CN112968966B - Scheduling method, scheduling device, electronic equipment and storage medium - Google Patents

Scheduling method, scheduling device, electronic equipment and storage medium Download PDF

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CN112968966B
CN112968966B CN202110219367.2A CN202110219367A CN112968966B CN 112968966 B CN112968966 B CN 112968966B CN 202110219367 A CN202110219367 A CN 202110219367A CN 112968966 B CN112968966 B CN 112968966B
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scheduling
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weight
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CN112968966A (en
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刘成乾
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Beijing Baidu Netcom Science and Technology Co Ltd
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Beijing Baidu Netcom Science and Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • G06F9/45533—Hypervisors; Virtual machine monitors
    • G06F9/45558—Hypervisor-specific management and integration aspects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L61/00—Network arrangements, protocols or services for addressing or naming
    • H04L61/45—Network directories; Name-to-address mapping
    • H04L61/4505—Network directories; Name-to-address mapping using standardised directories; using standardised directory access protocols
    • H04L61/4511—Network directories; Name-to-address mapping using standardised directories; using standardised directory access protocols using domain name system [DNS]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L61/00—Network arrangements, protocols or services for addressing or naming
    • H04L61/50—Address allocation
    • H04L61/5007—Internet protocol [IP] addresses
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
    • H04L67/61—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources taking into account QoS or priority requirements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
    • H04L69/22—Parsing or analysis of headers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • G06F9/45533—Hypervisors; Virtual machine monitors
    • G06F9/45558—Hypervisor-specific management and integration aspects
    • G06F2009/45595—Network integration; Enabling network access in virtual machine instances
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

The disclosure provides a scheduling method, a scheduling device, electronic equipment and a storage medium, and relates to the technical fields of cloud computing such as cloud network technology and private cloud. The specific implementation scheme is as follows: acquiring a weight value, wherein the weight value is used for representing address scheduling priority information; receiving request messages sent by a plurality of Virtual Machines (VM) deployed in a Virtual Private Cloud (VPC); according to the duty ratio of the weight value in the weight sum, scheduling the message analysis of the plurality of VMs, and selecting a target VM from the plurality of VMs; analyzing the request message sent by the target VM, and feeding back analysis records in a targeted mode to the target VM. By adopting the method and the device, intelligent scheduling and targeted feedback of request message analysis can be realized.

Description

Scheduling method, scheduling device, electronic equipment and storage medium
Technical Field
The disclosure relates to the technical field of cloud computing, and in particular relates to the technical fields of cloud network technology, private cloud and the like.
Background
In network communication, since the IP address is a series of numbers, it is not easy for the user to record, and a domain name can be used to log in to a website to realize network communication. The domain name is the identification of a computer or a group of computers on the internet, which is formed by a series of names separated by 'dots', and can be converted into an IP address of a server through a domain name service system (DNS, domain Name System), so that people can access the service on the internet more simply and conveniently, and the addressing and network communication can be performed through the IP address.
DNS can also resolve a request message sent by a Virtual Machine (VM) deployed in a Virtual private cloud (VPC, virtual Private Cloud), however, intelligent scheduling for the resolution of the request message cannot be achieved currently.
Disclosure of Invention
The disclosure provides a scheduling method, a scheduling device, electronic equipment and a storage medium.
According to an aspect of the present disclosure, there is provided a scheduling method, including:
acquiring a weight value, wherein the weight value is used for representing address scheduling priority information;
receiving request messages sent by a plurality of Virtual Machines (VM) deployed in a Virtual Private Cloud (VPC);
according to the duty ratio of the weight value in the weight sum, scheduling the message analysis of the plurality of VMs, and selecting a target VM from the plurality of VMs;
analyzing the request message sent by the target VM, and feeding back analysis records in a targeted mode to the target VM.
According to another aspect of the present disclosure, there is provided a scheduling apparatus including:
the acquisition module is used for acquiring a weight value, wherein the weight value is used for representing address scheduling priority information;
the receiving module is used for receiving request messages sent by a plurality of virtual machines VM deployed in the virtual private cloud VPC;
the scheduling module is used for scheduling the message analysis of the plurality of VMs according to the duty ratio of the weight value in the weight sum, and selecting a target VM from the plurality of VMs;
and the feedback module is used for analyzing the request message sent by the target VM and carrying out targeted feedback analysis and recording on the target VM.
According to another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the methods provided by any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the method provided by any one of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a computer program product comprising computer instructions which, when executed by a processor, implement the method provided by any one of the embodiments of the present disclosure.
By adopting the method and the device, the weight value can be acquired, and the weight value is used for representing the address scheduling priority information; receiving request messages sent by a plurality of VMs deployed in a VPC; according to the duty ratio of the weight value in the weight sum, scheduling the message analysis of the plurality of VMs, and selecting a target VM from the plurality of VMs; analyzing the request message sent by the target VM, and carrying out targeted feedback analysis and recording on the request message to the target VM, so that intelligent scheduling and targeted feedback of the request message analysis can be realized.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a flow diagram of a scheduling method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a system framework to which a scheduling method of an embodiment of the present disclosure is applied;
FIG. 3 is a system framework diagram of a scheduling method to which embodiments of the present disclosure are applied;
FIG. 4 is a flowchart of an application example applying a scheduling method of an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of the composition and structure of a scheduling apparatus according to an embodiment of the present disclosure;
fig. 6 is a block diagram of an electronic device for implementing a scheduling method of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: a exists alone, A and B exist together, and B exists alone. The term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, e.g., including at least one of A, B, C, may mean including any one or more elements selected from the group consisting of A, B and C. The terms "first" and "second" herein mean a plurality of similar technical terms and distinguishes them, and does not limit the meaning of the order, or only two, for example, a first feature and a second feature, which means that there are two types/classes of features, the first feature may be one or more, and the second feature may be one or more.
In addition, numerous specific details are set forth in the following detailed description in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements, and circuits well known to those skilled in the art have not been described in detail in order not to obscure the present disclosure.
According to an embodiment of the present disclosure, a scheduling method is provided, and fig. 1 is a schematic flow chart of a scheduling method according to an embodiment of the present disclosure, where the method may be applied to a scheduling apparatus, for example, where the apparatus may be deployed in a server or other processing device for execution, where configuration of a domain name resolution rule may be performed, scheduling for requesting targeted resolution of a message, and so on. In some possible implementations, the method may also be implemented by way of a processor invoking computer readable instructions stored in a memory. As shown in fig. 1, includes:
s101, acquiring a weight value, wherein the weight value is used for representing address scheduling priority information.
S102, receiving request messages sent by a plurality of VMs deployed in the VPC.
S103, scheduling the message analysis is carried out on the VMs according to the ratio of the weight value in the weight sum, and a target VM is selected from the VMs.
S104, analyzing the request message sent by the target VM, and carrying out targeted feedback analysis and recording on the target VM.
In one example of S101-S104, the processing logic of S101-S103 is implemented in a DNS server, namely: configuring a weight value in the DNS server, wherein the weight value is one of configuration information allowing message domain name resolution, and can be used for representing address scheduling priority information; after receiving DNS request messages sent by a plurality of VMs deployed in a VPC, the DNS server performs message analysis scheduling on the plurality of VMs according to the duty ratio of the weight value in the weight sum, selects a target VM from the plurality of VMs, analyzes the DNS request messages sent by the target VM, and feeds back analysis records to the target VM in a targeted manner.
By adopting the method and the device, the weight value can be acquired, and the weight value is used for representing the address scheduling priority information; receiving request messages sent by a plurality of VMs deployed in a VPC; according to the duty ratio of the weight value in the weight sum, scheduling the message analysis of the plurality of VMs, and selecting a target VM from the plurality of VMs; analyzing the request message sent by the target VM, and feeding back analysis records in a targeted mode to the target VM. Because the weight value (namely the address scheduling priority information expressed by the weight value) exists in the configuration of the DNS server, the source IP address in the DNS request and the ratio of the weight value configured by each address in advance to the total weight value (such as the ratio calculated by adopting a random algorithm) are scheduled for analysis processing, so that corresponding analysis records are fed back to the corresponding VM in a targeted mode, and therefore intelligent scheduling and targeted feedback of the request message analysis are realized.
The system architecture for network communication of the VPC with the DNS server is introduced as follows:
isolation of resources from each other can be achieved by VPC, i.e.: the isolation of resources such as a security group, a subnet and the like is realized among different VPCs, meanwhile, the isolation of DNS is also realized, and the DNS resolution domains configured in the VPCs do not have any influence on other VPCs. Because multiple resolution records can be configured in the DNS server, when the DNS server receives a DNS request message sent by a deployment VM in the VPC and performs DNS resolution on the DNS request message, all the hit resolution records are returned, and different priorities can be set for resolution of different VMs, where the resolution method does not distinguish between the VM corresponding to different address priorities, especially in an application scenario where the same VPC starts the same user service where multiple VMs are deployed, the scheduling method for resolution is inefficient and brings inconvenience to the user service, as shown in fig. 2, fig. 2 is a schematic diagram of a system frame of the scheduling method for applying the embodiment of the present disclosure, where 2 subnets (subnets 1 and 2) are deployed in the same VPC (e.g. VPC-1), where multiple VMs (e.g. VM1 and VM 2) can be deployed on one or more physical machines in subnets 1, and where one VM (e.g. VM 3) can be deployed on one physical machine in subnets 2. Since multiple VMs (e.g., VM1, VM2, and VM 3) are configured in the same VPC (e.g., VPC-1) and the same user service can be deployed on multiple VMs, the DNS server is configured to: binding with the VPC, for the user service, pre-configured: when the DNS server resolves the same-name and same-type a records of the same-name and different-resolution IP addresses (corresponding to respective addresses of the plurality of VMs) (e.g., mirrorxxx.com a), the DNS server does not distinguish between the VM corresponding to different address priorities when resolving the same-name and same-type a records for the plurality of VMs deployed in the VPC, so that VM1, VM2, and VM3 may obtain the same 3 resolution records, as shown in fig. 2, that is, in the VPC, scheduling of domain name intelligent resolution cannot be achieved.
In one embodiment, the weight value includes: and respectively subordinate address segment information or weight values correspondingly configured for the address information of the plurality of VMs. According to the embodiment, the importance degree of analysis scheduling of the VMs can be evaluated according to the weight value.
In an embodiment, the scheduling of the message parsing is performed on the multiple VMs according to the ratio of the weight value to the weight sum, and selecting a target VM from the multiple VMs includes: taking a random value for the duty ratio of the weight value in the weight sum; and carrying out the scheduling of the message analysis on the plurality of VMs according to the random value, and selecting a target VM from the plurality of VMs. By adopting the embodiment, the scheduling decision is carried out by adopting the random value with fairness, so that a plurality of VMs are more fairly treated and the load is more balanced.
In an embodiment, the scheduling of the message parsing for the multiple VMs according to the random value, selecting a target VM from the multiple VMs, includes: acquiring a target weight interval to which the random value corresponding to the target VM belongs; and determining the target VM under the condition that the target weight interval corresponds to the pre-configured weight interval. By adopting the embodiment, the random value is matched with the pre-configured weight interval so as to decide how to schedule the multiple VMs in a targeted manner, and the target VM can be selected from the multiple VMs.
In an embodiment, the analyzing the request message sent by the target VM and the targeted feedback analysis record to the target VM includes: selecting a target analysis record corresponding to the target VM from at least two preconfigured analysis records; and feeding back the target analysis record to the target VM. By adopting the embodiment, after the target VM is selected from the plurality of VMs, the target analysis record corresponding to the target VM can be selected from at least two preconfigured analysis records so as to feed back the target analysis record to the target VM, thereby respectively obtaining different analysis records corresponding to different target VMs from the plurality of VMs and realizing targeted feedback of the analysis records.
In an example, fig. 3 is a schematic system frame diagram of applying the scheduling method of the embodiment of the present disclosure, compared to the schematic system frame diagram in fig. 2, the scheduling method running in the system architecture shown in fig. 3 may distinguish between different VMs, especially in an application scenario where the same VPC initiates the same user service where multiple VMs are deployed, and the use of the resolved scheduling method greatly improves efficiency and may bring more convenience to the user service, as shown in fig. 3, 2 subnets (subnet 1 and subnet 2) are deployed in the same VPC (e.g. VPC-1), multiple VMs (e.g. VM1 and VM 2) may be deployed on one or multiple physical machines in subnet 1, and one VM (e.g. VM 3) may be deployed on one physical machine in subnet 2. Since multiple VMs (e.g., VM1, VM2, and VM 3) are configured in the same VPC (e.g., VPC-1) and the same user service can be deployed on multiple VMs, the DNS server is configured to: binding with the VPC, for the user service, pre-configured: when the DNS server resolves the same-name and same-type a records (such as a minor. Xxx. Com a) of the same-name and different-resolution IP addresses (corresponding to the respective addresses of the plurality of VMs), the DNS server may distinguish between the plurality of VMs deployed in the VPC, so that by adopting the embodiment and implementation described above, by means of intelligent scheduling in which VM1, VM2 and VM3 may resolve by domain name, after selecting a VM from the plurality of VMs according to the address priority indicated by the weight value, different resolution records corresponding to different VMs are respectively obtained. Among the analysis records "mirror. XXX.com A192.168.1.12weight (5)", "mirror. XXX.com A192.168.1.13 weight (3)", "mirror. XXX.com A192.168.1.14 weight (2)", the "weight (5), weight (3), weight (2)" are weight values respectively configured for VM1, VM2, VM3, thereby realizing the address scheduling priority information expressed in weight values. The three records are combined into one record, the total weight is 10, the random value is taken according to the duty ratio of different weight values in the total weight, and the random value is seen to fall into the weight interval, so that a decision is made as to how to pertinently schedule a plurality of VMs (VM 1, VM2 and VM 3), and accordingly, the analysis record is pertinently fed back to the matched VM, ACL attributes (namely address related information represented by the ACL) can be set in the analysis record, for example, the ACL attributes are configured by adopting different division granularities such as AZ granularity, subnet granularity, VM and the like. For example, through the AZ-A, the AZ-B can distinguish the machine rooms to which different VMs belong respectively, so that the problem of analysis across the machine rooms can be avoided. By adopting the method, the system and the device, the random value can be taken according to the duty ratio of different weight values in the weight sum, so as to decide how to schedule a plurality of VMs in a targeted manner, and after VM is selected from the plurality of VMs, different analysis records corresponding to different VMs are respectively obtained. The address related information represented by the ACL can be set at will by adopting different division granularities according to the matching precision requirement, so that the intelligent scheduling of AZ granularity analysis, the intelligent scheduling of subnet granularity analysis and the intelligent scheduling of analysis according to the granularity of VM (or IP corresponding to VM) are respectively realized according to different granularities.
In one embodiment, the method further comprises: and pre-configuring the address scheduling priority information expressed by the weight value according to at least one parameter of storage capacity, running energy consumption, resource configuration and supporting network bandwidth corresponding to the plurality of VMs. Taking storage capacity as an example, in the process of randomly configuring a weight value according to requirements, a user needs to want to walk a large-flow task, then a VM with large storage capacity can be configured, the large-flow task is walked, the VM is ranked in a first priority, and a large weight, for example, the weight value is configured to be 5; the next allocation weight value 3, the next allocation weight value 2 and the like, and the calculation of the random value not only considers the scheduling priority of each VM, but also considers the fairness and the load balance of the resource proportion of each VM.
Application example:
the first processing flow of the embodiment of the application disclosure comprises the following contents:
fig. 4 is a flowchart of an application example to which the scheduling method of the embodiment of the present disclosure is applied, including: analyzing the DNS request message, and extracting a source IP address from the DNS request message; searching a DNS record to obtain an analysis record corresponding to the DNS request message; taking weight values corresponding to all analysis records, and obtaining a weight sum according to the weight values; taking a random value smaller than the sum of the weights; taking a weight interval in which the random value is located, so as to analyze scheduling decisions of a plurality of VMs; and returning the analysis record to the corresponding VM.
In an example shown in connection with fig. 3, the configuration VPC intra-subnetwork has AZ properties and the same subnetwork may not span AZ, i.e. AZ may be mapped into segments of the subnetwork. When creating the DNS record, the address scheduling priority information corresponding to the IP address or address segment of the record can be configured at the same time, and the address scheduling priority information is represented by a weight value, so that after the DNS server receives the request message to be resolved sent by the multiple VMs, the source IP address of the request message is extracted, the record to be resolved of the resolved message is searched, and after the VM is selected from the multiple VMs according to the address priority represented by the weight value, different resolved records corresponding to the different VMs are respectively obtained. Among the analysis records "mirror. XXX.com A192.168.1.12weight (5)", "mirror. XXX.com A192.168.1.13 weight (3)", "mirror. XXX.com A192.168.1.14 weight (2)", the "weight (5), weight (3), weight (2)" are weight values respectively configured for VM1, VM2, VM3, thereby realizing the address scheduling priority information expressed in weight values. In the process of scheduling for analysis, as shown in fig. 3, three records may be combined into one record, and the sum of the weights of the three records is 5+3+2=10, and a random value below 10 is taken from the sum of the weights each time, so as to determine how to schedule multiple VMs (VM 1, VM2, VM 3) in a targeted manner, and in which weight interval the random value falls, the corresponding record is returned to the corresponding VM, so that the analysis record is fed back to the corresponding VM in a targeted manner.
For the weight interval, the random value is in the [0,5] interval, and the analysis record corresponding to 192.168.1.12 is returned to the corresponding VM; the random value is in the [5,8] interval, and the corresponding analysis record of 192.168.1.13 is returned to the corresponding VM; the random value is in the interval of [8, 10], and the corresponding analysis record of 192.168.1.14 is returned to the corresponding VM. Instead of returning all three records as shown in fig. 2, i.e., different VMs return the same resolved record.
Typically, a VPC (commonly known as a big pool) is first created in the network, and the VPC is given an address field, e.g., 0/16; this address field then creates a subnet, and a segment, e.g., 2.0/24 (commonly known as a pool), is then split into the subnets before creating the VM. The analysis record in the DNS is bound with the VPC, and the VPC has a plurality of sub-network segments and attributes, such as an AZ attribute which is bound with the sub-network, and the like, can also be used for sub-network segmentation and the like; to determine which machine room a subnet belongs to, for example, subnet 1 corresponds to AZ-a in fig. 3; subnet 2 corresponds to AZ-B. The same service can be deployed in different machine rooms, namely: the subnet 1 corresponding to the AZ-A can restrict the DNS server to only analyze the services of the AZ-A and not analyze the AZ-B (if the AZ-B is analyzed at the same time, the machine room is crossed); the subnet 2 corresponding to the AZ-B can restrict the DNS server to only analyze the services of the AZ-B, so that the execution of the server across the machine room is avoided after the restriction.
Through the application example, besides the configuration weight value, ACL configuration can be further performed according to user requirements, the ACL is configured according to different granularities, even if the same service is deployed by different VMs, the scheduling can be performed according to the address scheduling priority, different analysis records can be obtained in a targeted manner, and finally, the efficiency of the whole VPC is greatly improved.
By adopting the method and the device, in the analysis scene aiming at a plurality of records of the same NAME, the weight value can be set for each record, when DNS analysis is carried out each time, the random value is taken from the total weight value, and the random value falls in which record interval, so that which record is returned, and intelligent scheduling is realized.
According to an embodiment of the present disclosure, there is provided a scheduling apparatus, and fig. 5 is a schematic diagram of a composition structure of the scheduling apparatus according to an embodiment of the present disclosure, and as shown in fig. 5, a scheduling apparatus 500 includes: an obtaining module 501, configured to obtain a weight value, where the weight value is used to characterize address scheduling priority information; a receiving module 502, configured to receive request messages sent by a plurality of VMs deployed in a VPC; a scheduling module 503, configured to perform scheduling of message analysis on the multiple VMs according to the ratio of the weight value in the weight sum, and select a target VM from the multiple VMs; the feedback module 504 is configured to parse the request message sent by the target VM, and perform targeted feedback parsing and recording on the target VM.
In one embodiment, the weight value includes: and respectively subordinate address segment information or weight values correspondingly configured for the address information of the plurality of VMs.
In one embodiment, the scheduling module includes: the duty ratio operation sub-module is used for taking a random value for the duty ratio of the weight value in the weight sum; and the scheduling sub-module is used for scheduling the message analysis on the plurality of VMs according to the random value, and selecting a target VM from the plurality of VMs.
In an embodiment, the scheduling sub-module is configured to: acquiring a target weight interval to which the random value corresponding to the target VM belongs; and determining the target VM under the condition that the target weight interval corresponds to the pre-configured weight interval.
In an embodiment, the feedback module is configured to select a target resolution record corresponding to the target VM from at least two resolution records that are preconfigured; and feeding back the target analysis record to the target VM.
In an embodiment, the system further includes a weight configuration module, configured to pre-configure the weight value according to at least one parameter of storage capacity, running energy consumption, resource configuration, and supporting network bandwidth corresponding to the multiple VMs.
The functions of each module in each apparatus of the embodiments of the present disclosure may be referred to the corresponding descriptions in the above methods, which are not repeated herein.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
Fig. 6 is a block diagram of an electronic device for implementing a scheduling method of an embodiment of the present disclosure. The electronic device may be the aforementioned deployment device or proxy device. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the electronic device 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 can also be stored. The computing unit 601, ROM602, and RAM 603 are connected to each other by a bus 604. An input output (I/O) interface 605 is also connected to bus 604.
A number of components in the electronic device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, mouse, etc.; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the electronic device 600 to exchange information/data with other devices through a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as scheduling methods. For example, in some embodiments, the scheduling method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 600 via the ROM602 and/or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the scheduling method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the scheduling method by any other suitable means (e.g. by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed aspects are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.

Claims (10)

1. A scheduling method, the method comprising:
acquiring address segment information or weight values correspondingly configured for address information respectively affiliated to a plurality of virtual machines VM in a virtual private cloud VPC, wherein the weight values are used for representing address scheduling priority information;
receiving request messages sent by a plurality of VMs deployed in the VPC;
scheduling the message analysis of the plurality of VMs according to the duty ratio of the weight value in the weight sum, and selecting a target VM from the plurality of VMs, wherein the weight sum is the sum of weight values configured by all VMs in the VPC;
analyzing the request message sent by the target VM, and feeding back analysis records to the target VM in a targeted manner;
and performing scheduling of message analysis on the multiple VMs according to the duty ratio of the weight value in the weight sum, and selecting a target VM from the multiple VMs, wherein the scheduling comprises the following steps:
taking a random value for the duty ratio of the weight value in the weight sum;
and carrying out the scheduling of the message analysis on the plurality of VMs according to the random value, and selecting the target VM from the plurality of VMs.
2. The method of claim 1, wherein the scheduling the message parsing of the plurality of VMs according to the random value, selecting the target VM from the plurality of VMs, comprises:
acquiring a target weight interval to which the random value corresponding to the target VM belongs;
and determining the target VM under the condition that the target weight interval corresponds to the pre-configured weight interval.
3. The method of claim 1, wherein the parsing the request message sent by the target VM and the targeted feedback parsing record to the target VM includes:
selecting a target analysis record corresponding to the target VM from at least two preconfigured analysis records;
and feeding back the target analysis record to the target VM.
4. A method according to any one of claims 1-3, further comprising:
and pre-configuring the weight value according to at least one parameter of storage capacity, running energy consumption, resource configuration and supporting network bandwidth corresponding to the plurality of VMs.
5. A scheduling apparatus, the apparatus comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring address segment information or weight values correspondingly configured for address information correspondingly affiliated to a plurality of virtual machines VM in a virtual private cloud VPC, and the weight values are used for representing address scheduling priority information;
the receiving module is used for receiving request messages sent by a plurality of VMs deployed in the VPC;
the scheduling module is used for scheduling the message analysis of the plurality of VMs according to the duty ratio of the weight value in the weight sum, and selecting a target VM from the plurality of VMs, wherein the weight sum is the sum of weight values configured by all VMs in the VPC;
the feedback module is used for analyzing the request message sent by the target VM and carrying out targeted feedback analysis and recording on the target VM;
wherein, the dispatch module includes:
the duty ratio operation sub-module is used for taking a random value for the duty ratio of the weight value in the weight sum;
and the scheduling sub-module is used for scheduling the message analysis on the plurality of VMs according to the random value, and selecting the target VM from the plurality of VMs.
6. The apparatus of claim 5, wherein the scheduling sub-module is configured to:
acquiring a target weight interval to which the random value corresponding to the target VM belongs;
and determining the target VM under the condition that the target weight interval corresponds to the pre-configured weight interval.
7. The apparatus of claim 5, wherein the feedback module is configured to:
selecting a target analysis record corresponding to the target VM from at least two preconfigured analysis records;
and feeding back the target analysis record to the target VM.
8. The apparatus of any of claims 5-7, further comprising a weight configuration module to:
and pre-configuring the weight value according to at least one parameter of storage capacity, running energy consumption, resource configuration and supporting network bandwidth corresponding to the plurality of VMs.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.
10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1-4.
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