CN114401382A - Machine scheduling method and device and electronic equipment - Google Patents
Machine scheduling method and device and electronic equipment Download PDFInfo
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- CN114401382A CN114401382A CN202111555207.1A CN202111555207A CN114401382A CN 114401382 A CN114401382 A CN 114401382A CN 202111555207 A CN202111555207 A CN 202111555207A CN 114401382 A CN114401382 A CN 114401382A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/14—Systems for two-way working
- H04N7/141—Systems for two-way working between two video terminals, e.g. videophone
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
- G06F16/9024—Graphs; Linked lists
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/10—Active monitoring, e.g. heartbeat, ping or trace-route
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
Abstract
The disclosure relates to a machine scheduling method, a machine scheduling device and electronic equipment, and belongs to the technical field of computers. Wherein, the method comprises the following steps: obtaining a machine scheduling request, wherein the machine scheduling request comprises a source machine and a target machine; acquiring a shortest path between a source machine and a target machine according to the stored graph data; determining an optimal path between a source machine and a target machine according to the process load of an intermediate machine in the shortest path; and scheduling the intermediate machine corresponding to the optimal path and the process of the intermediate machine to the source machine. According to the machine scheduling method, the shortest path between the source machine and the target machine is obtained based on the graph data, the optimal path is determined based on the process load of the intermediate machine in the shortest path, the machine and the process to be scheduled are determined according to the optimal path, the shortest path algorithm based on the graph data is adopted, accurate scheduling of the machine is achieved, timeliness and stability of audio and video call response are guaranteed, and user experience is improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for scheduling a machine, and an electronic device.
Background
The global user audio and video interconnection system needs to ensure that users in various regions around the world can be quickly accessed to carry out audio and video conversation. The more accurate the dispatching system of the core system-media node of the interconnection system is to machine dispatching, the more timely and stable the response of audio and video calls can be ensured, and the product use experience of users is improved.
However, the related technical scheme is not accurate enough in machine scheduling, cannot guarantee timeliness and stability of audio and video call response, and reduces user experience.
Disclosure of Invention
The disclosure provides a machine scheduling method, a machine scheduling device and electronic equipment, and aims to at least solve the problems that scheduling of a machine in the related art is not accurate enough, timeliness and stability of audio and video call response cannot be guaranteed, and user experience is reduced. The technical scheme of the disclosure is as follows:
according to a first aspect of the embodiments of the present disclosure, a machine scheduling method is provided, including: obtaining a machine scheduling request, wherein the machine scheduling request comprises a source machine and a target machine; acquiring a shortest path between the source machine and the target machine according to pre-stored graph data; determining an optimal path between the source machine and the target machine according to the process load of the intermediate machine in the shortest path; and scheduling the intermediate machine corresponding to the optimal path and the process of the intermediate machine to the source machine.
In one embodiment of the present disclosure, the machine scheduling method further includes: acquiring link data among a plurality of machines; and generating the graph data according to the link data among the plurality of machines, wherein the nodes in the graph data are the machines, and the edges in the graph data are the link quality data generated according to the link data.
In one embodiment of the present disclosure, the obtaining the shortest path between the source machine and the target machine according to the pre-stored graph data includes: querying the shortest path between the source machine and the target machine in a pre-stored full-source shortest path, the full-source shortest path being generated according to the graph data by using a full-source shortest path algorithm
In one embodiment of the present disclosure, the machine scheduling method further includes: and if the shortest path between the source machine and the target machine cannot be inquired in the full source shortest path, acquiring the shortest path between the source machine and the target machine by adopting a single source shortest path algorithm according to the graph data.
In one embodiment of the present disclosure, the obtaining the shortest path between the source machine and the target machine according to the pre-stored graph data includes: and if the pre-stored configuration information does not include the configuration path between the source machine and the target machine, acquiring the shortest path between the source machine and the target machine according to the graph data.
In one embodiment of the present disclosure, the machine scheduling method further includes: and if the pre-stored configuration information comprises a configuration path between the source machine and the target machine, determining the configuration path as the shortest path between the source machine and the target machine.
According to a second aspect of the embodiments of the present disclosure, there is provided a machine scheduling apparatus, including: the system comprises a first obtaining module, a second obtaining module and a third obtaining module, wherein the first obtaining module is used for obtaining a machine scheduling request which comprises a source machine and a target machine; the second acquisition module is used for acquiring the shortest path between the source machine and the target machine according to prestored graph data; a determining module, configured to determine an optimal path between the source machine and the target machine according to a process load of an intermediate machine in the shortest path; and the scheduling module is used for scheduling the intermediate machine corresponding to the optimal path and the process of the intermediate machine to the source machine.
In one embodiment of the present disclosure, the machine scheduling apparatus further includes: the third acquisition module is used for acquiring link data among a plurality of machines; a generating module, configured to generate the graph data according to link data between the multiple machines, where a node in the graph data is the machine, and an edge in the graph data is link quality data generated according to the link data.
In an embodiment of the disclosure, the second obtaining module is specifically configured to: and inquiring the shortest path between the source machine and the target machine in a pre-stored full-source shortest path, wherein the full-source shortest path is generated by adopting a full-source shortest path algorithm according to the graph data.
In an embodiment of the disclosure, the second obtaining module is further configured to: and if the shortest path between the source machine and the target machine cannot be inquired in the full source shortest path, acquiring the shortest path between the source machine and the target machine by adopting a single source shortest path algorithm according to the graph data.
In an embodiment of the disclosure, the second obtaining module is specifically configured to: and if the pre-stored configuration information does not include the configuration path between the source machine and the target machine, acquiring the shortest path between the source machine and the target machine according to the graph data.
In an embodiment of the disclosure, the second obtaining module is further configured to: and if the pre-stored configuration information comprises a configuration path between the source machine and the target machine, determining the configuration path as the shortest path between the source machine and the target machine.
According to a third aspect of embodiments of the present disclosure, there is provided an electronic device comprising a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement the machine scheduling method as previously described.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium, wherein instructions, when executed by a processor of an electronic device, enable the electronic device to perform the machine scheduling method as described above.
According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the machine scheduling method as described above.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects: the method comprises the steps of obtaining the shortest path between a source machine and a target machine based on graph data, determining the optimal path based on the process load of an intermediate machine in the shortest path, determining the machine and the process to be scheduled according to the optimal path, and realizing accurate scheduling of the machine by adopting a shortest path algorithm based on the graph data, so that the timeliness and the stability of audio and video call response are ensured, and the user experience is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure and are not to be construed as limiting the disclosure.
FIG. 1 is a flow diagram illustrating a method of scheduling a machine in accordance with an exemplary embodiment.
FIG. 2 is a flow chart illustrating a method of machine scheduling in accordance with another exemplary embodiment.
FIG. 3 is a flow chart illustrating a method of machine scheduling in accordance with another exemplary embodiment.
FIG. 4 is a flow chart illustrating a method of machine scheduling in accordance with another exemplary embodiment.
FIG. 5 is a block diagram illustrating a machine scheduler in accordance with an exemplary embodiment.
FIG. 6 is a block diagram of an electronic device shown in accordance with an example embodiment.
Detailed Description
In order to make the technical solutions of the present disclosure better understood by those of ordinary skill in the art, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Fig. 1 is a flowchart illustrating a machine scheduling method according to an exemplary embodiment, where as shown in fig. 1, the machine scheduling method may specifically include the following steps:
s101, a machine scheduling request is obtained, wherein the machine scheduling request comprises a source machine and a target machine.
It should be noted that the machine scheduling method according to the embodiment of the present disclosure may be executed by the machine scheduling apparatus according to the embodiment of the present disclosure, and the machine scheduling apparatus according to the embodiment of the present disclosure may be configured in any electronic device to execute the machine scheduling method according to the embodiment of the present disclosure. The electronic device may be provided in a media scheduling system or the like.
In this embodiment, in the global user audio/video interconnection system, when a user a initiates an audio/video request to a user B, a machine in which the user a is located is a source machine, a machine in which the user B is located is a target machine, the source machine sends a machine scheduling request, and the machine scheduling device identifies the source machine and the target machine in the machine scheduling request. Those skilled in the art will appreciate that the source machine and the target machine in the machine scheduling request may be uniquely represented by an identification of the machine, such as the name of the machine, routing address, etc.
S102, obtaining the shortest path between the source machine and the target machine according to the pre-stored graph data.
In this embodiment, link data between multiple machines in a cluster may be obtained in advance, graph data is generated according to the link data between the multiple machines, nodes in the graph data are the machines, and edges in the graph data are link quality data generated according to the link data. The link data may specifically be ping data or the like.
ping is a computer network tool used to test whether a data packet can reach a specific host through Internet Protocol (IP), and the operation principle of ping is to transmit a request echo data packet of Internet Control Message Protocol (ICMP) to a target host and wait for receiving the echo data packet. The program estimates the packet loss rate (packet loss rate for short) and the Round-trip time (network delay, Round-trip delay time) of the packet according to the time and the number of successful responses, and the packet loss rate and the network delay are ping data.
Two vertexes corresponding to the source machine and the target machine are found in the graph data, and the shortest path between the two vertexes is determined based on the link quality data in the graph data and a shortest path algorithm, such as source machine-intermediate machine 1-intermediate machine 2-target machine.
S103, determining the optimal path between the source machine and the target machine according to the process load of the intermediate machine in the shortest path.
In this embodiment, the intermediate machine is a machine other than the source machine and the destination machine at both ends in the shortest path. Because the load conditions of different processes of each intermediate machine in the shortest path are different, for each intermediate machine, a process with less load can be selected as a target process to obtain an optimal path, and the optimal path comprises all machines (including a source machine, a target machine and all intermediate machines) in the shortest path and target processes of all intermediate machines.
And S104, scheduling the intermediate machine corresponding to the optimal path and the process of the intermediate machine to the source machine.
In this embodiment, the intermediate machine and the process of the intermediate machine corresponding to the optimal path determined in step S103 are scheduled to the source machine, so that the source machine performs routing forwarding based on the intermediate machine and the process of the intermediate machine corresponding to the optimal path, thereby implementing audio and video communication between the user a and the user B.
According to the machine scheduling method provided by the embodiment of the disclosure, the shortest path between the source machine and the target machine is obtained based on the graph data, the optimal path is determined based on the process load of the intermediate machine in the shortest path, the machine and the process to be scheduled are determined according to the optimal path, and the shortest path algorithm based on the graph data is adopted, so that the machine is accurately scheduled, the timeliness and the stability of audio and video call response are ensured, and the user experience is improved.
On the basis of the foregoing embodiment, as shown in fig. 2, the step S102 "obtaining the shortest path between the source machine and the destination machine according to the pre-stored graph data" may specifically include the following steps:
s201, inquiring the shortest path between the source machine and the target machine in the pre-stored all-source shortest paths.
In this embodiment, a full-source shortest path algorithm, for example, Floyd-Warshall algorithm, may be adopted to generate a full-source shortest path in advance according to the graph data, where the full-source shortest path refers to a shortest path from all vertices to vertices in the graph data. And inquiring the shortest path between two vertexes corresponding to the source machine and the target machine in the full source shortest path, namely the shortest path between the source machine and the target machine.
S202, the shortest path between the source machine and the target machine is not searched in the full source shortest paths, and then the shortest path between the source machine and the target machine is obtained by adopting a single source shortest path algorithm according to the graph data.
In this embodiment, the shortest path between two vertices corresponding to the source machine and the destination machine is not found in the full-source shortest path, and then the shortest path between the source machine and the destination machine is obtained by using a single-source shortest path algorithm, such as Dijkstra algorithm, according to the graph data.
Therefore, the shortest path between the source machine and the target machine is inquired in the prestored all-source shortest path, the shortest path calculation is not needed, only the calculated shortest path is inquired, and the shortest path acquisition efficiency is improved. If the shortest path cannot be searched in the pre-stored full-source shortest paths, a single-source shortest path algorithm is adopted to obtain the shortest path, and the shortest path can be successfully obtained.
On the basis of any of the above embodiments, as shown in fig. 3, the step S102 "obtaining the shortest path between the source machine and the destination machine according to the pre-stored graph data" may specifically include the following steps:
s301, if the pre-stored configuration information does not include the configuration path between the source machine and the target machine, the shortest path between the source machine and the target machine is obtained according to the graph data.
In this embodiment, pre-stored configuration information for machine scheduling is obtained, and whether a configuration path between a source machine and a target machine is pre-configured is searched for in the configuration information. And if the configuration path between the source machine and the target machine is not included in the pre-stored configuration information, acquiring the shortest path between the source machine and the target machine according to the graph data.
Further, the machine scheduling of the embodiment of the present disclosure may further include: and if the configuration path between the source machine and the target machine is included in the pre-stored configuration information, determining the configuration path as the shortest path between the source machine and the target machine.
Thus, the shortest path between the source machine and the target machine is searched in the configuration information stored in advance, and the scheduling of the specified path can be realized. If the shortest path is not found in the pre-stored configuration information, the shortest path is obtained according to the graph data, and the shortest path can be successfully obtained.
For clarity of explaining the machine scheduling method according to the embodiment of the present disclosure, a detailed process of the machine scheduling method according to the embodiment of the present disclosure is described below with reference to fig. 4. As shown in fig. 4, the method for scheduling a device according to the embodiment of the present disclosure specifically includes:
s401, link data among a plurality of machines is acquired.
S402, generating graph data according to the link data among the machines.
S403, obtaining a machine scheduling request, wherein the machine scheduling request comprises a source machine and a target machine.
S404, querying a configuration path between the source machine and the target machine in the pre-stored configuration information. If yes, go to step S405. If the query is not received, step S406 or S407 is executed.
S405, determining the configuration path as the shortest path between the source machine and the target machine. Step S408 is performed.
S406, the shortest path between the source machine and the target machine is inquired from all the prestored source shortest paths. Step S408 is performed.
S407, if the shortest path between the source machine and the target machine cannot be inquired in the full source shortest paths, the shortest path between the source machine and the target machine is acquired by adopting a single source shortest path algorithm according to the graph data. Step S408 is performed.
S408, determining the optimal path between the source machine and the target machine according to the process load of the intermediate machine in the shortest path.
And S409, scheduling the intermediate machine corresponding to the optimal path and the process of the intermediate machine to the source machine.
FIG. 5 is a block diagram illustrating a machine scheduler in accordance with an exemplary embodiment. Referring to fig. 5, the apparatus includes a first obtaining module 51, a second obtaining module 52, a determining module 53 and a scheduling module 54.
The first obtaining module 51 is configured to obtain a machine scheduling request, where the machine scheduling request includes a source machine and a target machine.
The second acquisition module 52 is configured to acquire a shortest path between the source machine and the destination machine according to pre-stored graph data.
The determination module 53 is configured to determine an optimal path between the source machine and the target machine based on the process load of the intermediate machine in the shortest path.
The scheduling module 54 is configured to schedule the intermediate machine and the process of the intermediate machine corresponding to the optimal path to the source machine.
In one embodiment of the present disclosure, the machine scheduling apparatus further includes: the third acquisition module is used for acquiring link data among a plurality of machines; the generating module is used for generating graph data according to link data among a plurality of machines, nodes in the graph data are the machines, and edges in the graph data are the link quality data generated according to the link data.
In an embodiment of the present disclosure, the second obtaining module 52 is specifically configured to: and inquiring the shortest path between the source machine and the target machine in the prestored all-source shortest paths, wherein the all-source shortest paths are generated by adopting an all-source shortest path algorithm according to the graph data.
In one embodiment of the present disclosure, the second obtaining module 52 is further configured to: and if the shortest path between the source machine and the target machine cannot be inquired in the full source shortest path, acquiring the shortest path between the source machine and the target machine by adopting a single source shortest path algorithm according to the graph data.
In an embodiment of the present disclosure, the second obtaining module 52 is specifically configured to: if the configuration information stored in advance does not include the configuration path between the source machine and the target machine, the shortest path between the source machine and the target machine is acquired according to the graph data.
In one embodiment of the present disclosure, the second obtaining module 52 is further configured to: and if the pre-stored configuration information comprises a configuration path between the source machine and the target machine, determining the configuration path as the shortest path between the source machine and the target machine.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
The machine scheduling device of the embodiment of the disclosure acquires the shortest path between the source machine and the target machine based on the graph data, determines the optimal path based on the process load of the intermediate machine in the shortest path, determines the machine and the process to be scheduled according to the optimal path, and adopts the shortest path algorithm based on the graph data, thereby realizing accurate scheduling of the machine, ensuring the timeliness and stability of audio and video call response, and improving the user experience.
Fig. 6 is a block diagram illustrating an electronic device 600 for machine scheduling according to an example embodiment, and referring to fig. 6, the electronic device 600 includes:
a memory 610 and a processor 620, a bus 630 connecting different components (including the memory 610 and the processor 620), wherein the memory 610 stores computer programs, and the machine scheduling method of the embodiment of the disclosure is realized when the processor 620 executes the programs.
A program/utility 680 having a set (at least one) of program modules 670 may be stored, for example, in memory 610, such program modules 670 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. The program modules 670 generally perform the functions and/or methods of the embodiments described in this disclosure.
The electronic device 600 may also communicate with one or more external devices 690 (e.g., keyboard, pointing device, display 691, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., network card, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may be through input/output (I/O) interfaces 692. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 693. As shown in FIG. 6, the network adapter 693 communicates with the other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in FIG. 6, other hardware and/or software modules may be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processor 620 executes various functional applications and data processing by executing programs stored in the memory 610.
It should be noted that, for the implementation process and the technical principle of the electronic device of the embodiment, reference is made to the foregoing explanation of the machine scheduling method of the embodiment of the present disclosure, and details are not described here again.
The electronic equipment provided by the embodiment of the disclosure can execute the machine scheduling method, the shortest path between the source machine and the target machine is obtained based on the graph data, the optimal path is determined based on the process load of the intermediate machine in the shortest path, the machine and the process to be scheduled are determined according to the optimal path, and the shortest path algorithm based on the graph data is adopted, so that the accurate scheduling of the machine is realized, the timeliness and the stability of the audio and video call response are ensured, and the user experience is improved.
To implement the above embodiments, the present disclosure also proposes a computer-readable storage medium comprising instructions, such as the memory 610 comprising instructions, executable by the processor 620 of the electronic device 600 to perform the above method. Alternatively, the computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
To implement the above embodiments, the present disclosure also proposes a computer program product comprising a computer program, which when executed by the processor 620 of the electronic device 600 implements the above method.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A method for scheduling a machine, comprising:
obtaining a machine scheduling request, wherein the machine scheduling request comprises a source machine and a target machine;
acquiring a shortest path between the source machine and the target machine according to pre-stored graph data;
determining an optimal path between the source machine and the target machine according to the process load of the intermediate machine in the shortest path;
and scheduling the intermediate machine corresponding to the optimal path and the process of the intermediate machine to the source machine.
2. The machine scheduling method of claim 1, further comprising:
acquiring link data among a plurality of machines;
and generating the graph data according to the link data among the plurality of machines, wherein the nodes in the graph data are the machines, and the edges in the graph data are the link quality data generated according to the link data.
3. The machine scheduling method of claim 1, wherein said obtaining the shortest path between the source machine and the target machine according to the pre-stored graph data comprises:
and inquiring the shortest path between the source machine and the target machine in a pre-stored full-source shortest path, wherein the full-source shortest path is generated by adopting a full-source shortest path algorithm according to the graph data.
4. The machine scheduling method of claim 3 wherein said obtaining the shortest path between the source machine and the target machine from pre-stored graph data further comprises:
and if the shortest path between the source machine and the target machine cannot be inquired in the full source shortest path, acquiring the shortest path between the source machine and the target machine by adopting a single source shortest path algorithm according to the graph data.
5. The machine scheduling method of claim 1, wherein said obtaining the shortest path between the source machine and the target machine according to the pre-stored graph data comprises:
and if the pre-stored configuration information does not include the configuration path between the source machine and the target machine, acquiring the shortest path between the source machine and the target machine according to the graph data.
6. The machine scheduling method of claim 5, further comprising:
and if the pre-stored configuration information comprises a configuration path between the source machine and the target machine, determining the configuration path as the shortest path between the source machine and the target machine.
7. A machine scheduling apparatus, comprising:
the system comprises a first obtaining module, a second obtaining module and a third obtaining module, wherein the first obtaining module is used for obtaining a machine scheduling request which comprises a source machine and a target machine;
the second acquisition module is used for acquiring the shortest path between the source machine and the target machine according to prestored graph data;
a determining module, configured to determine an optimal path between the source machine and the target machine according to a process load of an intermediate machine in the shortest path;
and the scheduling module is used for scheduling the intermediate machine corresponding to the optimal path and the process of the intermediate machine to the source machine.
8. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the machine scheduling method of any of claims 1-6.
9. A computer-readable storage medium whose instructions, when executed by a processor of an electronic device, enable the electronic device to perform the machine scheduling method of any of claims 1-6.
10. A computer program product comprising a computer program, wherein the computer program, when executed by a processor, implements the machine scheduling method of any one of claims 1-6.
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| CN115578694A (en) * | 2022-11-18 | 2023-01-06 | 合肥英特灵达信息技术有限公司 | Video analysis computing power scheduling method, system, electronic equipment and storage medium |
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| CN115578694A (en) * | 2022-11-18 | 2023-01-06 | 合肥英特灵达信息技术有限公司 | Video analysis computing power scheduling method, system, electronic equipment and storage medium |
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