure 5 A structural block diagram of an example electronic device that can be used to implement embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0019] Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, which include various details of the embodiments of the present disclosure to assist in understanding them. These should be considered in their context only as exemplifications. Thus, one of ordinary skill in the art will recognize that variations and modifications of the embodiments described herein can be made while remaining within the scope of the present disclosure. Also, for the purpose of clarity and a concise description, descriptions of well-known functions and constructions are omitted from the following description.

[0020] In the present disclosure, the terms "first", "second", and the like are used to describe various elements only and do not intend to limit the positional relationship, the time relationship, or the importance of the elements, and such terms are only used to distinguish one element from another element. In some examples, the first element and the second element can refer to the same instance of the element, and in some cases, based on the context of the description, they can also refer to different instances.

[0021] The terms used in the description of various examples described in the present disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the number of elements is specifically limited, the element can be one or more than one, if the number of elements is not specifically limited, unless the context clearly indicates otherwise. In addition, the term "and / or" used in the present disclosure encompasses any one of the listed items and all possible combinations thereof.

[0022] Embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0023] Figure 1 A schematic diagram of an example system 100 in which various methods and apparatuses described herein can be implemented according to embodiments of the present disclosure is shown. Reference is made to Figure 1The system 100 includes one or more client devices 101, 102, 103, 104, 105 and 106, a server 120, and one or more communication networks 110 coupling the one or more client devices to the server 120. The client devices 101, 102, 103, 104, 105 and 106 can be configured to execute one or more applications.

[0024] In embodiments of this disclosure, server 120 may run one or more services or software applications that enable the execution of scheduling methods applied to a cloud service platform.

[0025] In some embodiments, server 120 may also provide other services or software applications, which may include non-virtual and virtual environments. In some embodiments, these services may be provided as web-based services or cloud services, such as to users of client devices 101, 102, 103, 104, 105, and / or 106 under a Software as a Service (SaaS) model.

[0026] exist Figure 1 In the configuration shown, server 120 may include one or more components that implement the functions performed by server 120. These components may include software components, hardware components, or combinations thereof that can be executed by one or more processors. Users operating client devices 101, 102, 103, 104, 105, and / or 106 can sequentially interact with server 120 using one or more client applications to utilize the services provided by these components. It should be understood that various different system configurations are possible and may differ from system 100. Therefore, Figure 1 This is an example of a system used to implement the various methods described herein, and is not intended to be limiting.

[0027] Users can use client devices 101, 102, 103, 104, 105, and / or 106 to send service requests. The client devices can provide an interface that allows users to interact with the client devices. The client devices can also output information to the user through this interface. Although... Figure 1 Only six client devices are described, but those skilled in the art will understand that this disclosure can support any number of client devices.

[0028] Client devices 101, 102, 103, 104, 105, and / or 106 may include various categories of computer devices, such as portable handheld devices, general-purpose computers (such as personal computers and laptops), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, gaming systems, thin clients, various messaging devices, sensors, or other sensing devices. These computer devices can run various categories and versions of software applications and operating systems, such as Microsoft Windows, Apple iOS, UNIX-like operating systems, Linux or Linux-like operating systems (such as Google Chrome OS); or include various mobile operating systems, such as Microsoft Windows Mobile OS, iOS, Windows Phone, and Android. Portable handheld devices may include cellular phones, smartphones, tablets, personal digital assistants (PDAs), etc. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. Gaming systems may include various handheld gaming devices, internet-enabled gaming devices, etc. Client devices can run a variety of different applications, such as various Internet-related applications, communication applications (e.g., email applications), short message service (SMS) applications, and can use various communication protocols.

[0029] Network 110 can be any type of network well known to those skilled in the art, and can use any of a variety of available protocols (including but not limited to TCP / IP, SNA, IPX, etc.) to support data communication. By way of example only, one or more networks 110 can be a local area network (LAN), an Ethernet-based network, a token ring network, a wide area network (WAN), the Internet, a virtual network, a virtual private network (VPN), an intranet, an extranet, a blockchain network, a public switched telephone network (PSTN), an infrared network, a wireless network (e.g., Bluetooth, WIFI), and / or any combination of these and / or other networks.

[0030] Server 120 may include one or more general-purpose computers, special-purpose server computers (e.g., PC (personal computer) servers, UNIX servers, mid-range servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and / or combination. Server 120 may include one or more virtual machines running a virtual operating system, or other computing architectures involving virtualization (e.g., one or more flexible pools of logical storage devices that can be virtualized to maintain virtual storage devices for servers). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

[0031] The computing unit in server 120 can run one or more operating systems, including any of the aforementioned operating systems and any commercially available server operating system. Server 120 can also run any of a variety of additional server applications and / or middleware applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

[0032] In some implementations, server 120 may include one or more applications to analyze and merge data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105, and 106. Server 120 may also include one or more applications to display data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

[0033] In some implementations, server 120 can be a server for a distributed system or a server integrated with blockchain. Server 120 can also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. A cloud server is a host product in the cloud computing service system, designed to address the shortcomings of traditional physical hosts and Virtual Private Server (VPS) services, such as high management difficulty and weak business scalability.

[0034] System 100 may also include one or more databases 130. In some embodiments, these databases may be used to store data and other information. For example, one or more of the databases 130 may be used to store information such as audio files and video files. Databases 130 may reside in various locations. For example, a database used by server 120 may be local to server 120, or it may be located away from server 120 and may communicate with server 120 via a network-based or dedicated connection. Databases 130 may be of different categories. In some embodiments, the database used by server 120 may be, for example, a relational database. One or more of these databases may store, update, and retrieve data from and from the databases in response to commands.

[0035] In some embodiments, one or more of the databases 130 may also be used by an application to store application data. The databases used by the application may be different categories of databases, such as key-value stores, object stores, or regular stores supported by a file system.

[0036] Figure 1The system 100 can be configured and operated in various ways to enable the application of the various methods and apparatus described in this disclosure.

[0037] To optimize resource allocation, improve service performance, and meet compliance requirements, cloud service providers can divide their cloud service platforms into multiple service partitions based on geographical regions. By partitioning cloud service services based on geographical regions, cloud service providers can optimize resource allocation, improve service performance, and reduce network latency according to geographical location. Each service partition corresponding to a geographical region can contain a complete set of cloud service resources, such as elastic computing, block storage, object storage, VPC (Virtual Private Cloud) networks, elastic public IPs (Elastic IPs), and images, thereby providing cloud services to users based on independent resource and service environments.

[0038] In related technologies, when a user purchases cloud service resources, the cloud service corresponding to that user is typically bound to a specific service partition (e.g., the service partition corresponding to the user's geographical region). This ensures that the physical distance between the deployment location of the cloud computing resources and the user's location is minimized, thereby reducing cloud service latency and improving user experience. In this scenario, a service outage occurs when the service partition corresponding to the user fails.

[0039] Based on this, this disclosure provides a scheduling method for cloud service platforms. When the cloud service platform includes multiple first service partitions, the user's configuration information is used to indicate multiple target partitions that can be used. While building a redundancy mechanism and improving the reliability of cloud services by utilizing multiple target partitions, the scheduling priority is determined based on the access latency of each target service partition to reduce cloud service latency and improve cloud service efficiency.

[0040] Figure 2 A flowchart illustrating a scheduling method 200 applied to a cloud service platform according to an exemplary embodiment of the present disclosure is shown, the cloud service platform including a plurality of first service partitions. For example... Figure 2 As shown, method 200 includes:

[0041] Step S201: In response to receiving a service request from a target user, determine a plurality of first target partitions from the plurality of first service partitions based on the service partition configuration information of the target user;

[0042] Step S202: Based on the access latency of the plurality of first target partitions, determine the priority of each first target partition among the plurality of first target partitions; and

[0043] Step S203: Based on the priority of each first target partition, schedule the service request to the plurality of first target partitions so that the processing devices included in the plurality of first target partitions can process the service request.

[0044] By applying the scheduling method 200 described above for cloud service platforms, multiple target partitions can be indicated using user configuration information. By utilizing multiple first target partitions, redundant resources can be provided for user service requests, thereby improving cloud service reliability. Simultaneously, the scheduling priority of multiple first target partitions can be determined based on the access latency of each first target partition. By optimizing the scheduling of multiple first target partitions, cloud service latency can be reduced, and service efficiency improved.

[0045] In some examples, the aforementioned multiple first service partitions can be derived based on geographical regions. Each service partition can contain a complete set of cloud service resources and thus provide cloud services to users based on independent resource and service environments. In this case, when a target user purchases cloud service resources, different first service partitions will have different network latencies, thereby affecting cloud service efficiency. By applying the above method 200 to schedule the hardware resources of the cloud platform, it is possible to utilize multiple first target partitions to provide redundant first service partitions for target users, improve cloud service reliability, optimize service latency, and improve service efficiency.

[0046] In some examples, the service partition configuration information for the target user can be configured by the target user when purchasing cloud service resources. In one example, the user can directly select multiple desired first target partitions and save them as service partition configuration information. For example, if the user selects partitions A and B, partitions A and B can be directly designated as the first target partitions. In another example, the user can also select the desired number of first target partitions. For example, when the user configures the number of first target partitions to be 2, 2 first target partitions can be selected from multiple first service partitions on the cloud service platform based on this. This selection step can be implemented based on the hardware resource information (e.g., computing resource margin, storage resource margin) or access latency of each first service partition, which is not limited in this disclosure.

[0047] In practical applications, users can purchase public IP addresses from cloud service platforms to meet their business needs. For example, they can dynamically bind or unbind the purchased public IP addresses from cloud product instances. This allows for flexible switching between different instances when a cloud product instance fails, quickly restoring access to the public IP address and ensuring business continuity. Furthermore, the purchased public IP addresses can be used to provide higher-level security measures for cloud products, effectively protecting the cloud platform's data and application security.

[0048] Understandably, in the application of public IP addresses, IP address blocks are typically divided according to geographical regions. As mentioned earlier, service partitions of cloud service platforms are also based on geographical regions. In related technologies, when a user purchases a cloud service product based on a public IP address, the purchased product service will also be bound to the service partition corresponding to the public IP address. When the service partition fails, it will lead to the interruption of cloud services.

[0049] Based on this, according to some embodiments, the service request includes a request for an Elastic IP address. Therefore, by applying the above method 200 to cloud services based on public IP addresses, a multi-target partition active-active mechanism can be constructed for the Elastic IP address resources purchased by the user, thereby improving the reliability of cloud services.

[0050] In some examples, service requests may also include other content, such as various types of data processing requests, data storage and access requests, email service requests, etc. As long as the hardware resources of the cloud service platform can be scheduled for the user, this disclosure does not limit the type of cloud service requested by the user.

[0051] According to some embodiments, each of the plurality of first service partitions includes a plurality of second service partitions. Method 200 further includes: for each of the plurality of first target partitions, determining the availability of the plurality of second service partitions within that first target partition; based on the availability of the plurality of second service partitions, determining at least one second target partition from the plurality of second service partitions; and processing the service request using the at least one second target partition. In this example, when the first service partition of the cloud service platform includes a plurality of second service partitions, by applying the above-described technical means, redundant resources at both the first service partition level and the second service partition level can be configured for users in the cloud service platform. Flexible scheduling is performed at the first service partition level based on the access latency of each first target partition (first service partition). Furthermore, disaster recovery management is implemented at the second service partition level, improving service reliability without affecting cloud service efficiency.

[0052] In some examples, multiple second service partitions of a cloud service platform can correspond to multiple physical networks, and each physical network can include multiple processing devices in a physical network. By scheduling the service requests of a target user to multiple second target partitions, the service requests to be processed can be accessed to the physical networks corresponding to each second target partition, so that the processing devices in each physical network can process the service requests, thereby providing cloud services to the user.

[0053] In some examples, the steps described above for determining the availability of multiple second service partitions can be implemented using various link availability detection methods, thereby determining the availability of communication connections for each second service partition. In some examples, the hardware resource information (e.g., remaining processing resources, remaining storage resources) of each second service partition can be further determined, and multiple second target partitions can be selected based on this.

[0054] In some examples, all available second service partitions can be designated as the second target partitions, and all available partitions can be used to distribute the service requests of the target users in order to achieve load balancing of cloud service resources.

[0055] In practical applications, cloud service platforms typically utilize gateways to control all business traffic entering and leaving cloud service partitions, enabling cloud service users to effectively access and utilize the hardware resources within the cloud service platform. For example, a gateway can convert public network protocol requests from the internet into communication protocol data between various devices within the cloud service platform domain, thereby managing hardware resources within the cloud service platform domain. Furthermore, gateways can also implement network security protection and traffic load balancing configuration functions to improve the resource utilization of the cloud service platform.

[0056] Based on this, according to some embodiments, each of the plurality of second service partitions includes multiple gateways. Method 200 further includes: managing the second service partition using the multiple gateways included in each second service partition, so that the service request can access the processing device included in the second service partition through the multiple gateways; and, in response to determining that a target gateway has failed, managing the second service partition using other gateways included in the second service partition to which the target gateway belongs. Thus, when a target gateway responsible for managing a second service partition fails, the routing of that target gateway can be promptly cancelled, and other networks can be used to reload the service traffic of the second service partition. This further improves the reliability of cloud services by constructing a redundancy mechanism at the gateway level.

[0057] According to some embodiments, determining the priority of each first target partition based on the access latency of the plurality of first target partitions in step S202 includes: determining the priority of each first target partition based on the difference between the access latencies of each first target partition. Therefore, scheduling priority information can be determined more accurately based on the difference between the access latencies of each first target partition, improving cloud service efficiency.

[0058] According to some embodiments, determining the priority of each first target partition based on the difference in access latency among the first target partitions includes: in response to determining that the difference in access latency among the first target partitions is not greater than a time difference threshold, determining that each first target partition has the same priority. Therefore, it is possible to determine whether a mechanism for equal scheduling of multiple hosts is applied to multiple first target partitions based on a time difference threshold, thereby improving the utilization of cloud processing resources and enhancing cloud service efficiency.

[0059] In some examples, when the priority of each first target partition is the same, service request traffic can be evenly distributed to multiple first target partitions to improve the resource utilization of each first target partition and achieve load balancing.

[0060] According to some embodiments, determining the priority of each first target partition based on the difference in access latency among the first target partitions includes: in response to determining that the difference in access latency between the third partition and the fourth partition is greater than the time difference threshold, determining that the priority of the third partition is higher than the priority of the fourth partition. Therefore, it is possible to determine whether a master-slave scheduling mechanism is applied to multiple first target partitions based on the time difference threshold, thereby improving the utilization of cloud processing resources and enhancing cloud service efficiency.

[0061] In some examples, when different primary target partitions correspond to different priorities, user traffic can be scheduled based on a master and backup model. For instance, the third partition mentioned above can be used as the primary load balancer, and the fourth partition as the backup. When a user's service request is received, the request traffic is first scheduled to the third partition for processing. If the third partition fails, the request traffic is then transferred to the backup partition for processing to ensure the continuity of cloud services.

[0062] According to some embodiments, method 200 further includes: monitoring the availability of the plurality of first target partitions; updating the plurality of first target partitions in response to determining that the availability of the plurality of first target partitions has changed; and scheduling the service request to the updated plurality of first target partitions. Performing link availability detection on the first target partitions to achieve disaster recovery can improve the reliability of cloud services.

[0063] Figure 3 A schematic diagram of the structure of a cloud service platform according to an exemplary embodiment of this disclosure is shown. Figure 3As shown, the cloud service platform includes a first service partition 3100 and a second service partition 3200. The first service partition 3100 includes second service partitions 3110 and 3120, and the first service partition 3200 includes second service partitions 3210 and 3220. In this example, each second service partition corresponds to a set of physical network hardware devices, specifically including a physical network (such as...) used to achieve data interconnection between the second service partition and the scheduler 3300. Figure 3 The physical networks shown (3111, 3121, 3211, 3221) are used to manage two gateways (e.g., ...) for each second service partition. Figure 3 Gateways 3112, 3113, 3122, 3123, 3212, 3213, 3222, and 3223 (as shown) and processing devices (e.g.) Figure 3 The processing devices 3114, 3124, 3214, and 3224 are shown. See also... Figure 3 The solid arrows indicate the data flow direction corresponding to user service requests, while the dashed arrows indicate the control flow direction used to configure the various components of the cloud service platform. In this example, the cloud service platform is configured with a scheduler 3300 and a scheduling controller 3400. The administrator of the cloud service platform can use the scheduling controller 3400 to configure the target addresses of each first service partition for the scheduler 3300, and can also pass the service partition configuration information and scheduling policies of the target user to the scheduler 3300. This allows the scheduler to determine the available first target partitions and the priorities of each first target partition in the cloud service platform, and then schedule the service request traffic from the user to each first target partition, that is, to send the service request information to the multiple sets of physical networks included in each first target partition.

[0064] See also Figure 3 In this example, each first service partition is configured with a partition controller (such as...). Figure 3 The partition controllers 3130 and 3230 shown can each control the gateways in the first service partition to which they belong, enabling the gateways to publish or revoke routing information, thereby controlling the load of user service requests on each group of physical networks or on each gateway. When a gateway or a processing device in the physical network fails, the partition controller can promptly revoke the routing information of the failed gateway and reconfigure other gateways to ensure the continuity of service request processing.

[0065] Based on the management of hardware resources within the first service partition by each partition controller, the scheduling controller 3400 can monitor the availability of each first service partition. When a failure occurs in a first service partition, the failure information can be transmitted to the scheduler 3300, so that the scheduler 3300 can reschedule service requests, avoid cloud service interruptions, and improve service reliability.

[0066] According to one aspect of this disclosure, a scheduling device for use in a cloud service platform is also provided. Figure 4 A structural block diagram of a scheduling apparatus 400 applied to a cloud service platform according to an exemplary embodiment of the present disclosure is shown, the cloud service platform including a plurality of first service partitions. For example... Figure 4 As shown, the device 400 includes:

[0067] The first determining unit 401 is configured to, in response to receiving a service request from a target user, determine a plurality of first target partitions from the plurality of first service partitions based on the service partition configuration information of the target user;

[0068] The second determining unit 402 is configured to determine the priority of each of the plurality of first target partitions based on the access latency of the plurality of first target partitions; and

[0069] The scheduling unit 403 is configured to schedule the service request to the plurality of first target partitions based on the priority of each first target partition, so that the processing devices included in the plurality of first target partitions can process the service request.

[0070] According to some embodiments, each of the plurality of first service partitions includes a plurality of second service partitions, and the apparatus 400 further includes: a third determining unit configured to determine the availability of a plurality of second service partitions in each of the plurality of first target partitions; a fourth determining unit configured to determine at least one second target partition from the plurality of second service partitions based on the availability of the plurality of second service partitions; and a first processing unit configured to process the service request using the at least one second target partition.

[0071] According to some embodiments, each of the plurality of second service partitions includes a plurality of gateways, and the apparatus 400 further includes: a second processing unit configured to manage the second service partition using the plurality of gateways included in each second service partition, such that the service request can access the processing apparatus included in the second service partition through the plurality of gateways, and the second processing unit is further configured to manage the second service partition using other gateways included in the second service partition to which the target gateway belongs in response to determining that a target gateway has failed.

[0072] According to some embodiments, the second determining unit 402 is configured to determine the priority of each first target partition based on the difference between the access latency of each first target partition.

[0073] According to some embodiments, the second determining unit 402 is configured to: determine that each first target partition has the same priority in response to determining that the difference in access latency of each first target partition is not greater than a time difference threshold.

[0074] According to some embodiments, the second determining unit 402 is configured to: in response to determining that the difference between the access latency of the third partition and the access latency of the fourth partition is greater than the time difference threshold, determine that the priority of the third partition is higher than the priority of the fourth partition.

[0075] According to some embodiments, the apparatus 400 further includes: a monitoring unit configured to monitor the availability of the plurality of first target partitions; an updating unit configured to update the plurality of first target partitions in response to determining that the availability of the plurality of first target partitions has changed, and the scheduling unit 403 is further configured to schedule the service request to the updated plurality of first target partitions.

[0076] According to some embodiments, the service request includes a request for an Elastic Public Address.

[0077] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0078] According to another aspect of this disclosure, an electronic device is also provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the scheduling method applied to a cloud service platform described above.

[0079] According to another aspect of this disclosure, a non-transitory computer-readable storage medium storing computer instructions is also provided, wherein the computer instructions are used to cause the computer to execute the scheduling method applied to a cloud service platform described above.

[0080] According to another aspect of this disclosure, a computer program product is also provided, including a computer program, wherein the computer program, when executed by a processor, implements the above-described scheduling method applied to a cloud service platform.

[0081] refer to Figure 5The present invention describes a structural block diagram of an electronic device 500 that can serve as a server or client of the present disclosure, which is an example of a hardware device that can be applied to various aspects of the present disclosure. The electronic device is intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0082] like Figure 5 As shown, device 500 includes a computing unit 501, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 502 or a computer program loaded from storage unit 508 into random access memory (RAM) 503. RAM 503 may also store various programs and data required for the operation of device 500. The computing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0083] Multiple components in device 500 are connected to I / O interface 505, including: input unit 506, output unit 507, storage unit 508, and communication unit 509. Input unit 506 can be any type of device capable of inputting information to device 500. Input unit 506 can receive input numerical or character information and generate key signal inputs related to user settings and / or function control of the electronic device, and may include, but is not limited to, a mouse, keyboard, touchscreen, trackpad, trackball, joystick, microphone, and / or remote control. Output unit 507 can be any type of device capable of presenting information, and may include, but is not limited to, a monitor, speaker, video / audio output terminal, vibrator, and / or printer. Storage unit 508 may include, but is not limited to, a hard disk and an optical disk. Communication unit 509 allows device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers, and / or chipsets, such as Bluetooth™ devices, 802.11 devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0084] The computing unit 501 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose 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 501 performs the various methods and processes described above, such as scheduling methods applied to a cloud service platform. For example, in some embodiments, the scheduling method applied to a cloud service platform can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed on device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the scheduling method applied to a cloud service platform described above can be performed. Alternatively, in other embodiments, computing unit 501 may be configured to execute scheduling methods applied to a cloud service platform by any other suitable means (e.g., by means of firmware).

[0085] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0086] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This 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 when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0087] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0088] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0089] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), the Internet, and blockchain networks.

[0090] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0091] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0092] While embodiments or examples of this disclosure have been described with reference to the accompanying drawings, it should be understood that the methods, systems, and devices described above are merely exemplary embodiments or examples, and the scope of the invention is not limited by these embodiments or examples, but only by the granted claims and their equivalents. Various elements in the embodiments or examples may be omitted or replaced by their equivalents. Furthermore, the steps may be performed in a different order than that described in this disclosure. Further, various elements in the embodiments or examples may be combined in various ways. Importantly, as the technology evolves, many elements described herein can be replaced by equivalents that appear after this disclosure.

Claims

1. A scheduling method applied to a cloud service platform, wherein, The cloud service platform comprises a plurality of first service partitions, and the method comprises: in response to receiving a service request of a target user, determining a plurality of first target partitions from the plurality of first service partitions based on service partition configuration information of the target user; determining a priority of each first target partition in the plurality of first target partitions based on access latency of the plurality of first target partitions, comprising: in response to determining that a difference between access latencies of respective first target partitions is not greater than a time difference threshold, determining that the priority of each first target partition is the same; and in response to determining that there are a third partition and a fourth partition in the plurality of first target partitions with a difference between access latencies greater than the time difference threshold, determining that the priority of a partition with lower access latency in the third partition and the fourth partition is higher than the priority of a partition with higher access latency in the third partition and the fourth partition; and based on the priority of each first target partition, scheduling the service request to the plurality of first target partitions to enable processing devices included in the plurality of first target partitions to process the service request, comprising: in response to the priority of the plurality of first target partitions being the same, evenly distributing traffic of the service request to the plurality of first target partitions; and in response to the priority of the plurality of first target partitions being different, taking a first target partition with higher priority as a primary load zone and taking a first target partition with lower priority as a backup zone to preferentially schedule the service request to the primary load zone when no failure occurs in the primary load zone.

2. The method of claim 1, wherein, Each first service partition in the plurality of first service partitions comprises a plurality of second service partitions, and the method further comprises: for each first target partition in the plurality of first target partitions, determining availability of a plurality of second service partitions in the first target partition; based on the availability of the plurality of second service partitions, determining at least one second target partition from the plurality of second service partitions; and processing the service request using the at least one second target partition.

3. The method of claim 2, wherein, Each second service partition in the plurality of second service partitions comprises a plurality of gateways, and the method further comprises: managing each second service partition using a plurality of gateways included in the second service partition to enable the service request to access processing devices included in the second service partition through the plurality of gateways; and in response to determining that a target gateway fails, managing the second service partition to which the target gateway belongs using other gateways included in the second service partition.

4. The method of any one of claims 1-3, further comprising: monitoring availability of the plurality of first target partitions; in response to determining that the availability of the plurality of first target partitions changes, updating the plurality of first target partitions; and scheduling the service request to the updated plurality of first target partitions. The service request comprises a request for a resilient public network address.

5. The method of any one of claims 1-3, wherein, The cloud service platform comprises a plurality of first service partitions, and the apparatus comprises:

6. A scheduling apparatus applied to a cloud service platform, wherein, ​ a first determining unit configured to determine, in response to receiving a service request of a target user, a plurality of first target partitions from the plurality of first service partitions based on service partition configuration information of the target user; a second determining unit configured to determine a priority of each of the plurality of first target partitions based on access latencies of the plurality of first target partitions, the second determining unit being further configured to: determine that the priorities of each of the plurality of first target partitions are the same in response to determining that differences between the access latencies of the respective first target partitions are not greater than a time difference threshold; and determine that a priority of a first target partition with a lower access latency is higher than a priority of a second target partition with a higher access latency in response to determining that the plurality of first target partitions include the first target partition and the second target partition with the differences between the access latencies being greater than the time difference threshold; and a scheduling unit configured to schedule the service request to the plurality of first target partitions based on the priorities of each of the plurality of first target partitions to enable processing devices included in the plurality of first target partitions to process the service request, the scheduling unit being further configured to: distribute traffic of the service request evenly to the plurality of first target partitions in response to the priorities of the plurality of first target partitions being the same; and schedule the service request to a first target partition with a higher priority as a primary load zone and a first target partition with a lower priority as a backup zone in response to the priorities of the plurality of first target partitions being different to prioritize scheduling the service request to the primary load zone when the primary load zone does not fail.

7. The apparatus of claim 6, wherein, each of the plurality of first service partitions includes a plurality of second service partitions, the apparatus further comprising: a third determining unit configured to determine, for each of the plurality of first target partitions, availability of the plurality of second service partitions in the first target partition; a fourth determining unit configured to determine, based on the availability of the plurality of second service partitions, at least one second target partition from the plurality of second service partitions; and a first processing unit configured to process the service request using the at least one second target partition.

8. The apparatus of claim 7, wherein, each of the plurality of second service partitions includes a plurality of gateways, the apparatus further comprising: a second processing unit configured to manage each of the plurality of second service partitions using the plurality of gateways included in the second service partition to enable the service request to access processing devices included in the second service partition through the plurality of gateways, the second processing unit being further configured to manage the second service partition using other gateways included in the second service partition to which a target gateway belongs in response to determining that the target gateway fails.

9. The apparatus of any of claims 6-8, further comprising: a monitoring unit configured to monitor availability of the plurality of first target partitions; an updating unit configured to update the plurality of first target partitions in response to determining that the availability of the plurality of first target partitions changes, The scheduling unit is further configured to schedule the service request to the updated plurality of first target partitions.

10. The apparatus of any one of claims 6-8, wherein, The service request comprises a request for a flexible public network address. 11.An electronic device comprising: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

12. A non-transitory computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions are for causing a computer to perform the method of any one of claims 1-5.

13. A computer program product comprising a computer program, wherein, The computer program, when executed by a processor, implements the method of any one of claims 1-5.

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