CN111651253A - Method and device for scheduling computing resources - Google Patents
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Abstract
Translated fromChinese
Description
Translated fromChinese技术领域technical field
本申请涉及通信领域，尤其涉及一种算力资源的调度方法及装置。The present application relates to the field of communications, and in particular, to a method and device for scheduling computing resources.
背景技术Background technique
随着人工智能(Artificial Intelligence,AI)技术的发展，计算在社会生产中变得越来越重要。随着计算需求大量增加，本地计算难以满足用户的全部要求，很多计算任务需要边缘节点(内部计算节点)为其提供算力资源。然而，当多个内部计算节点为计算任务提供算力资源时，软件定义网络SDN控制器需要对算力资源进行调度。With the development of artificial intelligence (AI) technology, computing becomes more and more important in social production. With the large increase in computing demands, local computing cannot meet all the requirements of users, and many computing tasks require edge nodes (internal computing nodes) to provide computing resources for them. However, when multiple internal computing nodes provide computing resources for computing tasks, the software-defined network SDN controller needs to schedule computing resources.
现有技术方案中，软件定义网络(Software Defined Network，SDN)控制器管理多个内部计算节点。用户终端将计算任务所需的算力资源会通过用户端设备CPE(CustomerPremise Equipment)上传至SDN控制器。之后，SDN控制器管理多个内部计算节点为计算任务提供算力资源。然而，在SDN控制器管理多个内部计算节点为计算任务提供算力资源时，SDN控制器不仅需要根据每一个内部计算节点的算力资源，为内部计算节点分配计算子任务，还需要计算较多CPE与内部计算节点之间的路由，大大增加了SDN控制器的负载。In the prior art solution, a software defined network (Software Defined Network, SDN) controller manages multiple internal computing nodes. The user terminal uploads the computing power resources required by the computing task to the SDN controller through the customer premises equipment CPE (CustomerPremise Equipment). After that, the SDN controller manages multiple internal computing nodes to provide computing resources for computing tasks. However, when the SDN controller manages multiple internal computing nodes to provide computing resources for computing tasks, the SDN controller not only needs to allocate computing subtasks to the internal computing nodes according to the computing resources of each internal computing node, but also needs to calculate more Routing between multiple CPEs and internal computing nodes greatly increases the load on the SDN controller.
发明内容SUMMARY OF THE INVENTION
本申请提供一种算力资源的调度方法及装置，用于解决SDN控制器负载过大的问题。The present application provides a method and device for scheduling computing resources, which are used to solve the problem of excessive load on an SDN controller.
为达到上述目的，本申请采用如下技术方案：To achieve the above object, the application adopts the following technical solutions:
第一方面，本申请提供一种算力资源的调度方法，该方法包括：In a first aspect, the present application provides a method for scheduling computing resources, the method comprising:
SDN控制器接收用户端设备CPE发送的第一计算任务的需求信息；SDN控制器根据第一计算任务的需求信息、M个核心节点中每一个核心节点的网络状态、以及M个核心节点中每一个核心节点所能调度的空闲算力资源，确定N个目标核心节点，目标核心节点用于负责调度第一计算任务所需的算力资源，N为小于等于M的正整数；SDN控制器通过CPE向N个目标核心节点分配第二计算任务，所第二计算任务为第一计算任务的一部分。The SDN controller receives the requirement information of the first computing task sent by the client equipment CPE; the SDN controller according to the requirement information of the first computing task, the network status of each of the M core nodes, and each The idle computing resources that can be scheduled by a core node, determine N target core nodes, the target core nodes are used to schedule the computing resources required for the first computing task, N is a positive integer less than or equal to M; the SDN controller passes The CPE allocates the second computing task to the N target core nodes, where the second computing task is a part of the first computing task.
基于上述技术方案，SDN控制器根据计算任务的需求信息，以及核心节点的网络状态和核心节点所能调度的空闲算力，确定目标核心节点，保证目标核心节点可以满足任务需求，进而保障目标核心节点能够完成计算任务。由于核心节点管理了多个内部计算节点，核心节点可以调度的算力资源远大于一个内部计算节点的算力资源，因此，完成一个计算任务所需的核心节点的数量少于内部计算节点的数量。由于核心节点数量较少，且本发明中SDN控制器仅管理核心节点，因此本发明不仅减少了SDN控制器管理节点的数量，而且SDN控制器只需计算少量的CPE与目标核心节点之间的路由，降低了SDN控制器的负载。之后，SDN控制器通过CPE将计算任务分配至目标核心节点，由于目标核心节点负责调度计算任务所需的算力资源，因此核心节点可以分担SDN控制器的任务，进而有效降低SDN控制器的负载。Based on the above technical solutions, the SDN controller determines the target core node according to the demand information of the computing task, the network status of the core node and the idle computing power that can be scheduled by the core node, to ensure that the target core node can meet the task requirements, and then to ensure the target core node. Nodes are able to complete computing tasks. Since a core node manages multiple internal computing nodes, the computing resources that can be scheduled by a core node are much larger than that of an internal computing node. Therefore, the number of core nodes required to complete a computing task is less than the number of internal computing nodes. . Since the number of core nodes is small, and the SDN controller in the present invention only manages the core nodes, the present invention not only reduces the number of nodes managed by the SDN controller, but also only needs to calculate a small number of CPEs and the target core node. routing, reducing the load on the SDN controller. After that, the SDN controller allocates computing tasks to the target core node through CPE. Since the target core node is responsible for scheduling computing resources required for computing tasks, the core nodes can share the tasks of the SDN controller, thereby effectively reducing the load of the SDN controller. .
第二方面，本申请提供一种算力资源的调度装置，该装置包括：In a second aspect, the present application provides an apparatus for scheduling computing resources, the apparatus comprising:
接收单元，用于接收用户端设备CPE发送的第一计算任务；处理单元，用于根据所述第一计算任务的需求信息、M个核心节点中每一个核心节点的网络状态、以及所述M个核心节点中每一个核心节点所能调度的总空闲算力资源，确定N个目标核心节点，所述目标核心节点用于负责调度所述第一计算任务所需的算力资源，所述总空闲算力资源为一个核心节点管理的全部计算节点的空闲算力资源之和，N为小于等于M的正整数；发送单元，用于通过所述CPE向所述N个目标核心节点分配第二计算任务，所述第二计算任务为所述第一计算任务的一部分。a receiving unit, configured to receive the first computing task sent by the client device CPE; The total idle computing resources that can be scheduled by each of the core nodes are determined, and N target core nodes are determined. The target core nodes are used for scheduling the computing resources required by the first computing task. The idle computing power resource is the sum of the idle computing power resources of all computing nodes managed by one core node, and N is a positive integer less than or equal to M; the sending unit is used for allocating the second core node to the N target core nodes through the CPE. A computing task, the second computing task is a part of the first computing task.
一种可能的设计中，所述第一计算任务的需求信息包括：网络时延、网络抖动、网络丢包率、以及算力资源。In a possible design, the requirement information of the first computing task includes: network delay, network jitter, network packet loss rate, and computing resources.
一种可能的设计中，所述处理单元，还用于对于所述N个目标核心节点中的每一个目标核心节点，所述SDN控制器确定所述目标核心节点和所述CPE之间的路由。In a possible design, the processing unit is further configured to, for each of the N target core nodes, the SDN controller to determine a route between the target core node and the CPE .
一种可能的设计中，所述目标核心节点和所述CPE之间的路由包括第一路由和第二路由。In a possible design, the route between the target core node and the CPE includes a first route and a second route.
第三方面，本申请提供了一种算力资源的调度装置，该装置包括：处理器和通信接口；通信接口和处理器耦合，处理器用于运行计算机程序或指令，以实现如第一方面和第一方面的任一种可能的实现方式中所描述的算力资源的调度方法。In a third aspect, the present application provides an apparatus for scheduling computing power resources, the apparatus includes: a processor and a communication interface; the communication interface is coupled to the processor, and the processor is configured to run a computer program or instructions to implement the first aspect and The method for scheduling computing resources described in any possible implementation manner of the first aspect.
第四方面，本申请提供了一种计算机可读存储介质，计算机可读存储介质中存储有指令，当指令在计算机上运行时，使得计算机执行上述第一方面和第一方面的任一种可能的实现方式中所描述的算力资源的调度方法。In a fourth aspect, the present application provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed on a computer, the computer is made to execute any one of the first aspect and the first aspect. The scheduling method of computing resources described in the implementation manner of .
第五方面，本申请提供一种包含指令的计算机程序产品，当计算机程序产品在计算机上运行时，使得计算机执行上述第一方面和第一方面的任一种可能的实现方式中所描述的算力资源的调度方法。In a fifth aspect, the present application provides a computer program product comprising instructions, when the computer program product is run on a computer, the computer program product enables the computer to execute the computation described in the first aspect and any possible implementation manner of the first aspect. Manpower resource scheduling method.
第六方面，本申请提供一种芯片，芯片包括处理器和通信接口，通信接口和处理器耦合，处理器用于运行计算机程序或指令，以实现如第一方面和第一方面的任一种可能的实现方式中所描述的XX方法。In a sixth aspect, the present application provides a chip, the chip includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run a computer program or instruction to realize any possibility as the first aspect and the first aspect The implementation of the XX method described in.
上述方案中，算力资源的调度装置、计算机设备、计算机存储介质、计算机程序产品或者芯片所能解决的技术问题以及实现的技术效果可以参见上述第一方面所解决的技术问题以及技术效果，在此不再赘述。In the above solution, the technical problems and technical effects that can be solved by the scheduling device, computer equipment, computer storage medium, computer program product or chip of computing power resources and the technical effects achieved can refer to the technical problems and technical effects solved in the first aspect above. This will not be repeated here.
附图说明Description of drawings
图1为本申请实施例提供的一种通信系统的系统架构图；FIG. 1 is a system architecture diagram of a communication system provided by an embodiment of the present application;
图2为本申请实施例提供的一种通信系统的系统架构图；FIG. 2 is a system architecture diagram of a communication system provided by an embodiment of the present application;
图3为本申请实施例提供的一种算力资源的调度方法的流程示意图；3 is a schematic flowchart of a method for scheduling computing resources provided by an embodiment of the present application;
图4为本申请实施例提供的另一种算力资源的调度方法的流程示意图；4 is a schematic flowchart of another method for scheduling computing resources provided by an embodiment of the present application;
图5为本申请实施例提供的一种目标外部计算节点的确定方法的流程示意图；5 is a schematic flowchart of a method for determining a target external computing node according to an embodiment of the present application;
图6为本申请实施例提供的一种算力资源的调度装置的结构示意图；FIG. 6 is a schematic structural diagram of an apparatus for scheduling computing resources according to an embodiment of the present application;
图7为本申请实施例提供的另一种算力资源的调度装置的结构示意图。FIG. 7 is a schematic structural diagram of another apparatus for scheduling computing resources provided by an embodiment of the present application.
具体实施方式Detailed ways
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本申请保护的范围。The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.
本文中字符“/”，一般表示前后关联对象是一种“或者”的关系。例如，A/B可以理解为A或者B。The character "/" in this text generally indicates that the related objects are an "or" relationship. For example, A/B can be understood as A or B.
本申请的说明书和权利要求书中的术语“第一”和“第二”是用于区别不同的对象，而不是用于描述对象的特定顺序。The terms "first" and "second" in the description and claims of the present application are used to distinguish different objects, rather than to describe a specific order of the objects.
此外，本申请的描述中所提到的术语“包括”和“具有”以及它们的任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或模块的过程、方法、系统、产品或设备没有限定于已列出的步骤或模块，而是可选地还包括其他没有列出的步骤或模块，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或模块。Furthermore, references to the terms "comprising" and "having" in the description of this application, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or modules is not limited to the listed steps or modules, but may optionally also include other unlisted steps or modules, or optionally also Other steps or modules inherent to these processes, methods, products or devices are included.
另外，在本申请实施例中，“示例性的”、或者“例如”等词用于表示作例子、例证或说明。本申请中被描述为“示例性的”或“例如”的任何实施例或设计方案不应被解释为比其它实施例或设计方案更优选或更具优势。确切而言，使用“示例性的”、或者“例如”等词旨在以具体方式呈现概念。In addition, in the embodiments of the present application, words such as "exemplary" or "for example" are used to represent examples, illustrations or illustrations. Any embodiment or design described in this application as "exemplary" or "such as" should not be construed as preferred or advantageous over other embodiments or designs. Rather, use of words such as "exemplary" or "such as" is intended to present concepts in a specific manner.
为了便于理解本申请的技术方案，下面先对本申请实施例涉及的一些概念进行简单介绍。In order to facilitate understanding of the technical solutions of the present application, some concepts involved in the embodiments of the present application are briefly introduced below.
1、算力1. Computing power
算力在不同的应用场景中有不同的衡量单位，用于比特币的每秒哈希运算次数(H/S)，用于AI和图形处理的每秒浮点运算次数(FLOP/S)，智能社会对算力的诉求主要是浮点运算能力。比特币网络必须为了安全目的而进行密集的数学和加密相关操作。例如，当网络达到10Th/s的哈希率时，意味着它可以每秒进行10万亿次计算。The computing power has different measurement units in different application scenarios, such as the number of hash operations per second (H/S) for Bitcoin, the number of floating point operations per second (FLOP/S) for AI and graphics processing, The demand for computing power in the intelligent society is mainly floating-point computing power. The Bitcoin network must perform intensive mathematical and cryptographic related operations for security purposes. For example, when the network reaches a hash rate of 10Th/s, it means it can perform 10 trillion calculations per second.
2、网络节点2. Network nodes
网络节点是指一台电脑或其他设备与一个有独立地址和具有传送或接收数据功能的网络相连。节点可以是工作站、客户、网络用户或个人计算机，还可以是服务器、打印机和其他网络连接的设备。每一个工作站﹑服务器、终端设备、网络设备，即拥有自己唯一网络地址的设备都是网络节点。A network node is a computer or other device connected to a network with an independent address and the ability to transmit or receive data. Nodes can be workstations, clients, network users, or personal computers, as well as servers, printers, and other network-connected devices. Every workstation, server, terminal device, network device, that is, a device with its own unique network address, is a network node.
3、移动边缘计算(Mobile Edge Computing,MEC)3. Mobile Edge Computing (MEC)
MEC可以利用无线接入网络就近提供电信用户IT所需服务和云端计算功能，创造出一个具备高性能、低延迟与高带宽的电信级服务环境，加速网络中各项内容、服务及应用的快速下载，使用户享有不间断的高质量网络体验。MEC can use the wireless access network to provide telecom users with IT services and cloud computing functions nearby, creating a carrier-class service environment with high performance, low latency and high bandwidth, accelerating the speed of various content, services and applications in the network. download, allowing users to enjoy an uninterrupted high-quality web experience.
以上是对本申请所涉及的术语的介绍，以下不再赘述。下面对本申请实施例的实施环境进行介绍。The above is an introduction to the terms involved in this application, which will not be repeated below. The implementation environment of the embodiments of the present application will be introduced below.
如图1所示，为本申请实施例提供的一种通信系统的架构示意图。该通信系统包括：终端、CPE、SDN控制器、核心节点、以及内部计算节点。As shown in FIG. 1 , it is a schematic structural diagram of a communication system provided by an embodiment of the present application. The communication system includes: a terminal, a CPE, an SDN controller, a core node, and an internal computing node.
其中，终端可以为各种具有通信功能的手持设备、车载设备、可穿戴设备、计算机，本申请实施例对此不作任何限定。例如，手持设备可以是智能手机。车载设备可以是车载导航系统。可穿戴设备可以是智能手环。计算机可以是个人数字助理(personal digitalassistant，PDA)电脑、平板型电脑以及膝上型电脑(laptop computer)。The terminal may be various handheld devices, vehicle-mounted devices, wearable devices, and computers with communication functions, which are not limited in this embodiment of the present application. For example, the handheld device may be a smartphone. The in-vehicle device may be an in-vehicle navigation system. The wearable device can be a smart bracelet. The computer may be a personal digital assistant (PDA) computer, a tablet computer, and a laptop computer.
CPE是一种接收移动信号并以无线WIFI信号转发出来的移动信号接入设备，它也是一种将高速4G或者5G信号转换成WiFi信号的设备，可支持同时上网的终端数量也较多。CPE is a mobile signal access device that receives mobile signals and forwards them with wireless WIFI signals. It is also a device that converts high-speed 4G or 5G signals into WiFi signals. The number of terminals that can support simultaneous Internet access is also large.
SDN控制器是软件定义网络中的应用程序，负责流量控制以确保智能网络。SDN控制器是基于如OpenFlow等协议，允许服务器通过交换机发送数据包。其核心技术OpenFlow通过将网络设备的控制面与数据面分离开来，从而实现了网络流量的灵活控制，使网络作为管道变得更加智能，为核心网络及应用的创新提供了良好的平台。An SDN controller is an application in software-defined networking that is responsible for traffic control to ensure an intelligent network. SDN controllers are based on protocols such as OpenFlow that allow servers to send packets through switches. Its core technology, OpenFlow, separates the control plane and data plane of network devices, thereby realizing flexible control of network traffic, making the network more intelligent as a pipeline, and providing a good platform for the innovation of core networks and applications.
SDN控制器可以管理M个核心节点，一个核心节点可以管理L个内部计算节点。以图1为例，SDN控制器管理核心节点A、核心节点B、核心节点C，核心节点A管理内部计算节点Aa、内部计算节点Ab、内部计算节点Ac。The SDN controller can manage M core nodes, and one core node can manage L internal computing nodes. Taking FIG. 1 as an example, the SDN controller manages core node A, core node B, and core node C, and core node A manages internal computing node Aa, internal computing node Ab, and internal computing node Ac.
在本申请实施例中，核心节点为网络节点，内部计算节点为具有MEC功能的网络节点，核心节点所属的运营商与内部计算节点所属的运营商相同。In the embodiment of the present application, the core node is a network node, the internal computing node is a network node with MEC function, and the operator to which the core node belongs is the same as the operator to which the internal computing node belongs.
可选的，该通信系统还可以包括外部计算节点。如图2所示，为本申请实施例提供的另一种通信系统的架构示意图。该通信系统包括：终端、CPE、SDN控制器、核心节点、内部计算节点、以及外部计算节点。Optionally, the communication system may further include external computing nodes. As shown in FIG. 2 , it is a schematic structural diagram of another communication system provided by an embodiment of the present application. The communication system includes: a terminal, a CPE, an SDN controller, a core node, an internal computing node, and an external computing node.
在本申请实施例中，外部计算节点为具有MEC功能的网络节点，核心节点和内部计算节点所属的运营商与外部计算节点所属的运营商不同。In the embodiment of the present application, the external computing node is a network node with MEC function, and the operators to which the core node and the internal computing node belong are different from the operators to which the external computing node belongs.
需要说明的是，在核心节点所能调度的算力资源无法满足计算任务所需的算力资源时，核心节点可以借助外部计算节点为计算任务提供算力资源。例如，核心节点A可以请求外部计算节点Ad为计算任务提供算力资源。It should be noted that when the computing resources that can be scheduled by the core nodes cannot meet the computing resources required by the computing tasks, the core nodes can provide computing resources for the computing tasks with the help of external computing nodes. For example, the core node A may request the external computing node Ad to provide computing resources for computing tasks.
本申请实施例提供的技术方案可以应用于上述通信系统。本申请实施例描述的网络架构以及业务场景是为了更加清楚的说明本申请实施例的技术方案，并不构成对于本申请实施例提供的技术方案的限定，本领域普通技术人员可知，随着网络架构的演变和新业务场景的出现，本申请实施例提供的技术方案对于类似的技术问题，同样适用。The technical solutions provided by the embodiments of the present application can be applied to the above communication system. The network architecture and service scenarios described in the embodiments of the present application are for the purpose of illustrating the technical solutions of the embodiments of the present application more clearly, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. The evolution of the architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.
如图3所示，为本申请实施例提供的一种算力资源的调度方法，该方法包括以下步骤：As shown in FIG. 3 , a method for scheduling computing resources provided in an embodiment of the present application includes the following steps:
S101、SDN控制器接收CPE发送的第一计算任务。S101. The SDN controller receives the first computing task sent by the CPE.
需要说明的是，第一计算任务为需要调用算力资源来实现的任务。第一计算任务由数据和算法组成。例如，第一计算任务可以为人脸识别。It should be noted that the first computing task is a task that needs to be implemented by invoking computing resources. The first computational task consists of data and algorithms. For example, the first computing task may be face recognition.
可选的，在SDN控制器接收CPE发送的第一计算任务后，SDN控制器对第一计算任务进行解析，获取第一计算任务的信息。Optionally, after the SDN controller receives the first computing task sent by the CPE, the SDN controller parses the first computing task to obtain information of the first computing task.
其中，第一计算任务的信息包括任务ID(Identity Document)和需求信息。需求信息包括：网络时延需求、网络抖动需求、网络丢包率需求、以及算力资源需求。The information of the first computing task includes a task ID (Identity Document) and requirement information. The requirement information includes: network delay requirement, network jitter requirement, network packet loss rate requirement, and computing resource requirement.
需要说明的是，网络时延需求为计算任务对于网络时延的要求。网络抖动需求用于指示计算任务对于网络抖动的要求。网络丢包率需求为计算任务对于网络丢包率的要求。算力资源需求为计算任务对于算力资源的要求。例如，实现人脸识别任务时，网络时延需求为E2E 5ms，网络抖动需求为网络抖动小于1ms，网络丢包率需求为网络丢包率小于0.0001，算力资源需求为100TFLOPS。It should be noted that the network delay requirement is the requirement of the computing task for the network delay. The network jitter requirement is used to indicate the computing task's requirement for network jitter. The network packet loss rate requirement is the requirement of the computing task for the network packet loss rate. The computing power resource requirement is the computing power resource requirement of the computing task. For example, when implementing the face recognition task, the network latency requirement is E2E 5ms, the network jitter requirement is that the network jitter is less than 1ms, the network packet loss rate is that the network packet loss rate is less than 0.0001, and the computing resource requirement is 100TFLOPS.
S102、SDN控制器根据第一计算任务的需求信息、M个核心节点中每一个核心节点的网络状态、以及M个核心节点中每一个核心节点所能调度的总空闲算力资源，确定N个目标核心节点。S102. The SDN controller determines N number of computing resources according to the requirement information of the first computing task, the network status of each of the M core nodes, and the total idle computing resources that can be scheduled by each of the M core nodes. target core node.
其中，核心节点的网络状态包括：网络时延、网络抖动、网络丢包率。总空闲算力资源为一个核心节点管理的全部内部计算节点的空闲算力资源之和。目标核心节点用于负责调度第一计算任务所需的算力资源。N为小于等于M的正整数。The network status of the core node includes: network delay, network jitter, and network packet loss rate. The total idle computing resources are the sum of the idle computing resources of all internal computing nodes managed by a core node. The target core node is used for scheduling computing resources required for the first computing task. N is a positive integer less than or equal to M.
可选的，在SDN控制器确定N个目标核心节点之前，N个目标核心节点中每一个目标核心节点分别向SDN控制器发送该目标核心节点的信息。目标核心节点的信息包括：网络状态、总空闲算力资源、以及网络地址。Optionally, before the SDN controller determines the N target core nodes, each of the N target core nodes sends the information of the target core node to the SDN controller respectively. The information of the target core node includes: network status, total idle computing resources, and network address.
一种可能的实现方式，控制器根据第一计算任务的网络时延需求、网络抖动需求、网络丢包率需求，以及M个核心节点中每一个核心节点的网络状态，从M个核心节点中确定Q个核心节点。其中，Q个核心节点的网络状态均满足第一计算任务的网络时延需求、网络抖动需求、网络丢包率需求。控制器根据第一计算任务的算力资源需求和M个核心节点中每一个核心节点所能调度的总空闲算力资源，从Q个核心节点中确定一个或多个目标核心节点。In a possible implementation manner, the controller selects from the M core nodes according to the network delay requirements, network jitter requirements, network packet loss rate requirements of the first computing task, and the network status of each of the M core nodes. Determine Q core nodes. The network states of the Q core nodes all meet the network delay requirements, network jitter requirements, and network packet loss rate requirements of the first computing task. The controller determines one or more target core nodes from the Q core nodes according to the computing resource requirements of the first computing task and the total idle computing resources that can be scheduled by each of the M core nodes.
一种可能的设计中，若Q个核心节点中存在总空闲算力资源大于等于第一计算任务的算力资源需求的核心节点，则控制器确定总空闲算力资源大于等于第一计算任务的算力资源需求的核心节点中的任一核心节点为目标核心节点。也就是说，第一计算任务所需的算力资源由一个目标核心节点负责调度。In a possible design, if there are core nodes whose total idle computing resources are greater than or equal to the computing resource requirements of the first computing task among the Q core nodes, the controller determines that the total idle computing resources are greater than or equal to the computing resources of the first computing task. Any one of the core nodes with computing power resource requirements is the target core node. That is to say, the computing resources required by the first computing task are scheduled by a target core node.
另一种可能的设计中，若Q个核心节点中每一个核心节点的总空闲算力资源均小于第一计算任务的算力资源需求，则控制器确定多个目标核心节点，该多个目标核心节点的总空闲算力资源之和大于等于第一计算任务的算力资源需求。In another possible design, if the total idle computing resources of each of the Q core nodes are less than the computing resource requirements of the first computing task, the controller determines multiple target core nodes, and the multiple target core nodes The sum of the total idle computing resources of the core nodes is greater than or equal to the computing resource requirements of the first computing task.
可选的，若控制器确定多个目标核心节点，则控制器将第一计算任务进行拆分，确定多个第二计算任务。其中，第二计算任务是第一计算任务的一部分，第二计算任务所需的算力资源由该第二计算任务分配到的目标核心节点负责调度。Optionally, if the controller determines multiple target core nodes, the controller divides the first computing task to determine multiple second computing tasks. The second computing task is a part of the first computing task, and the computing resources required by the second computing task are scheduled by the target core node to which the second computing task is allocated.
示例性的，第一计算任务的算力资源需求为750TFLOPS。控制器将第一计算任务拆分为第二计算任务a和第二计算任务b，第二计算任务a的算力资源需求为300TFLOPS，第二计算任务b的算力资源需求为450Exemplarily, the computing resource requirement of the first computing task is 750TFLOPS. The controller splits the first computing task into a second computing task a and a second computing task b. The computing resource requirement of the second computing task a is 300TFLOPS, and the computing resource requirement of the second computing task b is 450 TFLOPS.
TFLOPS。TFLOPS.
S103、SDN控制器通过CPE向N个目标核心节点分配第二计算任务。S103. The SDN controller allocates the second computing task to the N target core nodes through the CPE.
一种可能的实现方式，SDN控制器根据第二计算任务的任务ID，以及该第二计算任务分配到的目标核心节点的网络地址，通过CPE向该目标核心节点分配该任务ID对应的第二计算任务。A possible implementation manner, the SDN controller assigns the second task ID corresponding to the task ID to the target core node through the CPE according to the task ID of the second computing task and the network address of the target core node to which the second computing task is allocated. computing tasks.
可选的，在SDN控制器向N个目标核心节点分配第二计算任务之前，对于N个目标核心节点中的每一个目标核心节点，SDN控制器确定目标核心节点和CPE之间的路由。需要说明的是，目标核心节点和CPE之间的路由包括第一路由和第二路由。Optionally, before the SDN controller assigns the second computing task to the N target core nodes, for each target core node in the N target core nodes, the SDN controller determines a route between the target core node and the CPE. It should be noted that the route between the target core node and the CPE includes a first route and a second route.
一种可能的设计中，第一路由为目标核心节点和CPE之间的最优路径，第二路由为目标核心节点和CPE之间的次优路径。In a possible design, the first route is the optimal path between the target core node and the CPE, and the second route is the suboptimal path between the target core node and the CPE.
需要说明的是，控制器可以根据网络抖动、网络丢包率、网络时延等因素，确定目标核心节点和CPE之间的最优路径和次优路径。It should be noted that the controller may determine the optimal path and the sub-optimal path between the target core node and the CPE according to factors such as network jitter, network packet loss rate, and network delay.
可以理解的是，控制器确定目标核心节点与CPE之间的第一路由和第二路由，并向CPE发送第一路由和第二路由。这样一来，在第一路由的网络状态不稳定时，CPE可以选择第二路由，提高了网络的健壮性。而CPE选择最优路径进行数据传输，可以提高网络的稳定性。It can be understood that the controller determines the first route and the second route between the target core node and the CPE, and sends the first route and the second route to the CPE. In this way, when the network state of the first route is unstable, the CPE can select the second route, which improves the robustness of the network. The CPE selects the optimal path for data transmission, which can improve the stability of the network.
基于图3所示的技术方案，SDN控制器根据计算任务的需求信息，以及核心节点的网络状态和核心节点所能调度的空闲算力，确定目标核心节点，保证目标核心节点可以满足任务需求，进而保障目标核心节点能够完成计算任务。由于核心节点管理了多个内部计算节点，核心节点可以调度的算力资源远大于一个内部计算节点的算力资源，因此，完成一个计算任务所需的核心节点的数量少于内部计算节点的数量。由于核心节点数量较少，且本发明中SDN控制器仅管理核心节点，因此本发明不仅减少了SDN控制器管理节点的数量，而且SDN控制器只需计算少量的CPE与目标核心节点之间的路由，降低了SDN控制器的负载。之后，SDN控制器通过CPE将计算任务分配至目标核心节点，由于目标核心节点负责调度计算任务所需的算力资源，因此核心节点可以分担SDN控制器的任务，进而有效降低SDN控制器的负载。Based on the technical solution shown in Figure 3, the SDN controller determines the target core node according to the demand information of the computing task, the network status of the core node and the idle computing power that can be scheduled by the core node, and ensures that the target core node can meet the task requirements. This ensures that the target core node can complete the computing task. Since a core node manages multiple internal computing nodes, the computing resources that can be scheduled by a core node are much larger than that of an internal computing node. Therefore, the number of core nodes required to complete a computing task is less than the number of internal computing nodes. . Since the number of core nodes is small, and the SDN controller in the present invention only manages the core nodes, the present invention not only reduces the number of nodes managed by the SDN controller, but also only needs to calculate a small number of CPEs and the target core node. routing, reducing the load on the SDN controller. After that, the SDN controller allocates computing tasks to the target core node through CPE. Since the target core node is responsible for scheduling computing resources required for computing tasks, the core nodes can share the tasks of the SDN controller, thereby effectively reducing the load of the SDN controller. .
在SDN控制器通过CPE向N个目标核心节点分配第二计算任务后，目标核心节点接收第二计算任务，并调度第二计算任务所需的算力资源。After the SDN controller allocates the second computing task to the N target core nodes through the CPE, the target core node receives the second computing task and schedules computing resources required by the second computing task.
下面对目标核心节点为第二计算任务调度算力资源的过程，进行具体介绍。如图4所示，为本申请实施例提供的一种算力资源的调度方法，该方法包括以下步骤：The process of scheduling computing resources for the second computing task by the target core node will be described in detail below. As shown in FIG. 4 , a method for scheduling computing resources provided in an embodiment of the present application includes the following steps:
S201、目标核心节点接收SDN控制器通过CPE发送的第二计算任务。S201. The target core node receives the second computing task sent by the SDN controller through the CPE.
其中，第二计算任务为第一计算任务的一部分。Wherein, the second computing task is a part of the first computing task.
S202、目标核心节点向其管理的L个内部计算节点分别发送第一请求消息。S202: The target core node sends a first request message to the L internal computing nodes managed by the target core node.
其中，第一请求消息用于指示L个内部计算节点中每一个内部计算节点向目标核心节点发送该内部计算节点的空闲算力资源。The first request message is used to instruct each of the L internal computing nodes to send the idle computing resources of the internal computing node to the target core node.
一种可能的设计中，第一请求消息包括第二计算任务的需求信息。可选的，第一请求消息还可以包括消息标识、第二计算任务的任务标识、保留字段、以及校验位中的一项或多项。In a possible design, the first request message includes requirement information of the second computing task. Optionally, the first request message may further include one or more of a message identifier, a task identifier of the second computing task, a reserved field, and a check bit.
需要说明的是，在本申请实施例的实际应用中，第一请求消息可以有不同的名称，例如内部算力通证等，本申请实施例对此不做限定。It should be noted that, in the practical application of the embodiments of the present application, the first request message may have different names, such as an internal computing power token, etc., which are not limited in the embodiments of the present application.
S203、目标核心节点接收L个内部计算节点中每一个内部计算节点发送的第一响应消息。S203: The target core node receives the first response message sent by each of the L internal computing nodes.
其中，第一响应消息包括内部计算节点的空闲算力资源和网络地址。可选的，第一响应消息还可以包括消息标识、第二计算任务的任务标识、第二计算任务的需求信息、保留字段、以及校验位中的一项或多项。The first response message includes idle computing resources and network addresses of the internal computing nodes. Optionally, the first response message may further include one or more of a message identifier, a task identifier of the second computing task, requirement information of the second computing task, a reserved field, and a check digit.
S204、目标核心节点判断总空闲算力资源是否大于等于第二计算任务的算力资源需求。S204. The target core node determines whether the total idle computing resources are greater than or equal to the computing resource requirements of the second computing task.
可选的，在目标核心节点判断总空闲算力资源是否大于等于第二计算任务的算力资源需求之前，目标核心节点根据每一个内部计算节点的空闲算力资源，确定总空闲算力资源。Optionally, before the target core node determines whether the total idle computing resources are greater than or equal to the computing resource requirements of the second computing task, the target core node determines the total idle computing resources according to the idle computing resources of each internal computing node.
一种可能的设计中，若总空闲算力资源大于等于第二计算任务的算力资源需求，则目标核心节点执行步骤S205。In a possible design, if the total idle computing resources are greater than or equal to the computing resource requirements of the second computing task, the target core node executes step S205.
另一种可能的设计中，若总空闲算力资源小于第二计算任务的算力资源需求，则目标核心节点执行步骤S206。In another possible design, if the total idle computing resource is less than the computing resource requirement of the second computing task, the target core node executes step S206.
S205、目标核心节点确定为第二计算任务提供算力资源的P个目标内部计算节点。S205. The target core node determines P target internal computing nodes that provide computing resources for the second computing task.
其中，P个目标内部计算节点属于L个内部计算节点的子集，P个目标内部计算节点的空闲算力资源之和大于等于第二计算任务所需的算力资源P为小于L的正整数。Among them, the P target internal computing nodes belong to a subset of the L internal computing nodes, and the sum of the idle computing resources of the P target internal computing nodes is greater than or equal to the computing resource P required by the second computing task is a positive integer less than L .
一种可能的实现方式，若L个内部计算节点的空闲算力资源之和大于等于第二计算任务所需的算力资源，则目标核心节点确定为第二计算任务提供算力资源的P个目标内部计算节点。A possible implementation, if the sum of the idle computing resources of the L internal computing nodes is greater than or equal to the computing resources required by the second computing task, the target core node determines the P number of computing resources that provide computing resources for the second computing task. The target internal compute node.
可选的，目标核心节点将第二计算任务进行拆分，确定P个第三计算任务。其中，第三计算任务是第二计算任务的一部分，第三计算任务所需的算力资源由该第三计算任务分配到的目标内部计算节点负责提供。第三计算任务所需的算力资源，小于等于该第三计算任务分配到的目标内部计算节点的空闲算力资源。Optionally, the target core node splits the second computing task to determine P third computing tasks. The third computing task is a part of the second computing task, and the computing resources required by the third computing task are provided by the target internal computing node to which the third computing task is allocated. The computing resources required by the third computing task are less than or equal to the idle computing resources of the target internal computing node allocated by the third computing task.
可选的，目标核心节点根据第三计算任务的任务标识，以及该第三计算任务分配到的内部计算节点的网络地址，向该内部计算节点分配该任务标识对应的第三计算任务。Optionally, the target core node allocates a third computing task corresponding to the task identifier to the internal computing node according to the task identifier of the third computing task and the network address of the internal computing node to which the third computing task is allocated.
S206、目标核心节点确定为第二计算任务提供算力资源的目标外部计算节点、或目标内部计算节点和目标外部计算节点。S206. The target core node determines a target external computing node that provides computing resources for the second computing task, or a target internal computing node and a target external computing node.
可以理解的是，若目标核心节点接收到第二计算任务后，目标核心节点所能调度的总空闲算力资源发生改变，导致目标核心节点管理的L个内部计算节点的空闲算力资源之和小于第二计算任务所需的算力资源，目标核心节点无法为第二计算任务调度足够的算力资源。因此，目标核心节点需要借助外部计算节点为第二计算任务提供算力资源。It can be understood that if the target core node receives the second computing task, the total idle computing resources that can be scheduled by the target core node will change, resulting in the sum of the idle computing resources of the L internal computing nodes managed by the target core node. If the computing resources are smaller than the computing resources required by the second computing task, the target core node cannot schedule enough computing resources for the second computing task. Therefore, the target core node needs to provide computing resources for the second computing task by means of an external computing node.
一种可能的设计中，若L个内部计算节点中存在为第二计算任务提供算力资源的目标内部计算节点，且所有目标内部计算节点提供的空闲算力之和小于第二计算任务所需的算力资源，则控制器确定目标内部计算节点和目标外部计算节点共同为第二计算任务提供算力资源。In a possible design, if there is a target internal computing node that provides computing resources for the second computing task among the L internal computing nodes, and the sum of idle computing power provided by all target internal computing nodes is less than that required by the second computing task computing resources, the controller determines that the target internal computing node and the target external computing node jointly provide computing resources for the second computing task.
另一种可能的设计中，若所有内部计算节点均无法为第二计算任务提供算力资源，则目标核心节点确定目标外部计算节点为第二计算任务提供算力资源。In another possible design, if all internal computing nodes cannot provide computing resources for the second computing task, the target core node determines that the target external computing node provides computing resources for the second computing task.
基于图4所示的技术方案，目标核心节点接收到第二计算任务，并判断目标核心节点的总空闲算力资源是否大于等于第二计算任务所需的算力资源，进而确定为第二计算任务提供算力资源的目标内部计算节点和/或目标外部节点，分担了SDN控制器的任务，避免由SDN控制器确定为计算任务提供算力资源的目标内部计算节点和/或目标外部节点，有效地降低了SDN控制器的负载。Based on the technical solution shown in FIG. 4 , the target core node receives the second computing task, and determines whether the total idle computing resources of the target core node are greater than or equal to the computing resources required by the second computing task, and then determine the second computing task as the second computing task. The target internal computing node and/or the target external node that provides computing resources for the task share the task of the SDN controller, avoiding the SDN controller determining the target internal computing node and/or the target external node that provides computing resources for the computing task, The load of the SDN controller is effectively reduced.
下面对步骤S206的实现过程，进行具体介绍。如图5所示，为本申请实施例提供的一种目标外部计算节点的确定方法，该方法包括以下步骤：The implementation process of step S206 is described in detail below. As shown in FIG. 5 , a method for determining a target external computing node provided by an embodiment of the present application includes the following steps:
S301、目标核心节点向Z个外部计算节点分别发送第二请求消息。S301. The target core node sends a second request message to the Z external computing nodes respectively.
其中，第二请求消息包括算力出价和第三计算任务的算力资源需求。第二请求消息用于指示Z个外部计算节点中每一个外部计算节点向目标核心节点发送该外部计算节点的算力回价，Z为正整数。Wherein, the second request message includes the computing power bid and the computing power resource requirement of the third computing task. The second request message is used to instruct each of the Z external computing nodes to send the computing power price of the external computing node to the target core node, and Z is a positive integer.
可选的，第二请求消息还可以包括消息标识、第三计算任务的任务标识、保留字段、以及校验位中的一项或多项。Optionally, the second request message may further include one or more of a message identifier, a task identifier of the third computing task, a reserved field, and a check digit.
需要说明的是，在本申请实施例的实际应用中，第二请求消息可以有不同的名称，例如外部算力通证等，本申请实施例对此不做限定。It should be noted that, in practical applications of the embodiments of the present application, the second request message may have different names, such as external computing power tokens, etc., which are not limited in the embodiments of the present application.
在本申请实施例中，算力出价用于指示目标核心节点能够接受第k个外部计算节点付出的代价。算力回价用于指示该外部计算节点提供算力资源需要付出的代价。In this embodiment of the present application, the computing power bid is used to indicate that the target core node can accept the price paid by the kth external computing node. The computing power return is used to indicate the price that the external computing node needs to pay for providing computing resources.
一种可能的设计中，算力回价通过公式一确定：In a possible design, the hash rate is determined by formula 1:
A＝B×C 公式一A＝B×C Formula 1
其中，A为外部计算节点的算力回价，B为第三计算任务的算力资源需求，C为外部计算节点的服务单价。Among them, A is the computing power return price of the external computing node, B is the computing power resource demand of the third computing task, and C is the service unit price of the external computing node.
示例性的，计算任务的算力资源需求为50TFLOPS，外部计算节点的服务单价为1元/TFLOPS，则外部计算节点的算力回价为50元。Exemplarily, the computing power resource requirement of the computing task is 50TFLOPS, the service unit price of the external computing node is 1 yuan/TFLOPS, and the computing power return price of the external computing node is 50 yuan.
一种可能的设计中，算力出价通过公式二确定：In a possible design, the computing power bid is determined by formula 2:
D＝B×F 公式二D=B×F Formula 2
其中，D为算力出价，B为第三计算任务的算力资源需求，F为目标核心节点能够接受的服务单价。Among them, D is the computing power bid, B is the computing power resource demand of the third computing task, and F is the service unit price that the target core node can accept.
S302、目标核心节点接收Z个外部计算节点中每一个外部节点发送的第二响应消息。S302. The target core node receives the second response message sent by each of the Z external computing nodes.
其中，第二响应消息包括外部计算节点的算力回价。Wherein, the second response message includes the computing power return price of the external computing node.
可选的，第二响应消息还可以包括消息标识、第三计算任务的任务标识、算力出价、第三计算任务的算力资源需求、保留字段、以及校验位中的一项或多项。Optionally, the second response message may also include one or more of the message identifier, the task identifier of the third computing task, the computing power bid, the computing power resource requirement of the third computing task, a reserved field, and a check digit. .
S303、若Z个外部计算节点中存在算力回价小于等于算力出价的外部计算节点，则目标核心节点确定为第二计算任务提供算力资源的目标外部计算节点。S303. If there is an external computing node whose computing power price is less than or equal to the computing power bid among the Z external computing nodes, the target core node determines the target external computing node that provides computing power resources for the second computing task.
一种可能的实现方式，若Z个外部计算节点中存在算力回价小于等于算力出价的外部计算节点，则目标核心节点确定算力回价最小的外部计算节点为目标外部计算节点。In one possible implementation, if there is an external computing node whose computing power price is less than or equal to the computing power bid among the Z external computing nodes, the target core node determines the external computing node with the smallest computing power price as the target external computing node.
可以理解的是，运营商优先选择算力回价较低的外部计算节点为计算任务提供算力资源，能够降低实现计算任务的成本。It is understandable that operators prefer to select external computing nodes with lower computing power return to provide computing resources for computing tasks, which can reduce the cost of computing tasks.
基于图5所示的技术方案，目标核心节点能够根据算力出价和外部计算节点的算力回价，确定目标外部计算节点，分担了SDN控制器的任务，避免由SDN控制器确定为计算任务提供算力资源的目标外部计算节点，有效地降低了SDN控制器的负载。Based on the technical solution shown in Figure 5, the target core node can determine the target external computing node according to the computing power bid and the computing power return price of the external computing node, which shares the task of the SDN controller and avoids being determined by the SDN controller as a computing task The target external computing node that provides computing resources effectively reduces the load of the SDN controller.
上述主要从计算机设备的角度对本申请实施例提供的方案进行了介绍。可以理解的是，计算机设备为了实现上述功能，其包含了执行各个功能相应的硬件结构和/或软件模块。本领域技术人员应该很容易意识到，结合本申请所公开的实施例描述的各示例的算力资源的调度方法，本申请能够以硬件或硬件和计算机软件的结合形式来实现。某个功能究竟以硬件还是计算机软件驱动硬件的方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。The solutions provided by the embodiments of the present application have been introduced above mainly from the perspective of computer equipment. It can be understood that, in order to realize the above-mentioned functions, the computer device includes corresponding hardware structures and/or software modules for executing each function. Those skilled in the art should easily realize that the method for scheduling computing resources of each example described in conjunction with the embodiments disclosed in this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is performed by hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.
本申请实施例可以根据上述方法示例对算力资源的调度装置进行功能模块或者功能单元的划分，例如，可以对应各个功能划分各个功能模块或者功能单元，也可以将两个或两个以上的功能集成在一个处理模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块或者功能单元的形式实现。其中，本申请实施例中对模块或者单元的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。In this embodiment of the present application, the computing power resource scheduling apparatus may be divided into functional modules or functional units according to the foregoing method examples. For example, each functional module or functional unit may be divided into each function, or two or more functions may be divided into two or more functional units. integrated in a processing module. The above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software functional modules or functional units. Wherein, the division of modules or units in the embodiments of the present application is schematic, and is only a logical function division, and there may be other division manners in actual implementation.
如图6所示，本发明实施例提供了一种算力资源的调度装置，包括：As shown in FIG. 6 , an embodiment of the present invention provides an apparatus for scheduling computing resources, including:
接收单元101，用于接收用户端设备CPE发送的第一计算任务；A receiving unit 101, configured to receive the first computing task sent by the client equipment CPE;
处理单元102，用于根据所述第一计算任务的需求信息、M个核心节点中每一个核心节点的网络状态、以及所述M个核心节点中每一个核心节点所能调度的总空闲算力资源，确定N个目标核心节点，所述目标核心节点用于负责调度所述第一计算任务所需的算力资源，所述总空闲算力资源为一个核心节点管理的全部计算节点的空闲算力资源之和，N为小于等于M的正整数；The processing unit 102 is configured to, according to the requirement information of the first computing task, the network status of each of the M core nodes, and the total idle computing power that can be scheduled by each of the M core nodes resources, determine N target core nodes, the target core nodes are used for scheduling the computing resources required by the first computing task, and the total idle computing resources are the idle computing resources of all computing nodes managed by one core node. The sum of human resources, N is a positive integer less than or equal to M;
发送单元103，用于通过所述CPE向所述N个目标核心节点分配第二计算任务，所述第二计算任务为所述第一计算任务的一部分。The sending unit 103 is configured to allocate a second computing task to the N target core nodes through the CPE, where the second computing task is a part of the first computing task.
可选的，所述第一计算任务的需求信息包括：网络时延、网络抖动、网络丢包率、以及算力资源。Optionally, the requirement information of the first computing task includes: network delay, network jitter, network packet loss rate, and computing resources.
可选的，所述处理单元，还用于对于所述N个目标核心节点中的每一个目标核心节点，所述SDN控制器确定所述目标核心节点和所述CPE之间的路由。Optionally, the processing unit is further configured to, for each of the N target core nodes, the SDN controller determine a route between the target core node and the CPE.
可选的，所述目标核心节点和所述CPE之间的路由包括第一路由和第二路由。Optionally, the route between the target core node and the CPE includes a first route and a second route.
图7示出了上述实施例中所涉及的算力资源的调度装置的又一种可能的结构。该算力资源的调度装置包括：处理器201和通信接口202。处理器201用于对装置的动作进行控制管理，例如，执行上述方法实施例中所示的方法流程中的各个步骤，和/或用于执行本文所描述的技术的其它过程。通信接口202用于支持该算力资源的调度装置与其他网络实体的通信。算力资源的调度装置还可以包括存储器203和总线204，存储器203用于存储装置的程序代码和数据。FIG. 7 shows yet another possible structure of the apparatus for scheduling computing resources involved in the above embodiment. The apparatus for scheduling computing resources includes: a
其中，上述处理器201可以实现或执行结合本发明公开内容所描述的各种示例性的逻辑方框，单元和电路。该处理器可以是中央处理器，通用处理器，数字信号处理器，专用集成电路，现场可编程门阵列或者其他可编程逻辑器件、晶体管逻辑器件、硬件部件或者其任意组合。其可以实现或执行结合本发明公开内容所描述的各种示例性的逻辑方框，单元和电路。处理器也可以是实现计算功能的组合，例如包含一个或多个微处理器组合，DSP和微处理器的组合等。The above-mentioned
存储器203可以包括易失性存储器，例如随机存取存储器；该存储器也可以包括非易失性存储器，例如只读存储器，快闪存储器，硬盘或固态硬盘；该存储器还可以包括上述种类的存储器的组合。The
总线204可以是扩展工业标准结构(Extended Industry StandardArchitecture，EISA)总线等。总线204可以分为地址总线、数据总线、控制总线等。为便于表示，图7中仅用一条粗线表示，但并不表示仅有一根总线或一种类型的总线。The
通过以上的实施方式的描述，所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。From the description of the above embodiments, those skilled in the art can clearly understand that for the convenience and brevity of the description, only the division of the above functional modules is used as an example for illustration. In practical applications, the above functions can be allocated as required. It is completed by different functional modules, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. For the specific working process of the system, apparatus and unit described above, reference may be made to the corresponding process in the foregoing method embodiments, and details are not described herein again.
本申请实施例提供一种包含指令的计算机程序产品，当该计算机程序产品在计算机上运行时，使得该计算机执行上述方法实施例中的端口分类方法。The embodiments of the present application provide a computer program product containing instructions, when the computer program product runs on a computer, the computer is made to execute the port classification method in the above method embodiments.
本申请实施例还提供一种计算机可读存储介质，计算机可读存储介质中存储有指令，当该指令在计算机上运行时，使得该计算机执行上述方法实施例所示的方法流程中的端口分类方法。Embodiments of the present application further provide a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed on a computer, the computer is made to perform the port classification in the method flow shown in the above method embodiments method.
其中，计算机可读存储介质，例如可以是但不限于电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子(非穷举的列表)包括：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机存取存储器(Random Access Memory，RAM)、只读存储器(Read-Only Memory，ROM)、可擦式可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、寄存器、硬盘、光纤、便携式紧凑磁盘只读存储器(Compact Disc Read-Only Memory，CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合、或者本领域熟知的任何其它形式的计算机可读存储介质。一种示例性的存储介质耦合至处理器，从而使处理器能够从该存储介质读取信息，且可向该存储介质写入信息。当然，存储介质也可以是处理器的组成部分。处理器和存储介质可以位于特定用途集成电路(Application Specific Integrated Circuit，ASIC)中。在本申请实施例中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any combination of the above. More specific examples (non-exhaustive list) of computer readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (Read-Only Memory, ROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, EPROM), registers, hard disk, optical fiber, portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM) ), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing, or any other form of computer-readable storage medium known in the art. An exemplary storage medium is coupled to the processor, such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and the storage medium may be located in an Application Specific Integrated Circuit (ASIC). In the embodiments of the present application, the computer-readable storage medium may be any tangible medium containing or storing a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device.
由于本发明的实施例中的算力资源的调度装置、计算机可读存储介质、计算机程序产品可以应用于上述方法，因此，其所能获得的技术效果也可参考上述方法实施例，本发明实施例在此不再赘述。Since the computing power resource scheduling device, computer-readable storage medium, and computer program product in the embodiments of the present invention can be applied to the above methods, the technical effects that can be obtained can also refer to the above method embodiments, and the present invention implements The example will not be repeated here.
以上，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何在本申请揭露的技术范围内的变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应该以权利要求的保护范围为准。The above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any changes or substitutions within the technical scope disclosed in the present application should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.
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Cited By (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112153153A (en)* | 2020-09-28 | 2020-12-29 | 北京大学深圳研究生院 | Coordinated distributed intra-network resource scheduling method and system and storage medium |
| CN112465359A (en)* | 2020-12-01 | 2021-03-09 | 中国联合网络通信集团有限公司 | Calculation power calling method and device |
| CN112710915A (en)* | 2020-12-18 | 2021-04-27 | 北京百度网讯科技有限公司 | Method and device for monitoring power equipment, electronic equipment and computer storage medium |
| CN113037819A (en)* | 2021-02-26 | 2021-06-25 | 杭州雾联科技有限公司 | Edge computing resource sharing method, device and equipment |
| CN113157444A (en)* | 2021-03-29 | 2021-07-23 | 中国联合网络通信集团有限公司 | Computing power service authentication method, device and readable storage medium |
| CN113296905A (en)* | 2021-03-30 | 2021-08-24 | 阿里巴巴新加坡控股有限公司 | Scheduling method, scheduling device, electronic equipment, storage medium and software product |
| CN113641124A (en)* | 2021-08-06 | 2021-11-12 | 珠海格力电器股份有限公司 | Calculation force distribution method and device, controller and building control system |
| CN113852950A (en)* | 2021-06-28 | 2021-12-28 | 山东浪潮科学研究院有限公司 | Computing network-oriented intelligent mobility tracking scheduling method and device |
| CN113867973A (en)* | 2021-12-06 | 2021-12-31 | 腾讯科技（深圳）有限公司 | Resource allocation method and device |
| WO2022073229A1 (en)* | 2020-10-10 | 2022-04-14 | Telefonaktiebolaget Lm Ericsson (Publ) | Method and apparatus for managing load of network node |
| CN114500521A (en)* | 2020-11-13 | 2022-05-13 | 中国移动通信有限公司研究院 | Computing power scheduling method, device, scheduling equipment, system and storage medium |
| WO2022100365A1 (en)* | 2020-11-12 | 2022-05-19 | 华为云计算技术有限公司 | Method, system, and device for managing artificial intelligence application task, and storage medium |
| CN114691349A (en)* | 2020-12-31 | 2022-07-01 | 维沃移动通信有限公司 | Information processing method, device, equipment and storage medium |
| CN114700957A (en)* | 2022-05-26 | 2022-07-05 | 北京云迹科技股份有限公司 | Robot control method and device with low computational power requirement of model |
| WO2022143750A1 (en)* | 2020-12-31 | 2022-07-07 | 维沃移动通信有限公司 | Information processing method and apparatus, device, and storage medium |
| CN114756340A (en)* | 2022-03-17 | 2022-07-15 | 中国联合网络通信集团有限公司 | Computing power scheduling system, method, device and storage medium |
| CN114785851A (en)* | 2022-04-20 | 2022-07-22 | 中国电信股份有限公司 | Resource calling processing method and device, storage medium and electronic equipment |
| CN114867065A (en)* | 2022-05-18 | 2022-08-05 | 中国联合网络通信集团有限公司 | Base station computing force load balancing method, equipment and storage medium |
| WO2022174675A1 (en)* | 2021-02-22 | 2022-08-25 | 华为技术有限公司 | Computing power information processing method, first network device, and system |
| CN115002862A (en)* | 2021-03-02 | 2022-09-02 | 中国移动通信有限公司研究院 | Network system for computing power processing, service processing method and computing power network element node |
| CN115426327A (en)* | 2022-11-04 | 2022-12-02 | 北京邮电大学 | Calculation force scheduling method and device, electronic equipment and storage medium |
| CN116132449A (en)* | 2023-02-14 | 2023-05-16 | 苏州万集车联网技术有限公司 | Computing power scheduling method, device, electronic equipment and storage medium |
| WO2023142091A1 (en)* | 2022-01-29 | 2023-08-03 | 华为技术有限公司 | Computing task scheduling apparatus, computing apparatus, computing task scheduling method and computing method |
| WO2023160319A1 (en)* | 2022-02-24 | 2023-08-31 | 华为技术有限公司 | Task execution method and related device |
| CN116739202A (en)* | 2023-08-15 | 2023-09-12 | 深圳华越南方电子技术有限公司 | Power routing method, system, equipment and storage medium |
| CN117434990A (en)* | 2023-12-20 | 2024-01-23 | 成都易联易通科技有限责任公司 | Granary environment control method and system |
| WO2024140290A1 (en)* | 2022-12-30 | 2024-07-04 | 华为技术有限公司 | Method for processing computing task, and related apparatus |
| WO2025007648A1 (en)* | 2023-07-06 | 2025-01-09 | 华为技术有限公司 | Computing task scheduling method and communication apparatus |
| WO2025130494A1 (en)* | 2023-12-20 | 2025-06-26 | 华为技术有限公司 | Communication method and apparatus |
| WO2025140333A1 (en)* | 2023-12-29 | 2025-07-03 | 华为技术有限公司 | Communication method and apparatus |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070076728A1 (en)* | 2005-10-04 | 2007-04-05 | Remi Rieger | Self-monitoring and optimizing network apparatus and methods |
| CN107273179A (en)* | 2016-04-07 | 2017-10-20 | 中国移动通信有限公司研究院 | The dispatching method and device of a kind of hardware resource |
| CN107404733A (en)* | 2017-08-22 | 2017-11-28 | 山东省计算中心（国家超级计算济南中心） | A kind of 5G method of mobile communication and system based on MEC and layering SDN |
| CN105027512B (en)* | 2014-01-29 | 2018-05-18 | 华为技术有限公司 | Data transmission method, transfer control method and equipment |
| CN108513655A (en)* | 2015-10-13 | 2018-09-07 | 施耐德电器工业公司 | Software definition automated system and its framework |
| CN110012508A (en)* | 2019-04-10 | 2019-07-12 | 中南大学 | A resource allocation method and system for edge computing for ultra-dense networks |
| CN110515731A (en)* | 2019-08-22 | 2019-11-29 | 北京浪潮数据技术有限公司 | A kind of data processing method, apparatus and system |
| CN110891093A (en)* | 2019-12-09 | 2020-03-17 | 中国科学院计算机网络信息中心 | A method and system for selecting edge computing nodes in a delay-sensitive network |
- 2020
- 2020-05-28CNCN202010471068.3Apatent/CN111651253B/enactiveActive
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070076728A1 (en)* | 2005-10-04 | 2007-04-05 | Remi Rieger | Self-monitoring and optimizing network apparatus and methods |
| CN105027512B (en)* | 2014-01-29 | 2018-05-18 | 华为技术有限公司 | Data transmission method, transfer control method and equipment |
| CN108513655A (en)* | 2015-10-13 | 2018-09-07 | 施耐德电器工业公司 | Software definition automated system and its framework |
| CN107273179A (en)* | 2016-04-07 | 2017-10-20 | 中国移动通信有限公司研究院 | The dispatching method and device of a kind of hardware resource |
| CN107404733A (en)* | 2017-08-22 | 2017-11-28 | 山东省计算中心（国家超级计算济南中心） | A kind of 5G method of mobile communication and system based on MEC and layering SDN |
| CN110012508A (en)* | 2019-04-10 | 2019-07-12 | 中南大学 | A resource allocation method and system for edge computing for ultra-dense networks |
| CN110515731A (en)* | 2019-08-22 | 2019-11-29 | 北京浪潮数据技术有限公司 | A kind of data processing method, apparatus and system |
| CN110891093A (en)* | 2019-12-09 | 2020-03-17 | 中国科学院计算机网络信息中心 | A method and system for selecting edge computing nodes in a delay-sensitive network |
Non-Patent Citations (3)
| Title |
|---|
| SUKJIN CHOO 等: "Optimal Task Offloading and Resource Allocation", 《2018 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY CONVERGENCE》* |
| 唐雄燕 等: "中国联通算力网络白皮书", 《中国联通》* |
| 雷波 等: "运营商边缘计算网络技术白皮书", 《边缘计算产业联盟（ECC）与网络5.0 产业和技术创新联盟（N5A）》* |
Cited By (44)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112153153B (en)* | 2020-09-28 | 2023-01-20 | 北京大学深圳研究生院 | Coordinated distributed intra-network resource scheduling method and system and storage medium |
| CN112153153A (en)* | 2020-09-28 | 2020-12-29 | 北京大学深圳研究生院 | Coordinated distributed intra-network resource scheduling method and system and storage medium |
| WO2022073229A1 (en)* | 2020-10-10 | 2022-04-14 | Telefonaktiebolaget Lm Ericsson (Publ) | Method and apparatus for managing load of network node |
| WO2022100365A1 (en)* | 2020-11-12 | 2022-05-19 | 华为云计算技术有限公司 | Method, system, and device for managing artificial intelligence application task, and storage medium |
| CN114500521B (en)* | 2020-11-13 | 2025-01-14 | 中国移动通信有限公司研究院 | A computing power scheduling method, device, scheduling equipment, system and storage medium |
| CN114500521A (en)* | 2020-11-13 | 2022-05-13 | 中国移动通信有限公司研究院 | Computing power scheduling method, device, scheduling equipment, system and storage medium |
| CN112465359A (en)* | 2020-12-01 | 2021-03-09 | 中国联合网络通信集团有限公司 | Calculation power calling method and device |
| CN112465359B (en)* | 2020-12-01 | 2024-03-15 | 中国联合网络通信集团有限公司 | Computing power calling method and device |
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| WO2022143748A1 (en)* | 2020-12-31 | 2022-07-07 | 维沃移动通信有限公司 | Information processing method and apparatus, device, and storage medium |
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| CN114756340A (en)* | 2022-03-17 | 2022-07-15 | 中国联合网络通信集团有限公司 | Computing power scheduling system, method, device and storage medium |
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| CN115426327A (en)* | 2022-11-04 | 2022-12-02 | 北京邮电大学 | Calculation force scheduling method and device, electronic equipment and storage medium |
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| CN117434990A (en)* | 2023-12-20 | 2024-01-23 | 成都易联易通科技有限责任公司 | Granary environment control method and system |
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