CN115907398A - Low-voltage power distribution and utilization data processing method and device based on cloud edge cooperation - Google Patents
Low-voltage power distribution and utilization data processing method and device based on cloud edge cooperation Download PDFInfo
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Abstract
The invention discloses a cloud edge cooperation-based low-voltage power distribution and utilization data processing method and device, wherein the method comprises the following steps: acquiring a first performance index from an edge server and a cloud server, and performing normalization processing to obtain a second performance index; according to the second performance index, obtaining an index score after evaluation, and selecting a cloud edge coordination mode according to the marked score; in the cloud-assisted edge mode, the edge terminal performs time delay compensation and allocates computing resources according to historical data of a cloud end, and low-voltage power consumption data are processed in parallel; in the edge-assisted cloud mode, the cloud terminal carries out time delay compensation and distributes computing resources according to the low-voltage power distribution and utilization data of the edge end and historical data of the cloud terminal, and low-voltage power distribution and utilization data are processed in parallel. By adopting the embodiment of the invention, diversified collaborative mode selection can be realized, and different requirements of different power services on resources when processing low-voltage power distribution data can be met; the edge end and the cloud end perform time delay compensation according to historical data, and the cloud edge cooperation efficiency is improved.
Description
Technical Field
The invention relates to the technical field of distribution and power utilization, in particular to a cloud edge cooperation-based low-voltage distribution and power utilization data processing method and device.
Background
The power distribution network is composed of overhead lines, cables, towers, distribution transformers, isolating switches, reactive power compensators, accessory facilities and the like, and plays a role of using electric energy in the power network. In the running production process of a power grid, a low-voltage distribution network is connected with power production and power consumption, is the last link of delivering power commodities to users, and is related to the power consumption quality of thousands of users. However, with the development of economy and society, the demand of national production and living electricity utilization is greatly improved, a large number of power distribution service terminals and users are connected to a power distribution network to generate massive power distribution and utilization data, and if the data are not processed in time, the working efficiency of the power distribution network is seriously influenced, and further the electricity utilization quality of the users is influenced. In order to meet the requirement of low-voltage power distribution and utilization data processing, the cloud-edge cooperative data processing technology has gradually gained wide application by virtue of computing resources provided by a cloud server and an edge server. On one hand, the low-voltage power consumption data has large information amount, various services and complex calculation, and different services have different requirements on time delay, database resources and the like; on the other hand, due to the fact that uncertain time delay is caused by the prior knowledge or historical data sending, data receiving and task processing, the traditional cloud-edge cooperative data processing method does not consider the uncertain time delay, the time delay is increased, and cloud-edge cooperative performance is affected.
Disclosure of Invention
The invention provides a cloud-edge-based cooperative low-voltage power distribution and utilization data processing method and device, and aims to solve the technical problem that in the prior art, the cloud-edge cooperative performance is reduced due to the fact that a cloud-edge cooperative mode is single and uncertain time delay is not considered.
In order to solve the technical problem, an embodiment of the present invention provides a cloud-edge coordination-based low-voltage power distribution and utilization data processing method, including:
acquiring a first performance index from an edge server and a cloud server, and performing normalization processing to obtain a second performance index; wherein the second performance indicator comprises: information acquisition frequency, available computing resources, available channel bandwidth and historical time delay performance;
according to the second performance index, obtaining an index score after index evaluation, and selecting a cloud edge collaborative mode according to the index score; wherein the cloud edge collaborative mode comprises: a cloud-assisted edge mode or edge-assisted cloud mode;
when a cloud auxiliary edge mode is selected, the edge server performs time delay compensation and allocates computing resources according to historical data sent by the cloud server, and low-voltage power consumption data are processed in parallel;
when the edge-assisted cloud mode is selected, the cloud server performs time delay compensation and allocates computing resources according to the low-voltage distribution power data and the historical data stored in the cloud end sent by the edge server, and the low-voltage distribution power data are processed in parallel.
According to the method, after the first performance index is obtained, normalization processing is carried out, information acquisition frequency, available computing resources, available channel bandwidth and historical time delay performance which can be used for evaluation and calculation are obtained, computing resources and communication resources of an edge end and a cloud end are comprehensively considered, index scores obtained through calculation are adopted for cloud-edge collaborative mode selection, diversified collaborative mode selection is achieved, and different requirements of different power services on resources when low-voltage power distribution data are processed can be met; in addition, when the low-voltage power consumption data are processed, the edge end and the cloud end perform time delay compensation according to historical data, and the cloud-edge cooperation efficiency is improved.
Further, the obtaining of the first performance index from the edge server and the cloud server, and performing normalization processing to obtain a second performance index specifically include:
acquiring a first performance index according to the computing resource and the communication resource of the edge server and the computing resource and the communication resource of the cloud server;
and according to a normalization formula, carrying out linear change on the first performance index and mapping the first performance index to a preset interval to obtain the second performance index.
Further, the normalization formula is:
wherein P is a first performance index to be normalized, P min Is the minimum value of the first performance index to be normalized, P max Is the maximum value of the first performance index to be normalized, and X is the second performance index.
According to the method, after the first performance is subjected to normalization processing, a second performance index which can be used for evaluation calculation is obtained, information acquisition frequency, available calculation resources, available channel bandwidth and historical time delay performance of the edge end and the cloud end are covered, and different requirements of different power services on resources when low-voltage power distribution data are processed are considered in subsequent evaluation, so that various cloud-edge cooperative modes are selected.
Further, according to the second performance index, obtaining an index score after performing index evaluation, and according to the index score, selecting a cloud-edge collaborative mode, specifically:
calculating a ratio of a second performance index of the edge server to a second performance index of the cloud server, and evaluating to obtain an index score by combining weight parameters of the second performance indexes;
and comparing the index score with a preset value, and selecting a cloud edge collaborative mode according to a comparison result.
Further, the expression of the index score is as follows:
wherein f is e (t) available computing resources of the edge server for the t-th time slot, f c (t) available computing resources of the cloud server for the t-th time slot, B e (t) available channel bandwidth of edge server for t-th time slot, B c (T) available channel bandwidth of cloud server for T-th time slot, T e com (T-1) historical delay performance of the T-1 th time slot edge server, T c com (t-1) historical time delay performance of the cloud server at the t-1 th time slot, wherein (t) is information acquisition frequency of the t-th time slot; alpha, beta, chi and delta are respectively weight parameters of available computing resources, available channel bandwidth, historical time delay performance and information acquisition frequency.
Further, the comparing the index score with a preset value, and selecting a cloud edge collaborative mode according to a comparison result specifically comprises:
comparing the index score with a preset value;
when the index score is larger than the preset value, selecting a cloud auxiliary edge mode;
and when the prime index score is not greater than the preset value, selecting a side-assisted cloud mode.
When index evaluation is carried out, the ratio of second performance indexes of the edge end and the cloud end is calculated by considering information acquisition frequency, available computing resources, available channel bandwidth and historical time delay performance, so that a cloud-assisted edge mode is adopted when the available computing resources and the available channel bandwidth of the edge end are large and the historical time delay performance is small; and otherwise, a side-assisted cloud mode is adopted, so that different requirements of different power services on resources when low-voltage power distribution electricity consumption data are processed are met.
Further, the edge server performs time delay compensation and allocates computing resources according to the historical data sent by the cloud server, and processes the low-voltage power consumption data in parallel, specifically:
the edge server receives the historical data sent by the cloud server, and obtains a service delay requirement, a service database resource requirement and a historical calculation delay from the historical data;
the edge server groups the low-voltage power distribution and utilization data according to a first preset quantity and calculates a first data quantity of each group according to the service delay requirement and the resource requirement of the service database;
the edge server calculates the time delay according to the history, and calculates the time delay uncertainty of the edge server;
the edge server calculates to obtain a first calculation resource of each group according to the time delay uncertainty of the edge server, the first data volume of each group and the available calculation resource of the edge server;
and after the edge server distributes computing resources according to the first computing resources of each group, the edge server processes each group of data of the low-voltage power distribution and utilization data in parallel.
Further, the cloud server performs time delay compensation and allocates computing resources according to the low-voltage power distribution and utilization data sent by the edge server and historical data stored at a cloud, and processes the low-voltage power distribution and utilization data in parallel, specifically:
the cloud server receives the low-voltage power distribution and utilization data sent by the edge server, and acquires a service delay requirement, a service database resource requirement, historical calculation delay and historical transmission delay from the historical data;
the cloud server groups the low-voltage power distribution and utilization data according to a second preset quantity and calculates a second data quantity of each group according to the service delay requirement and the resource requirement of the service database;
the cloud server calculates the time delay uncertainty of the cloud server according to the historical calculation time delay and the historical transmission time delay;
the cloud server calculates to obtain second computing resources of each group according to the time delay uncertainty of the cloud server, the second data volume of each group and the available computing resources of the edge server;
and after the cloud server distributes computing resources according to the second computing resources of each group, the cloud server processes each group of data of the low-voltage power distribution and utilization data in parallel.
According to the invention, when the low-voltage distribution power utilization data are processed, the time delay uncertainty is calculated through the historical data, and the calculation resources required to be allocated for processing each group of low-voltage distribution power utilization data are determined through the experimental uncertainty, so that the time delay compensation is realized, and the processing efficiency of the low-voltage distribution power utilization data is improved.
Further, after the performing the delay compensation and allocating the computing resource, the method further includes:
calculating to obtain the current time delay of the edge server according to the distribution result of the calculation resources, or calculating to obtain the current time delay of the cloud server;
and updating the historical time delay performance according to the current time delay of the edge server or the current time delay of the cloud server.
After the calculation resource is allocated, the historical time delay performance is updated according to the allocation result, so that the performance index is updated in time, the accuracy of next collaborative mode selection is improved, the calculation resource and the communication resource of the edge end or the cloud end are fully used, and the processing efficiency of the low-voltage distribution power consumption data is further improved.
On the other hand, the embodiment of the invention also provides a low-voltage power distribution and utilization data processing device based on cloud edge cooperation, which comprises: the system comprises an index generation module, a mode selection module, a first processing module and a second processing module;
the index generation module is used for acquiring a first performance index from the edge server and the cloud server and carrying out normalization processing to obtain a second performance index; wherein the second performance indicator comprises: information collection frequency, available computing resources, available channel bandwidth and historical delay performance;
the mode selection module is used for obtaining an index score after index evaluation according to the second performance index and selecting a cloud edge cooperative mode according to the index score; wherein the cloud edge collaborative mode comprises: a cloud-assisted edge mode or edge-assisted cloud mode;
the first processing module is used for enabling the edge server to perform time delay compensation and allocate computing resources according to historical data sent by the cloud server when the mode selection module selects the cloud auxiliary edge mode, and processing low-voltage power consumption data in parallel;
and the second processing module is used for enabling the cloud server to perform time delay compensation and allocate computing resources according to the low-voltage power distribution and utilization data and historical data stored at the cloud end sent by the edge server when the mode selection module selects the edge auxiliary cloud mode, and processing the low-voltage power distribution and utilization data in parallel.
According to the method, after the first performance index is obtained, normalization processing is carried out, information acquisition frequency, available computing resources, available channel bandwidth and historical time delay performance which can be used for evaluation and calculation are obtained, computing resources and communication resources of an edge end and a cloud end are comprehensively considered, index scores obtained through calculation are adopted for cloud-edge collaborative mode selection, diversified collaborative mode selection is achieved, and different requirements of different power services on resources when low-voltage power distribution data are processed can be met; in addition, when the low-voltage power consumption data are processed, the edge end and the cloud end perform time delay compensation according to historical data, and the cloud-edge cooperation efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of an embodiment of a low-voltage distribution and utilization data processing method based on cloud-edge coordination according to the present invention;
fig. 2 is a schematic flow chart of another embodiment of the cloud-edge-based cooperative low-voltage distribution and utilization data processing method provided by the present invention;
fig. 3 is a schematic flowchart of another embodiment of the cloud-edge-based collaborative low-voltage distribution and utilization data processing method according to the present invention;
fig. 4 is a schematic structural diagram of an embodiment of the cloud-edge-based cooperative data processing device for low-voltage distribution and utilization provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
The existing cloud-edge cooperative data processing method cannot select a cloud-edge cooperative mode according to computing resources, communication resources, historical time delay performance and the like, cannot adapt to differentiated data processing requirements, and is difficult to fully utilize computing resources of an edge server and a cloud server. In addition, the existing cloud-edge collaborative data processing method does not consider the uncertain time delay caused by data reception and the task processing when computing resources are used, so that the time delay is increased, and the cloud-edge collaborative performance is influenced. Therefore, the invention provides a cloud edge cooperation-based low-voltage power distribution and utilization data processing method and device, which are used for solving the problems and comprise the following steps:
example one
Referring to fig. 1, a schematic flow chart of an embodiment of a cloud-edge-based cooperative low-voltage distribution and power utilization data processing method provided by the present invention mainly includes steps 101 to 104, which are as follows:
step 101: acquiring a first performance index from an edge server and a cloud server, and performing normalization processing to obtain a second performance index; wherein the second performance indicator comprises: frequency of information collection, available computing resources, available channel bandwidth, and historical latency performance.
In this embodiment, a cloud-edge collaborative low-voltage distribution and power utilization data model may be used for processing, where the data model includes a cloud server, an edge server, and a low-voltage distribution network; the first performance index obtained in the edge server and the cloud server may be normalized in the edge server to obtain a second performance index.
In this embodiment, the historical delay performance of each time slot can be recorded by constructing a time slot model, assuming that there are T time slots in the transmission process, and the set is denoted as T = {1, …, …, }; by constructing the time slot model, the time delay performance of each time slot can be recorded, and the time delay performance of the previous time slot is utilized to perform index comprehensive scoring during cloud edge collaborative mode evaluation.
In this embodiment, the available computing resources include available computing resources of the edge server and available computing resources of the cloud server, the available channel bandwidth includes an available channel bandwidth of the edge server and an available channel bandwidth of the cloud server, and the historical latency performance includes historical latency performance of the edge measurement and historical latency performance of the cloud server.
Further, the obtaining of the first performance index from the edge server and the cloud server, and performing normalization processing to obtain a second performance index specifically include:
acquiring a first performance index according to the computing resource and the communication resource of the edge server and the computing resource and the communication resource of the cloud server;
and according to a normalization formula, carrying out linear change on the first performance index and mapping the first performance index to a preset interval to obtain the second performance index.
In this embodiment, the preset interval may be an interval [0-1].
In this embodiment, the normalization formula is:
wherein P is a first performance index to be normalized, P min Is the minimum value of the first performance index to be normalized, P max Is the maximum value of the first performance index to be normalized, and X is the second performance index.
According to the invention, after the first performance is normalized, a second performance index which can be used for evaluation calculation is obtained, and the information acquisition frequency, available calculation resources, available channel bandwidth and historical time delay performance of the edge end and the cloud end are covered, so that different requirements of different power services on resources when processing low-voltage power distribution data are considered in the subsequent evaluation, and thus, various cloud-edge cooperative mode selections are provided.
Step 102: according to the second performance index, obtaining an index score after index evaluation, and selecting a cloud edge collaborative mode according to the index score; wherein the cloud edge collaborative mode comprises: a cloud-assisted edge mode or edge-assisted cloud mode; when the cloud auxiliary edge mode is selected, executing step 103; when the edge-assisted cloud mode is selected, step 104 is performed.
Because the requirements of each power service on resources are different, for example, the power utilization information acquisition service needs higher information acquisition frequency to ensure the real-time performance of information, the monitoring service has higher requirements on computing resources to realize image processing analysis, and the control service needs higher bandwidth and lower transmission delay to realize the quick transmission of control commands; therefore, in this embodiment, index evaluation is performed by using information acquisition frequency, available computing resources, available channel bandwidth and historical delay performance, computing resources and communication resources of the edge end and the cloud end are comprehensively considered, and various cloud-edge collaborative mode selections are adopted to meet different requirements of different power services on resources.
Further, according to the second performance index, after the index evaluation is performed, an index score is obtained, and according to the index score, a cloud-edge collaborative mode is selected, specifically:
calculating a ratio of a second performance index of the edge server to a second performance index of the cloud server, and evaluating to obtain an index score by combining weight parameters of the second performance indexes;
and comparing the index score with a preset value, and selecting a cloud edge collaborative mode according to a comparison result.
In this embodiment, the expression of the index score is:
wherein f is e (t) available computing resources of the edge server for the t-th time slot, f c (t) available computing resources of the cloud server for the t-th time slot, B e (t) available channel bandwidth of edge server for t-th time slot, B c (T) available channel bandwidth of cloud server for tth time slot, T e com (T-1) historical delay performance of the T-1 th time slot edge server, T c com (t-1) historical time delay performance of the cloud server at the t-1 th time slot, wherein (t) is information acquisition frequency of the t-th time slot; alpha, beta, chi and delta are respectively weight parameters of available computing resources, available channel bandwidth, historical time delay performance and information acquisition frequency.
In this embodiment, the weight parameter of the available computing resource, the weight parameter of the available channel bandwidth, the weight parameter of the historical delay performance, and the weight parameter of the information acquisition frequency are used to measure the importance degree of different indexes.
In this embodiment, the comparing the index score with the preset value, and selecting the cloud edge collaborative mode according to the comparison result specifically includes:
comparing the index score with a preset value;
when the index score is larger than the preset value, selecting a cloud auxiliary edge mode;
and when the prime index score is not greater than the preset value, selecting a side-assisted cloud mode.
In this embodiment, the second performance index of the edge end or the edge server and the second performance index of the cloud end or the cloud server are compared in the form of a ratio through index scoring, wherein the performance of the edge server is in direct proportion to the index scoring, the performance of the cloud server is in inverse proportion to the index scoring, and when available computing resources and available channel bandwidths of the edge server are large and historical time delay is small, the cloud edge collaborative mode is selected; when the available computing resources and the available channel bandwidth of the cloud server are large and the historical time delay is small, the cloud side collaborative mode selects and assists the cloud mode. Therefore, by reasonably selecting the preset value, the end with higher performance can be selected to process a large amount of low-voltage power distribution and utilization data.
In this embodiment, in special cases, for example: since the index score is in direct proportion to the information acquisition frequency, when the information acquisition frequency is large, the data volume is large, the communication overhead is large, the transmission time is long, and at the moment, the cloud auxiliary side mode is prone to be selected to reduce the communication overhead.
When index evaluation is carried out, the ratio of second performance indexes of the edge end and the cloud end is calculated by considering information acquisition frequency, available computing resources, available channel bandwidth and historical time delay performance, so that a cloud-assisted edge mode is adopted when the available computing resources and the available channel bandwidth of the edge end are large and the historical time delay performance is small; and otherwise, a side-assisted cloud mode is adopted, so that different requirements of different power services on resources when low-voltage power distribution electricity consumption data are processed are met.
Step 103: and the edge server performs time delay compensation and allocates computing resources according to the historical data sent by the cloud server, and low-voltage power consumption data are processed in parallel.
Step 104: and the cloud server performs time delay compensation and allocates computing resources according to the low-voltage power distribution and utilization data sent by the edge server and historical data stored at the cloud end, and processes the low-voltage power distribution and utilization data in parallel.
In this embodiment, no matter in the cloud-assisted side mode or the side-assisted cloud mode, the low-voltage power distribution and utilization data of the edge server are processed, and delay compensation and computing resource allocation are performed according to historical data on the cloud server. In the cloud-assisted side mode, the cloud server sends historical data or priori knowledge to the edge server, after the edge server acquires the historical data or the priori knowledge, the mode of grouping the low-voltage distribution power utilization data can be adopted to further realize the distribution of computing resources to all groups of data, and the historical data or the priori knowledge is utilized to perform time delay compensation; in the side-assisted cloud mode, the edge server sends low-voltage power distribution and utilization data to the cloud server, the cloud server compensates time delay caused by data receiving and task processing after receiving the data and processing a task in a previous time period, and computing resource allocation is achieved on each group of data in a mode of grouping the low-voltage power distribution and utilization data.
Referring to fig. 2, a schematic flow chart of another embodiment of the cloud-edge-based cooperative low-voltage distribution and power utilization data processing method provided by the present invention mainly includes steps 201 to 205, which are as follows:
in this embodiment, step 103 specifically includes step 201 to step 205.
Step 201: and the edge server receives the historical data sent by the cloud server, and acquires a service delay requirement, a service database resource requirement and historical calculation delay from the historical data.
Step 202: and the edge server groups the low-voltage power distribution and utilization data according to a first preset quantity and calculates a first data quantity of each group according to the service delay requirement and the resource requirement of the service database.
In this embodiment, the first preset number may be set according to the type of the power service, and the first data amount of each group may be calculated according to the total amount of the low-voltage distribution power data and the first preset number. The first data volume of each group is the data volume of each group of data after the low-voltage power utilization data are grouped in the edge server.
Step 203: and the edge server calculates the time delay according to the history, and calculates to obtain the time delay uncertainty of the edge server.
In this embodiment, the expression of the uncertainty of the delay of the edge server is:
wherein, T n com,e (i) Computing the time delay, T, for the edge server for the nth set of data for the ith time slot n com,e (j) Calculated time delay, T, for the edge server for the jth slot group data n n delay,e (t) experimental uncertainty of the edge server for the nth set of data for the tth time slot.
Step 204: and the edge server calculates to obtain the first calculation resource of each group according to the time delay uncertainty of the edge server, the first data volume of each group and the available calculation resource of the edge server.
In this embodiment, the expression of the first computing resource is:
wherein f is e (t) the total amount of available computing resources of the ith slot edge server, A n (T) is the first data amount of the nth data set, T n delay (t) is the calculated time delay uncertainty of the nth group of data, ω and ξ are the weight parameter of the data amount of the edge server and the weight parameter of the calculated time delay uncertainty of the edge server, respectively, and the sum of ω and ξ is 1,f e n (t) is a first computational resource of n groups of data of the t-th slot.
Step 205: and after the edge server distributes computing resources according to the first computing resources of each group, the edge server processes each group of data of the low-voltage power distribution and utilization data in parallel.
Referring to fig. 3, a schematic flow chart of another embodiment of the cloud-edge-based cooperative low-voltage distribution and power utilization data processing method provided by the present invention mainly includes steps 301 to 305, which are as follows:
in this embodiment, step 103 specifically includes step 301 to step 305.
Step 301: and the cloud server receives the low-voltage power distribution and utilization data sent by the edge server, and acquires a service delay requirement, a service database resource requirement, historical calculation delay and historical transmission delay from the historical data.
In this embodiment, the cloud server further needs to obtain historical transmission delay from the historical data, and since the cloud server receives low-voltage power distribution and utilization data transmitted by the edge server, which may cause delay, and the cloud server may also cause a certain delay when processing a task of a previous period, the historical transmission delay needs to be considered when subsequently calculating the uncertainty of the delay.
Step 302: and the cloud server groups the low-voltage power distribution and utilization data according to a second preset quantity and calculates a second data quantity of each group according to the service delay requirement and the resource requirement of the service database.
In this embodiment, the second preset quantity may be set according to the type of the power service, and the second data quantity of each group may be calculated according to the total amount of the low-voltage distribution power data and the second preset quantity. And the second data volume of each group is the data volume of each group of data after the low-voltage power consumption data are grouped in the cloud server.
Step 303: and the cloud server calculates the time delay uncertainty of the cloud server according to the historical calculation time delay and the historical transmission time delay.
In this embodiment, the expression of the uncertainty of the time delay of the cloud server is:
wherein, T k com,c (i (calculation delay of cloud server of ith group data of ith slot, T) k com,c (j (computing latency of cloud server for jth slot kth group data, T) trans (i) Transmission delay, T, for allocating power to the ith time slot trans (j) Allocating transmission time delay, T, of the electrical data to the jth time slot k delay,c (t) is the latency uncertainty of the cloud server for the kth group of data for the tth time slot.
Step 304: and the cloud server calculates to obtain the second computing resource of each group according to the time delay uncertainty of the cloud server, the second data volume of each group and the available computing resource of the edge server.
In this embodiment, the expression of the second computing resource is:
wherein f is c (t) is the total amount of available computing resources of the t-th time slot cloud server, A k (T) is a second data amount of the kth group of data, T k delay,c (t) latency uncertainty, σ and of cloud server for kth group data
A weight parameter of the data volume of the cloud server and a weight parameter of the time delay uncertainty of the cloud server, respectively, and sigma and->
Constant sum of 1,f c n (t) is a second computing resource of the cloud server for the nth set of data for the tth time slot.
Step 305: and after the cloud server distributes computing resources according to the second computing resources of each group, the cloud server processes each group of data of the low-voltage power distribution and utilization data in parallel.
According to the invention, when the low-voltage distribution electricity data is processed, the time delay uncertainty is calculated through historical data, and the calculation resources required to be distributed for processing each group of low-voltage distribution electricity data are determined through the experimental uncertainty, so that the time delay compensation is realized, and the processing efficiency of the low-voltage distribution electricity data is improved.
Further, after the performing the delay compensation and allocating the computing resource, the method further includes:
calculating to obtain the current time delay of the edge server according to the distribution result of the calculation resources, or calculating to obtain the current time delay of the cloud server;
and updating the historical time delay performance according to the current time delay of the edge server or the current time delay of the cloud server.
In this embodiment, the expression of the current delay of the edge server or the current delay of the cloud server is:
wherein epsilon (t) is the number of CPU cycles required by the t-th time slot cloud server or the edge server to calculate 1bit data, A n (t) is the first or second data quantity of the nth group of data of the t time slot, f n (t) a first computing resource or a second computing resource allocated for the nth set of data for the tth time slot,
is the current delay of the nth group of data. And the values of the related variables have differences according to the difference of the cloud edge collaborative modes.
In this embodiment, the current time delay of the edge server or the current time delay of the cloud server is stored in the cloud server, and the historical time delay performance of cloud-edge cooperation is updated.
After the calculation resource is allocated, the historical time delay performance is updated according to the allocation result, so that the performance index is updated in time, the accuracy of next collaborative mode selection is improved, the calculation resource and the communication resource of the edge end or the cloud end are fully used, and the processing efficiency of the low-voltage distribution power consumption data is further improved.
Fig. 4 is a schematic structural diagram of an embodiment of the cloud-edge-based cooperative low-voltage distribution and utilization data processing device provided in the present invention, which mainly includes: an index generation module 401, a mode selection module 402, a first processing module 403 and a second processing module 404.
In this embodiment, the index generation module 401 is configured to obtain a first performance index from an edge server and a cloud server, and perform normalization processing to obtain a second performance index; wherein the second performance indicator comprises: frequency of information collection, available computing resources, available channel bandwidth, and historical latency performance.
The mode selection module 402 is configured to obtain an index score after performing index evaluation according to the second performance index, and select a cloud-edge collaborative mode according to the index score; wherein the cloud edge collaborative mode comprises: a cloud-assisted edge mode or an edge-assisted cloud mode.
The first processing module 403 is configured to, when the mode selection module 402 selects the cloud auxiliary edge mode, enable the edge server to perform time delay compensation and allocate computing resources according to the historical data sent by the cloud server, and process low-voltage power consumption data in parallel.
The second processing module 404 is configured to, when the mode selection module 402 selects the edge-assisted cloud mode, enable the cloud server to perform delay compensation and allocate computing resources according to the low-voltage power distribution and utilization data and historical data stored in a cloud end, which are sent by the edge server, and process the low-voltage power distribution and utilization data in parallel.
In this embodiment, the cloud-edge-based collaborative low-voltage power distribution and utilization data processing device further includes a time delay calculation module and an update module; the time delay calculation module is used for calculating to obtain the current time delay of the edge server according to the distribution result of the calculation resources, or calculating to obtain the current time delay of the cloud server; and the updating module is used for updating the historical time delay performance according to the current time delay of the edge server or the current time delay of the cloud server.
According to the method, after the first performance index is obtained, normalization processing is carried out, information acquisition frequency, available computing resources, available channel bandwidth and historical time delay performance which can be used for evaluation and calculation are obtained, computing resources and communication resources of an edge end and a cloud end are comprehensively considered, index scores obtained through calculation are adopted for cloud-edge collaborative mode selection, diversified collaborative mode selection is achieved, and different requirements of different power services on resources when low-voltage power distribution data are processed can be met; in addition, when the low-voltage power consumption data are processed, the edge end and the cloud end perform time delay compensation according to historical data, and the cloud-edge cooperation efficiency is improved.
The above-mentioned embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, and it should be understood that the above-mentioned embodiments are only examples of the present invention and are not intended to limit the scope of the present invention. It should be understood that any modifications, equivalents, improvements and the like, which come within the spirit and principle of the invention, may occur to those skilled in the art and are intended to be included within the scope of the invention.
Claims (10)
1. A low-voltage power distribution and utilization data processing method based on cloud edge cooperation is characterized by comprising the following steps:
acquiring a first performance index from an edge server and a cloud server, and performing normalization processing to obtain a second performance index; wherein the second performance indicator comprises: information collection frequency, available computing resources, available channel bandwidth and historical delay performance;
according to the second performance index, obtaining an index score after index evaluation, and selecting a cloud edge collaborative mode according to the index score; wherein the cloud edge collaborative mode comprises: a cloud-assisted edge mode or edge-assisted cloud mode;
when a cloud auxiliary edge mode is selected, the edge server performs time delay compensation and allocates computing resources according to historical data sent by the cloud server, and low-voltage power consumption data are processed in parallel;
when the edge-assisted cloud mode is selected, the cloud server performs time delay compensation and allocates computing resources according to the low-voltage distribution power data and the historical data stored in the cloud end sent by the edge server, and the low-voltage distribution power data are processed in parallel.
2. The cloud-edge-cooperation-based low-voltage distribution and power utilization data processing method as claimed in claim 1, wherein a first performance index is obtained from the edge server and the cloud server, and normalization processing is performed to obtain a second performance index, specifically:
acquiring a first performance index according to the computing resource and the communication resource of the edge server and the computing resource and the communication resource of the cloud server;
and according to a normalization formula, carrying out linear change on the first performance index and mapping the first performance index to a preset interval to obtain the second performance index.
3. The cloud-edge-based collaborative low-voltage distribution and utilization data processing method according to claim 2, wherein the normalization formula is:
wherein P is a first performance index to be normalized, P min Is the minimum value of the first performance index to be normalized, P max Is the maximum value of the first performance index to be normalized, and X is the second performance index.
4. The cloud-edge-based cooperative low-voltage distribution and power utilization data processing method as claimed in claim 1, wherein according to the second performance index, an index score is obtained after index evaluation is performed, and according to the index score, a cloud-edge cooperative mode is selected, specifically:
calculating a ratio of a second performance index of the edge server to a second performance index of the cloud server, and evaluating to obtain an index score by combining weight parameters of the second performance indexes;
and comparing the index score with a preset value, and selecting a cloud edge collaborative mode according to a comparison result.
5. The cloud-edge-based collaborative low-voltage distribution and utilization data processing method as claimed in claim 4, wherein the index score expression is as follows:
wherein f is e (t) available computing resources of the edge server for the t-th time slot, f c (t) is the t-th time slotAvailable computing resources of the cloud server of, B e (t) available channel bandwidth of edge server for t-th time slot, B c (T) available channel bandwidth of cloud server for tth time slot, T e com (T-1) historical delay performance of the T-1 th time slot edge server, T c com (t-1) historical time delay performance of the cloud server at the t-1 th time slot, wherein (t) is information acquisition frequency of the t-th time slot; alpha, beta, chi and delta are respectively weight parameters of available computing resources, available channel bandwidth, historical time delay performance and information acquisition frequency.
6. The cloud-edge-based cooperative low-voltage power distribution and utilization data processing method as claimed in claim 5, wherein the index score is compared with a preset value, and a cloud-edge cooperative mode is selected according to a comparison result, specifically:
comparing the index score with a preset value;
when the index score is larger than the preset value, selecting a cloud auxiliary edge mode;
and when the prime index score is not greater than the preset value, selecting a side-assisted cloud mode.
7. The cloud-edge-cooperation-based low-voltage power distribution and utilization data processing method as claimed in claim 1, wherein the edge server performs time delay compensation and allocates computing resources according to historical data sent by the cloud server, and processes the low-voltage power distribution and utilization data in parallel, specifically:
the edge server receives the historical data sent by the cloud server, and obtains a service delay requirement, a service database resource requirement and a historical calculation delay from the historical data;
the edge server groups the low-voltage power distribution and utilization data according to a first preset quantity and calculates a first data quantity of each group according to the service delay requirement and the resource requirement of the service database;
the edge server calculates the time delay according to the history, and calculates the time delay uncertainty of the edge server;
the edge server calculates to obtain a first calculation resource of each group according to the time delay uncertainty of the edge server, the first data volume of each group and the available calculation resource of the edge server;
and after the edge server distributes computing resources according to the first computing resources of each group, the edge server processes each group of data of the low-voltage power distribution and utilization data in parallel.
8. The cloud-edge-cooperation-based low-voltage power distribution and utilization data processing method as claimed in claim 1, wherein the cloud server performs delay compensation and allocates computing resources according to the low-voltage power distribution and utilization data sent by the edge server and historical data stored in a cloud, and processes the low-voltage power distribution and utilization data in parallel, specifically:
the cloud server receives the low-voltage power distribution and utilization data sent by the edge server, and acquires a service delay requirement, a service database resource requirement, a historical calculation delay and a historical transmission delay from the historical data;
the cloud server groups the low-voltage power distribution and utilization data according to a second preset quantity and calculates a second data quantity of each group according to the service delay requirement and the resource requirement of the service database;
the cloud server calculates the time delay uncertainty of the cloud server according to the historical calculation time delay and the historical transmission time delay;
the cloud server calculates to obtain second computing resources of each group according to the time delay uncertainty of the cloud server, the second data volume of each group and the available computing resources of the edge server;
and after the cloud server distributes computing resources according to the second computing resources of each group, each group of data of the low-voltage power distribution and utilization data is processed in parallel.
9. The cloud-edge coordination based low-voltage distribution and utilization data processing method according to any one of claims 1 to 8, further comprising, after the performing delay compensation and allocating computing resources:
calculating to obtain the current time delay of the edge server according to the distribution result of the calculation resources, or calculating to obtain the current time delay of the cloud server;
and updating the historical time delay performance according to the current time delay of the edge server or the current time delay of the cloud server.
10. The utility model provides a low pressure power consumption data processing apparatus based on cloud limit is in coordination which characterized in that includes: the system comprises an index generation module, a mode selection module, a first processing module and a second processing module;
the index generation module is used for acquiring a first performance index from the edge server and the cloud server and carrying out normalization processing to obtain a second performance index; wherein the second performance metric comprises: information collection frequency, available computing resources, available channel bandwidth and historical delay performance;
the mode selection module is used for obtaining an index score after index evaluation according to the second performance index and selecting a cloud edge cooperation mode according to the index score; wherein the cloud edge collaborative mode comprises: a cloud-assisted edge mode or edge-assisted cloud mode;
the first processing module is used for enabling the edge server to perform time delay compensation and allocate computing resources according to historical data sent by the cloud server when the mode selection module selects the cloud auxiliary edge mode, and processing low-voltage power consumption data in parallel;
and the second processing module is used for enabling the cloud server to perform time delay compensation and allocate computing resources according to the low-voltage power distribution and utilization data and historical data stored at the cloud end sent by the edge server when the mode selection module selects the edge auxiliary cloud mode, and processing the low-voltage power distribution and utilization data in parallel.
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| CN116680625A (en) * | 2023-08-04 | 2023-09-01 | 山东华科信息技术有限公司 | Cloud edge end cooperation-based distribution network multi-scene matching data processing method and system |
| CN117194048A (en) * | 2023-04-13 | 2023-12-08 | 山东华科信息技术有限公司 | Collaborative method for business data |
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| CN117194048A (en) * | 2023-04-13 | 2023-12-08 | 山东华科信息技术有限公司 | Collaborative method for business data |
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| CN116680625A (en) * | 2023-08-04 | 2023-09-01 | 山东华科信息技术有限公司 | Cloud edge end cooperation-based distribution network multi-scene matching data processing method and system |
| CN116680625B (en) * | 2023-08-04 | 2024-01-05 | 山东华科信息技术有限公司 | Cloud edge end cooperation-based distribution network multi-scene matching data processing method and system |
| CN117591496A (en) * | 2024-01-18 | 2024-02-23 | 中核武汉核电运行技术股份有限公司 | High-reliability time sequence data transmission and storage system based on cloud edge cooperation |
| CN117591496B (en) * | 2024-01-18 | 2024-05-03 | 中核武汉核电运行技术股份有限公司 | High-reliability time sequence data transmission and storage system based on cloud edge cooperation |
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