CN111930512A - Optimized grouping method and system for improving edge acquisition efficiency - Google Patents
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Abstract
The invention discloses an optimized grouping method and system for improving edge acquisition efficiency, which comprises the following steps: sorting the data node set according to the size of the initial address; dividing a data node set into a plurality of subsets according to a set rule according to an address difference value between adjacent data nodes; screening effective groups for each subset, and determining all possible group acquisition strategies based on the screened effective groups; calculating the acquisition time of each group acquisition strategy, and determining the optimal group acquisition strategy; and combining the optimal grouping acquisition strategies of all the subsets to obtain the optimal grouping acquisition strategy of the whole data node set. The method has the advantages of shorter time for edge acquisition by the grouping optimization strategy, higher efficiency, greatly reduced time delay of edge acquisition and improved real-time property of edge acquisition.
Description
Technical Field
The invention relates to the technical field of edge acquisition, in particular to an optimized grouping method and system for improving edge acquisition efficiency.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In an application scenario of edge acquisition and edge calculation, a conventional edge acquisition method generally acquires information of all data nodes needing edge acquisition, and then sequentially generates an acquisition instruction of each data node according to the node information; and performing edge acquisition on each data node by using the acquisition instruction of the data node, and acquiring the node state and the data of the acquired data according to the rule of the protocol. The method collects data in sequence and in series among nodes, and the edge collection efficiency is very slow due to the fact that the ratio of effective load data to protocol data is too small and the time consumption of execution of a plurality of instructions is low.
The prior art optimizes the conventional edge acquisition method and logically divides the address space into a plurality of groups according to a fixed address length. And distributing the nodes to be acquired into corresponding groups according to the addresses of the nodes. The data to be acquired is acquired in groups, so that the serial acquisition among the nodes is optimized to be the serial acquisition among the groups, and the acquisition efficiency can be improved by several times to tens of times due to the logic structure of the parallel acquisition of the data nodes in the groups.
However, in practical applications, the inventor finds that the grouping method is a fixed address range grouping, defines logical addresses, and groups all nodes in the range. The method often cannot find a relatively reasonable grouping method, and the effect of acquisition optimization is reduced on the contrary due to an unreasonable or non-optimal grouping method in part of cases; such as:
the method comprises six Modbus-RTU protocols, wherein the register type is a data node (node or data point for short) for holding a register, and the addresses are 0, 31, 32, 63, 64 and 65; the grouping method using 32 addresses for one logical grouping results in: [0, 31], [32, 63], [64, 65 ]; the packet [0, 31] collects the data of all the data nodes with the addresses of 0 to 31; at this time, the data payload has 32 data points, the payload has 2 data points, and the dummy payload has 30 data points. For this grouping, the percentage of valid data points was 6.25%. In addition, protocol leading data and protocol trailing data are also arranged in the communication protocol, and the total effective data percentage is 5.7% which is too low. The replied data contains a large amount of redundant invalid load data, and when a serial port mode is used and the baud rate is low or other modes are adopted, the data transmission time of the large amount of redundant data is very time-consuming, and the acquisition efficiency is reduced.
Disclosure of Invention
In view of this, the invention provides an optimized grouping method and system for improving the efficiency of edge acquisition, and an optimized grouping strategy is adopted to improve the efficiency of edge acquisition.
In order to achieve the above purpose, in some embodiments, the following technical solutions are adopted:
an optimized grouping method for improving edge acquisition efficiency comprises the following steps:
sorting the data node set according to the size of the initial address;
dividing a data node set into a plurality of subsets according to a set rule according to an address difference value between adjacent data nodes;
screening effective groups for each subset, and determining all possible group acquisition strategies based on the screened effective groups; calculating the acquisition time of each group acquisition strategy, and determining the optimal group acquisition strategy;
and combining the optimal grouping acquisition strategies of all the subsets to obtain the optimal grouping acquisition strategy of the whole data node set.
In other embodiments, the following technical solutions are adopted:
an optimized grouping system for improving edge acquisition efficiency, comprising:
means for sorting the set of data nodes according to starting address size;
the device is used for splitting the data node set into a plurality of subsets according to a set rule according to the address difference value between adjacent data nodes;
the system is used for screening effective groups for each subset, and determining all possible group acquisition strategies based on the screened effective groups; a device for calculating the collection time of each group collection strategy and determining the optimal group collection strategy;
and the device is used for combining the optimal grouping acquisition strategies of all the subsets to obtain the optimal grouping acquisition strategy of the whole data node set.
In other embodiments, the following technical solutions are adopted:
a terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer readable storage medium stores a plurality of instructions adapted to be loaded by a processor and to perform the above-described optimized grouping method for improving edge gather efficiency.
In other embodiments, the following technical solutions are adopted:
a computer readable storage medium having stored therein a plurality of instructions adapted to be loaded by a processor of a terminal device and to execute the above optimized grouping method for improving edge gather efficiency.
Compared with the prior art, the invention has the beneficial effects that:
compared with a grouping strategy with fixed address length, the grouping optimization strategy of the method has shorter time for edge acquisition and higher efficiency, can greatly reduce the time delay of the edge acquisition and improve the real-time property of the edge acquisition.
The invention divides the whole data node set into a plurality of subsets to be processed respectively, thereby greatly reducing the data volume needing to be processed at a time and reducing the requirement on the performance of the data processing equipment.
According to the invention, through setting multiple effective grouping screening strategies, the grouping which does not meet the requirements can be directly filtered, and the grouping acquisition strategy is determined based on the screened effective grouping, so that the complexity of data processing is reduced, and the data processing efficiency is improved.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
Fig. 1 is a flowchart of an optimized grouping method for improving edge acquisition efficiency according to an embodiment of the present invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
Example one
In one or more embodiments, an optimized grouping method for improving edge acquisition efficiency is disclosed, referring to fig. 1, including the following steps:
step S101: sorting the data node set according to the size of the initial address;
step S102: dividing a data node set into a plurality of subsets according to a set rule according to an address difference value between adjacent data nodes;
specifically, firstly, determining an address difference value between every two adjacent data nodes, and sequencing the data nodes from large to small; then the resolution is carried out according to the following process:
(1) splitting two non-split adjacent data nodes with the maximum address difference value;
(2) judging whether a subset meets a set condition after the data nodes are split;
(3) if not, entering the step (4); if yes, intercepting the subset, and entering the step (5);
(4) returning to the step (1) to continue splitting;
(5) judging whether the data node set is completely split or not, and if so, finishing; otherwise, returning to the step (1) to continue splitting the residual data nodes.
Wherein the subset satisfying the set condition includes:
condition 1: the number of nodes in the subset does not exceed the limited value X (X subset number limit parameter).
Condition 2: the address range of the subset does not exceed the limited value Y (Y subset address range limitation parameter).
When the two conditions are both satisfied, determining that the subset satisfies the condition; the values of X and Y can be flexibly configured according to requirements; the smaller the values of X and Y are, the more the number of the subsets is, the lower the optimization degree is, and the lower the time complexity is; the larger the values of X and Y, the larger the number of subsets, the higher the optimization degree and the higher the time complexity.
In this embodiment, the maximum number of the subsets is set as needed, and if the number of the split subsets reaches the maximum number, it is determined that the data node set is split completely.
It should be noted that when the address difference between consecutive data nodes, that is, adjacent data nodes, is 1, splitting is not required.
For example, the data node set obtained by sorting the starting address size is as follows:
x represents that node data exists under the current address, O represents that the node data does not exist under the current address, and 1-10 are addresses of data nodes.
When splitting is performed, the address difference between two data nodes with addresses 3 and 6 is the largest, so the data set is split into:
and judging whether the two subsets meet the condition or not, and then splitting the subsets which do not meet the condition.
Step S103: screening effective groups for each subset, and determining all possible group acquisition strategies based on the screened effective groups; calculating the acquisition time of each group acquisition strategy, and determining the optimal group acquisition strategy;
specifically, the specific process of screening valid packets includes:
(1) firstly, traversing all possible grouping modes of data nodes in a subset; if there are n data nodes, the number of all packets is:
such as: the subset has 5 points [0, 31, 32, 63, 64 ], denoted [ A, B, C, D, E ] for convenience of description. All possible grouping modes include the following 15 types:
(2) in addition to the grouping of the individual data nodes (such as A, B, C, D, E described above), the remaining grouping modes are screened, and the grouping screening method includes:
grouping and screening the adhesivity:
when the address difference value of any two adjacent data nodes is smaller than a set value Z, rejecting all groups only containing any one of the two data nodes; when the difference between two data nodes is smaller than Z, the two data nodes are called a bonded node pair. The smaller the value of Z, the greater the number of packets filtered and the lower the degree of optimization.
Exclusion group screening:
when the address difference value of any two adjacent data nodes is larger than a set value L, rejecting all groups containing the two nodes at the same time; these two nodes are referred to as an exclusive node pair. The larger the value of L, the greater the number of packets filtered and the lower the degree of optimization.
Thirdly, grouping and screening address ranges:
if the address difference value between the first data node and the last data node in the packet is larger than a set address range M, rejecting the packet; the smaller the value of M, the greater the number of packets filtered and the lower the degree of optimization.
Grouping efficiency screening:
generating an acquisition instruction of a corresponding group according to the rule of the protocol, determining the acquisition time of each group, and rejecting the groups with low acquisition efficiency based on the acquisition time; for example: the acquisition time for group a was 5 seconds, for group B was 3 seconds, and for group AB was 10 seconds. And (4) considering that the grouping efficiency of the grouping AB is low, and rejecting.
And the remaining groups after layer-by-layer screening are effective groups.
In some embodiments, a direct detection method may be adopted to obtain an acquisition time of each packet, where the acquisition time is an overall time used for a data acquisition command to start sending to a receiving and analyzing device to return data; the method mainly comprises the following steps: the acquisition equipment sends the generated acquisition instruction to the lower equipment for data acquisition, the lower equipment receives the acquisition instruction and then responds, the acquisition equipment receives the data and analyzes the data and the like; the response time comprises the time for inquiring and collecting the data according to the collecting instruction and the time for returning the inquired data to the collecting equipment.
In view of the fact that the direct probing method is used to determine the acquisition time of each packet, this method is inefficient in that the actual probing data acquisition command is required to start sending to the overall time spent on receiving and analyzing the data returned by the lower device.
Thus, in other embodiments, the acquisition time for each packet is obtained using a predictive analysis method. Specifically, when data interaction is performed between the data acquisition device and the lower device, the required time S mainly includes: data acquisition command data transmission time S1Data analysis and processing time S of lower device4Sending time S of response data of lower equipment2And a fixed delay time S consumed for each acquisition3(ii) a I.e. S ═ S1+S2+S3+S4；
Wherein, the time S1And time S2For collecting the most time-spent in the event, and the time S1Is proportional to the length of the instruction data, time S2Proportional to the length of the data returned by the lower device.
Therefore, the specific process of obtaining the acquisition time of each packet by using the predictive analysis method includes:
(1) data acquisition command data transmission time S1：
The content and the length LEN of the command data can be determined through the generated grouping acquisition instruction; after the length LEN of the command data is determined, the sending time of the command data can be calculated through the current parameters. For example: serial port 232 mode, baud rate 9600, no check bit, data bit 8 bit, stop bit 1 bit. The data sending time can be calculated by the length LEN and the current parameter, and 9600/(1+8+1) ≈ 960byte/S, and LEN/960S is required in total, namely, the time a consumed for sending a command of 100 bytes is 100/960 ≈ 0.1 second.
(2) Sending time S of lower equipment response data2：
Since the communication protocol between the requester and the responder is fixed, the data format and the data length LE of the response can be deduced from the request instructionAnd N is added. Further calculating the sending time S of the response data of the lower device2。
(3) Fixed delay time S consumed for each acquisition3：
Each acquisition is due to the delay time S of the analysis processing3The time is controllable and fixed and is a fixed parameter under the control of the acquisition equipment.
(4) Data analysis and processing time S of lower device4：
Although the parameters of each manufacturer are different for each protocol, the data analysis and processing time S of the lower device4Are all less than 1ms and are negligible.
Such as:
there are some differences in the instructions for each type of register for each vendor or each protocol, taking the modbus protocol as an example:
for example, the 03 function code format of modbus protocol:
collecting commands: {0103000000204412}
Protocol fixed format: [ device number ] [ function code ] [ start address ] [ unit length ] [ CRC check ]
The device number is fixed by one byte; the function code is fixed by one byte; the start address is fixed by two bytes; the length of the register unit is fixed by two bytes; the CRC check fixes 2 bytes;
the instruction length is fixed by 8 bytes, about 8 ms.
The slave replies with data: { 01034088880000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000003131B 7E 8}
Protocol fixed format: [ device number ] [ function code ] [ byte number ] [ data ] [ CRC check ]
The device number is fixed by one byte; the function code is fixed by one byte; the byte number is fixed by one byte;
the data length is determined by the unit length in the acquisition command. For example: the data with the unit length field and the sequence number [5,6] in the acquisition instruction is 0x 000 x20, namely 0x0020, and is converted into the data with the 10-system length of 32, namely 32 register units, each register unit has 2 bytes, and the available data length is 64 bytes.
The CRC check fixes 2 bytes;
the reply data amounts to 69 bytes, about 69 ms.
The command sending time is 8ms, the response data sending time is 69ms, and the fixed parameter D delay time is added to estimate the collection time of the packet.
In this embodiment, a combination of a plurality of valid packets, which include all nodes and each node includes only once, is determined as one packet acquisition policy.
Determining all possible grouping collection strategies based on the screened effective groups, wherein the specific process comprises the following steps:
sorting according to the address of the initial data node according to the principle that the initial nodes of the effective groups in each row are the same, and respectively placing the effective groups into different rows; such as:
firstly, selecting a first group of a group acquisition strategy, sequentially polling a first row, and selecting one group as the first group; and if all the groups in the first row are completely traversed, the collection strategy is completely traversed.
And determining the tail node of the last collection strategy group, and selecting the next node as the starting node of the next group.
Finding out the row where the starting node is located, and then sequentially selecting each group; until the last node E is found.
For example, ABC of the first row is selected as an acquisition strategy head group, and the group is added into an acquisition strategy set; then taking the node D as the head node of the next group, and selecting the group from the fourth row, wherein D or DE can be selected; if node D is selected, continue to select group E from the fifth row, resulting in a group acquisition policy: ABC/D/E; if the node DE is selected, a packet acquisition policy is obtained: ABC/DE.
And calculating the sum of the acquisition time of all the groups in each group acquisition strategy, and selecting the group acquisition strategy with the shortest acquisition time as the optimal group acquisition strategy of the subset.
Step S104: and combining the optimal grouping acquisition strategies of all the subsets to obtain the optimal grouping acquisition strategy of the whole data node set.
Compared with the traditional edge acquisition method or the fixed grouping edge acquisition method, the method can find the optimized grouping acquisition strategy by using the shortest time, has shorter time for edge acquisition and higher efficiency, can greatly reduce the time delay of edge acquisition and improve the real-time property of edge acquisition.
Example two
In one or more embodiments, an optimized grouping system for improving edge acquisition efficiency is disclosed, comprising:
means for sorting the set of data nodes according to starting address size;
the device is used for splitting the data node set into a plurality of subsets according to a set rule according to the address difference value between adjacent data nodes;
the system is used for screening effective groups for each subset, and determining all possible group acquisition strategies based on the screened effective groups; a device for calculating the collection time of each group collection strategy and determining the optimal group collection strategy;
and the device is used for combining the optimal grouping acquisition strategies of all the subsets to obtain the optimal grouping acquisition strategy of the whole data node set.
It should be noted that the specific working manner of the apparatus is implemented by using the method disclosed in step S101 to step S104 in the first embodiment, and details are not described again.
EXAMPLE III
In one or more embodiments, a terminal device is disclosed, which includes a server, where the server includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the optimized grouping method for improving edge capture efficiency in the first embodiment. For brevity, no further description is provided herein.
It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general purpose processors, digital signal processors DSP, application specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and so on. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may include both read-only memory and random access memory, and may provide instructions and data to the processor, and a portion of the memory may also include non-volatile random access memory. For example, the memory may also store device type information.
In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software.
The optimized grouping method for improving the edge acquisition efficiency in the first embodiment may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, among other storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor. To avoid repetition, it is not described in detail here.
Those of ordinary skill in the art will appreciate that the various illustrative elements, i.e., algorithm steps, described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. An optimized grouping method for improving edge acquisition efficiency is characterized by comprising the following steps:
sorting the data node set according to the size of the initial address;
dividing a data node set into a plurality of subsets according to a set rule according to an address difference value between adjacent data nodes;
screening effective groups for each subset, and determining all possible group acquisition strategies based on the screened effective groups; calculating the acquisition time of each group acquisition strategy, and determining the optimal group acquisition strategy;
and combining the optimal grouping acquisition strategies of all the subsets to obtain the optimal grouping acquisition strategy of the whole data node set.
2. The optimal grouping method for improving the edge collection efficiency according to claim 1, wherein the data node set is split into a plurality of subsets according to a set rule according to an address difference between adjacent data nodes, and the specific process includes:
(1) splitting two non-split adjacent data nodes with the maximum address difference value;
(2) judging whether a subset meets a set condition after the data nodes are split;
(3) if not, entering the step (4); if yes, intercepting the subset, and entering the step (5);
(4) returning to the step (1) to continue splitting;
(5) judging whether the data node set is completely split or not, and if so, finishing; otherwise, returning to the step (1) to continue splitting the residual data nodes.
3. The optimal grouping method for improving the edge acquisition efficiency according to claim 2, wherein the setting of the conditions in the step (2) specifically comprises:
the number of nodes in the subset does not exceed a set value X;
the address range of the subset does not exceed the set value Y.
4. The optimal grouping method for improving the edge collection efficiency according to claim 1, wherein for each subset, the effective grouping is screened by a specific process comprising:
acquiring all possible grouping modes of the data nodes in the subset;
and screening the rest grouping modes except the grouping of the single data node, wherein the grouping screening method at least adopts one mode of the following modes:
when the address difference value of any two adjacent data nodes is smaller than a set value Z, rejecting all groups only containing any one of the two data nodes;
when the address difference value of any two adjacent data nodes is larger than a set value L, rejecting all groups containing the two nodes simultaneously;
if the difference value of the address of the first data node and the address of the last data node in the group is larger than the set address range M, rejecting the group;
and fourthly, determining the acquisition time of each group, and rejecting the groups with low acquisition efficiency based on the acquisition time.
5. The method as claimed in claim 1, wherein a combination of a plurality of valid packets containing all data nodes and each data node containing only once is determined as a packet collection policy.
6. The optimal grouping method for improving the edge acquisition efficiency as claimed in claim 1, wherein the acquisition time of each grouping acquisition strategy is calculated, and the one with the shortest acquisition time is selected as the optimal grouping acquisition strategy.
7. The optimized grouping method for improving the edge acquisition efficiency as claimed in claim 1, wherein the acquisition time of each grouping acquisition strategy comprises: the data acquisition command starts to be sent to the whole time spent on receiving and analyzing the data returned by the lower equipment;
alternatively, the first and second electrodes may be,
determining the acquisition time of each group acquisition strategy by adopting a predictive analysis method, wherein the specific process comprises the following steps:
length estimation data acquisition instruction sending time S based on data acquisition instruction1；
Determining the length of response data based on the data acquisition instruction, and estimating the sending time S of the response data of the lower equipment based on the data length2；
The data acquisition time is as follows: s ═ S1+S2+S3+S4(ii) a Wherein S is3The fixed delay time in the data acquisition process is a fixed value; s4The data analysis and processing time for the lower equipment is generally ignored;
the method is adopted to obtain the acquisition time of each group in the group acquisition strategy, and further obtain the acquisition time of the group acquisition strategy.
8. An optimized grouping system for improving edge acquisition efficiency, comprising:
means for sorting the set of data nodes according to starting address size;
the device is used for splitting the data node set into a plurality of subsets according to a set rule according to the address difference value between adjacent data nodes;
the system is used for screening effective groups for each subset, and determining all possible group acquisition strategies based on the screened effective groups; a device for calculating the collection time of each group collection strategy and determining the optimal group collection strategy;
and the device is used for combining the optimal grouping acquisition strategies of all the subsets to obtain the optimal grouping acquisition strategy of the whole data node set.
9. A terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; a computer readable storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the optimized grouping method for improving edge gather efficiency of any of claims 1-7.
10. A computer-readable storage medium having stored thereon a plurality of instructions, wherein the instructions are adapted to be loaded by a processor of a terminal device and to perform the optimized grouping method for improving edge gather efficiency as claimed in any one of claims 1 to 7.
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| CN112910860A (en) * | 2021-01-19 | 2021-06-04 | 广州特瑞电气设备有限公司 | Modbus communication protocol-based data frame combining acquisition and aggregation transmission method and device, and intelligent gateway |
| CN113194038A (en) * | 2021-04-06 | 2021-07-30 | 重庆芯力源科技有限公司 | Data forwarding method of intelligent edge gateway |
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