Edge cloud node data adaptive transmission method

Abstract

The invention discloses an edge cloud node data adaptive transmission method, which relates to the technical field of information transmission, and comprises the following steps: firstly, starting information transmission, and starting to work by an edge cloud node; then, the edge cloud node sends a test information packet to an edge cloud server at the information acquisition starting time; the edge cloud server performs network state test based on the test information packet to obtain a network state index at the moment; after receiving the network state index, the edge cloud node evaluates the network state index to obtain a suitable optimal transmission strategy; the edge cloud server reads edge cloud node queue data; and finally, the edge cloud node transmits data to the edge cloud server based on the optimal transmission strategy or the normal transmission strategy. According to the invention, for an edge cloud node data transmission scene, the network state is obtained when the data is sent each time, the data transmission strategy is adaptively judged, and the efficiency of edge cloud collection of the data collected by the edge cloud node is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of information transmission, and in particular to an edge cloud node data adaptive transmission method. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.

[0003] In the field of industrial automation, the reliability and fault detection mechanism of intelligent equipment are crucial to ensure the continuity of production processes and reduce maintenance costs. Existing technologies such as cloud computing have massive computing and storage capabilities, but there are response delays and bandwidth limitations. Edge computing has high real-time performance but limited resources. Cloud-edge collaboration combines the advantages of both. It improves response speed and reduces bandwidth requirements through edge processing, while enhancing data processing capabilities and achieving more efficient data management capabilities. Intelligent operation and maintenance technology based on cloud-edge collaboration has received widespread attention and application. With the rise of edge computing technology, the importance of edge node device data transmission strategy in intelligent equipment fault detection scenarios has gradually become prominent. It aims to collect robot operation data in real time through edge node devices, and dynamically adjust the data transmission mode according to data characteristics and network conditions, thereby achieving efficient collaboration with the cloud to improve the real-time and accuracy of fault detection. The core function of edge cloud in a distributed computing environment is to collect data from multiple edge nodes, which are distributed in different geographical locations and are responsible for monitoring, collecting and transmitting various types of data, such as sensor readings, device status updates, etc. Due to the limited processing capacity of edge cloud, it is necessary to ensure that the amount of information received does not exceed its processing limit.

[0004] In the field of intelligent equipment operation and maintenance, edge computing technology is increasingly becoming one of the key technologies to improve data processing efficiency and reduce latency. As an important part of edge computing, edge cloud deploys data processing and storage resources close to the edge of the network, enabling data to be processed closer to the data source, thereby reducing the latency of data transmission from edge cloud to central cloud. However, although edge cloud provides convenience in data transmission, it still faces great challenges in ensuring the integrity of uploaded data in an environment where network status fluctuates frequently.

[0005] Fluctuations in network status, such as bandwidth fluctuations, increased bit error rates, and significantly increased packet loss, may cause incomplete data uploaded by edge nodes to the edge cloud. This not only increases the difficulty of edge cloud data processing, but may also affect the real-time and accuracy of the data.

[0006] In summary, existing technologies generally evaluate network status based on bandwidth utilization or several single indicators, but bandwidth alone cannot fully reflect network status in scenarios with high transmission accuracy. In addition, existing strategies are generally based on multi-path forwarding strategies, that is, when the quality of point-to-point communication decreases, the optimal path is found, without considering combining multiple transmission strategies to cope with network fluctuations. In order to meet this challenge, an adaptive data transmission method is urgently needed to adapt to the ever-changing network environment and ensure the effective transmission of data. Summary of the invention

[0007] The purpose of the present invention is to provide an edge cloud node data adaptive transmission method to solve the problems existing in the prior art.

[0008] The technical solution of the present invention is as follows:

[0009] An edge cloud node data adaptive transmission method, comprising:

[0010] Step S1: Information transmission starts and the edge cloud node starts working;

[0011] Step S2: In order to evaluate the current network status, the edge cloud node will send a test information packet to the edge cloud server at the information collection start time;

[0012] Step S3: The edge cloud server performs a network status test based on the test information packet to obtain a current network status indicator;

[0013] Step S4: After receiving the network status indicator, the edge cloud node evaluates the network status indicator and obtains a suitable optimal transmission strategy;

[0014] Step S5: The edge cloud server reads the edge cloud node queue data;

[0015] Step S6: The edge cloud node transmits data to the edge cloud server based on the optimal transmission strategy or the normal transmission strategy obtained in step S4.

[0016] Furthermore, the test information packet includes: data in a specific format, which is used to measure the network's bit error rate BER, packet loss rate PLR, and bandwidth utilization BW U and delay time ΔT.

[0017] Furthermore, the network status indicators include: network bit error rate BER, packet loss rate PLR, bandwidth utilization BW U and delay time ΔT.

[0018] Furthermore, the calculation formula of the bit error rate BER of the network is as follows:

[0019]

[0020] Among them, BER represents bit error rate, E represents the number of erroneous bits, and T represents the total number of transmitted bits;

[0021] The calculation formula of the packet loss rate PLR ​​is as follows:

[0022]

[0023] Among them, PLR represents the packet loss rate, P L Indicates the number of lost packets, P T Indicates the total number of transmitted data packets;

[0024] The bandwidth utilization BW U The calculation formula is as follows:

[0025]

[0026] Among them, BW U Indicates bandwidth utilization, BW A Represents the actual bandwidth used, BW T Represents the total bandwidth;

[0027] The calculation formula of the delay time ΔT is as follows:

[0028] ΔT=T2-T1

[0029] Among them, ΔT represents the delay time, T1 represents the sending time, and T2 represents the receiving time.

[0030] Furthermore, the step S4 comprises:

[0031] Step S41: Analyze the bit error rate BER, packet loss rate PLR, and bandwidth utilization BW respectively. U The four network status indicators of delay time ΔT are used to set the normal status critical value;

[0032] Step S42: Based on the normal state critical value set in step S41, a preset evaluation strategy is used to obtain a suitable optimal transmission strategy.

[0033] Furthermore, the evaluation strategy includes:

[0034] First: determine the bit error rate BER and packet loss rate PLR. If both exceed the normal state critical value at the same time, adopt a retransmission strategy;

[0035] Second: Determine the bandwidth utilization BW U and delay time ΔT. If both exceed the critical value of normal state at the same time, a multipath strategy is adopted;

[0036] Third: Determine whether the bit error rate BER or packet loss rate PLR ​​exceeds the normal state critical value. If so, adopt the packet subdivision strategy.

[0037] Furthermore, the retransmission strategy includes:

[0038] The retransmission strategy is used to handle lost packets during data transmission; when the sender does not receive an acknowledgment from the receiver, the packet is resent;

[0039] Assume that the sender sends a data packet. If no confirmation is received within the predetermined timeout period T, the data packet is resent;

[0040] T r =T i +ΔT

[0041] Among them, T r is the retransmission time, T i is the initial sending time, and ΔT is the waiting time for confirmation.

[0042] Furthermore, the multipath strategy includes:

[0043] Multipath strategies involve sending packets through multiple different paths to improve transmission reliability and efficiency;

[0044] Assume that there are m paths through which a data packet P can be sent; each path has a different transmission rate, and the total transmission rate is the sum of the transmission rates of all paths;

[0045] R=R1+R2+…+R m

[0046] Among them, R is the total transmission rate, R1, R2, ..., R m is the transmission rate of each path.

[0047] Furthermore, the subcontracting strategy includes:

[0048] The packetization strategy is the process of dividing a large data packet into multiple smaller data packets for transmission in order to adapt to the maximum transmission unit limit of the network layer or to improve transmission efficiency;

[0049] For a data packet of size L, if it exceeds the maximum transmission unit of the network layer, it will be divided into n smaller fragments, each of which is L / n in size;

[0050]

[0051] Where L is the size of the original data packet, is the size of each shard, and n is the number of shards.

[0052] Furthermore, the step S5 comprises:

[0053] The edge cloud server collects edge cloud node data. The amount of information collected by the edge cloud server from the edge cloud node is expressed by the following formula:

[0054]

[0055] Where I represents the total amount of information received by the edge cloud server, L i represents the amount of information of the i-th edge cloud node, F i Indicates whether the i-th collection point has collected data, F i =0 or F i =1, 0 means that the i-th edge cloud node does not transmit data, and 1 means that the i-th edge cloud node transmits data at the transmission time.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. The present invention can monitor the network status in real time and dynamically adjust the data transmission strategy according to the current network conditions. This method can select the most appropriate transmission strategy according to the changes in network bandwidth, delay, packet loss rate and other indicators to reduce data loss and improve transmission efficiency. At the same time, the adaptive data transmission method can also realize dynamic data packetization and retransmission to cope with transmission interruptions caused by network fluctuations.

[0058] 2. The present invention adopts an adaptive data transmission method, and the edge cloud node can automatically adjust the data transmission strategy according to the change of network status, thereby improving the efficiency and reliability of data transmission, which can not only reduce the delay and loss in the data transmission process, but also improve the efficiency and accuracy of edge cloud data processing. Therefore, the adaptive data transmission method is the key to achieving efficient data transmission and is of great significance to the development of edge computing technology.

[0059] 3. The present invention is aimed at edge cloud node data transmission scenarios. It obtains the network status each time data is sent, adaptively determines the data transmission strategy, and improves the efficiency of edge cloud collecting data from edge cloud nodes.

[0060] 4. The present invention also provides a connection structure of an edge cloud node device, which is composed of a microcomputer, an analog-to-digital converter, a power amplifier and an antenna. It has a smaller size and is more convenient to be deployed in the edge cloud node device. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a flow chart of a method for adaptive transmission of edge cloud node data;

[0062] Figure 2This is a schematic diagram of the composition of edge cloud node devices;

[0063] Figure 3 A timing diagram for sending and receiving data of the present invention;

[0064] Figure 4 Flowchart of adaptive data transmission for edge cloud nodes. DETAILED DESCRIPTION

[0065] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0066] The features and performance of the present invention are further described in detail below in conjunction with the embodiments.

[0067] Embodiment 1

[0068] First of all, it should be noted that when building edge cloud node devices, the design should follow the principles of lightweight and high efficiency, aiming to reduce the number of physical components of the device to reduce the weight of the device and reduce energy consumption. At the same time, the device has the characteristics of small size and easy deployment. This design concept aims to achieve rapid deployment of equipment in resource-constrained edge environments.

[0069] In the assembly line system of modern smart factories, intelligent equipment such as robotic arms and automatic guided vehicles (AGVs) play the role of edge computing nodes. These equipment collect and process key data in the production process in real time through precise sensors and actuators. In this scenario, in order to meet the needs of real-time monitoring and optimization of production processes, intelligent equipment uses an adaptive data transmission strategy to transmit data, and then the edge cloud server aggregates and preprocesses the data, and then transmits the compressed information to the central cloud server through an efficient data synchronization mechanism. This process reflects the efficient collaboration of cloud-edge collaborative technology on data, ensuring the timeliness and reliability of data transmission of smart factory assembly lines in complex network environments.

[0070] In the construction of smart factories, the demand for real-time, flexibility and efficiency is growing. In order to meet this demand, smart factories are gradually transforming from traditional centralized cloud computing architecture to more decentralized and flexible edge cloud systems. The introduction of edge cloud systems provides smart factories with a computing environment that is close to the data source and has real-time processing capabilities, thereby achieving the immediacy of data processing and analysis.

[0071] In the cloud-edge collaborative system, the edge cloud node is responsible for collecting sensor data in real time and processing it. Specifically, the process involves the following steps: First, the edge cloud node captures raw data from various sensors through its sensor interface; then, the collected information is processed, including data elimination and compression, in order to optimize data transmission efficiency. On this basis, the information is encoded and modulated, and the digital signal is converted into an analog signal through a digital-to-analog converter (DAC). Subsequently, the analog signal is enhanced by a power amplifier (PA) to ensure that the signal has sufficient energy level. Finally, the amplified signal is radiated through the antenna to achieve wireless communication with the edge cloud server. As a result, the edge cloud node not only realizes the proximal processing of data, but also ensures the efficient transmission of information to the edge cloud server, providing a basis for subsequent data analysis, storage and forwarding to the central cloud server.

[0072] In the edge cloud, in order to achieve optimal resource allocation and real-time processing of edge node data, it is necessary to ensure efficient data flow between the edge cloud and edge nodes. In this context, the node adaptive transmission strategy can dynamically adjust the data transmission mode according to factors such as network status, thereby improving the overall performance and reliability of the system.

[0073] Therefore, this embodiment proposes an edge cloud node data adaptive transmission method, which can effectively alleviate the problem of data loss during transmission under network fluctuations. It selects data transmission strategies in real time by comparing the network status indicator value with the indicator critical state to adapt to different network environments and needs, thereby improving the utilization efficiency of network resources, transmission efficiency, and network robustness. It has the advantages of real-time response, flexibility, intelligence, high efficiency, reliability, and stability.

[0074] It should be noted that, in this embodiment, the transmission strategy proposed mainly includes: a packetization strategy, a retransmission strategy, and a switching of a multi-path strategy.

[0075] In this embodiment, specifically, the retransmission strategy includes:

[0076] The retransmission strategy is used to handle lost packets during data transmission; when the sender does not receive an acknowledgment from the receiver, the packet is resent;

[0077] Assume that the sender sends a data packet. If no acknowledgment (ACK) is received within a predetermined timeout period T, the data packet is resent;

[0078] T r =T i +ΔT

[0079] Among them, T r is the retransmission time, T i is the initial sending time, and ΔT is the waiting time for confirmation.

[0080] In this embodiment, specifically, the multipath strategy includes:

[0081] Multipath strategies involve sending packets through multiple different paths to improve transmission reliability and efficiency;

[0082] Assume that there are m paths through which a data packet P can be sent; each path has a different transmission rate, and the total transmission rate is the sum of the transmission rates of all paths;

[0083] R=R1+R2+…+R m

[0084] Among them, R is the total transmission rate, R1, R2, ..., R m is the transmission rate of each path.

[0085] In this embodiment, specifically, the subcontracting strategy includes:

[0086] The packetization strategy is the process of dividing a large data packet into multiple smaller data packets for transmission in order to adapt to the maximum transmission unit limit of the network layer or to improve transmission efficiency;

[0087] For a data packet of size L, if it exceeds the maximum transmission unit of the network layer, it will be split into n smaller fragments, each of which is L / n in size (assuming L is divisible by n);

[0088]

[0089] Where L is the size of the original data packet, is the size of each shard, and n is the number of shards.

[0090] This embodiment takes into account the actual structure of edge cloud node devices, information collection and data transmission strategies, aiming to build an efficient and reliable system operation logic. From data collection to the selection of transmission strategies, and then to the adaptive transmission of data, it ensures that the system can operate stably in complex environments, while optimizing the efficiency and quality of data transmission. The following steps show the system logic operation of this embodiment.

[0091] See also Figure 1 , an edge cloud node data adaptive transmission method, comprising:

[0092] Step S1: Information transmission starts and the edge cloud node starts working;

[0093] Step S2: In order to evaluate the current network status, the edge cloud node will send a test information packet to the edge cloud server at the information collection start time;

[0094] Step S3: The edge cloud server performs a network status test based on the test information packet to obtain a current network status indicator;

[0095] Step S4: After receiving the network status indicator, the edge cloud node evaluates the network status indicator and obtains a suitable optimal transmission strategy;

[0096] Step S5: The edge cloud server reads the edge cloud node queue data;

[0097] Step S6: The edge cloud node transmits data to the edge cloud server based on the optimal transmission strategy or the normal transmission strategy obtained in step S4.

[0098] In this embodiment, the test information packet includes: data in a specific format, which is used to measure the network's bit error rate BER (Bit Error Rate), packet loss rate PLR ​​(Packet Error Rate), bandwidth utilization BW U (Bandwidth utilization) and delay time ΔT (Time delay).

[0099] In this embodiment, the network status indicators include: network bit error rate BER, packet loss rate PLR, bandwidth utilization BW U and delay time ΔT.

[0100] In this embodiment, specifically, the calculation formula of the bit error rate BER of the network is as follows:

[0101]

[0102] Among them, BER represents bit error rate, E represents the number of erroneous bits, and T represents the total number of transmitted bits;

[0103] The calculation formula of the packet loss rate PLR ​​is as follows:

[0104]

[0105] Among them, PLR represents the packet loss rate, P L Indicates the number of lost packets, PT Indicates the total number of transmitted data packets;

[0106] The bandwidth utilization BW U The calculation formula is as follows:

[0107]

[0108] Among them, BW U Indicates bandwidth utilization, BW A Represents the actual bandwidth used, BW T Represents the total bandwidth;

[0109] The calculation formula of the delay time ΔT is as follows:

[0110] ΔT=T2-T1

[0111] Among them, ΔT represents the delay time, T1 represents the sending time, and T2 represents the receiving time;

[0112] That is, by analyzing the transmission of these test packets, the performance of the network can be monitored in real time. In addition, by comparing the test results in different time periods, the changing trend of network performance can also be understood.

[0113] In this embodiment, specifically, step S4 includes:

[0114] Step S41: Analyze the bit error rate BER, packet loss rate PLR, and bandwidth utilization BW respectively. U The four network status indicators of delay time ΔT are used to set the normal status critical values; they are:

[0115] BER=a,PLR=b,BW U =c,ΔT=d

[0116] Step S42: Based on the normal state critical value set in step S41, a preset evaluation strategy is used to obtain a suitable optimal transmission strategy.

[0117] In this embodiment, specifically, the evaluation strategy includes:

[0118] First: determine the bit error rate BER and packet loss rate PLR. If both exceed the critical value of the normal state at the same time, adopt a retransmission strategy. It should be noted that the purpose of the retransmission strategy is to ensure reliable data transmission in an unreliable network environment. This strategy involves the process of resending lost data packets when data loss or damage is detected during data transmission.

[0119] Second: Determine the bandwidth utilization BW Uand delay time ΔT. If both exceed the critical value of the normal state at the same time, a multipath strategy is adopted. It should be noted that the multipath strategy optimizes the performance and reliability of data transmission by utilizing multiple parallel or alternative paths.

[0120] Third: Determine whether the bit error rate BER or packet loss rate PLR ​​exceeds the normal state critical value. If it exceeds, adopt the packetization strategy. It should be noted that the packetization strategy refers to dividing the continuous data stream into discrete data units, namely the so-called packets, for efficient transmission in the network. The core of this strategy is to divide the original data sequence into smaller, easier to manage fragments, while ensuring that these fragments can be accurately reassembled at the receiving end to restore the original data stream.

[0121] In this embodiment, specifically, step S5 includes:

[0122] The edge cloud server collects edge cloud node data. The amount of information collected by the edge cloud server from the edge cloud node can be expressed by the following formula:

[0123]

[0124] Where I represents the total amount of information received by the edge cloud server, L i represents the amount of information of the i-th edge cloud node, F i Indicates whether the i-th collection point has collected data, F i =0 or F i =1, 0 means that the i-th edge cloud node does not transmit data, and 1 means that the i-th edge cloud node transmits data at the transmission time.

[0125] In this embodiment, specifically, step S6 includes:

[0126] The collected edge cloud node data is transmitted according to the strategy determined in step S4, namely, the retransmission strategy, the multi-path strategy, the packetization strategy or the normal transmission strategy.

[0127] Embodiment 2

[0128] The existing cloud-edge collaborative system needs to upload the data collected by the edge node to the edge cloud, but the network fluctuations are large at this time. If general point-to-point transmission is used, it is easy to cause data loss. Therefore, a suitable information transmission strategy needs to be adopted. The bit error rate, packet loss rate, bandwidth utilization and delay time can fully display the network status and play an important role in network quality evaluation. By querying the historical data of the edge node transmission network, the normal state critical values ​​of the four indicators of bit error rate, packet loss rate, bandwidth utilization and delay time can be obtained. Assume that the normal state critical values ​​of the four indicators are:

[0129] BER=0.1%,PLR=1%,BWU =80%,ΔT=0.1s

[0130] When the indicator exceeds the critical value of the normal state, it will cause information loss, etc. In order to formulate a suitable transmission strategy, the following steps are taken at the beginning of information collection to determine the information transmission strategy.

[0131] Step S1: Information transmission starts and the edge cloud node starts working.

[0132] Step S2: In order to evaluate the current network status, the edge cloud node will send a test information packet to the edge cloud at the information collection start time;

[0133] By analyzing the transmission of these test packets, the performance of the network can be monitored in real time. In addition, by comparing the test results in different time periods, the changing trend of network performance can also be understood.

[0134] Step S3: The edge cloud server performs a network status test based on the test information packet to obtain the current network status indicator.

[0135] Step S4: After receiving the network status indicator, the edge cloud node evaluates the four indicators and obtains the best transmission strategy. The normal state critical values ​​of the four indicators, bit error rate, packet loss rate, bandwidth utilization and delay time, are set as follows: BER = 0.1%, PLR = 1%, BW U =80%, ΔT=0.1s, the following evaluation strategies are available:

[0136] First: determine the bit error rate BER and packet loss rate PLR. If both exceed the normal state critical value at the same time, adopt a retransmission strategy;

[0137] Second: Determine the bandwidth utilization BW U and delay time ΔT. If both exceed the critical value of normal state at the same time, a multipath strategy is adopted;

[0138] Third: Determine whether the bit error rate BER or packet loss rate PLR ​​exceeds the normal state critical value. If so, adopt the packet subdivision strategy.

[0139] Step S5: the edge cloud server reads the edge cloud node queue data, that is, the edge cloud server collects the edge cloud node data.

[0140] Step S6: Transmit the collected edge cloud node data according to the strategy determined in step S4, i.e., the retransmission strategy, multi-path strategy, packet sub-strategy or normal transmission strategy.

[0141] Embodiment 3

[0142] Figure 1The figure is a flow chart of adaptive data transmission of edge cloud nodes, which shows the overall process from the beginning to the end of information collection, mainly including sending test network status information, receiving the returned network status, determining which data transmission strategy to adopt according to the network status, and collecting edge cloud node data. The specific calculation process of the edge cloud node transmission data strategy mainly includes the network status calculation indicators bit error rate, packet loss rate, bandwidth utilization and delay time. By judging the data transmission indicator value, the transmission strategy is adaptively selected, and the network status is continuously judged after the collected data is uploaded to cope with the change of network status.

[0143] Figure 2 For the actual use scenario of edge cloud, in smart factories, intelligent devices such as robotic arms and AGVs will collect environmental data, equipment status, and operating performance in real time, and perform preliminary processing such as data elimination through edge cloud node devices to reduce data transmission delays and network burdens. The edge cloud server is close to the edge of the network, providing nearby data processing and storage capabilities. Data is aggregated on the edge cloud server. The central cloud server is located in a remote data center and has powerful computing power and storage resources. The central cloud is responsible for coordinating the computing task allocation, data synchronization and backup of edge nodes to ensure efficient system collaboration and data consistency.

[0144] Figure 3 The edge cloud node device is an integrated communication node consisting of a microcomputer, an analog-to-digital converter, a power amplifier, and a transmitting antenna. The advantages of this device are that it is easy to deploy, small in size, and has low space requirements, making it highly flexible and applicable in a variety of application scenarios. The microcomputer, as the core processing unit, is responsible for performing tasks such as data processing, storage, and transmission. The analog-to-digital converter (ADC) converts digital signals into analog signals for further processing by the computer. The power amplifier (PA) is responsible for amplifying its power to meet the transmission requirements of the transmitting antenna. The transmitting antenna is responsible for radiating the amplified signal into space to achieve wireless communication.

[0145] Figure 4 This is a timing diagram of sending and receiving data in the present invention. The edge cloud data node first sends a test packet to the edge cloud server, and the edge cloud server calculates the current network status. The edge cloud server sends the calculated network status data back to the edge cloud node. The edge cloud node calculates which outgoing strategy to adopt based on the current network indicators. After obtaining the transmission strategy, the collected data is transmitted to the edge and server for adaptively determining the transmission strategy and improving data transmission efficiency.

[0146] The above-mentioned embodiments only express the specific implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the protection scope of the present application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the technical solution concept of the present application, and these all belong to the protection scope of the present application.

[0147] This background section is provided to generally present the context of the invention, and the work of the presently named inventors, the work to the extent described in this background section, and aspects of this section that did not constitute prior art at the time of application are neither explicitly nor implicitly admitted to be prior art to the present invention.

Claims

1. A method for adaptively transmitting data of edge cloud nodes, characterized in that: include: Step S1: Information transmission starts and the edge cloud node starts working; Step S2: In order to evaluate the current network status, the edge cloud node will send a test information packet to the edge cloud server at the information collection start time; Step S3: The edge cloud server performs a network status test based on the test information packet to obtain a current network status indicator; Step S4: After receiving the network status indicator, the edge cloud node evaluates the network status indicator and obtains a suitable optimal transmission strategy; Step S5: The edge cloud server reads the edge cloud node queue data; Step S6: The edge cloud node transmits data to the edge cloud server based on the optimal transmission strategy or the normal transmission strategy obtained in step S4.

2. The method for adaptively transmitting edge cloud node data according to claim 1, characterized in that: The test information packet includes: data in a specific format, which is used to measure the network's bit error rate BER, packet loss rate PLR, and bandwidth utilization BW U and delay time ΔT.

3. The method for adaptively transmitting edge cloud node data according to claim 2, characterized in that: The network status indicators include: network bit error rate BER, packet loss rate PLR, bandwidth utilization BW U and delay time ΔT.

4. The method for adaptively transmitting edge cloud node data according to claim 3, characterized in that: The calculation formula of the bit error rate BER of the network is as follows: Among them, BER represents bit error rate, E represents the number of erroneous bits, and T represents the total number of transmitted bits; The calculation formula of the packet loss rate PLR ​​is as follows: Among them, PLR represents the packet loss rate, P L Indicates the number of lost packets, P T Indicates the total number of transmitted data packets; The bandwidth utilization BW U The calculation formula is as follows: Among them, BW U Indicates bandwidth utilization, BW A Represents the actual bandwidth used, BW T Represents the total bandwidth; The calculation formula of the delay time ΔT is as follows: ΔT=T2-T1 Among them, ΔT represents the delay time, T1 represents the sending time, and T2 represents the receiving time.

5. The method for adaptively transmitting edge cloud node data according to claim 3, characterized in that: The step S4 comprises: Step S41: Analyze the bit error rate BER, packet loss rate PLR, and bandwidth utilization BW respectively. U The four network status indicators of delay time ΔT are used to set the normal status critical value; Step S42: Based on the normal state critical value set in step S41, a preset evaluation strategy is used to obtain a suitable optimal transmission strategy.

6. The method for adaptively transmitting edge cloud node data according to claim 5, characterized in that: The evaluation strategy includes: First: determine the bit error rate BER and packet loss rate PLR. If both exceed the normal state critical value at the same time, adopt a retransmission strategy; Second: Determine the bandwidth utilization BW U and delay time ΔT. If both exceed the critical value of normal state at the same time, a multipath strategy is adopted; Third: Determine whether the bit error rate BER or packet loss rate PLR ​​exceeds the normal state critical value. If so, adopt the packet subdivision strategy.

7. The method for adaptively transmitting edge cloud node data according to claim 6, characterized in that: The retransmission strategy includes: The retransmission strategy is used to handle lost packets during data transmission; when the sender does not receive an acknowledgment from the receiver, the packet is resent; Assume that the sender sends a data packet. If no confirmation is received within the predetermined timeout period T, the data packet is resent; T r =T i +ΔT Among them, T r is the retransmission time, T i is the initial sending time, and ΔT is the waiting time for confirmation.

8. The method for adaptively transmitting edge cloud node data according to claim 6, characterized in that: The multipath strategy includes: Multipath strategies involve sending packets through multiple different paths to improve transmission reliability and efficiency; Assume that there are m paths through which a data packet P can be sent; each path has a different transmission rate, and the total transmission rate is the sum of the transmission rates of all paths; R=R1+R2+…+R m Among them, R is the total transmission rate, R1, R2, ..., R m is the transmission rate of each path.

9. The method for adaptively transmitting data of edge cloud nodes according to claim 6, characterized in that: The subcontracting strategy includes: The packetization strategy is the process of dividing a large data packet into multiple smaller data packets for transmission in order to adapt to the maximum transmission unit limit of the network layer or to improve transmission efficiency; For a data packet of size L, if it exceeds the maximum transmission unit of the network layer, it will be divided into n smaller fragments, each of which is L / n in size; Where L is the size of the original data packet, is the size of each shard, and n is the number of shards.

10. The method for adaptively transmitting edge cloud node data according to claim 1, characterized in that: The step S5 comprises: The edge cloud server collects edge cloud node data. The amount of information collected by the edge cloud server from the edge cloud node is expressed by the following formula: Where I represents the total amount of information received by the edge cloud server, L i represents the amount of information of the i-th edge cloud node, F i Indicates whether the i-th collection point has collected data, F i =0 or F i =1, 0 means that the i-th edge cloud node does not transmit data, and 1 means that the i-th edge cloud node transmits data at the transmission time.

Images