CN113553362A - Carbon energy consumption monitoring method and device based on consensus mechanism and storage medium - Google Patents
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Abstract
The invention provides a carbon energy consumption monitoring method, a carbon energy consumption monitoring device and a storage medium based on a consensus mechanism, wherein the carbon energy consumption monitoring method comprises the following steps: acquiring a numerical value of carbon energy consumption data in each area within a preset time period, and performing reverse sorting on each acquisition node according to the numerical value of the numerical value to obtain a first sorting result; acquiring an identification value corresponding to each acquisition node in a first sequencing result; determining an acquisition node for acquiring carbon energy data in a certain area, and placing an identification value corresponding to the acquisition node at a preset position in a first sequencing result to obtain a second sequencing result; obtaining a password fragment value in each region based on a preset time period and the quantity value of the carbon energy consumption data in each region, and placing the password fragment value of each region at the rear part of the corresponding identification value in the second sequencing result or replacing the corresponding identification value to obtain a third sequencing result; and transmitting and storing the carbon energy consumption data by taking a third sequencing result corresponding to the acquisition node in each region as a key.
Description
Technical Field
The present invention relates to carbon energy monitoring technologies, and in particular, to a carbon energy consumption monitoring method and apparatus based on a consensus mechanism, and a storage medium.
Background
Carbon energy sources include high carbon energy sources, low carbon energy sources, and the like. The high-carbon energy refers to a fuel energy with a high carbon (C) element emission proportion coefficient, and coal, petroleum and the like belong to the high-carbon energy. When environmental protection conditions of a certain area, a certain industrial area, a certain factory, and a certain company are counted, the consumption of carbon energy is used for judgment. For the carbon energy monitoring of a certain company, the environmental protection performance of the company in production and life can be reflected.
For monitoring carbon energy consumption data, the safety of the carbon energy data during transmission and storage needs to be guaranteed, and the carbon energy data is prevented from being acquired and utilized by lawbreakers.
Disclosure of Invention
Embodiments of the present invention provide a carbon energy consumption monitoring method and apparatus based on a consensus mechanism, and a storage medium, which can generate keys for transmitting and storing carbon energy data based on the consensus mechanism, so that the keys at a plurality of associated collection nodes and areas are different but associated, and security during transmission and storage of the carbon energy data can be effectively ensured.
In a first aspect of the embodiments of the present invention, a carbon energy consumption monitoring method based on a consensus mechanism is provided, where multiple acquisition nodes are configured in advance, where each acquisition node is configured to acquire carbon energy consumption data in a corresponding region, and each acquisition node processes the carbon energy consumption data based on the consensus mechanism by the following steps:
acquiring a numerical value of carbon energy consumption data in each area within a preset time period, and performing reverse sorting on each acquisition node according to the numerical value of the numerical value to obtain a first sorting result;
acquiring an identification value corresponding to each acquisition node in a first sequencing result;
determining an acquisition node for acquiring carbon energy data in a certain area, and placing an identification value corresponding to the acquisition node at a preset position in a first sequencing result to obtain a second sequencing result;
obtaining a password fragment value in each region based on a preset time period and the quantity value of the carbon energy consumption data in each region, and placing the password fragment value of each region at the rear part of the corresponding identification value in the second sequencing result or replacing the corresponding identification value to obtain a third sequencing result;
and transmitting and storing the carbon energy consumption data by taking a third sequencing result corresponding to the acquisition node in each region as a key.
Optionally, in a possible implementation manner of the first aspect, the obtaining an identification value corresponding to each collection node in the first sorting result includes:
acquiring the number of acquisition nodes, and acquiring identification values of corresponding number and identification arrangement results of the identification values based on the number of the acquisition nodes;
and the acquisition nodes in the first sequencing result are in one-to-one correspondence with the identifiers in the identifier sequencing result according to the sequencing order, and the identifier value corresponding to each acquisition node is obtained.
Optionally, in a possible implementation manner of the first aspect, determining a collection node for collecting carbon energy data in a certain area, and placing an identification value corresponding to the collection node at a preset position in the first ranking result to obtain a second ranking result includes:
combining the extracted identification value with a preset filling identification to obtain a fusion identification;
and determining a preset position in the first sequencing result, and placing the fusion identifier at the preset position in the first sequencing result to obtain a second sequencing result.
Optionally, in one possible implementation manner of the first aspect, the obtaining the password segment value in each area based on the preset time period and the quantity value of the carbon energy consumption data in each area includes:
determining a starting time point and an ending time point of a preset time period, and determining a first sub-segment value of a time dimension based on the starting time point and the ending time point;
acquiring the quantity value of the carbon energy consumption data in each region, and determining a second sub-segment value of the carbon energy consumption dimension based on the quantity value of the carbon energy consumption data in each region;
and combining the first sub-fragment value and the second sub-fragment value to obtain a password fragment value.
Optionally, in a possible implementation manner of the first aspect, determining a start time point and an end time point of the preset time period, and determining the first sub-segment value of the time dimension based on the start time point and the end time point includes:
the first sub-segment value is calculated by the following formula,
wherein the content of the first and second substances,S 1is the first sub-segment value and is,k iis as followsiThe weight value for each of the preset time periods,k p is as followspWeight value of a predetermined time period t2A quantized value, t, of an end time point of a preset time period1Is a quantized value of a start time point of a preset time period。
Optionally, in a possible implementation manner of the first aspect, obtaining a quantity value of the carbon energy consumption data in each area, and determining a second sub-segment value of the carbon energy consumption dimension based on the quantity value of the carbon energy consumption data in each area includes:
the second sub-segment value is calculated by the following formula,
wherein the content of the first and second substances,S 2is the second sub-segment value and is,L m is as followsmThe magnitude of the carbon energy consumption data in each area,L q is as followsqThe magnitude of the carbon energy consumption data in each area,Hthe coefficient of the adjustment is adjusted,Tthe values are normalized with respect to time.
Optionally, in a possible implementation manner of the first aspect, the combining the first sub-segment value and the second sub-segment value to obtain the cipher segment value includes:
and multiplying the first sub-fragment value and the second sub-fragment value to obtain a password fragment value.
Optionally, in a possible implementation manner of the first aspect, placing the cipher fragment value of each region at the rear of the corresponding identification value in the second ordering result to obtain a third ordering result includes:
wherein, the identification value and the password fragment value are characters with different forms;
and determining an identification value and a password fragment value corresponding to the acquisition node in each area, and sequentially setting the identification value at the front and the password fragment value at the back.
In a second aspect of the embodiments of the present invention, a carbon energy consumption monitoring apparatus based on a consensus mechanism is provided, where a plurality of acquisition nodes are configured in advance, where each acquisition node is configured to acquire carbon energy consumption data in a corresponding region, and each acquisition node processes the carbon energy consumption data based on the consensus mechanism by the following steps:
the first sequencing module is used for acquiring the quantity value of the carbon energy consumption data in each area in a preset time period and performing reverse sequencing on each acquisition node according to the quantity value to obtain a first sequencing result;
the identification value acquisition module is used for acquiring the identification value corresponding to each acquisition node in the first sequencing result;
the second sorting module is used for determining a collection node for collecting carbon energy data in a certain area and placing an identification value corresponding to the collection node at a preset position in the first sorting result to obtain a second sorting result;
the third sorting module is used for obtaining a password segment value in each region based on a preset time period and the quantity value of the carbon energy consumption data in each region, and placing the password segment value of each region at the rear part of the corresponding identification value in the second sorting result or replacing the corresponding identification value to obtain a third sorting result;
and the storage transmission module is used for transmitting and storing the carbon energy consumption data by taking the third sequencing result corresponding to the acquisition node in each region as a key.
In a third aspect of the embodiments of the present invention, a storage medium is provided, in which a computer program is stored, which, when being executed by a processor, is adapted to implement the method according to the first aspect of the present invention and various possible designs of the first aspect of the present invention.
The invention provides a carbon energy consumption monitoring method and device based on a consensus mechanism and a storage medium. The key for transmitting and storing the carbon energy data can be generated based on a consensus mechanism, so that the keys of a plurality of associated acquisition nodes and areas are different but associated, and the safety of the carbon energy data during transmission and storage is effectively guaranteed.
In the invention, each acquisition node generates different keys in the acquisition process of the carbon energy data. The relevance of each acquisition node can be obtained through the first sequencing result, namely the key of each acquisition node is generated by taking the first sequencing result as a bottom plate, and the first sequencing result at each acquisition node is the same. Because the main bodies of the acquisition nodes in each region are different, the main bodies of the acquisition nodes are correspondingly processed to obtain a second sequencing result, so that the keys at the acquisition nodes are different on the basis of the first sequencing result. In order to increase the complexity of the key, the invention combines the carbon energy consumption data in each area with the second sequencing result, so that the character quantity of the key in the second sequencing result meets a certain quantity, and the quantity value of the carbon energy consumption data in a certain area can be reflected. The generated key is correlated with the carbon energy consumption data for each region.
The key of each acquisition node provided by the invention is dynamically generated. Moreover, when the dynamic key is generated, each node has a certain relevance, and when each acquisition node generates the dynamic key, carbon energy consumption data acquired by all other acquisition nodes are also considered. The complexity, randomness and dynamic property of the key are guaranteed, and the safety of data transmission and storage is high.
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FIG. 1 is a schematic flow chart of a first embodiment of a carbon energy consumption monitoring method based on a consensus mechanism;
FIG. 2 is a schematic flow chart of a second embodiment of a carbon energy consumption monitoring method based on a consensus mechanism;
fig. 3 is a schematic structural diagram of a carbon energy consumption monitoring apparatus based on a consensus mechanism according to a first embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
It should be understood that, in various embodiments of the present invention, the sequence numbers of the processes do not mean the execution sequence, and the execution sequence of the processes should be determined by the functions and the internal logic of the processes, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
It should be understood that in the present application, "comprising" and "having" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that, in the present invention, "a plurality" means two or more. "and/or" is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "comprises A, B and C" and "comprises A, B, C" means that all three of A, B, C comprise, "comprises A, B or C" means that one of A, B, C comprises, "comprises A, B and/or C" means that any 1 or any 2 or 3 of A, B, C comprises.
It should be understood that in the present invention, "B corresponding to a", "a corresponds to B", or "B corresponds to a" means that B is associated with a, and B can be determined from a. Determining B from a does not mean determining B from a alone, but may be determined from a and/or other information. And the matching of A and B means that the similarity of A and B is greater than or equal to a preset threshold value.
As used herein, "if" may be interpreted as "at … …" or "when … …" or "in response to a determination" or "in response to a detection", depending on the context.
The technical solution of the present invention will be described in detail below with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments.
The invention provides a carbon energy consumption monitoring method based on a consensus mechanism, which is characterized in that a plurality of acquisition nodes are configured in advance as shown in figure 1, wherein each acquisition node is used for acquiring carbon energy consumption data in a corresponding area. The collection node may be an integrated device that may include various sensors, such as a voltage sensor, a current sensor, a flow sensor, a carbon dioxide sensor, a carbon emission detection sensor, and the like. Various sensors can be arranged in each area, and carbon emission of different enterprises can be monitored through the various sensors.
For example, a vehicle-building enterprise, which does not generate electricity, may be equipped with sensors including voltage sensors, current sensors, carbon emission detection sensors, and the like to monitor the consumption of carbon energy.
For example, a cement plant with power generation function, which may generate power by itself and use commercial power, may monitor carbon emission through a combination of various sensors such as a voltage sensor, a current sensor, a flow sensor, a carbon dioxide sensor, a carbon emission detection sensor, and the like.
The monitoring of the carbon energy consumption data by the acquisition node belongs to the prior art, and the invention is not elaborated excessively.
Each acquisition node processes carbon energy consumption data through the following steps based on a consensus mechanism, and the method comprises the following steps:
step S110, obtaining the quantity value of the carbon energy consumption data in each area in a preset time period, and performing reverse sorting on each acquisition node according to the quantity value to obtain a first sorting result. The preset time period may be 1 hour, 2 hours, 3 hours, and the like. For example, there are 4 collection nodes, as shown in table 1:
TABLE 1
Then the first sequencing result is the collection node 4, the collection node 1, the collection node 3, and the collection node 2.
And step S120, acquiring an identification value corresponding to each acquisition node in the first sequencing result. The identification value may be an english word such as say A, C, D, E, F or the like. And may also be arabic numerals such as 1,2, 3, 4, 5, and so forth.
Step S120 includes:
acquiring the number of the acquisition nodes, and acquiring identification values of the corresponding number and identification arrangement results of the identification values based on the number of the acquisition nodes. The identification value may have several values, say A, AA, AB, ZZ, etc. The present invention presets the order of the identification values. When the identification value is an english word, the order of the identification value may be AA, AB, AC, AD … ZZ. When the number of collection nodes is 4, the identification value may be the first 4 in the ordering, i.e., AA, AB, AC, AD.
And in the step, the corresponding identification value of each node is obtained according to the carbon energy consumption data of each acquisition node.
And the acquisition nodes in the first sequencing result are in one-to-one correspondence with the identifiers in the identifier sequencing result according to the sequencing order, and the identifier value corresponding to each acquisition node is obtained. For example, the first ordering result is collection node 4, collection node 1, collection node 3, and collection node 2, and the order of the identification values is AA, AB, AC, and AD. At this time, the identification value corresponding to the collection node 4 is AA, the identification value corresponding to the collection node 1 is AB, the identification value corresponding to the collection node 3 is AC, and the identification value of the collection node 2 is AD.
This step may enable each collection node to generate a respective second ordering result.
Step S130, determining a collection node for collecting carbon energy data in a certain area, and placing an identification value corresponding to the collection node at a preset position in the first sequencing result to obtain a second sequencing result. The method comprises the steps that each acquisition node obtains the same first sequencing result, the corresponding second sequencing result is customized for each acquisition node, and the identification value corresponding to the acquisition node is placed at the preset position in the first sequencing result during customization. For example, the first ordering result is AA, AB, AC, and AD, at this time, the second ordering result that the collection node 3 needs to be generated is generated, and at this time, the identification value corresponding to the collection node 3 is placed at the preset position. The preset position may be a first position of the first ordering result, and the second ordering result generated at the collection node 3 at this time is AC, AA, AB, AD.
In step S130, the method includes:
and combining the extracted identification value with a preset filling identification to obtain a fusion identification. In some specific cases, for example, when the second sorting result of the collection node 4 is generated, since the corresponding identification value AA itself is located at the first position of the first sorting result, the second sorting result may be consistent with the first sorting result, and in order to ensure that each second sorting result is inconsistent with the first sorting result, the extracted identification value is processed at this time to obtain the fusion identification.
For example, if the preset padding identifier is &, the fusion identifier is obtained by fusing the identifier AA and the padding identifier.
And determining a preset position in the first sequencing result, and placing the fusion identifier at the preset position in the first sequencing result to obtain a second sequencing result. The preset position is the first position in the first sorting result, and the second sorting result of the collecting node 4 is AA & and AB, AC, and AD.
Through the technical scheme, each second sequencing result is different from each second sequencing result, so that the step of calculating the key at each acquisition node can be synchronous, and each node has similar calculation steps when accounting is carried out.
And S140, obtaining a password segment value in each region based on a preset time period and the quantity value of the carbon energy consumption data in each region, and placing the password segment value of each region at the rear part of the corresponding identification value in the second sequencing result or replacing the corresponding identification value to obtain a third sequencing result.
When the first sorting result and the second sorting result are obtained, only the relation of the magnitude of the quantity value of the carbon energy consumption data at each collecting node is referred to, and at this time, the number of characters of the key generated based on the first sorting result and the second sorting result is small, the safety is low, and only the dimension of the magnitude of the quantity value of the energy consumption data at each collecting node is considered. Therefore, the present invention will generate a third ranking result according to the time dimension and the quantity dimension of the carbon energy consumption data.
And the third sequencing result is obtained on the basis of the second sequencing result, the password fragments corresponding to each region and the acquisition node are obtained according to the preset time period of each region and the quantity value of the carbon energy consumption data in each region, and each password fragment is placed at the rear part of the corresponding identification value in the second sequencing result or replaces the corresponding identification value to obtain the third sequencing result.
In the scheme that the password fragments are placed behind the corresponding identification values in the second sorting result to obtain the third sorting result, for example, the second sorting results generated at the collecting node 3 are AC & ltSUB & gt, AA, AB, and AD, and the password fragments generated at each collecting node are as shown in table 2, then the third sorting results generated at this time are AC & ltSUB & gt 44682, AA77890, AB50309, and AD 32788.
Placing each password fragment in a scheme in which the second sorting result replaces the corresponding identification value to obtain a third sorting result, for example, the second sorting result generated at the collecting node 3 is AC & ltx & gt, AA, AB, and AD, and the password fragment generated at each collecting node is as shown in table 2, and then the generated third sorting result is 44682 & ltx & gt, 77890, 50309, 32788;
TABLE 2
Through the two ways of generating the third sorting result, each acquisition node can generate a unique third sorting result. Since the code segment considers the time dimension and the numerical dimension of the carbon energy consumption data, the third sequencing result generated by each acquisition node is different when the third sequencing result is transversely compared with other acquisition nodes. And the third ordering result generated by each collection node at the previous time instance is also different.
By the method, the complexity of the key generated based on the third sequencing result is guaranteed, the data size is reduced, and the fact that the generated key is different every time is guaranteed. And the key of each preset time period is dynamically changed, so that the encryption is better.
As shown in fig. 2, step S140 includes:
step S1401, determining a starting time point and an ending time point of a preset time period, and determining a first sub-segment value of a time dimension based on the starting time point and the ending time point.
Determining a start time point and an end time point of a preset time period, the determining a first sub-segment value of the time dimension based on the start time point and the end time point comprising:
the first sub-segment value is calculated by the following formula,
wherein the content of the first and second substances,S 1is the first sub-segment value and is,k i is the weight value of the ith preset time period,k p is as followspThe weight value for each of the preset time periods,t 2is a quantized value of the end time point of the preset time period,t 1is a quantized value of a starting time point of a preset time period.
In the present invention, the preset time period may be set periodically by one day, for example, one preset time period is 24 hours a day. However, in production and life, the carbon emission amount at each time point is different, and the carbon emission amount is large in the daytime, so that the magnitude of the carbon energy consumption data collected and monitored at each collection node is large, and therefore, the data needs to be stored once at a small interval, that is, the data in the cache is stored in the storage unit. More energy consumption data cannot be stored in the cache, so that the slow operation and even breakdown of the system caused by more occupied cache are avoided.
The preset time period of the present invention may be different, for example, half a day may be 30 points to a preset event period, and night may be 120 minutes to a time period.
Since the preset time periods are different in magnitude, the present invention sets different weight values for different time periods.
When the first sub-segment value is calculated, the weight ratio of each time segment is calculated, and the first sub-segment value related to the time dimension is obtained by combining time.t 1A quantized value of a starting time point of a preset time period,t 2Is a quantized value of an end time point of the preset time period.
For example, in one day, there are 86400 seconds and the time is 00: the quantized value of 00:01 is 1, and the quantized value of 23:59:59 is 86400.
Step S1402, obtaining a quantity value of the carbon energy consumption data in each region, and determining a second sub-segment value of the carbon energy consumption dimension based on the quantity value of the carbon energy consumption data in each region.
Obtaining a quantity value of the carbon energy consumption data in each region, and determining a second sub-segment value of the carbon energy consumption dimension based on the quantity value of the carbon energy consumption data in each region comprises:
the second sub-segment value is calculated by the following formula,
wherein the content of the first and second substances,S 2is the second sub-segment value and is,L m is as followsmThe magnitude of the carbon energy consumption data in each area,L q is as followsqAmount of carbon energy consumption data within an individual regionThe value of the one or more of the one,Hthe coefficient of the adjustment is adjusted,Tthe values are normalized with respect to time.
In the invention, the ratio of the quantity value of the carbon energy consumption data collected by each collection node to the quantity value of the total carbon energy consumption data is fully considered. Since the carbon energy consumption data of each collection node may be different for each time period, the present invention determines the second sub-segment value by calculating the magnitude of the carbon energy consumption data in each collection node. Is adjusted by an adjustment factor so that
The size of the particles can not be too small,Hmay be a constant.
The length of the period for collecting the data reflecting the energy consumption of each carbon source can be determined, and when the preset time period is longer,
the larger the adjustment factor is, the larger the adjustment factor is. Because the preset time period is larger only when the carbon emission is less, in order to ensure that the quantity value of the second sub-segment value in each preset time period does not differ greatly, the invention can dynamically adjust the adjustment coefficient and ensure the consistency of the quantity value of the second sub-segment value.
Step S1403, the first sub-segment value and the second sub-segment value are combined to obtain a password segment value. The first sub-segment value may be 327 and the second sub-segment value may be 88, and the resulting cipher segment value is 32788. This way is to combine the first sub-segment and the second sub-segment values.
In one possible embodiment, combining the first sub-segment value and the second sub-segment value to obtain the cipher segment value comprises:
and multiplying the first sub-fragment value and the second sub-fragment value to obtain a password fragment value. When the password fragment value is obtained, the invention can adopt various modes, the first sub-fragment value can be 327, the second sub-fragment value can be 88, and the obtained password fragment value is 327 multiplied by 88 and is equal to 28776.
When the password fragment value is obtained by combining the first sub-fragment value and the second sub-fragment value in two modes, a direct combination mode can be adopted, and a multiplication mode can also be adopted, the difference of the two modes lies in the direct combination mode, so that the source tracing is facilitated, the first sub-fragment value and the second sub-fragment value are conveniently determined, the multiplication mode can possibly change the digital quantity of the first sub-fragment value and the second sub-fragment value, and the source tracing is not easy to occur.
In one possible embodiment, the placing the cipher fragment value of each region at the rear of the corresponding identification value in the second sorting result or replacing the corresponding identification value to obtain a third sorting result includes:
wherein the identification value and the password fragment value are characters of different forms. For example, the identification value is an English word and the password segment is an Arabic numeral.
And determining an identification value and a password fragment value corresponding to the acquisition node in each area, and sequentially setting the identification value at the front and the password fragment value at the back.
The invention can combine or replace the identification value and the password fragment value according to the preset sequence of the identification value and the password fragment value to obtain a corresponding third sequencing result.
And S150, transmitting and storing the carbon energy consumption data by taking a third sequencing result corresponding to the acquisition node in each area as a key.
The third sequencing result is obtained through the above mode, and the dimensionality of the quantity value of the carbon energy consumption data among the collection nodes, the dimensionality of the preset time period of each collection node and the dimensionality of the quantity value of the carbon energy consumption data are fully considered. Each acquisition node generates a corresponding and unique key based on the consensus, so that the keys generated among the acquisition nodes have certain relevance and are different.
The acquisition nodes in the invention can be acquisition nodes at a block chain, when each acquisition node generates a corresponding key, other blocks carry out accounting to generate a corresponding key table, wherein the key table can have the key corresponding to each transmitted and stored carbon energy consumption data.
When each acquisition node acquires and monitors carbon energy consumption data, other acquisition nodes can also perform corresponding accounting.
The person in each collection node having the corresponding management authority may view the key table, and the corresponding management authority may be the highest authority.
The invention also provides a carbon energy consumption monitoring device based on a consensus mechanism, as shown in fig. 3, a plurality of acquisition nodes are configured in advance, wherein each acquisition node is used for acquiring carbon energy consumption data in a corresponding region, and each acquisition node processes the carbon energy consumption data based on the consensus mechanism through the following steps, including:
the first sequencing module is used for acquiring the quantity value of the carbon energy consumption data in each area in a preset time period and performing reverse sequencing on each acquisition node according to the quantity value to obtain a first sequencing result;
the identification value acquisition module is used for acquiring the identification value corresponding to each acquisition node in the first sequencing result;
the second sorting module is used for determining a collection node for collecting carbon energy data in a certain area and placing an identification value corresponding to the collection node at a preset position in the first sorting result to obtain a second sorting result;
the third sorting module is used for obtaining a password segment value in each region based on a preset time period and the quantity value of the carbon energy consumption data in each region, and placing the password segment value of each region at the rear part of the corresponding identification value in the second sorting result or replacing the corresponding identification value to obtain a third sorting result;
and the storage transmission module is used for transmitting and storing the carbon energy consumption data by taking the third sequencing result corresponding to the acquisition node in each region as a key.
The storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, a storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Additionally, the ASIC may reside in user equipment. Of course, the processor and the storage medium may reside as discrete components in a communication device. The storage medium may be read-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetic tapes, floppy disks, optical data storage devices, and the like.
The present invention also provides a program product comprising execution instructions stored in a storage medium. The at least one processor of the device may read the execution instructions from the storage medium, and the execution of the execution instructions by the at least one processor causes the device to implement the methods provided by the various embodiments described above.
In the above embodiments of the terminal or the server, it should be understood that the Processor may be a Central Processing Unit (CPU), other general-purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. The carbon energy consumption monitoring method based on the consensus mechanism is characterized in that a plurality of acquisition nodes are configured in advance, wherein each acquisition node is used for acquiring carbon energy consumption data in a corresponding area, and each acquisition node processes the carbon energy consumption data based on the consensus mechanism through the following steps:
acquiring a numerical value of carbon energy consumption data in each area within a preset time period, and performing reverse sorting on each acquisition node according to the numerical value of the numerical value to obtain a first sorting result;
acquiring an identification value corresponding to each acquisition node in a first sequencing result;
determining an acquisition node for acquiring carbon energy data in a certain area, and placing an identification value corresponding to the acquisition node at a preset position in a first sequencing result to obtain a second sequencing result;
obtaining a password fragment value in each region based on a preset time period and the quantity value of the carbon energy consumption data in each region, and placing the password fragment value of each region at the rear part of the corresponding identification value in the second sequencing result or replacing the corresponding identification value to obtain a third sequencing result;
and transmitting and storing the carbon energy consumption data by taking a third sequencing result corresponding to the acquisition node in each region as a key.
2. The carbon energy consumption monitoring method based on the consensus mechanism as claimed in claim 1,
the obtaining of the identification value corresponding to each collection node in the first sequencing result includes:
acquiring the number of acquisition nodes, and acquiring identification values of corresponding number and identification arrangement results of the identification values based on the number of the acquisition nodes;
and the acquisition nodes in the first sequencing result are in one-to-one correspondence with the identifiers in the identifier sequencing result according to the sequencing order, and the identifier value corresponding to each acquisition node is obtained.
3. The carbon energy consumption monitoring method based on the consensus mechanism as claimed in claim 2,
the determining of the collection node for collecting the carbon energy data in a certain area, and the placing of the identification value corresponding to the collection node at the preset position in the first sequencing result to obtain a second sequencing result includes:
combining the extracted identification value with a preset filling identification to obtain a fusion identification;
and determining a preset position in the first sequencing result, and placing the fusion identifier at the preset position in the first sequencing result to obtain a second sequencing result.
4. The carbon energy consumption monitoring method based on the consensus mechanism as claimed in claim 3,
the obtaining of the password segment value in each region based on the preset time period and the quantity value of the carbon energy consumption data in each region includes:
determining a starting time point and an ending time point of a preset time period, and determining a first sub-segment value of a time dimension based on the starting time point and the ending time point;
acquiring the quantity value of the carbon energy consumption data in each region, and determining a second sub-segment value of the carbon energy consumption dimension based on the quantity value of the carbon energy consumption data in each region;
and combining the first sub-fragment value and the second sub-fragment value to obtain a password fragment value.
5. The carbon energy consumption monitoring method based on the consensus mechanism as claimed in claim 4,
the determining a starting time point and an ending time point of a preset time period, and the determining a first sub-segment value of a time dimension based on the starting time point and the ending time point comprises:
the first sub-segment value is calculated by the following formula,
wherein the content of the first and second substances,S 1is the first sub-segment value and is,k iis as followsiThe weight value for each of the preset time periods,k pis as followspThe weight value for each of the preset time periods,t 2is a quantized value of the end time point of the preset time period,t 1is a quantized value of a starting time point of a preset time period.
6. The carbon energy consumption monitoring method based on the consensus mechanism as claimed in claim 5,
the obtaining of the quantity value of the carbon energy consumption data in each region, and the determining of the second sub-segment value of the carbon energy consumption dimension based on the quantity value of the carbon energy consumption data in each region includes:
the second sub-segment value is calculated by the following formula,
wherein the content of the first and second substances,S 2is the second sub-segment value and is,
is as followsmMagnitude of carbon energy consumption data, L, in individual regionqIs as followsqThe magnitude of the carbon energy consumption data in each region, H is the adjustment coefficient, and T is the time normalization value.
7. The carbon energy consumption monitoring method based on the consensus mechanism as claimed in claim 6,
combining the first sub-segment value and the second sub-segment value to obtain a cipher segment value comprises:
and multiplying the first sub-fragment value and the second sub-fragment value to obtain a password fragment value.
8. The carbon energy consumption monitoring method based on the consensus mechanism as claimed in claim 7,
placing the cipher fragment value of each region at the rear of the corresponding identification value in the second sorting result to obtain a third sorting result comprises:
wherein, the identification value and the password fragment value are characters with different forms;
and determining an identification value and a password fragment value corresponding to the acquisition node in each area, and sequentially setting the identification value at the front and the password fragment value at the back.
9. Carbon energy consumption monitoring devices based on consensus mechanism, characterized in that, dispose a plurality of collection nodes in advance, wherein every collection node is used for gathering the carbon energy consumption data in the corresponding region, every collection node is based on consensus mechanism through following steps to carbon energy consumption data processing, include:
the first sequencing module is used for acquiring the quantity value of the carbon energy consumption data in each area in a preset time period and performing reverse sequencing on each acquisition node according to the quantity value to obtain a first sequencing result;
the identification value acquisition module is used for acquiring the identification value corresponding to each acquisition node in the first sequencing result;
the second sorting module is used for determining a collection node for collecting carbon energy data in a certain area and placing an identification value corresponding to the collection node at a preset position in the first sorting result to obtain a second sorting result;
the third sorting module is used for obtaining a password segment value in each region based on a preset time period and the quantity value of the carbon energy consumption data in each region, and placing the password segment value of each region at the rear part of the corresponding identification value in the second sorting result or replacing the corresponding identification value to obtain a third sorting result;
and the storage transmission module is used for transmitting and storing the carbon energy consumption data by taking the third sequencing result corresponding to the acquisition node in each region as a key.
10. Storage medium, characterized in that a computer program is stored in the storage medium, which computer program, when being executed by a processor, is adapted to carry out the method of any one of claims 1 to 8.
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