CN114615294B - Electric power internet of things gateway edge calculation method - Google Patents
Electric power internet of things gateway edge calculation method Download PDFInfo
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- CN114615294B CN114615294B CN202210176072.6A CN202210176072A CN114615294B CN 114615294 B CN114615294 B CN 114615294B CN 202210176072 A CN202210176072 A CN 202210176072A CN 114615294 B CN114615294 B CN 114615294B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y10/00—Economic sectors
- G16Y10/35—Utilities, e.g. electricity, gas or water
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/66—Arrangements for connecting between networks having differing types of switching systems, e.g. gateways
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0893—Assignment of logical groups to network elements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
Abstract
The invention provides an electric power internet of things gateway edge calculation method, which comprises the following steps: determining an edge computing process of the power internet of things gateway, setting an edge computing rule, making a side cloud coordination mode, and guiding the edge computing process, the edge computing rule and the side cloud coordination mode of the power internet of things gateway into a cache module for caching; starting the power internet of things gateway; and calling an edge calculation flow of the power internet of things gateway stored in the buffer module, realizing edge task allocation according to the edge calculation flow of the power internet of things gateway and a side cloud cooperation mode, obtaining data information of the power terminal equipment, and performing edge calculation according to an edge calculation rule aiming at the data information to obtain a calculation result. According to the electric power internet of things gateway edge computing method, the tasks issued by the electric power network are cooperatively distributed in a side cloud cooperation mode, and the matching of the sensing network and the communication network to the task data is improved.
Description
Technical Field
The invention relates to the field of power system state monitoring, in particular to a power internet of things gateway edge calculation method.
Background
At present, the problem that cooperative distribution of power edge users is difficult to achieve in an electric power internet of things gateway edge computing method is not suitable for dynamically-changed power grid tasks, and similar task information is difficult to match between an electric power internet of things and a communication network and a perception network, so that the invention provides the electric power internet of things gateway edge computing method, cooperative distribution of tasks issued by the electric power network is achieved in a side cloud cooperative mode, and matching of the perception network and the communication network to task data is improved.
Disclosure of Invention
The invention aims to provide an edge calculation method for an electric power internet of things gateway, which aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a method for computing an edge of a power Internet of things gateway comprises the following steps:
determining an edge computing process of the power internet of things gateway, setting an edge computing rule, making a side cloud coordination mode, and guiding the edge computing process, the edge computing rule and the side cloud coordination mode of the power internet of things gateway into a cache module for caching;
starting the power internet of things gateway;
calling the electric power internet of things gateway edge calculation flow stored in the buffer module, realizing edge task allocation according to the edge cloud cooperation mode and the electric power internet of things gateway edge calculation flow, obtaining data information of electric power terminal equipment, and performing edge calculation according to the edge calculation rule aiming at the data information to obtain a calculation result.
Further, when the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are imported into a cache module for caching, the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are converted into a computer program language to form a program file, and then the program file related to the edge computing process of the power internet of things gateway, the program file related to the edge computing rule and the program file related to the edge cloud cooperation mode are interactively transmitted into the cache module for caching through information.
Further, setting a network control access mode;
establishing a task scheduling model and determining a task scheduling scheme;
according to the task scheduling scheme, probability calculation is carried out on the power internet of things gateway task scheduling to obtain scheduling limit probability;
and formulating an edge task allocation strategy according to the scheduling limit probability to obtain an edge cloud coordination mode of task allocation.
Further, the setting of the network control access mode includes: and establishing a routing control protocol and a determined communication protocol for the electric power internet of things gateway, wherein the establishment of the routing control protocol for the electric power internet of things gateway is based on sensing basic characteristics of a network, the routing control protocol takes a source node as a starting point, the routing control protocol is diffused to branch nodes according to the levels of the branch nodes, and a stage routing protocol and a stage transmission mode are included between the nodes.
Further, the communication protocol includes an ethernet protocol and a wireless network protocol, and the communication protocol is switched randomly, and when the ethernet protocol is used for transmission, the wireless network protocol is changed to immediately switch to transmit through the wireless network if the ethernet network fails, and/or when the wireless network protocol is used for transmission, the ethernet protocol is changed to immediately switch to transmit through the ethernet network if the wireless network fails.
Further, the establishing of the task scheduling model is to establish the task scheduling model according to the processing condition of the power terminal device to the task in the heterogeneous network for task coordination, and includes: determining parameter information for processing a task by power terminal equipment, wherein the parameter information comprises: time delay of the power terminal equipment and energy consumption of the power terminal equipment for completing the task; defining time delay of the power terminal equipment and weight constraint conditions of energy consumption of the power terminal equipment for completing the task, and determining the time delay of the power terminal equipment and the weight of the energy consumption of the power terminal equipment for completing the task; weighting the time delay of the power terminal equipment and the energy consumption of the power terminal equipment for completing the task according to the time delay of the power terminal equipment and the weight of the energy consumption of the power terminal equipment for completing the task to obtain a task scheduling model of the power terminal equipment; the determining the task scheduling scheme comprises the following steps: determining a global optimal task allocation target according to the task scheduling model of the power terminal equipment; and performing optimization analysis on the global optimal task allocation target to obtain a task scheduling scheme.
Further, according to the task scheduling scheme, probability calculation is performed on the power internet of things gateway task scheduling, and the probability calculation includes: analyzing the task scheduling scheme to determine a scheduling target node; respectively calculating a first limit probability under the time limit and a second limit probability under the task data fluctuation range; determining the scheduling limitation probability according to the first limitation probability and the second limitation probability.
Further, an edge task allocation strategy is formulated according to the scheduling limit probability, and an edge cloud coordination mode of task allocation is obtained, wherein the method comprises the following steps:
determining task allocation parameters of the edge power terminal equipment by combining the scheduling limit probability with basic parameter information collected and transmitted by the power internet of things gateway; wherein, the basic parameter information that electric power thing allies oneself with the gateway and gathers transmission includes: the number of power terminal devices, the information transmission rate and the node path;
performing test simulation according to the terminal device task allocation parameters in the network control access mode to obtain test information, and performing feature extraction in the test information through a feature extraction algorithm to obtain feature description information;
performing data matching according to the feature description information, and determining a most matched edge task allocation strategy through an optimization model;
the electric power internet of things gateway tracks according to the most matched edge task allocation strategy, and realizes edge cloud cooperative matching under the control of a network technology;
and verifying the edge cloud cooperative matching, if the difference between the actual matching and the ideal matching is greater than the threshold, the edge cloud cooperative effect is poor, the edge cloud cooperative mode needs to be set again, and if the difference between the actual matching and the ideal matching is not greater than the threshold, the edge cloud cooperative matching is successful.
Further, when data information of the power terminal device is obtained, a self-adaptive data information acquisition method is adopted for data information acquisition, and the self-adaptive data information acquisition method comprises the following steps: the method comprises the steps of carrying out self-adaptive adjustment on an acquisition interval according to a revolving door algorithm in the data information acquisition process, carrying out self-adaptive adjustment on the acquisition interval according to smoothness of acquired data information in the data information acquisition process, and carrying out self-adaptive adjustment on the acquisition interval according to the revolving door algorithm and carrying out self-adaptive adjustment on the acquisition interval according to the smoothness of the acquired data information in the data information acquisition process.
Further, performing edge calculation on the data information according to the edge calculation rule, including: filtering data information and calculating edges; wherein, the data information filtering comprises:
analyzing the data information to determine data analysis information;
judging the data analysis information to obtain filtering information; the judgment comprises the following steps: first judgement and second judgement, first judgement is the judgement the data analysis information is in the interval within range of maximum and minimum, if in the interval within range of maximum and minimum, then for filtering information, keep, if not in the interval within range of maximum and minimum, then for surplus information, abandon, the second judgement is whether judgement increment threshold satisfies the preset condition, if satisfy the preset condition, then for filtering information, keep, if do not satisfy the preset condition, then for surplus information, abandon.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic step diagram of an edge calculation method for an electric power internet of things gateway according to the present invention;
fig. 2 is a schematic diagram of a method formulated in an edge cloud coordination manner in the electric power internet of things gateway edge computing method according to the present invention;
fig. 3 is a schematic diagram of a communication protocol in the method for calculating an edge of an electrical internet of things gateway according to the present invention;
fig. 4 is a schematic flow diagram illustrating data information filtering in the method for computing an edge of an electric power internet of things gateway according to the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in fig. 1, an embodiment of the present invention provides a method for calculating an edge of an electric power internet of things gateway, including:
step one, determining an edge computing process of an electric power internet of things gateway, setting an edge computing rule, making a side cloud coordination mode, and guiding the edge computing process, the edge computing rule and the side cloud coordination mode of the electric power internet of things gateway into a cache module for caching;
step two, starting the electric power internet of things gateway;
and step three, calling the edge calculation flow of the electric power internet of things gateway stored in the buffer module, realizing edge task allocation according to the edge cloud cooperation mode according to the edge calculation flow of the electric power internet of things gateway, obtaining data information of electric power terminal equipment, and performing edge calculation according to the edge calculation rule aiming at the data information to obtain a calculation result.
According to the technical scheme, when the electric power internet of things gateway edge computing is carried out, the preparation stage and the computing stage are divided by the step of starting the electric power internet of things gateway, in the preparation stage, the electric power internet of things gateway edge computing process is respectively determined, the edge computing rule is set, the edge cloud coordination mode is customized, then the electric power internet of things gateway edge computing process, the edge computing rule and the edge cloud coordination mode are imported and cached, and files of the electric power internet of things gateway edge computing process, the edge computing rule and the edge cloud coordination mode are imported and cached into a cache module when the electric power internet of things gateway edge computing process, the edge computing rule and the edge cloud coordination mode are imported and cached. The method comprises the steps of entering a calculation stage after the power internet of things gateway is started, calling an edge calculation process of the power internet of things gateway stored in a storage module for execution in the calculation stage, realizing edge task allocation according to a side cloud cooperation mode when the edge calculation process of the power internet of things gateway is executed, allocating access nodes according to the edge tasks, obtaining data information of power terminal equipment, carrying out edge calculation on the data information of the power terminal equipment according to edge calculation rules until the edge calculation process of the power internet of things gateway is finished executing and outputting calculation results. According to the technical scheme, the cooperative distribution of tasks issued by the power network is realized in the edge cloud cooperative mode, the matching of the sensing network and the communication network to task data is improved, the comprehensiveness of the acquired data information of the power terminal equipment is improved, the calculation result obtained by the edge calculation of the power internet of things gateway is more accurate, the edge calculation process of the power internet of things gateway, the edge calculation rule and the edge cloud cooperative mode are led into the cache module for caching, the edge calculation process of the power internet of things gateway can be determined, the edge calculation rule is set, the edge cloud cooperative mode can be used for multiple times, the calling and the execution can be facilitated, and the efficiency of the edge calculation method of the power internet of things gateway is improved.
In an embodiment provided by the invention, when the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are imported into a cache module for caching, the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are converted into a computer program language to form a program file, and then the program file related to the edge computing process of the power internet of things gateway, the program file related to the edge computing rule and the program file related to the edge cloud cooperation mode are transmitted into the cache module for caching through information interaction.
According to the technical scheme, when the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are imported into the cache module for caching, when the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are cached, the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are converted into computer program languages, the computer program languages are stored in the form of program files, the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are input in an information interaction mode, and the import of the program files of the edge computing process of the power internet of things gateway, the program files of the edge computing rule and the program files of the edge cloud cooperation mode is achieved. According to the technical scheme, the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are input in an information interaction mode, the program file of the edge computing process, the program file of the edge computing rule and the program file of the edge cloud cooperation mode of the power internet of things gateway are led in, so that convenience is brought, interaction feedback can be achieved, the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are converted into computer program languages, and the computer program languages are stored in the form of the program files, so that the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway can be repeatedly used, and can be called for direct use conveniently during use, time consumed for analyzing the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway during use is saved, use efficiency is improved, and the size of the program file of the edge computing process, the program file of the edge computing rule and the program file of the edge cloud cooperation mode of the power internet of things gateway is small, and occupied storage space is saved.
As shown in fig. 2, in an embodiment provided by the present invention, the making of the edge cloud coordination manner includes:
s01, setting a network control access mode;
s02, establishing a task scheduling model and determining a task scheduling scheme;
s03, according to the task scheduling scheme, probability calculation is carried out on the power internet of things gateway task scheduling, and scheduling limit probability is obtained;
and S04, formulating an edge task allocation strategy according to the scheduling limit probability to obtain a side cloud coordination mode of task allocation.
According to the technical scheme, when a side cloud coordination mode is established and side cloud coordination is realized, firstly, a network control access mode is set; then, establishing a task scheduling model and determining a task scheduling scheme; then, according to the task scheduling scheme, probability calculation is carried out on the power internet of things gateway task scheduling, and scheduling limit probability is obtained; and finally, formulating an edge task allocation strategy according to the scheduling limit probability to obtain an edge cloud coordination mode of task allocation.
In an embodiment of the present invention, the setting a network control access method includes: establishing a routing control protocol and a communication determining protocol for the electric power internet of things gateway, wherein the establishment of the routing control protocol for the electric power internet of things gateway is based on sensing basic characteristics of a network, and the routing control protocol takes a source node as a starting point, spreads to branch nodes according to the levels of the branch nodes, and comprises a stage routing protocol and a stage transmission mode between the nodes.
According to the technical scheme, when a network control access mode is set, not only a routing control protocol needs to be established, but also a communication protocol needs to be determined, diffusion is carried out from a source node to branch nodes according to the level of the branch nodes on the basis of sensing basic characteristics of a network, so that the routing control protocol is obtained, and a stage routing protocol and a stage transmission mode between the nodes need to be determined when the routing control protocol is established.
According to the technical scheme, the route control protocol is determined through the phase route protocol and the phase transmission mode between the nodes, the gateway of the Internet of things can identify the type of the power task according to different transmission methods, and the processing speed of the task data is improved.
As shown in fig. 3, in one embodiment of the present invention, the communication protocols include an ethernet protocol and a wireless network protocol, the communication protocols are randomly switched, and when the ethernet protocol is used for transmission, the wireless network protocol is changed and immediately switched to transmit through the wireless network if the ethernet network fails, and/or when the wireless network protocol is used for transmission, the ethernet protocol is changed and immediately switched to transmit through the ethernet network if the wireless network fails.
The technical scheme can realize communication through the Ethernet protocol and can also realize communication through the wireless network protocol, when the Ethernet protocol is adopted, if the Ethernet fails, the wireless network protocol is changed, transmission is carried out through the wireless network immediately, when the wireless network protocol is adopted for transmission, if the wireless network fails, the Ethernet protocol is changed, transmission is carried out through the Ethernet immediately, and therefore random switching of the communication protocol is realized. According to the technical scheme, the Ethernet protocol and the wireless network protocol are used as communication protocols, so that smooth communication can be ensured, transmission is ensured, even if the currently adopted communication protocol fails, the other communication protocol can be replaced, and the use is not influenced. Moreover, the Ethernet protocol and the wireless network protocol are assisted to effectively reduce the influence of external influence factors such as network delay, system overhead and the like.
In an embodiment provided by the present invention, the establishing a task scheduling model is to establish a task scheduling model according to a processing condition of a power terminal device to a task in a heterogeneous network to perform task coordination, and the task scheduling model includes: determining parameter information for processing a task by power terminal equipment, wherein the parameter information comprises: the time delay of the power terminal equipment and the energy consumption of the power terminal equipment for completing the task; defining time delay of the power terminal equipment and weight constraint conditions of energy consumption of the power terminal equipment for completing the task, and determining the time delay of the power terminal equipment and the weight of the energy consumption of the power terminal equipment for completing the task; weighting the time delay of the electric power terminal equipment and the energy consumption of the electric power terminal equipment for completing the task according to the time delay of the electric power terminal equipment and the weight of the energy consumption of the electric power terminal equipment for completing the task to obtain a task scheduling model of the electric power terminal equipment; the task scheduling scheme determination comprises the following steps: determining a global optimal task allocation target according to the task scheduling model of the power terminal equipment; and performing optimization analysis on the global optimal task allocation target to obtain a task scheduling scheme.
The task scheduling model is established according to the processing condition of the power terminal equipment to the task in the heterogeneous network, so that task coordination is realizedThe method at least comprises the following steps: the time delay of the electric terminal equipment and the energy consumption of the electric terminal equipment for completing the task are defined, then weight constraint conditions of the time delay of the electric terminal equipment and the energy consumption of the electric terminal equipment for completing the task are defined,
and also
Wherein the content of the first and second substances,
represents the time delay weight value of the ith power terminal equipment,
and then, weighting the time delay of the power terminal equipment and the energy consumption of the power terminal equipment for completing the task according to the time delay weight of the power terminal equipment and the energy consumption weight of the power terminal equipment for completing the task to obtain a task scheduling model of the power terminal equipment. When the task scheduling scheme is determined, firstly, a global optimal task allocation target is determined according to a task scheduling model of the power terminal equipment and in combination with tasks, task offsets, channel numbers and position information of the power terminal equipment, and then the global optimal task allocation target is subjected to optimization analysis to obtain the task scheduling scheme. The task scheduling scheme obtained by the technical scheme is optimized, so that the comprehensive loss is minimum when scheduling is carried out according to the task scheduling scheme, errors can be effectively reduced, and the accuracy of edge calculation is improved.
In an embodiment provided by the present invention, performing probability calculation on power internet of things gateway task scheduling according to the task scheduling scheme includes: analyzing the task scheduling scheme to determine a scheduling target node; respectively calculating a first limit probability under the time limit and a second limit probability under the task data fluctuation range; determining the scheduling limitation probability according to the first limitation probability and the second limitation probability.
According to the technical scheme, when the probability calculation is carried out on the task scheduling of the power internet of things gateway according to the task scheduling scheme, firstly, the task scheduling scheme is analyzed to determine a scheduling target node, then, a first limiting probability under the time limit and a second limiting probability under the task data fluctuation range are respectively calculated to determine the scheduling limiting probability according to the first limiting probability and the second limiting probability, wherein the second limiting probability is determined according to the following formula:
in the formula, P2 represents a second limit probability, M represents the maximum value of the task data, N represents the minimum value of the task data, k represents a parameter, and the value of k is greater than 1;
when the parameter k takes 2 when the maximum value of the task data is 5 and the minimum value of the task data is 1, the second limit probability
The scheduling limit probability is determined according to the following formula:
in the above formula, P represents a scheduling constraint probability, P1 represents a first constraint probability, pi represents an expected constraint probability of the ith electric terminal equipment under a stable data transmission condition, qi represents a weight of the ith electric terminal equipment, and h represents a regulation parameter;
when the tuning parameter is 1, the scheduling limitation probability P may be expressed as P = P1 ∑ e i Pi+P2*∑ i Pi。
According to the technical scheme, when the first limit probability and the second limit probability are calculated, the problem of multiple contact between network nodes and the condition of a single-hop path are considered, weak instability of transmission data is also considered, so that the calculated first limit probability and the calculated second limit probability are optimized and considered more comprehensively, the first limit probability and the second limit probability are more accurate, in addition, the time condition and the data quantity condition are fully considered in the process of searching the target limit probability, and the method has strong objectivity.
In an embodiment provided by the present invention, formulating an edge task allocation policy according to the scheduling limit probability to obtain an edge cloud coordination manner of task allocation, includes:
determining task allocation parameters of the edge power terminal equipment by combining the scheduling limit probability with basic parameter information collected and transmitted by the power internet of things gateway; wherein, the basic parameter information that electric power thing allies oneself with the gateway and gathers transmission includes: the number of power terminal devices, the information transmission rate and the node path;
performing test simulation according to the terminal device task allocation parameters in the network control access mode to obtain test information, and performing feature extraction in the test information through a feature extraction algorithm to obtain feature description information;
performing data matching according to the feature description information, and determining a most matched edge task allocation strategy through an optimization model;
the electric power internet of things gateway tracks according to the most matched edge task allocation strategy, and realizes edge cloud cooperative matching under the control of a network technology;
and verifying the edge cloud cooperative matching, if the difference between the actual matching and the ideal matching is greater than the threshold, the edge cloud cooperative effect is poor, the edge cloud cooperative mode needs to be set again, and if the difference between the actual matching and the ideal matching is not greater than the threshold, the edge cloud cooperative matching is successful.
According to the technical scheme, when an edge task allocation strategy is formulated according to scheduling limit probability to obtain a side cloud coordination mode of task allocation, firstly, the scheduling limit probability is combined with basic parameter information collected and transmitted by an electric power internet of things gateway to determine task allocation parameters of edge electric power terminal equipment; wherein, the basic parameter information that electric power thing allies oneself with the gateway and gathers transmission includes: the number of power terminal devices, the information transmission rate and the node path; then, performing test simulation according to the task allocation parameters of the terminal equipment in a network control access mode to obtain test information, and performing feature extraction in the test information through a feature extraction algorithm to obtain feature description information; then, according to the feature description information, performing data matching, and determining a most matched edge task allocation strategy through an optimization model; then, the electric power internet of things gateway tracks according to the most matched edge task allocation strategy, and under the control of a network technology, edge cloud cooperative matching is realized; and finally, verifying the edge cloud cooperative matching, if the difference between the actual matching and the ideal matching is greater than the threshold, the edge cloud cooperative effect is poor, the edge cloud cooperative mode needs to be set again, and if the difference between the actual matching and the ideal matching is not greater than the threshold, the edge cloud cooperative matching is successful. According to the technical scheme, tracking can be carried out according to the most matched edge task allocation strategy, edge cloud cooperative matching is achieved under the control of a network technology, meanwhile, a better edge cloud cooperative effect can be achieved, and then the optimization degree of the edge task allocation strategy can be improved. The tasks are distributed uniformly, data information of the power terminal equipment can be obtained well, and therefore edge calculation is achieved more accurately.
In an embodiment provided by the present invention, when obtaining data information of an electric power terminal device, a self-adaptive data information collecting method is adopted to collect the data information, and the self-adaptive data information collecting method includes: the method comprises the steps of carrying out self-adaptive adjustment on an acquisition interval according to a revolving door algorithm in the data information acquisition process, carrying out self-adaptive adjustment on the acquisition interval according to smoothness of acquired data information in the data information acquisition process, and carrying out self-adaptive adjustment on the acquisition interval according to the revolving door algorithm and carrying out self-adaptive adjustment on the acquisition interval according to the smoothness of the acquired data information in the data information acquisition process.
According to the technical scheme, data information acquisition is carried out when data information of the power terminal equipment is obtained, a self-adaptive data information acquisition method is adopted when the data information acquisition is carried out, and the acquisition interval is adjusted in a self-adaptive mode in the acquisition process, wherein the self-adaptive data information acquisition method comprises the following steps: the method comprises the steps of performing self-adaptive adjustment on an acquisition interval according to a revolving door algorithm in the data information acquisition process, performing self-adaptive adjustment on the acquisition interval according to smoothness of acquired data information in the data information acquisition process, performing self-adaptive adjustment on the acquisition interval according to the revolving door algorithm and performing self-adaptive adjustment on the acquisition interval jointly according to smoothness of the acquired data information in the data information acquisition process, selecting a self-adaptive adjustment method according to the data information acquisition condition, generally performing self-adaptive adjustment on the acquisition interval according to the revolving door algorithm and performing self-adaptive adjustment on the acquisition interval jointly according to the adjustment and the intersection of the smoothness of the acquired data information in the data information acquisition process, performing real-time data compression on data, performing repeated comparison on the upper slope and the lower slope between every two data points through cyclic calculation, dynamically adjusting an access result and time alternation, dynamically adjusting the acquisition interval, performing real-time data compression on the data, combining the dynamically adjusted acquisition interval with the dynamically adjusted acquisition interval, combining the characteristics of the two, adjusting the acquisition interval of the data according to the change condition of the data, and reducing the data information acquisition interval when the data is larger; when the data fluctuation is small, increasing the data information acquisition interval; when the data fluctuates, the secondary acquisition frequency is adjusted according to the change characteristic of the data so as to enhance the performance of the original algorithm.
According to the technical scheme, the data information of the power terminal equipment can be more comprehensive and accurate through self-adaptive data information collection, the data is subjected to real-time data compression superior performance, the transplantation is easy to realize, the real-time data can be rapidly processed, the severe condition of data change is reflected by the dynamic adjustment collection interval, the data change is severe when the data smoothness is large, the data change is mild in hours, the adjustment of the data information collection interval can be performed according to the data, the combination of the real-time data compression and the dynamic adjustment collection interval on the data is very suitable for self-adaptive variable frequency collection, the data model is small, the codes are concise, the running speed is very high, and the result can be obtained through rapid calculation.
As shown in fig. 4, in an embodiment provided by the present invention, performing edge calculation on the data information according to the edge calculation rule includes: filtering data information and calculating edges; wherein, the data information filtering comprises:
analyzing the data information to determine data analysis information;
judging the data analysis information to obtain filtering information; the judgment comprises the following steps: first judgement and second judgement, first judgement is the judgement the data analysis information is in the interval within range of maximum and minimum, if in the interval within range of maximum and minimum, then for filtering information, keep, if not in the interval within range of maximum and minimum, then for surplus information, abandon, the second judgement is whether judgement increment threshold satisfies the preset condition, if satisfy the preset condition, then for filtering information, keep, if do not satisfy the preset condition, then for surplus information, abandon.
According to the technical scheme, edge calculation is carried out on the data information according to the edge calculation rule, the data information is filtered firstly, and then the edge calculation is carried out on the filtered data information; when data information is filtered, firstly analyzing the data information to determine data analysis information; then, to data analysis information judges respectively whether data analysis information is in the interval of the maximum and minimum value range and whether the judgment increment threshold value satisfies the preset condition, thereby obtaining the judgment result of the first judgment and the judgment result of the second judgment, when the first judgment, if in the interval of the maximum and minimum value range, then for the filter information, it is reserved, if not in the interval of the maximum and minimum value range, then for the surplus information, it is discarded, when the second judgment, if satisfy the preset condition, then for the filter information, it is reserved, if it is not satisfied the preset condition, then for the surplus information, it is discarded.
Above-mentioned technical scheme filters the interference that can reduce surplus information when making marginal calculation through data message, and the chaotic degree when reducing marginal calculation to reduce marginal calculation's probability of makeing mistakes, improve the rate of accuracy of calculated result. And when data information filters, as long as one of the first judgment and the second judgment meets the requirement, the data information can be retained by filtering, and the two judgments can be carried out simultaneously, so that the efficiency is high, and the time consumption is short.
It will be understood by those skilled in the art that the first and second embodiments of the present invention are merely directed to different stages of application.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (3)
1. An electric power internet of things gateway edge computing method is characterized by comprising the following steps:
determining an edge computing process of the power internet of things gateway, setting an edge computing rule, making a side cloud coordination mode, and guiding the edge computing process, the edge computing rule and the side cloud coordination mode of the power internet of things gateway into a cache module for caching;
starting the electric power internet of things gateway;
calling the edge calculation flow of the electric power internet of things gateway stored in the buffer module, according to the edge calculation flow of the electric power internet of things gateway, realizing edge task allocation according to the edge cloud cooperation mode, obtaining data information of electric power terminal equipment, and performing edge calculation according to the edge calculation rule aiming at the data information to obtain a calculation result;
the method for establishing the edge cloud cooperation mode comprises the following steps:
s01, setting a network control access mode;
s02, establishing a task scheduling model and determining a task scheduling scheme;
s03, according to the task scheduling scheme, probability calculation is carried out on the power internet of things gateway task scheduling, and scheduling limit probability is obtained;
s04, formulating an edge task allocation strategy according to the scheduling limit probability to obtain a side cloud coordination mode of task allocation;
the setting of the network control access mode comprises the following steps: establishing a routing control protocol and a communication determining protocol for the electric power internet of things gateway, wherein the establishment of the routing control protocol for the electric power internet of things gateway is based on sensing basic characteristics of a network, and the routing control protocol takes a source node as a starting point, and is diffused to branch nodes according to the levels of the branch nodes, and a stage routing protocol and a stage transmission mode are included between the nodes;
the task scheduling model is established according to the processing condition of the power terminal equipment in the heterogeneous network to the task to carry out task coordination, and the method comprises the following steps: determining parameter information for processing a task by power terminal equipment, wherein the parameter information comprises: the time delay of the power terminal equipment and the energy consumption of the power terminal equipment for completing the task; defining time delay of the power terminal equipment and weight constraint conditions of energy consumption of the power terminal equipment for completing the task, and determining the time delay of the power terminal equipment and the weight of the energy consumption of the power terminal equipment for completing the task; weighting the time delay of the power terminal equipment and the energy consumption of the power terminal equipment for completing the task according to the time delay of the power terminal equipment and the weight of the energy consumption of the power terminal equipment for completing the task to obtain a task scheduling model of the power terminal equipment; the determining the task scheduling scheme comprises the following steps: determining a global optimal task allocation target according to the task scheduling model of the power terminal equipment; performing optimization analysis on the global optimal task allocation target to obtain a task scheduling scheme;
according to the task scheduling scheme, probability calculation is carried out on the task scheduling of the power Internet of things gateway, and the probability calculation comprises the following steps: analyzing the task scheduling scheme to determine a scheduling target node; respectively calculating a first limit probability under the time limit and a second limit probability under the task data fluctuation range; determining the scheduling restriction probability according to the first restriction probability and the second restriction probability;
wherein the second limit probability is determined according to the following formula:
in the formula, P2 represents a second limit probability, M represents the maximum value of the task data, N represents the minimum value of the task data, k represents a parameter, and the value of k is greater than 1;
when the maximum value of the task data is 5 and the minimum value of the task data is 1, and the parameter k takes 2, the second limit probability
The scheduling limit probability is determined according to the following formula:
in the above formula, P represents a scheduling constraint probability, P1 represents a first constraint probability, pi represents an expected constraint probability of the ith electric terminal equipment under a stable data transmission condition, qi represents a weight of the ith electric terminal equipment, and h represents a regulation parameter;
when the tuning parameter is 1, the scheduling limitation probability P may be expressed as P = P1 ∑ e i Pi+P2*∑ i Pi；
Formulating an edge task allocation strategy according to the scheduling limit probability to obtain an edge cloud coordination mode of task allocation, wherein the edge cloud coordination mode comprises the following steps:
determining task allocation parameters of the edge power terminal equipment by combining the scheduling limit probability with basic parameter information collected and transmitted by the power internet of things gateway; wherein, the basic parameter information that electric power thing allies oneself with the gateway and gathers transmission includes: the number of power terminal devices, the information transmission rate and the node path;
performing test simulation according to the terminal device task allocation parameters in the network control access mode to obtain test information, and performing feature extraction in the test information through a feature extraction algorithm to obtain feature description information;
performing data matching according to the feature description information, and determining a most matched edge task allocation strategy through an optimization model;
the electric power internet of things gateway tracks according to the most matched edge task allocation strategy, and realizes edge cloud cooperative matching under the control of network technology;
verifying the edge cloud cooperative matching, if the difference between the actual matching and the ideal matching is greater than the threshold, resetting the edge cloud cooperative mode, and if the difference between the actual matching and the ideal matching is not greater than the threshold, successfully matching the edge cloud cooperative matching;
when data information of the power terminal equipment is obtained, a self-adaptive data information acquisition method is adopted for data information acquisition, and the self-adaptive data information acquisition method comprises the following steps: the method comprises the following steps of carrying out self-adaptive adjustment on an acquisition interval according to a revolving door algorithm in the data information acquisition process, carrying out self-adaptive adjustment on the acquisition interval according to smoothness of acquired data information in the data information acquisition process, and carrying out self-adaptive adjustment on the acquisition interval according to the revolving door algorithm and carrying out self-adaptive adjustment on the acquisition interval according to the smoothness of the acquired data information in the data information acquisition process;
performing edge calculation on the data information according to the edge calculation rule, including: data information filtering and edge calculation; wherein, the data information filtering comprises:
analyzing the data information to determine data analysis information;
judging the data analysis information to obtain filtering information; the judging comprises the following steps: first judgement and second judgement, first judgement is the judgement the data analysis information is in the interval within range of maximum and minimum, if in the interval within range of maximum and minimum, then for filtering information, keep, if not in the interval within range of maximum and minimum, then for surplus information, abandon, the second judgement is whether judgement increment threshold satisfies the preset condition, if satisfy the preset condition, then for filtering information, keep, if do not satisfy the preset condition, then for surplus information, abandon.
2. The method according to claim 1, wherein when the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are imported into a cache module for caching, the edge computing process, the edge computing rule and the edge cloud cooperation mode of the power internet of things gateway are converted into a computer program language to form a program file, and then the program file related to the edge computing process of the power internet of things gateway, the program file related to the edge computing rule and the program file related to the edge cloud cooperation mode are sent to the cache module for caching through information interaction.
3. The method of claim 1, wherein the communication protocols include an ethernet protocol and a wireless network protocol, and wherein the communication protocols are randomly switched, and wherein the wireless network protocol is changed to immediately switch to transmitting over the wireless network if the ethernet network fails during transmission using the ethernet protocol, and/or the ethernet protocol is changed to immediately switch to transmitting over the ethernet network if the wireless network fails during transmission using the wireless network protocol.
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