阅读说明：本技术 一种网络节点流控制方法、装置及云端服务器 (Network node flow control method and device and cloud server ) 是由 孙凤英 于 2021-09-23 设计创作，主要内容包括：本公开实施例提供一种网络节点流控制方法、装置及云端服务器,所述方法包括：获取所述网络节点组合中的流量检测信息；基于所述流量检测信息,获取各网络节点组合中的单一节点的单位时间流量；基于各网络节点组合中的单一节点的单位时间流量,确定各网络节点组合中的单一节点的预计距离空闲时间；基于各网络节点组合中的单一节点的预计距离空闲时间,以及单一节点关联的其他节点流量信息,对所述网络节点组合中内的单一节点进行流量控制。使用上述方法,可以实时监测节点流量信息,从而最大化利用节点资源,提升了节点利用率。(The embodiment of the disclosure provides a network node flow control method, a network node flow control device and a cloud server, wherein the method comprises the following steps: acquiring flow detection information in the network node combination; acquiring unit time flow of a single node in each network node combination based on the flow detection information; determining the estimated distance idle time of a single node in each network node combination based on the unit time flow of the single node in each network node combination; and carrying out flow control on the single node in each network node combination based on the expected distance idle time of the single node in each network node combination and other node flow information related to the single node. By using the method, the node flow information can be monitored in real time, so that the node resources are utilized to the maximum extent, and the node utilization rate is improved.)

1. A method of network node flow control, comprising:

acquiring flow detection information in a network node combination;

acquiring unit time flow of a single node in each network node combination based on the flow detection information;

determining the estimated distance idle time of a single node in each network node combination based on the unit time flow of the single node in each network node combination;

and carrying out flow control on the single node in each network node combination based on the expected distance idle time of the single node in each network node combination and other node flow information related to the single node.

2. The method according to claim 1, wherein the obtaining the traffic per unit time of a single node in each network node combination based on the traffic detection information comprises:

identifying current transmission data of a single node when the single node is detected in the traffic detection information;

if the current transmission data of the single node is cache data, acquiring the size information of the cache data, and acquiring the unit time flow of the single node based on the size information of the data.

3. The method of claim 2, wherein identifying the currently transmitted data for the single node comprises:

if the current transmission data of the single node is live streaming data, the instantaneous flow information of the single node is periodically detected, and the unit time flow of the single node is obtained through weighted average based on the instantaneous flow information.

4. The method of claim 3, wherein the controlling the flow of the single node in each network node combination based on the expected distance idle time of the single node and other node traffic information associated with the single node comprises:

if the current transmission data of the single node is cache data, calculating the size information of the residual data based on the size information of the cache data;

calculating a predicted distance idle time based on the remaining data size information and the single data traffic; or

If the current transmission data of the single node is live streaming data, periodically detecting the unit time flow;

and when the flow rate per unit time is lower than a first preset value, setting the predicted distance idle time as a second preset value.

5. A network node flow control apparatus, comprising:

the flow detection module is used for detecting flow detection information in the network node combination;

the calculation module is used for acquiring the unit time flow of a single node in each network node combination based on the flow detection information;

the time control module is used for determining the estimated distance idle time of a single node in each network node combination based on the unit time flow of the single node in each network node combination;

and the main control module is used for carrying out flow control on the single node in the network node combination based on the estimated distance idle time of the single node in each network node combination and other node flow information related to the single node.

6. The apparatus of claim 5, the computing module to further:

identifying current transmission data of a single node when the single node is detected in the traffic detection information;

if the current transmission data of the single node is cache data, acquiring the size information of the cache data, and acquiring the unit time flow of the single node based on the size information of the data.

7. The apparatus of claim 6, the computing module to further:

if the current transmission data of the single node is live streaming data, the instantaneous flow information of the single node is periodically detected, and the unit time flow of the single node is obtained through weighted average based on the instantaneous flow information.

8. The apparatus of claim 7, the master control module further to:

if the current transmission data of the single node is cache data, calculating the size information of the residual data based on the size information of the cache data;

calculating a predicted distance idle time based on the remaining data size information and the single data traffic; or

If the current transmission data of the single node is live streaming data, periodically detecting the unit time flow;

and when the flow rate per unit time is lower than a first preset value, setting the predicted distance idle time as a second preset value.

9. A computer readable storage medium storing instructions/executable code which, when executed by a processor of an electronic device, causes the electronic device to implement the method of any of claims 1-4.

10. Cloud server, characterized in that the cloud server comprises a processor, a machine-readable storage medium, and a network interface, the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is configured to be connected to at least one node control terminal in a communication manner, the machine-readable storage medium is configured to store a program, an instruction, or a code, and the processor is configured to execute the program, the instruction, or the code in the machine-readable storage medium to perform the network node flow control method according to any one of claims 1 to 4.

Technical Field

The present disclosure relates to the field of network node technologies, and in particular, to a network node flow control method and apparatus, and a cloud server.

Background

With the development of internet technology, more and more data needs to be transmitted via the internet. In the prior art, a plurality of network nodes are usually configured, and the transmission of network data is completed in a master node-slave node configuration manner in a grouping manner.

In the above manner, the master node usually collects the network resource utilization of each slave node, and in order to obtain the network resource utilization of the slave node in real time, the master node needs to continuously operate, which causes a burden to the master node. Meanwhile, the above method is not associated with data transmitted by the node, and thus lacks of foresight.

Disclosure of Invention

In order to overcome at least the above disadvantages in the prior art, an object of the present disclosure is to provide a method and an apparatus for controlling network node flow, and a cloud server.

In a first aspect, the present disclosure provides a method for controlling a network node flow, including:

acquiring flow detection information in a network node combination;

acquiring unit time flow of a single node in each network node combination based on the flow detection information;

determining the estimated distance idle time of a single node in each network node combination based on the unit time flow of the single node in each network node combination;

and carrying out flow control on the single node in each network node combination based on the expected distance idle time of the single node in each network node combination and other node flow information related to the single node.

In a second aspect, the present disclosure provides a network node flow control apparatus, including:

the flow detection module is used for detecting flow detection information in the network node combination;

the calculation module is used for acquiring the unit time flow of a single node in each network node combination based on the flow detection information;

the time control module is used for determining the estimated distance idle time of a single node in each network node combination based on the unit time flow of the single node in each network node combination;

and the main control module is used for carrying out flow control on the single node in the network node combination based on the estimated distance idle time of the single node in each network node combination and other node flow information related to the single node.

In a third aspect, an embodiment of the present disclosure provides a computer-readable storage medium, where instructions are stored, and when executed, cause a computer to perform the network node flow control method in the first aspect or any one of the possible designs of the first aspect.

In a fourth aspect, an embodiment of the present disclosure further provides a cloud server, where the cloud server includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is configured to be in communication connection with at least one node control terminal, the machine-readable storage medium is configured to store a program, an instruction, or a code, and the processor is configured to execute the program, the instruction, or the code in the machine-readable storage medium to perform the network node flow control method in any one of the first aspect or the possible design of the first aspect.

Based on any one of the above aspects, the method for controlling flow of network nodes in the embodiments of the present application obtains the traffic detection information in the network node combinations, obtains the unit time traffic of the single node in each network node combination based on the traffic detection information, determines the expected distance idle time of the single node in each network node combination based on the unit time traffic of the single node in each network node combination, and controls the flow of the single node in the network node combination based on the expected distance idle time of the single node in each network node combination and the traffic information of other nodes associated with the single node, with the above method, not only the node traffic information can be monitored in real time, but also the utilization relationship between the transmission data and the nodes is fully considered, so that the idle state of the node can be predicted in advance, thereby maximizing the utilization of the node resources, the node utilization rate is improved.

Drawings

To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present disclosure and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings may be obtained from the drawings without inventive effort.

Fig. 1 is a schematic view of an application scenario of a network node flow control system according to an embodiment of the present disclosure;

fig. 2 is a schematic flow chart of a network node flow control method according to an embodiment of the present disclosure;

fig. 3 is a functional block diagram of a network node flow control apparatus according to an embodiment of the present disclosure;

fig. 4 is a schematic block diagram of a structure of a cloud server for implementing the network node flow control method according to the embodiment of the present disclosure.

Detailed Description

The present disclosure is described in detail below with reference to the drawings, and the specific operation methods in the method embodiments can also be applied to the device embodiments or the system embodiments.

Fig. 1 is an interaction diagram of a network node flow control system 10 according to an embodiment of the present disclosure. The network node flow control system 10 may include a cloud server 100 and a node control terminal 200 communicatively connected to the cloud server 100. The network node flow control system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the network node flow control system 10 may include only a portion of the components shown in fig. 1 or may include other components.

In this embodiment, the node control terminal 200 may comprise a mobile device, a tablet computer, a laptop computer, etc., or any combination thereof. In some embodiments, the mobile device may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home devices may include control devices of smart electrical devices, smart monitoring devices, smart televisions, smart cameras, and the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a personal digital assistant, a gaming device, and the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or augmented reality device may include various virtual reality products and the like.

In this embodiment, the cloud server 100 and the node control terminal 200 in the network node flow control system 10 may execute the network node flow control method described in the following method embodiment in a matching manner, and specific steps executed by the cloud server 100 and the node control terminal 200 may refer to the detailed description of the following method embodiment.

To solve the technical problem in the foregoing background, fig. 2 is a schematic flow chart of a network node flow control method provided in the embodiment of the present disclosure, which may be executed by the cloud server 100 shown in fig. 1, and the network node flow control method is described in detail below.

Step S110, acquiring flow detection information in a network node combination;

step S120, based on the flow detection information, acquiring unit time flow of a single node in each network node combination;

step S130, determining the estimated distance idle time of the single node in each network node combination based on the unit time flow of the single node in each network node combination;

step S140, performing flow control on a single node in each network node combination based on the estimated distance idle time of the single node in each network node combination and other node flow information associated with the single node.

In one possible embodiment, step S120 further includes:

step S121, when detecting a single node in the flow detection information, identifying the current transmission data of the single node;

step S122, if the currently transmitted data of the single node is cache data, obtaining the size information of the cache data, and obtaining the unit time traffic of the single node based on the size information of the data.

In one possible embodiment, step S121 further includes:

step S1211, if the currently transmitted data of the single node is live streaming data, periodically detecting the instantaneous traffic information, and obtaining the unit time traffic of the single node by weighted average based on the instantaneous traffic information.

In one possible embodiment, step S140 further includes:

step S141, if the current transmission data of the single node is cache data, calculating the size information of the residual data based on the size information of the cache data;

step S142, calculating the estimated distance idle time based on the residual data size information and the single data flow; or

Step S143, if the current transmission data of the single node is live streaming data, periodically detecting the unit time flow;

and step S144, when the flow rate per unit time is lower than a first preset value, setting the estimated distance idle time as a second preset value.

Fig. 3 is a schematic diagram of functional modules of a network node flow control apparatus 300 according to an embodiment of the present disclosure, and in this embodiment, the network node flow control apparatus 300 may be divided into the functional modules according to a method embodiment executed by the cloud server 100, that is, the following functional modules corresponding to the network node flow control apparatus 300 may be used to execute the method embodiments executed by the cloud server 100. The network node flow control apparatus 300 may include a flow detection module 310, a calculation module 320, a time control module 330, and a main control module 340, and the functions of the functional modules of the network node flow control apparatus 300 are described in detail below.

The traffic detection module 310 may be configured to perform the step S110, namely, the traffic detection information in the network node combination.

The calculating module 320 may be configured to perform the step S120, namely, to obtain the flow rate per unit time of a single node in each network node combination based on the flow detection information.

The time control module 330 may be configured to perform the step S130, namely, determine the expected distance idle time of a single node in each network node combination based on the unit time traffic of the single node in each network node combination.

The main control module 340 may be configured to execute the step S140 described above, that is, configured to perform flow control on a single node in each network node combination based on the expected idle time of the single node and other node flow information associated with the single node.

In one possible embodiment, the calculating module 320 is further configured to:

identifying current transmission data of a single node when the single node is detected in the traffic detection information;

if the current transmission data of the single node is cache data, acquiring the size information of the cache data, and acquiring the unit time flow of the single node based on the size information of the data.

In one possible embodiment, the calculating module 320 is further configured to:

if the current transmission data of the single node is live streaming data, the instantaneous flow information of the single node is periodically detected, and the unit time flow of the single node is obtained through weighted average based on the instantaneous flow information.

In one possible embodiment, the main control module 340 is further configured to:

if the current transmission data of the single node is cache data, calculating the size information of the residual data based on the size information of the cache data;

calculating a predicted distance idle time based on the remaining data size information and the single data traffic; or

If the current transmission data of the single node is live streaming data, periodically detecting the unit time flow;

and when the flow rate per unit time is lower than a first preset value, setting the predicted distance idle time as a second preset value.

It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the flow rate detection module 310 may be a separate processing element, or may be integrated into a chip of the apparatus, or may be stored in a memory of the apparatus in the form of program code, and a processing element of the apparatus calls and executes the functions of the flow rate detection module 310. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), etc. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call the program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).

Fig. 4 is a schematic diagram illustrating a hardware structure of the cloud server 100 for implementing the control device according to the embodiment of the disclosure, as shown in fig. 4, the cloud server 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.

In a specific implementation process, at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, included in the network node flow control apparatus 300 shown in fig. 3), so that the processor 110 may perform the network node flow control method according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected through the bus 130, and the processor 110 may be configured to control the transceiving action of the transceiver 140, so as to perform data transceiving with the node control terminal 200.

For a specific implementation process of the processor 110, reference may be made to the above-mentioned method embodiments executed by the cloud server 100, and the implementation principle and the technical effect are similar, which are not described herein again.

In the embodiment shown in fig. 4, it should be understood that the processor may be a Central Processing Unit (CPU), other general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.

The machine-readable storage medium 120 may comprise high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.

The bus 130 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus 130 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.

In addition, the embodiment of the present disclosure also provides a readable storage medium, where a computer executing instruction is stored, and when a processor executes the computer executing instruction, the network node flow control method is implemented, for example.

The readable storage medium described above may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer.

Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present disclosure, and not for limiting the same; while the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present disclosure.