CN115277598B - Method and device for scheduling computing power resources and computer readable storage medium - Google Patents
Method and device for scheduling computing power resources and computer readable storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
- H04L47/76—Admission control; Resource allocation using dynamic resource allocation, e.g. in-call renegotiation requested by the user or requested by the network in response to changing network conditions
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
- H04L47/76—Admission control; Resource allocation using dynamic resource allocation, e.g. in-call renegotiation requested by the user or requested by the network in response to changing network conditions
- H04L47/762—Admission control; Resource allocation using dynamic resource allocation, e.g. in-call renegotiation requested by the user or requested by the network in response to changing network conditions triggered by the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
- H04L47/78—Architectures of resource allocation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/70—Admission control; Resource allocation
- H04L47/78—Architectures of resource allocation
- H04L47/783—Distributed allocation of resources, e.g. bandwidth brokers
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- 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
Abstract
The invention provides a method and a device for scheduling computing power resources and a computer readable storage medium, wherein the method comprises the following steps: receiving a service request sent by a node of a force calculation demand party in a preset range; acquiring a corresponding service type and a geographic position of the power calculation demand side node according to the service request; judging whether available computing power resources exist in a preset range or not according to the service type, the geographic position and a pre-stored superface computing power registry to meet the service request; and if yes, selecting the target computing power providing equipment to perform computing power resource scheduling for the computing power demand side node. The method, the device and the computer readable storage medium can solve the problems that the existing computing power scheduling method using edge computing has hidden danger of data leakage by means of third-party computing power and part of computing tasks are limited by network bandwidth and time.
Description
Technical Field
The invention relates to a method and a device for scheduling computing power resources and a computer readable storage medium.
Background
The occurrence of edge calculation changes the relative independence of the traditional cloud and the network, so that the calculation enters the network, the efficiency and the reliability of the edge calculation are deeply coupled with the bandwidth, the time delay, the safety, the isolation and the like of the network, the integrated high-efficiency service of the calculation network is realized, and most of calculation power demands which cannot be met by a single node can be effectively supplemented. The existing computing power scheduling method using edge computing has the problems that data leakage hidden danger exists by means of third-party computing power, and part of computing tasks are limited by network bandwidth and time.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a computing power resource scheduling method, a computing power resource scheduling device and a computer readable storage medium aiming at the defects of the prior art, and the method, the device and the computer readable storage medium integrate the own computing power in an area on the premise of ensuring the normal operation of equipment in the area, so as to solve the problems that the existing computing power scheduling method using edge computing has hidden danger of data leakage by means of third party computing power and still has part of computing tasks limited by network bandwidth and time.
In a first aspect, the present invention provides a method for scheduling computing power resources, including:
receiving a service request sent by a node of a force calculation demand party in a preset range;
acquiring a corresponding service type and a geographic position of the power calculation demand side node according to the service request;
judging whether available computing power resources exist in a preset range or not according to the service type, the geographic position and a pre-stored superface computing power registry to meet the service request;
and if yes, selecting the target computing power providing equipment to perform computing power resource scheduling for the computing power demand side node.
Preferably, the super-edge computing power registry includes computing power values, computing power types, geographic positions and average loads of various time periods of each computing power providing device in a preset range.
Preferably, before the determining, according to the service type, the geographic location and the pre-stored super-edge computing power registry, whether there is a target computing power providing device in which available computing power resources meet the service request in a preset range, the method further includes:
acquiring computing power resource information reported by each computing power providing device in a preset range and load information of each time period;
acquiring a calculation force value, a calculation force type and a geographic position of each calculation force providing device according to the calculation force resource information;
calculating the average load of each computing force providing device in each time period according to the load information of each time period;
the super-edge computing force registry is established according to the computing force value, the computing force type, the geographic position and the average load of each time period of each computing force providing device.
Preferably, the computing power resource information includes: at least one of chip type, main frequency, bus bit width, primary cache, core number and memory;
the load information includes at least one of a utilization rate of the chip and a utilization rate of the memory.
Preferably, the determining, according to the service type, the geographic location and a pre-stored super-edge computing power registry, whether there is a target computing power providing device with available computing power resources within a preset range to satisfy the service request specifically includes the following steps:
step S1, sorting all the computing force providing devices in the super-edge computing force registry according to the geographical position from small to large according to the distance between the computing force providing devices and the computing force demand side node;
step S2, removing the computing power providing equipment with the computing power type which is not matched with the service type in the sequenced super-edge computing power registry to obtain a list to be selected;
step S3, taking the computing power providing equipment arranged at the first position in the to-be-selected list as current equipment;
step S4, acquiring the real-time load of the current equipment and the average load of the current time period;
step S5, judging whether the calculation redundancy of the current equipment is larger than a first preset threshold value according to the real-time load of the current equipment and the average load of the current time period, if so, executing step S6, otherwise, taking the calculation providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to step S4;
and S6, judging whether the available computing power of the current equipment meets the service request according to the computing power value of the current equipment and the average load of the current time period, if so, taking the current equipment as target computing power providing equipment, otherwise, taking computing power providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to the step S4.
Preferably, in step S5, whether the power redundancy of the current device is greater than a first preset threshold is determined according to the real-time load of the current device and the average load of the current time period, which specifically includes:
subtracting a real-time load from the average load of the current equipment in the current time period to obtain the computational redundancy;
and judging whether the calculated force redundancy is larger than a first preset threshold value.
Preferably, in step S6, the determining whether the available computing power of the current device meets the service request according to the computing power value of the current device and the average load of the current time period specifically includes:
calculating the available computing force of the current device according to the following formula;
D＝(A-B)×C
wherein D is the available calculation force of the current equipment, A is the calculation force value of the current equipment, B is the average load of the current equipment in the current time period, and C is a second preset threshold;
and judging whether the available calculation force meets the service request.
Preferably, the method further comprises:
each computing force providing device within a preset range is subjected to containerized deployment to provide computing force.
Preferably, the selecting the target computing power providing device performs computing power resource scheduling for the computing power demand party node specifically includes:
acquiring service data corresponding to the service request and a service operation environment;
and forwarding the service data and the service running environment to target computing power providing equipment so that the target computing power providing equipment establishes the service running environment through containerized deployment and performs calculation, and returning the obtained calculation result to a computing power demand side node.
Preferably, the method further comprises:
and when no available computing power resource exists in the preset range to meet the target computing power providing equipment of the service request, forwarding the service request to an edge computing center or a cloud computing center outside the preset range to schedule the computing power resource.
In a second aspect, the present invention provides a computing power resource scheduling apparatus, comprising:
the receiving module is used for receiving a service request sent by the node of the force calculation demand party in a preset range;
the acquisition module is connected with the receiving module and is used for acquiring the corresponding service type and the geographic position of the node of the force calculation demand party according to the service request;
the judging module is connected with the acquiring module and is used for judging whether available computing power resources exist in a preset range or not according to the service type, the geographic position and a pre-stored super-edge computing power registry to meet the target computing power providing equipment of the service request;
and the scheduling module is connected with the judging module and is used for selecting the target computing power providing equipment to schedule computing power resources for the computing power demand side node when the judging module judges that the computing power demand side node is the computing power resource.
In a third aspect, the present invention provides a computing power resource scheduling apparatus comprising a memory and a processor, the memory having stored therein a computer program, the processor being arranged to run the computer program to implement the computing power resource scheduling method of the first aspect described above.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method for scheduling computing resources according to the first aspect.
According to the method, the device and the computer readable storage medium for scheduling the computing power resources, after the service request sent by the computing power demand side node in the preset range is received, the corresponding service type and the geographic position of the computing power demand side node are obtained according to the service request, then whether the available computing power resources meet the target computing power providing equipment of the service request or not is judged according to the service type, the geographic position and the pre-stored super-edge computing power registry in the preset range, if yes, the target computing power providing equipment is selected for the computing power demand side node to perform computing power resource scheduling, and as the target computing power providing equipment is selected in the preset range, compared with the existing computing power scheduling method using edge computing, the integration of the idle computing power in the preset range can be achieved, the problem that the computing power of a third party has potential data leakage hazards due to the computing power of the third party and the problem that part of computing tasks are limited by network bandwidth and time is still solved.
Drawings
FIG. 1 is a flow chart of a method for scheduling computing power resources according to embodiment 1 of the present invention;
fig. 2 is a schematic flow chart of step S103 in fig. 1;
fig. 3 is a schematic structural diagram of a computing power resource scheduling device according to embodiment 2 of the present invention;
fig. 4 is a schematic structural diagram of a computing power resource scheduling device in embodiment 3 of the present invention.
Detailed Description
In order to make the technical scheme of the present invention better understood by those skilled in the art, the following detailed description of the embodiments of the present invention will be given with reference to the accompanying drawings.
It is to be understood that the specific embodiments and figures described herein are merely illustrative of the invention, and are not limiting of the invention.
It is to be understood that the various embodiments of the invention and the features of the embodiments may be combined with each other without conflict.
It is to be understood that only the portions relevant to the present invention are shown in the drawings for convenience of description, and the portions irrelevant to the present invention are not shown in the drawings.
It should be understood that each unit and module in the embodiments of the present invention may correspond to only one physical structure, may be formed by a plurality of physical structures, or may be integrated into one physical structure.
It will be appreciated that, without conflict, the functions and steps noted in the flowcharts and block diagrams of the present invention may occur out of the order noted in the figures.
It is to be understood that the flowcharts and block diagrams of the present invention illustrate the architecture, functionality, and operation of possible implementations of systems, devices, nodes, methods according to various embodiments of the present invention. Where each block in the flowchart or block diagrams may represent a unit, module, segment, code, or the like, which comprises executable instructions for implementing the specified functions. Moreover, each block or combination of blocks in the block diagrams and flowchart illustrations can be implemented by hardware-based systems that perform the specified functions, or by combinations of hardware and computer instructions.
It should be understood that the units and modules related in the embodiments of the present invention may be implemented by software, or may be implemented by hardware, for example, the units and modules may be located in a processor.
Example 1:
the present embodiment provides a computing power resource scheduling method, as shown in fig. 1, including:
step S101: and receiving a service request sent by the node of the force calculation demand party in a preset range.
In this embodiment, the computing power demand side node is a node that performs a computing task in a computing power network but has insufficient computing power available per se, and the computing power network may be composed of one or more computing power demand side nodes and computing power providing devices within a preset range, and the preset range for receiving the service request may be a range covered by an industrial park.
Step S102: acquiring a corresponding service type and a geographic position of the power calculation demand side node according to the service request;
in the present embodiment, considering that the distance between the power demand party and the power provider party has an influence on the time delay of data transmission, the geographical position of the power demand party node is further acquired according to the service request after the service request is acquired.
Step S103: and judging whether available computing power resources exist in a preset range or not according to the service type, the geographic position and a pre-stored superface computing power registry to meet the target computing power providing equipment of the service request.
The over-edge computing force registry comprises computing force values, computing force types, geographic positions and average loads of all computing force providing devices in a preset range.
In this embodiment, the pre-stored super-edge computing power registry records computing power resource information of computing power providing devices, and each recorded computing power providing device is within a preset range, so as to ensure that data transmission between a computing power demand side node and the computing power providing device is within the preset range, and reduce risk of data leakage.
Optionally, before the determining, according to the service type, the geographic location and the pre-stored super-edge computing power registry, whether there is a target computing power providing device in which available computing power resources meet the service request in a preset range, the method further includes:
acquiring computing power resource information reported by each computing power providing device in a preset range and load information of each time period;
acquiring a calculation force value, a calculation force type and a geographic position of each calculation force providing device according to the calculation force resource information;
calculating the average load of each computing force providing device in each time period according to the load information of each time period;
the super-edge computing force registry is established according to the computing force value, the computing force type, the geographic position and the average load of each time period of each computing force providing device.
Optionally, the computing power resource information includes: at least one of chip type, main frequency, bus bit width, primary cache, core number and memory;
the load information includes at least one of a utilization rate of the chip and a utilization rate of the memory.
In this embodiment, the computing power providing device may be a local server device, which may include a server, an edge intelligent station, and a DPU (data processing unit, processing unit), and a network device, which may include a gateway, a switch, a router, and an intelligent network card.
When the super-edge computing power registry is established, the network equipment can only provide CPU (central processing unit ) computing power, and the local server equipment can provide various computing power, so that the network equipment and the local server equipment can be respectively registered, and the computing power types and computing power capabilities of the network equipment and the local server equipment can be separated.
Optionally, as shown in fig. 2, step S103 specifically includes the following steps:
step S1, sorting all the computing force providing devices in the super-edge computing force registry according to the geographical position from small to large according to the distance between the computing force providing devices and the computing force demand side node;
step S2, removing the computing power providing equipment with the computing power type which is not matched with the service type in the sequenced super-edge computing power registry to obtain a list to be selected;
step S3, taking the computing power providing equipment arranged at the first position in the to-be-selected list as current equipment;
step S4, acquiring the real-time load of the current equipment and the average load of the current time period;
step S5, judging whether the calculation redundancy of the current equipment is larger than a first preset threshold value according to the real-time load of the current equipment and the average load of the current time period, if so, executing step S6, otherwise, taking the calculation providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to step S4;
and S6, judging whether the available computing power of the current equipment meets the service request according to the computing power value of the current equipment and the average load of the current time period, if so, taking the current equipment as target computing power providing equipment, otherwise, taking computing power providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to the step S4.
In this embodiment, the computing force providing devices in the super-edge computing force registry are sorted from small to large according to the distance between the computing force providing devices and the computing force demand party node, and then the computing force providing devices are selected according to the sorting result, so that the time delay of data transmission during computing force scheduling can be reduced.
Taking into account the possibility that the computing power of the computing power providing device is occupied, acquiring the real-time load of the computing power providing device during the computing power scheduling can avoid the computing power scheduling failure caused by the insufficient available computing power of the computing power providing device.
Optionally, in step S5, determining whether the power redundancy of the current device is greater than a first preset threshold according to the real-time load of the current device and the average load of the current time period specifically includes:
subtracting a real-time load from the average load of the current equipment in the current time period to obtain the computational redundancy;
and judging whether the calculated force redundancy is larger than a first preset threshold value.
In this embodiment, since the computing power providing devices within the preset range are limited, there are some computing power providing devices executing computing tasks, and if the average load of the current device in the current period subtracted from the real-time load of the current device is greater than the first preset threshold, it is indicated that the real-time load of the current device is heavy, so that there is not enough computing power redundancy, and the current device cannot complete the computing power request.
Optionally, in step S6, the determining whether the available computing power of the current device meets the service request according to the computing power value of the current device and the average load of the current time period specifically includes:
calculating the available computing force of the current device according to the following formula;
D＝(A-B)×C
wherein D is the available calculation force of the current equipment, A is the calculation force value of the current equipment, B is the average load of the current equipment in the current time period, and C is a second preset threshold;
and judging whether the available calculation force meets the service request.
In this embodiment, the second preset threshold is used to perform redundancy protection on the computing power providing device, so as to avoid overload, and the second preset threshold may be set to 0.8.
Optionally, the method further comprises:
each computing force providing device within a preset range is subjected to containerized deployment to provide computing force.
Optionally, the selecting the target computing power providing device performs computing power resource scheduling for the computing power demand party node specifically includes:
acquiring service data corresponding to the service request and a service operation environment;
and forwarding the service data and the service running environment to target computing power providing equipment so that the target computing power providing equipment establishes the service running environment through containerized deployment and performs calculation, and returning the obtained calculation result to a computing power demand side node.
In this embodiment, the containerization is used to enable the computing power providing device to simplify the execution environment construction, configuration deployment and computing execution when executing the service request, and provide the computing power service externally in the form of an interface.
Optionally, the method further comprises:
and when no available computing power resource exists in the preset range to meet the target computing power providing equipment of the service request, forwarding the service request to an edge computing center or a cloud computing center outside the preset range to schedule the computing power resource.
In this embodiment, when the computing power providing device within the preset range cannot meet the service request, the service request is forwarded to the remote computing center to obtain the computing power.
In the computing power resource scheduling method provided in embodiment 1, after receiving a service request sent by a computing power demand side node in a preset range, acquiring a corresponding service type and a geographic position of the computing power demand side node according to the service request, and then judging whether a target computing power providing device with available computing power resources meeting the service request exists in the preset range according to the service type, the geographic position and a pre-stored super-edge computing power registry, if yes, selecting the target computing power providing device to perform computing power resource scheduling for the computing power demand side node.
Example 2:
as shown in fig. 3, the present embodiment provides a computing power resource scheduling apparatus, configured to execute the foregoing computing power resource scheduling method, including:
a receiving module 11, configured to receive a service request sent by a node of a force calculation requiring party within a preset range;
the acquisition module 12 is connected with the receiving module 11 and is used for acquiring the corresponding service type and the geographic position of the node of the force calculation demand party according to the service request;
the judging module 13 is connected with the acquiring module 12 and is used for judging whether a target computing power providing device with available computing power resources meeting the service request exists in a preset range according to the service type, the geographic position and a pre-stored super-edge computing power registry;
and the scheduling module 14 is connected with the judging module 13 and is used for selecting the target computing power providing equipment to perform computing power resource scheduling for the computing power demand side node when the judging module 13 judges yes.
Preferably, the super-edge computing power registry includes computing power values, computing power types, geographic locations, and average loads for each time period for each computing power providing device within a preset range.
Preferably, the apparatus further comprises:
the reporting module is used for acquiring the computing power resource information reported by each computing power providing device in a preset range and the load information of each time period;
the computing power module is used for acquiring computing power values, computing power types and geographic positions of each computing power providing device according to the computing power resource information;
a calculation module for calculating an average load of each computing force providing device in each time period according to the load information of each time period;
and the registration module is used for establishing a super-edge computing force registry according to the computing force value, the computing force type, the geographic position and the average load of each time period of each computing force providing device.
Preferably, the computing power resource information includes: at least one of chip type, main frequency, bus bit width, primary cache, core number and memory;
the load information includes at least one of a utilization rate of the chip and a utilization rate of the memory.
Preferably, the judging module 13 specifically includes:
the ordering unit is used for ordering all the computing power providing devices in the super-edge computing power registry from small to large according to the distance between the computing power providing devices and the computing power demand side node according to the geographic position;
the selecting unit is used for removing the computing power providing equipment with the computing power type which is not matched with the service type in the sorted super-edge computing power registry to obtain a list to be selected;
a current unit for taking the computing power providing device arranged at the first position in the list to be selected as a current device;
the acquisition unit is used for acquiring the real-time load of the current equipment and the average load of the current time period;
the first judging unit is used for judging whether the calculation redundancy of the current equipment is larger than a first preset threshold value according to the real-time load of the current equipment and the average load of the current time period, if so, executing the second judging unit, otherwise, taking the calculation providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to the acquiring unit;
and the second judging unit is used for judging whether the available computing power of the current equipment meets the service request according to the computing power value of the current equipment and the average load of the current time period, if so, the current equipment is used as target computing power providing equipment, otherwise, the computing power providing equipment which is ordered next to the current equipment in the to-be-selected list is used as new current equipment, and the new computing power providing equipment returns to the acquisition unit.
Preferably, the first judging unit specifically includes:
the redundancy unit is used for subtracting the real-time load from the average load of the current time period of the current equipment to obtain the computational redundancy;
and the third judging unit is used for judging whether the computational redundancy is larger than a first preset threshold value.
Preferably, the second judging unit specifically includes:
an available calculation force unit for calculating an available calculation force of the current device according to the following formula;
D＝(A-B)×C
wherein D is the available calculation force of the current equipment, A is the calculation force value of the current equipment, B is the average load of the current equipment in the current time period, and C is a second preset threshold;
and the fourth judging unit is used for judging whether the available calculation force meets the service request.
Preferably, the apparatus further comprises:
and the containerization module is used for containerizing and deploying the computing force providing devices within a preset range to provide computing force.
Preferably, the scheduling module 14 specifically includes:
the service unit is used for acquiring service data corresponding to the service request and a service operation environment;
and the return unit is used for forwarding the service data and the service running environment to the target computing power providing equipment so that the target computing power providing equipment establishes the service running environment through containerized deployment and performs calculation, and returning the obtained calculation result to the computing power demand side node.
Preferably, the apparatus further comprises:
and the remote module is used for forwarding the service request to an edge computing center or a cloud computing center outside the preset range to schedule the computing resources when the available computing resources do not exist in the preset range to meet the target computing power providing equipment of the service request.
Example 3:
as shown in fig. 4, the present embodiment provides a computing power resource scheduling apparatus for executing the above-described computing power resource scheduling method, including a memory 21 and a processor 22, the memory 21 storing therein a computer program, the processor 22 being configured to run the computer program to execute the computing power resource scheduling method in embodiment 1.
The memory 21 is connected to the processor 22, the memory 21 may be a flash memory, a read-only memory, or other memories, and the processor 22 may be a central processing unit or a single chip microcomputer.
Example 4:
the present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the computing power resource scheduling method in embodiment 1 described above.
Computer-readable storage media include volatile or nonvolatile, removable or non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, computer program modules or other data. Computer-readable storage media includes, but is not limited to, RAM (Random Access Memory ), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory, charged erasable programmable Read-Only Memory), flash Memory or other Memory technology, CD-ROM (Compact Disc Read-Only Memory), digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.
The computing power resource scheduling device and the computer readable storage medium provided in embodiments 2 to 4, after receiving a service request sent by a computing power demand node in a preset range, obtain a corresponding service type and a geographic position of the computing power demand node according to the service request, and then judge whether there is a target computing power providing device with available computing power resources meeting the service request in the preset range according to the service type, the geographic position and a pre-stored over-edge computing power registry, if yes, select the target computing power providing device to perform computing power resource scheduling for the computing power demand node.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.
Claims (11)
1. A method for scheduling computing power resources, comprising:
receiving a service request sent by a node of a force calculation demand party in a preset range;
acquiring a corresponding service type and a geographic position of the power calculation demand side node according to the service request;
judging whether available computing power resources meet target computing power providing equipment of the service request in a preset range according to the service type, the geographic position and a pre-stored super-edge computing power registry, wherein the super-edge computing power registry comprises computing power values, computing power types, geographic positions and average loads of various time periods of all computing power providing equipment in the preset range, the computing power providing equipment comprises local server equipment and network equipment, the local server equipment comprises a server, an edge intelligent station and a processing unit, the network equipment comprises a gateway, a switch, a router and an intelligent network card, and when the super-edge computing power registry is established, the network equipment and the local server equipment are respectively registered so as to separate computing power types and computing power capacities of the network equipment and the local server equipment;
if yes, selecting the target computing power providing equipment to perform computing power resource scheduling for the computing power demand side node;
the target computing power providing device for judging whether available computing power resources meet the service request in a preset range according to the service type, the geographic position and a pre-stored super-edge computing power registry specifically comprises the following steps:
step S1, sorting all the computing force providing devices in the super-edge computing force registry according to the geographical position from small to large according to the distance between the computing force providing devices and the computing force demand side node;
step S2, removing the computing power providing equipment with the computing power type which is not matched with the service type in the sequenced super-edge computing power registry to obtain a list to be selected;
step S3, taking the computing power providing equipment arranged at the first position in the to-be-selected list as current equipment;
step S4, acquiring the real-time load of the current equipment and the average load of the current time period;
step S5, judging whether the calculation redundancy of the current equipment is larger than a first preset threshold value according to the real-time load of the current equipment and the average load of the current time period, if so, executing step S6, otherwise, taking the calculation providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to step S4;
and S6, judging whether the available computing power of the current equipment meets the service request according to the computing power value of the current equipment and the average load of the current time period, if so, taking the current equipment as target computing power providing equipment, otherwise, taking computing power providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to the step S4.
2. The method for scheduling computing power resources according to claim 1, wherein before the determining whether there is a target computing power providing device in which available computing power resources meet the service request in a preset range according to the service type, the geographic location, and a pre-stored super-edge computing power registry, the method further comprises:
acquiring computing power resource information reported by each computing power providing device in a preset range and load information of each time period;
acquiring a calculation force value, a calculation force type and a geographic position of each calculation force providing device according to the calculation force resource information;
calculating the average load of each computing force providing device in each time period according to the load information of each time period;
the super-edge computing force registry is established according to the computing force value, the computing force type, the geographic position and the average load of each time period of each computing force providing device.
3. The computing power resource scheduling method of claim 2, wherein the computing power resource information comprises: at least one of chip type, main frequency, bus bit width, primary cache, core number and memory;
the load information includes at least one of a utilization rate of the chip and a utilization rate of the memory.
4. The method for scheduling computing power resources according to claim 1, wherein in step S5, whether the computing power redundancy of the current device is greater than a first preset threshold is determined according to the real-time load of the current device and the average load of the current time period, and specifically includes:
subtracting a real-time load from the average load of the current equipment in the current time period to obtain the computational redundancy;
and judging whether the calculated force redundancy is larger than a first preset threshold value.
5. The method for scheduling computing power resources according to claim 1, wherein in step S6, the determining whether the available computing power of the current device meets the service request according to the computing power value of the current device and the average load of the current time period specifically includes:
calculating the available computing force of the current device according to the following formula;
D＝(A-B)×C
wherein D is the available calculation force of the current equipment, A is the calculation force value of the current equipment, B is the average load of the current equipment in the current time period, and C is a second preset threshold;
and judging whether the available calculation force meets the service request.
6. The computing power resource scheduling method of claim 1, further comprising:
each computing force providing device within a preset range is subjected to containerized deployment to provide computing force.
7. The method for computing power resource scheduling according to claim 6, wherein the selecting the target computing power providing device performs computing power resource scheduling for the computing power demander node specifically includes:
acquiring service data corresponding to the service request and a service operation environment;
and forwarding the service data and the service running environment to target computing power providing equipment so that the target computing power providing equipment establishes the service running environment through containerized deployment and performs calculation, and returning the obtained calculation result to a computing power demand side node.
8. The computing power resource scheduling method of claim 1, further comprising:
and when no available computing power resource exists in the preset range to meet the target computing power providing equipment of the service request, forwarding the service request to an edge computing center or a cloud computing center outside the preset range to schedule the computing power resource.
9. A computing power resource scheduling apparatus, comprising:
the receiving module is used for receiving a service request sent by the node of the force calculation demand party in a preset range;
the acquisition module is connected with the receiving module and is used for acquiring the corresponding service type and the geographic position of the node of the force calculation demand party according to the service request;
the judging module is connected with the acquiring module and used for judging whether available computing power resources exist in a preset range or not to meet the target computing power providing equipment of the service request according to the service type, the geographic position and a pre-stored super-edge computing power registry, the super-edge computing power registry comprises computing power values, computing power types, geographic positions and average loads of all computing power providing equipment in the preset range, the computing power providing equipment comprises a local server equipment and a network equipment, the local server equipment comprises a server, an edge intelligent station and a processing unit, the network equipment comprises a gateway, a switch, a router and an intelligent network card, and when the super-edge computing power registry is established, the network equipment and the local server equipment are respectively registered so as to separate computing power types and computing power capacities of the network equipment and the local server equipment;
the scheduling module is connected with the judging module and is used for selecting the target computing power providing equipment to schedule computing power resources for the computing power demand side node when the judging module judges that the computing power demand side node is the computing power demand side node;
the judging module specifically comprises:
the ordering unit is used for ordering all the computing power providing devices in the super-edge computing power registry from small to large according to the distance between the computing power providing devices and the computing power demand side node according to the geographic position;
the selecting unit is used for removing the computing power providing equipment with the computing power type which is not matched with the service type in the sorted super-edge computing power registry to obtain a list to be selected;
a current unit for taking the computing power providing device arranged at the first position in the list to be selected as a current device;
the acquisition unit is used for acquiring the real-time load of the current equipment and the average load of the current time period;
the first judging unit is used for judging whether the calculation redundancy of the current equipment is larger than a first preset threshold value according to the real-time load of the current equipment and the average load of the current time period, if so, executing the second judging unit, otherwise, taking the calculation providing equipment which is ordered next to the current equipment in the to-be-selected list as new current equipment, and returning to the acquiring unit;
and the second judging unit is used for judging whether the available computing power of the current equipment meets the service request according to the computing power value of the current equipment and the average load of the current time period, if so, the current equipment is used as target computing power providing equipment, otherwise, the computing power providing equipment which is ordered next to the current equipment in the to-be-selected list is used as new current equipment, and the new computing power providing equipment returns to the acquisition unit.
10. A computing power resource scheduling apparatus comprising a memory and a processor, the memory having a computer program stored therein, the processor being arranged to run the computer program to implement the computing power resource scheduling method of any one of claims 1-8.
11. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the computing power resource scheduling method according to any of claims 1-8.
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