CN116402318B - Multi-stage computing power resource distribution method and device for power distribution network and network architecture - Google Patents
Multi-stage computing power resource distribution method and device for power distribution network and network architecture Download PDFInfo
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Abstract
The application provides a multi-stage computing power resource distribution method, device and network architecture for a power distribution network, and belongs to the technical field of power distribution networks. The multi-stage computing power resource allocation method facing the power distribution network comprises the following steps: when the task demand is generated by the end-side equipment, determining a required computing power resource according to the task demand; judging whether the resource quota of the terminal side equipment is remained or not according to the required computing power resource; under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained; the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources include computing power of the edge side device and computing power of the end side device. The dynamic matching between the service processing requirements and the power calculation resources is realized, so that the power calculation efficiency of the power distribution network is improved, and the power calculation resources are fully utilized.
Description
Technical Field
The application relates to the technical field of power distribution networks, in particular to a multi-stage computing power resource distribution method facing the power distribution network, a multi-stage computing power resource distribution device facing the power distribution network, a network architecture facing the multi-stage computing power resource distribution of the power distribution network, a machine-readable storage medium and a processor.
Background
Along with the construction of the power distribution Internet of things, a measuring system and other links accumulate a large amount of data information, the power distribution network has wide data information sources, large data information amount and complex relationship among different data, and efficient data information acquisition, transmission and analysis can provide important guarantee for reliable and stable power supply. The development of cloud computing, edge computing and terminals drives the distribution dispersion and generalization of computing power of the whole power distribution network, namely, computing power of different scales can be distributed around the underlying equipment at different distances. The calculation forces are efficiently utilized, seamless coordination of calculation forces at the cloud edge end is guaranteed, and meanwhile, data and the calculation forces are quickly connected and processed by means of a network.
Terminals, data and services under the new service ecology of the electric power Internet of things are continuously increased, and massive electric power data are required to be analyzed and calculated on edge computing equipment, so that efficient and flexible service processing and decision making are realized. However, at present, the service processing requirements and the computational power resources cannot be dynamically matched, so that the computational power efficiency of the power distribution network is low, and the computational power resources are not fully utilized.
Disclosure of Invention
The embodiment of the application aims to provide a multi-stage computing power resource distribution method facing a power distribution network, a multi-stage computing power resource distribution device facing the power distribution network, a network architecture of multi-stage computing power resource distribution facing the power distribution network, a machine-readable storage medium and a processor.
In order to achieve the above object, a first aspect of the present application provides a multi-level computing power resource allocation method for a power distribution network, including:
when the task demand is generated by the end-side equipment, determining a required computing power resource according to the task demand;
judging whether the resource quota of the terminal side equipment is remained or not according to the required computing power resource;
under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained;
the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources include computing power of the edge side device and computing power of the end side device.
In an embodiment of the present application, the determining the required computing power resource according to the task requirement includes:
dividing the task demands to generate a plurality of subtasks;
and determining the computing power resources corresponding to each subtask so as to obtain the required computing power resources.
In an embodiment of the present application, the method further includes:
setting priorities for the subtasks;
the determining the computing power resource corresponding to each subtask comprises the following steps:
and determining computing power resources corresponding to the subtasks in the resource quota of the terminal side device in sequence according to the priority order of the subtasks.
In the embodiment of the application, after determining the computing power resources corresponding to each subtask, the method further comprises the following steps:
establishing network connection according to the task demands to form an algorithm power network;
and sending each subtask to computing equipment corresponding to the computing power resource through the computing power network for processing.
In the embodiment of the present application, the sending the subtasks to the computing device corresponding to the computing resource through the computing network for processing includes:
acquiring network information of the power calculation network in real time;
a routing strategy is made according to the network information;
and sending each subtask to computing equipment corresponding to the computing power resource for processing according to the routing strategy.
In an embodiment of the present application, the method further includes:
setting priority for each terminal device;
and under the condition that the resource quota of the end side device remains, re-distributing the remaining resource quota to obtain a resource distribution result, wherein the method comprises the following steps:
and under the condition that the resource quota of the end side equipment is remained, re-distributing the remained resource quota according to the priority of each end side equipment to obtain a resource distribution result.
The second aspect of the present application provides a network architecture for distribution network-oriented multistage computing power resource allocation, for implementing the above distribution network-oriented multistage computing power resource allocation method, including: a base resource layer and a computing resource layer; wherein,
the basic resource layer is used for determining required computing power resources according to task requirements when the end side equipment generates the task requirements;
the computing power resource layer is used for judging whether the resource quota of the terminal side equipment is remained according to the required computing power resource; and under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained.
A third aspect of the present application provides a multi-stage computing power resource allocation apparatus for a power distribution network, including:
the determining module is used for determining required computing power resources according to task demands when the end-side equipment generates the task demands;
the judging module is used for judging whether the resource quota of the terminal side equipment remains or not according to the required computing power resource; the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources comprise computing power of edge side equipment and computing power of end side equipment;
and the allocation module is used for re-allocating the residual resource quota under the condition that the resource quota of the end side device is residual, so as to obtain a resource allocation result.
In an embodiment of the present application, the determining module includes:
the segmentation unit is used for segmenting the task demands and generating a plurality of subtasks;
and the resource determining unit is used for determining the computing power resources corresponding to each subtask so as to obtain the required computing power resources.
In an embodiment of the present application, the method further includes:
the setting module is used for setting priority for each subtask;
the resource determination unit includes:
the sequence determining subunit is configured to determine, in sequence, computing power resources corresponding to each subtask in the resource quota of the end-side device according to the priority sequence of each subtask.
A fourth aspect of the present application provides a processor configured to perform the above-described power distribution network oriented multi-level computing resource allocation method.
A fifth aspect of the application provides a machine-readable storage medium having stored thereon instructions that, when executed by a processor, cause the processor to be configured to perform the above-described multi-stage power distribution network-oriented method of computing power resource allocation.
Through the technical scheme, the computing power resources are dynamically adjusted by detecting the service demands in real time, so that efficient processing and integrated output of various tasks are completed, the reasonable distribution of the computing power resources is realized on the premise of meeting the service demands, and the required computing power demands are reliably provided for the service of the terminal equipment. The dynamic matching between the service processing requirements and the power calculation resources is realized, so that the power calculation efficiency of the power distribution network is improved, and the power calculation resources are fully utilized. And the edge side is provided with an edge terminal and an edge gateway to cooperatively operate with the cloud master station, so that reasonable configuration of different required services is realized.
Additional features and advantages of embodiments of the application will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain, without limitation, the embodiments of the application. In the drawings:
fig. 1 schematically illustrates a flow diagram of a multi-level computing resource allocation method for a power distribution network according to an embodiment of the present application;
FIG. 2 schematically illustrates a block diagram of a computing power resource allocation scheme in a multi-level computing power network, according to an embodiment of the application;
FIG. 3 schematically illustrates a multi-stage power network architecture diagram for a power distribution network in accordance with an embodiment of the present application;
fig. 4 schematically shows a block diagram of a multi-stage computing resource allocation device for a power distribution network according to an embodiment of the application;
fig. 5 schematically shows an internal structural view of a computer device according to an embodiment of the present application.
Description of the reference numerals
410-a determination module; 420-judging module; 430-an allocation module; a01-a processor; a02-a network interface; a03-an internal memory; a04-a display screen; a05-an input device; a06—a nonvolatile storage medium; b01-operating system; b02-computer program.
Detailed Description
The following describes the detailed implementation of the embodiments of the present application with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the application, are not intended to limit the application.
Referring to fig. 1-2, fig. 1 schematically illustrates a flowchart of a multi-level computing power resource allocation method for a power distribution network according to an embodiment of the present application; fig. 2 schematically shows a block diagram of a computing power resource allocation scheme in a multi-level computing power network according to an embodiment of the application.
The embodiment provides a multi-stage computing power resource allocation method for a power distribution network, which comprises the following steps:
step 210: when the task demand is generated by the end-side equipment, determining a required computing power resource according to the task demand;
in this embodiment, the terminal device mainly includes devices with a certain computing power and communication performance, such as an intelligent camera, an intelligent ammeter, a sensor, and the like, and may perform some column function operations, such as data acquisition, reasoning, instruction execution, and the like. The terminal side equipment generates task demands which comprise multiple types of tasks such as videos, images and characters, and the task demands can be input into a demand analysis module to analyze information such as business real-time demands, computing power resource demands, algorithm types and the like, so that the perception and identification of the task types are realized, and the follow-up needed execution actions of the tasks are determined. Since the computational power resources required for different task demands are different, the computational power resources required for the current task demands need to be determined.
In some embodiments, to more accurately determine the required computational power resources, the determining the required computational power resources according to the task requirements includes the steps of:
firstly, dividing the task demands to generate a plurality of subtasks;
then, the computing power resources corresponding to the subtasks are determined to obtain the required computing power resources.
In this embodiment, the tasks may be separated from each other from the perspective of real-time and resource requirements to obtain multiple subtasks. The division may be performed from the direction of the magnitude of the demand for computing power resources, and the specific division mode is not limited in this embodiment. The determining the corresponding computing power resource of each subtask can be determined according to the follow-up needed execution action of each subtask, and the computing power resource needed by the whole task can be obtained after each subtask determines the corresponding computing power resource. And the computing power resources corresponding to each subtask are determined respectively, so that the computing power resources required by the task demands can be obtained more accurately.
In some embodiments, considering that the subtasks may have priority when executing, when dividing the task requirements, the priorities may also be set for the subtasks; the process for determining the computing power resources corresponding to each subtask comprises the following steps: and determining computing power resources corresponding to the subtasks in the resource quota of the terminal side device in sequence according to the priority order of the subtasks.
In this embodiment, the setting of the priority is to label the priority of each subtask, which may be set according to a preset priority order. Such as: the subtask A is a non-real-time task, and the subtask B is a real-time task, and the subtask A can be set to have high priority and the subtask B can be set to have low priority. After the priority is set, the corresponding computing power resources can be determined according to the priority sequence, so that the subtasks with higher priority can be preferentially ensured to have the corresponding computing power resources, and the normal execution of the tasks is ensured.
For example: the computing power resources of the subtasks to be executed are matched, the demands of users, namely the computing demands and the network demands, are comprehensively considered, and therefore different task demands from different users are met. For non-real-time video tasks, the end-side device can upload data to an edge computing gateway in the area preferentially, and high-performance processors such as CPU, NPU, GPU and the like are configured in the gateway, so that complex instruction tasks can be processed. For tasks with high real-time requirements, data is preferentially uploaded to one edge terminal in the area range, and the edge terminal is provided with a CPU and an NPU, so that the calculation tasks can be completed in parallel. For high-strength calculation tasks such as model establishment, simulation, calculation force prediction, distribution and the like, the special processors such as cloud master station configuration CPU, DPU, TPU, GPU, FPGA and the like are selected to be carried out, and high-strength and high-complexity task processing can be carried out rapidly and stably.
In some embodiments, after determining the computing power resources corresponding to each sub-task, the method further comprises the steps of:
firstly, establishing network connection according to the task demands to form a computing power network;
and then, the subtasks are sent to the computing equipment corresponding to the computing resources for processing through the computing network.
In this embodiment, the network connection is dynamically established between the data and computing resource layers according to the task requirements. In order to realize optimal computing power resource allocation, the computing power allocation module and the computing power scheduling module divide tasks into task segments and model segments, and allocate different computing sub-tasks into different computing power resources of a computing power resource layer according to a used scheduling optimization algorithm.
The subtasks are sent to computing equipment corresponding to computing resources for processing through the computing network, and the subtasks comprise the following steps:
firstly, acquiring network information of the power calculation network in real time;
then, a routing strategy is made according to the network information;
and finally, sending each subtask to computing equipment corresponding to the computing power resource for processing according to the routing strategy.
In this embodiment, in the power network, the network resources provide transmission paths for various power tasks. In the subtask transmission process, information such as time delay, reliability, energy consumption, resource utilization rate and the like of the network are fed back to a network management module, and the information of the calculation service notification, the calculation state notification and the calculation notification scheduling information is synthesized to formulate a routing strategy. The specific subtasks are transmitted to equipment responsible for calculation, the calculation is carried out by the determined calculation equipment, and finally, the calculation result is transmitted back to the end side equipment, so that the remote measurement, remote signaling, remote control and remote adjustment of the end side equipment are finished, and the functions of panoramic sensing, fault diagnosis and positioning, automatic fault isolation, distributed resource cluster regulation and the like of the power distribution network can be realized through the APP configured by the application layer.
In the implementation process, the network information is acquired in real time so as to conveniently and accurately transmit each subtask to the computing equipment corresponding to the computing power resource for processing by conveniently and quickly making an optimal routing strategy.
Step 220: judging whether the resource quota of the terminal side equipment is remained or not according to the required computing power resource; the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources comprise computing power of edge side equipment and computing power of end side equipment;
in this embodiment, the history condition refers to an computing power resource occupied by the end-side device in a history task demand, before the end-side device executes a task, the master station executes the computing power and the network resource quota to the end-side device according to the history condition data, and the end-side device can upload the task according to the assigned computing power resource. The computing power of the edge side equipment comprises the computing power of the fusion terminal and the computing power of the edge gateway.
Step 230: under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained;
in this embodiment, when there is a surplus resource quota of the end-side device, the surplus resource quota may be allocated for a second time, that is, the surplus computing power resource is taken out and shared to other end-side devices for use.
In some embodiments, priorities may also be set for the respective end-side devices;
and under the condition that the resource quota of the end side device remains, re-distributing the remaining resource quota to obtain a resource distribution result, wherein the method comprises the following steps: and under the condition that the resource quota of the end side equipment is remained, re-distributing the remained resource quota according to the priority of each end side equipment to obtain a resource distribution result.
In this embodiment, the priority of the end-side device may be considered, and when there is a surplus resource quota of the end-side device, the surplus resource quota is preferentially allocated to the end-side device with a high priority level, so as to ensure that the end-side device with a high priority level has enough computing power resources.
In the implementation process, when the task demand is generated by the end-side equipment, determining the required calculation force resource according to the task demand; judging whether the resource quota of the terminal side equipment is remained or not according to the required computing power resource; and under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained. The dynamic matching between the service processing requirements and the power calculation resources is realized, so that the power calculation efficiency of the power distribution network is improved, and the power calculation resources are fully utilized. By detecting the service demands in real time, the computing power resources are dynamically adjusted, high-efficiency processing and integrated output of various tasks are completed, the reasonable distribution of the computing power resources is realized on the premise of meeting the service demands, and the required computing power demands are reliably provided for the service of the terminal side equipment. Meanwhile, by combining the computing power resource, the network resource and the priority level, the computing power requirement required by reliable service requirement is provided for the terminal side equipment. And the edge side is provided with an edge terminal and an edge gateway to cooperatively operate with the cloud master station, so that reasonable configuration of different required services is realized.
Fig. 1 is a flow chart of a method for multi-level computing power resource allocation for a power distribution network in one embodiment. It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
Referring to fig. 3, fig. 3 schematically illustrates a multi-stage power network architecture diagram for a power distribution network according to an embodiment of the present application. The embodiment provides a network architecture for multi-stage computing power resource distribution for a power distribution network, which is used for realizing the multi-stage computing power resource distribution method for the power distribution network, and comprises the following steps: a basic resource layer, a computing power network layer, a computing power resource layer, an application service layer and a computing power network management arrangement layer; wherein,
the basic resource layer is used for determining required computing power resources according to task requirements when the end side equipment generates the task requirements;
the computing power resource layer is used for judging whether the resource quota of the terminal side equipment is remained according to the required computing power resource; and under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained.
In this embodiment, the base resource layer includes end-side devices and network infrastructure. The terminal side equipment mainly comprises equipment with certain calculation power and communication performance such as an intelligent camera, an intelligent ammeter and a sensor, and can perform some column of functional operations such as data acquisition, reasoning, instruction execution and the like. The network infrastructure mainly refers to network infrastructure of connecting end side equipment, edge side equipment and a cloud master station, and comprises an SDN controller of a control plane, a traditional network manager and network equipment of a forwarding plane. The computing power network layer supports sensing and advertising of multidimensional resources and services such as network, calculation, storage and the like, and based on information such as computing power service advertising, computing power state advertising, network information advertising and the like, a computing power routing strategy is formulated through joint regulation and control of 'network+computing power', and service request on-demand scheduling at the routing layer is realized. The computing power resource layer distributes computing power resource demands to the edge terminal, the edge gateway and the cloud master station in the aspects of comprehensive business computing power modeling, computing power prediction, computing power identification, computing power measurement computing amount and real-time requirements, and flexible and controllable computing power resource distribution scheduling is realized in the network range. The computing resources include a variety of combinations of computing capabilities, such as CPU, NPU, GPU, DPU, TPU, FPGA. The application service layer realizes functions of panoramic monitoring, fault analysis, diagnosis, positioning, self-healing, distributed energy cluster control and the like of the power distribution network. The computing power network management arrangement layer completes the collaborative arrangement of computing power routing and computing power service. Specific functions include application management, computing power management, network management, security management and the like, and overall management of the computing power network is achieved.
In the implementation process, the dynamic matching between the service processing requirements and the computing power resources can be realized by constructing the network architecture of the multistage computing power resource distribution facing the power distribution network, so that the computing power efficiency of the power distribution network is improved, and the computing power resources are fully utilized. By detecting the service demands in real time, the computing power resources are dynamically adjusted, high-efficiency processing and integrated output of various tasks are completed, the reasonable distribution of the computing power resources is realized on the premise of meeting the service demands, and the required computing power demands are reliably provided for the service of the terminal side equipment. Meanwhile, by combining the computing power resource, the network resource and the priority level, the computing power requirement required by reliable service requirement is provided for the terminal side equipment. And the edge side is provided with an edge terminal and an edge gateway to cooperatively operate with the cloud master station, so that reasonable configuration of different required services is realized.
Referring to fig. 4, fig. 4 schematically shows a block diagram of a multi-stage computing power resource allocation apparatus for a power distribution network according to an embodiment of the present application. The embodiment provides a multi-stage computing power resource distribution device for a power distribution network, which comprises a determining module 410, a judging module 420 and a distribution module 430, wherein:
a determining module 410, configured to determine, when a task requirement is generated by an end-side device, a required computing power resource according to the task requirement;
a judging module 420, configured to judge whether a resource quota of the end-side device remains according to the required computing power resource; the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources comprise computing power of edge side equipment and computing power of end side equipment;
and the allocation module 430 is configured to, when the resource quota of the end-side device remains, re-allocate the remaining resource quota to obtain a resource allocation result.
Wherein the determining module 410 includes:
the segmentation unit is used for segmenting the task demands and generating a plurality of subtasks;
and the resource determining unit is used for determining the computing power resources corresponding to each subtask so as to obtain the required computing power resources.
Wherein, still include:
the setting module is used for setting priority for each subtask;
the resource determination unit includes:
the sequence determining subunit is configured to determine, in sequence, computing power resources corresponding to each subtask in the resource quota of the end-side device according to the priority sequence of each subtask.
In the implementation process, when the task demand is generated by the determining module 410, determining a required computing power resource according to the task demand; the judging module 420 judges whether the resource quota of the end side device remains according to the required computing power resource; and the allocation module 430 allocates the remaining resource quota again to obtain a resource allocation result when the resource quota of the end side device remains. The dynamic matching between the service processing requirements and the power calculation resources is realized, so that the power calculation efficiency of the power distribution network is improved, and the power calculation resources are fully utilized. By detecting the service demands in real time, the computing power resources are dynamically adjusted, high-efficiency processing and integrated output of various tasks are completed, the reasonable distribution of the computing power resources is realized on the premise of meeting the service demands, and the required computing power demands are reliably provided for the service of the terminal side equipment. Meanwhile, by combining the computing power resource, the network resource and the priority level, the computing power requirement required by reliable service requirement is provided for the terminal side equipment. By edge side arrangement
The multi-stage computing power resource allocation device for the power distribution network comprises a processor and a memory, wherein the determining module 410, the judging module 420, the allocation module 430 and the like are all stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The core can be provided with one or more cores, and dynamic matching between service processing requirements and computing power resources is realized by adjusting core parameters, so that the computing power efficiency of the power distribution network is improved, and the computing power resources are fully utilized.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip.
The embodiment of the application provides a machine-readable storage medium, wherein a program is stored on the machine-readable storage medium, and the program is executed by a processor to realize the multi-stage computing power resource allocation method facing a power distribution network.
The embodiment of the application provides a processor which is used for running a program, wherein the multi-stage computing power resource allocation method facing a power distribution network is executed when the program runs.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 5. The computer apparatus includes a processor a01, a network interface a02, a display screen a04, an input device a05, and a memory (not shown in the figure) which are connected through a system bus. Wherein the processor a01 of the computer device is adapted to provide computing and control capabilities. The memory of the computer device includes an internal memory a03 and a nonvolatile storage medium a06. The nonvolatile storage medium a06 stores an operating system B01 and a computer program B02. The internal memory a03 provides an environment for the operation of the operating system B01 and the computer program B02 in the nonvolatile storage medium a06. The network interface a02 of the computer device is used for communication with an external terminal through a network connection. The computer program is executed by the processor A01 to realize a multi-stage computing power resource allocation method facing the power distribution network. The display screen a04 of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device a05 of the computer device may be a touch layer covered on the display screen, or may be a key, a track ball or a touch pad arranged on a casing of the computer device, or may be an external keyboard, a touch pad or a mouse.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, the multi-stage computing power resource allocation apparatus for a power distribution network provided by the present application may be implemented in the form of a computer program, which may be executed on a computer device as shown in fig. 5. The memory of the computer device may store various program modules that make up the power distribution network-oriented multi-level computing resource allocation apparatus, such as the determination module 410, the determination module 420, and the allocation module 430 shown in fig. 4. The computer program constituted by the respective program modules causes the processor to execute the steps in the calling method of the file system of the respective embodiments of the present application described in the present specification.
The computer device shown in fig. 5 may perform step 210 through the determining module 410, step 220 through the judging module 420, and step 230 through the distributing module 430 in the multi-stage computing power resource distributing apparatus for a power distribution network as shown in fig. 4.
The embodiment of the application provides equipment, which comprises a processor, a memory and a program stored in the memory and capable of running on the processor, wherein the processor realizes the following steps when executing the program:
when the task demand is generated by the end-side equipment, determining a required computing power resource according to the task demand;
judging whether the resource quota of the terminal side equipment is remained or not according to the required computing power resource;
under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained;
the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources include computing power of the edge side device and computing power of the end side device.
In one embodiment, the determining the required computing power resources according to the task demands includes:
dividing the task demands to generate a plurality of subtasks;
and determining the computing power resources corresponding to each subtask so as to obtain the required computing power resources.
In one embodiment, further comprising:
setting priorities for the subtasks;
the determining the computing power resource corresponding to each subtask comprises the following steps:
and determining computing power resources corresponding to the subtasks in the resource quota of the terminal side device in sequence according to the priority order of the subtasks.
In one embodiment, after determining the computing power resources corresponding to each sub-task, the method further comprises:
establishing network connection according to the task demands to form an algorithm power network;
and sending each subtask to computing equipment corresponding to the computing power resource through the computing power network for processing.
In one embodiment, the sending the subtasks to the computing device corresponding to the computing resource through the computing network for processing includes:
acquiring network information of the power calculation network in real time;
a routing strategy is made according to the network information;
and sending each subtask to computing equipment corresponding to the computing power resource for processing according to the routing strategy.
In one embodiment, further comprising:
setting priority for each terminal device;
and under the condition that the resource quota of the end side device remains, re-distributing the remaining resource quota to obtain a resource distribution result, wherein the method comprises the following steps:
and under the condition that the resource quota of the end side equipment is remained, re-distributing the remained resource quota according to the priority of each end side equipment to obtain a resource distribution result.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (8)
1. The multi-stage computing power resource allocation method for the power distribution network is characterized by comprising the following steps of:
when the task demand is generated by the end-side equipment, determining a required computing power resource according to the task demand;
judging whether the resource quota of the terminal side equipment is remained or not according to the required computing power resource;
under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained;
the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources comprise computing power of edge side equipment and computing power of end side equipment;
wherein the determining the required computing power resource according to the task demand includes:
dividing the task demands to generate a plurality of subtasks;
setting priorities for the subtasks;
determining the computing power resources corresponding to each subtask to obtain the required computing power resources; comprising the following steps:
and determining computing power resources corresponding to the subtasks in the resource quota of the terminal side device in sequence according to the priority order of the subtasks.
2. The method for distributing power distribution network-oriented multi-level computing power resources according to claim 1, further comprising, after determining computing power resources corresponding to each sub-task:
establishing network connection according to the task demands to form an algorithm power network;
and sending each subtask to computing equipment corresponding to the computing power resource through the computing power network for processing.
3. The power distribution network-oriented multi-level computing power resource allocation method according to claim 2, wherein the sending the subtasks to computing devices corresponding to computing power resources for processing through the computing power network comprises:
acquiring network information of the power calculation network in real time;
a routing strategy is made according to the network information;
and sending each subtask to computing equipment corresponding to the computing power resource for processing according to the routing strategy.
4. The power distribution network-oriented multi-level computing power resource allocation method of claim 1, further comprising:
setting priority for each terminal device;
and under the condition that the resource quota of the end side device remains, re-distributing the remaining resource quota to obtain a resource distribution result, wherein the method comprises the following steps:
and under the condition that the resource quota of the end side equipment is remained, re-distributing the remained resource quota according to the priority of each end side equipment to obtain a resource distribution result.
5. A network architecture for distribution network-oriented multi-level computing resource allocation, for implementing the distribution network-oriented multi-level computing resource allocation method according to any one of claims 1-4, comprising: a base resource layer and a computing resource layer; wherein,
the basic resource layer is used for determining required computing power resources according to task requirements when the end side equipment generates the task requirements; comprising the following steps: dividing the task demands to generate a plurality of subtasks; setting priorities for the subtasks; determining the computing power resources corresponding to each subtask to obtain the required computing power resources; comprising the following steps: according to the priority order of the subtasks, determining computing power resources corresponding to the subtasks in the resource quota of the terminal side device in sequence;
the computing power resource layer is used for judging whether the resource quota of the terminal side equipment is remained according to the required computing power resource; and under the condition that the resource quota of the end side device remains, the remaining resource quota is re-allocated, and a resource allocation result is obtained.
6. A multi-level computing power resource allocation device for a power distribution network, comprising:
the determining module is used for determining required computing power resources according to task demands when the end-side equipment generates the task demands;
the judging module is used for judging whether the resource quota of the terminal side equipment remains or not according to the required computing power resource; the resource quota of the terminal side equipment is obtained by respectively distributing corresponding computing power resources to each terminal side equipment according to historical conditions; the computing power resources comprise computing power of edge side equipment and computing power of end side equipment;
the allocation module is used for re-allocating the residual resource quota under the condition that the resource quota of the end side device is residual, so as to obtain a resource allocation result;
wherein the determining module comprises:
the segmentation unit is used for segmenting the task demands and generating a plurality of subtasks;
the setting module is used for setting priority for each subtask;
the resource determining unit is used for determining the computing power resources corresponding to each subtask so as to obtain the required computing power resources;
the resource determination unit includes:
the sequence determining subunit is configured to determine, in sequence, computing power resources corresponding to each subtask in the resource quota of the end-side device according to the priority sequence of each subtask.
7. A processor configured to perform the power distribution network oriented multi-level computing resource allocation method according to any one of claims 1 to 4.
8. A machine-readable storage medium having instructions stored thereon, which when executed by a processor, cause the processor to be configured to perform the power distribution network-oriented multi-level computing resource allocation method according to any one of claims 1 to 4.
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