CN110602103B - Electronic lock protocol conversion optimization method and electronic lock protocol conversion optimizer - Google Patents
Electronic lock protocol conversion optimization method and electronic lock protocol conversion optimizer Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/08—Protocols for interworking; Protocol conversion
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
Abstract
The invention discloses an electronic lock protocol conversion optimization method and an electronic lock protocol conversion optimizer. The method comprises the following steps: step S1, receiving the electronic lock protocol conversion requirement sent by the terminal; step S2, obtaining characteristic data corresponding to each electronic lock protocol conversion scheme, wherein the characteristic data comprises a current electronic lock network congestion delay parameter, and a ratio of current electronic lock protocol conversion time consumption to consumed bandwidth cost; step S3, determining the optimal feature data according to the current network congestion delay parameter of the electronic lock of each feature data, the current ratio of the conversion time consumption of the electronic lock protocol to the cost of the consumed bandwidth; and step S4, taking the electronic lock protocol conversion scheme corresponding to the optimal characteristic data as the current optimal electronic lock protocol conversion scheme, and outputting the current optimal electronic lock protocol conversion scheme.
Description
Technical Field
The invention relates to the technical field of communication, in particular to an electronic lock protocol conversion optimization method and an electronic lock protocol conversion optimizer.
Background
With the rapid development of artificial intelligence and mobile edge computing, the number of edge termination devices has increased rapidly, while the amount of data generated by the edge termination devices has reached the level of the Zeyte (ZB). The centralized data processing cannot effectively process the massive data generated by the edge terminal device, and the edge cloud has been generally recognized as one of the main trends of the next generation digital transformation in the industry. The Mobile Edge Computing (MEC) migrates part of Computing tasks of a traditional cloud Computing platform to an access domain, deeply fuses traditional services and internet services, reduces end-to-end time delay of traditional service delivery, brings a brand new mode to operation of an operator, and establishes a brand new industry chain and an ecosphere. The 5G network is a fifth generation mobile communication network, and the peak theoretical transmission speed can reach tens of Gb per second. Under the circumstances, in the face of the increasingly urgent 5G edge computing requirement, the rapid and continuous development of the protocol conversion mechanism of the electronic fingerprint lock system for remotely transmitting fingerprint authorization based on 5G edge computing is of great significance.
In the prior art, with the rapid growth of 5G and edge cloud bearer services, the problems of inconvenient operation, prolonged operation time, dependence on manual auxiliary operation and the like caused by simultaneous operation of protocol conversion of an electronic lock are increasingly prominent. The existing electronic lock needs to carry out protocol conversion in a short distance, and the system does not fully consider the problems of inconvenient operation, prolonged operation time, dependence on manual auxiliary operation and the like caused by simultaneous and simultaneous operation.
Disclosure of Invention
The present invention is directed to solve at least one of the above technical problems in the prior art, and provides an electronic lock protocol conversion optimization method and an electronic lock protocol conversion optimizer.
In order to achieve the above object, the present invention provides an electronic lock protocol conversion optimization method, which includes:
step S1, receiving the electronic lock protocol conversion requirement sent by the terminal;
step S2, obtaining characteristic data corresponding to each electronic lock protocol conversion scheme, wherein the characteristic data comprises a current electronic lock network congestion delay parameter, and a ratio of current electronic lock protocol conversion time consumption to consumed bandwidth cost;
step S3, determining the optimal feature data according to the current network congestion delay parameter of the electronic lock of each feature data, the current ratio of the conversion time consumption of the electronic lock protocol to the cost of the consumed bandwidth;
and step S4, taking the electronic lock protocol conversion scheme corresponding to the optimal characteristic data as the current optimal electronic lock protocol conversion scheme, and outputting the current optimal electronic lock protocol conversion scheme.
Optionally, the feature data further includes a network congestion delay parameter of the electronic lock with the smallest history, and a ratio of time consumed for protocol conversion of the electronic lock with the smallest history to cost of consumed bandwidth; step S3 includes:
step S31, generating current judgment parameters corresponding to each characteristic data according to the current electronic lock network congestion delay parameter, the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio, the electronic lock network congestion delay parameter with the smallest history, and the electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data;
step S32, comparing the current judgment parameters corresponding to the characteristic data to determine the characteristic data with the minimum judgment parameters;
step S33, generating an evaluation value and an evaluation reference value corresponding to the feature data with the minimum judgment parameter according to the current network congestion delay parameter of the electronic lock in the feature data with the minimum judgment parameter, the current conversion time consumption of the electronic lock protocol and the consumed bandwidth cost ratio;
step S34, determining whether the evaluation value is less than or equal to the evaluation reference value, if so, performing step S37, otherwise, performing step S35;
step S35, generating an iterated electronic lock network congestion delay parameter and an iterated electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data according to the current electronic lock network congestion delay parameter and the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data;
step S36, taking the iterated electronic lock network congestion delay parameter of each feature data as the current electronic lock network congestion delay parameter of each feature data, taking the iterated electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data as the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data, and executing step S31;
step S37, determining that the feature data having the smallest judgment parameter is the optimum feature data, and executing step S4.
Optionally, step S31 is preceded by:
step S30a, setting an iteration initial parameter k equal to 0;
step S30b, adding 1 to the current iteration times k;
step S31 includes:
step S31a, according to the current network congestion delay parameter of the electronic lock, the current ratio of the conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, the minimum historical network congestion delay parameter of the electronic lock, the ratio of the conversion time consumption of the minimum historical electronic lock protocol to the consumed bandwidth cost, and the judgment parameter formula:
wherein the content of the first and second substances,
indicating the current electronic lock network congestion delay parameter,
represents the ratio of the time consumption of the protocol conversion of the current electronic lock to the cost of the consumed bandwidth, LGminNetwork congestion delay parameter, W, representing a minimum historical electronic lockGminRepresenting the ratio of time consumed to cost of consumed bandwidth for the protocol conversion of the electronic lock with the smallest history, ZkRepresenting the current judgment parameter, k representing the current iteration times, k belonging to [1, d ]]D is a preset threshold, k (mod2) represents the remainder of dividing k by 2, k (mod3) represents the remainder of dividing k by 3, m, n, and p represent adjustment constants, i, j, and t represent three-dimensional coordinates in a preset storage model corresponding to feature data, i represents an abscissa of the feature data, i is 0,1, 2, …, m, j represents an ordinate of the feature data, j is 0,1, 2, …, n, and t represents a vertical coordinate of the feature data, and t is 0,1, 2, …, and p.
Optionally, step S33 includes:
step S33a, according to the current network congestion delay parameter of the electronic lock, the ratio of the current conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, and the iterative evaluation value function formula in the feature data with the minimum judgment parameter:
calculating an evaluation value corresponding to the feature data with the minimum judgment parameter; wherein the content of the first and second substances,
to represent
The variance of the square of (a) is,
to represent
The variance of the square of (a) is,
denotes the base k (mod3) to
Is the logarithm of a true number, QkRepresenting a current evaluation value corresponding to the feature data with the minimum judgment parameter;
step S33b, according to the current network congestion delay parameter of the electronic lock, the current ratio of the conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, and the iterative evaluation reference value function formula in the feature data with the minimum judgment parameter:
calculating an evaluation reference value corresponding to the feature data with the minimum judgment parameter, wherein,
to represent
Number of square ofThe expectation is learned and the information is displayed,
to represent
Mathematical expectation of the square of RkAnd the evaluation reference value is the current evaluation reference value corresponding to the characteristic data with the minimum judgment parameter.
Optionally, step S34 includes:
step S34a, according to the evaluation value, evaluation reference value, and iterative evaluation condition generated in step S33: qk≤RkAnd judging whether the evaluation value and the evaluation reference value meet the iterative evaluation condition, if so, executing step S37, and if not, executing step S35.
Optionally, step S35 includes:
step S35a, current congestion delay parameter of electronic lock network according to each characteristic data
The ratio of the time consumption of protocol conversion of the current electronic lock to the cost of the consumed bandwidth
Generating a current composite vector corresponding to each feature data
Step S35b, current congestion delay parameter of electronic lock network according to each characteristic data
Minimum electronic lock network congestion delay parameter L in k iterationkminRatio of current electronic lock protocol conversion time consumption to consumed bandwidth cost
Ratio W of time consumption to cost of consumed bandwidth of protocol conversion of electronic lock with minimum k iterationkminAnd the formula:
calculating a depth unsupervised learning enhancement factor corresponding to each feature data in the (k + 1) th iteration
Where (k + π) mod3 represents the remainder of (k + π) divided by 3, π represents a constant, π ∈ (0, 1);
step S35c, a current complex vector corresponding to each feature data
Depth unsupervised learning enhancement factor corresponding to each feature data in (k + 1) th iteration
And the formula:
calculating a composite vector corresponding to each feature data in the k +1 th iteration
Wherein, delta represents a constant, and the number of the second electrode,
step S35d, according to the compound vector corresponding to each feature data in the k +1 th iteration
Determining the iterated congestion delay parameter of the electronic lock network of each feature data in the (k + 1) th iteration
Ratio of time consumption to bandwidth cost consumed by protocol conversion of electronic lock after iteration
Optionally, step S36 includes: iterative electronic lock network congestion delay parameter of each characteristic data in the (k + 1) th iteration
As the current congestion delay parameter of the electronic lock network of each feature data, and the ratio of the time consumption of the electronic lock protocol conversion after the iteration of each feature data in the (k + 1) th iteration to the cost of the consumed bandwidth
As the ratio of the consumed time to the consumed bandwidth cost of the current electronic lock protocol conversion of each feature data, step S30b is executed.
Optionally, step S35 is followed by:
step S35e, judging whether the value of the current iteration times k is larger than a preset threshold value d, if so, executing step S35f, and if not, executing step S36;
step S35f is executed to set the current feature data having the smallest judgment parameter as the optimum feature data, and step S4 is executed.
In order to achieve the above object, the present invention further provides an electronic lock protocol conversion optimizer, including:
the receiving module is used for receiving the electronic lock protocol conversion optimization requirement sent by the terminal;
the acquisition module is used for acquiring characteristic data corresponding to each electronic lock protocol conversion scheme, wherein the characteristic data comprise a current electronic lock network congestion delay parameter, and a ratio of current electronic lock protocol conversion time consumption to consumed bandwidth cost;
the determining module is used for determining optimal characteristic data according to the current network congestion delay parameter of the electronic lock of each characteristic data, the current conversion time consumption of the electronic lock protocol and the consumed bandwidth cost ratio;
and the output module is used for taking the electronic lock protocol conversion scheme corresponding to the optimal characteristic data as the current optimal electronic lock protocol conversion scheme and outputting the current optimal electronic lock protocol conversion scheme.
Optionally, the feature data further includes a network congestion delay parameter of the electronic lock with the smallest history, and a ratio of time consumed for protocol conversion of the electronic lock with the smallest history to cost of consumed bandwidth; the determining module is specifically configured to:
and step 37, determining that the current feature data with the minimum judgment parameter is the optimal feature data, and triggering an output module to execute the step of taking the electronic lock protocol conversion scheme corresponding to the optimal feature data as the current optimal electronic lock protocol conversion scheme and outputting the current optimal electronic lock protocol conversion scheme.
The invention has the following beneficial effects:
in the technical scheme of the electronic lock protocol conversion optimization method and the electronic lock protocol conversion optimizer, the optimal characteristic data is determined according to the current electronic lock network congestion delay parameter of each characteristic data, the ratio of the current electronic lock protocol conversion time consumption to the consumed bandwidth cost, the electronic lock protocol conversion scheme corresponding to the optimal characteristic data is used as the current optimal electronic lock protocol conversion scheme, and the current optimal electronic lock protocol conversion scheme is output. Therefore, remote operation of protocol conversion of the electronic lock in different places is facilitated, and low time delay of protocol conversion operation is realized.
Drawings
Fig. 1 is a flowchart of an electronic lock protocol conversion optimization method according to an embodiment of the present invention;
fig. 2 is a flowchart of an electronic lock protocol conversion optimization method according to a second embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a storage model corresponding to feature data;
fig. 4 is a schematic diagram illustrating an application of the electronic lock protocol conversion optimization method according to the second embodiment of the present invention;
FIG. 5 is a diagram illustrating an original protocol and a target protocol to be converted of an electronic lock;
fig. 6 is a schematic structural diagram of an electronic lock protocol conversion optimizer according to a third embodiment of the present invention;
fig. 7 is a schematic diagram of an application of the electronic lock protocol conversion optimizer according to a third embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the following describes in detail an electronic lock protocol conversion optimization method and an electronic lock protocol conversion optimizer provided in the present invention with reference to the accompanying drawings.
Fig. 1 is a flowchart of an electronic lock protocol conversion optimization method according to an embodiment of the present invention, and as shown in fig. 1, the electronic lock protocol conversion optimization method includes:
and step S1, receiving the electronic lock protocol conversion optimization requirement sent by the terminal.
And step S2, acquiring characteristic data corresponding to each electronic lock protocol conversion scheme, wherein the characteristic data comprises the current network congestion delay parameter of the electronic lock, and the ratio of the current time consumption of electronic lock protocol conversion to the consumed bandwidth cost.
And step S3, determining the optimal feature data according to the current network congestion delay parameter of the electronic lock of each feature data, the current ratio of the time consumed for converting the electronic lock protocol to the consumed bandwidth cost.
And step S4, taking the electronic lock protocol conversion scheme corresponding to the optimal characteristic data as the current optimal electronic lock protocol conversion scheme, and outputting the current optimal electronic lock protocol conversion scheme.
In the technical scheme of the method for optimizing conversion of the electronic lock protocol provided in this embodiment, the optimal feature data is determined according to the current network congestion delay parameter of the electronic lock of each feature data, the ratio of the current time consumption for conversion of the electronic lock protocol to the consumed bandwidth cost, the electronic lock protocol conversion scheme corresponding to the optimal feature data is used as the current optimal electronic lock protocol conversion scheme, and the current optimal electronic lock protocol conversion scheme is output. Therefore, remote operation of protocol conversion of the electronic lock in different places is facilitated, and low time delay of protocol conversion operation is realized.
Fig. 2 is a flowchart of an electronic lock protocol conversion optimization method according to a second embodiment of the present invention, and as shown in fig. 2, the electronic lock protocol conversion optimization method includes:
and step S1, receiving the electronic lock protocol conversion requirement sent by the terminal.
Specifically, in this embodiment, the protocol conversion requirement of the electronic lock may be actively reported and acquired by the terminal at preset time intervals, or periodically acquired by querying the terminal through a query mechanism.
The terminal is a terminal of an electronic lock operator, for example, the terminal is a mobile phone, a tablet computer, and the like. The electronic lock protocol conversion requirement can comprise information such as identification of a target electronic lock, original protocol, target protocol to be converted, identification of an electronic lock operator and the like. In this embodiment, the electronic lock may be an electronic fingerprint lock.
And step S2, acquiring characteristic data corresponding to each electronic lock protocol conversion scheme, wherein the characteristic data comprises the current network congestion delay parameter of the electronic lock, and the ratio of the current time consumption of electronic lock protocol conversion to the consumed bandwidth cost.
Each electronic lock protocol conversion scheme may be a preset electronic lock protocol conversion scheme adopted when historical time is used for processing historical electronic lock protocol conversion requirements.
When electronic lock protocol conversion is carried out on target electronic locks in historical electronic lock protocol conversion requirements by adopting each electronic lock protocol conversion scheme, initial electronic lock network congestion delay parameters corresponding to each electronic lock protocol conversion scheme and the ratio of time consumption and consumed bandwidth cost of the initial electronic lock protocol conversion can be determined.
After determining the initial network congestion delay parameter of the electronic lock corresponding to each electronic lock protocol conversion scheme and the ratio of the time consumption of the initial electronic lock protocol conversion to the cost of the consumed bandwidth, generating characteristic data corresponding to each electronic lock protocol conversion scheme according to the initial electronic lock network congestion delay parameter corresponding to each electronic lock protocol conversion scheme, the ratio of the time consumed for the initial electronic lock protocol conversion to the cost of the consumed bandwidth, the characteristic data comprises an initial electronic lock network congestion delay parameter, an initial electronic lock protocol conversion time consumption and consumed bandwidth cost ratio, wherein the initial network congestion delay parameter of the electronic lock is the current network congestion delay parameter of the electronic lock in step S2, the ratio of the initial electronic lock protocol conversion time consumption to the consumed bandwidth cost is the ratio of the current electronic lock protocol conversion time consumption to the consumed bandwidth cost in step S2. In this embodiment, the feature data further includes a network congestion delay parameter of the electronic lock with the smallest history, and a ratio of consumed time to consumed bandwidth cost of protocol conversion of the electronic lock with the smallest history.
In this embodiment, each electronic lock protocol conversion scheme may be used to process a plurality of historical electronic lock protocol conversion requirements, so that the number of the current electronic lock network congestion delay parameter and the ratio of the current electronic lock protocol conversion time consumption to the consumed bandwidth cost may be multiple. Network congestion delay parameter according to current electronic lock
The ratio of the time consumption of protocol conversion of the current electronic lock to the cost of the consumed bandwidth
Can generate the current composite vector corresponding to each characteristic data
Wherein i, j, and t represent three-dimensional coordinates in a preset storage model corresponding to the feature data, i represents an abscissa of the feature data, i is 0,1, 2, …, m, j represents an ordinate of the feature data, j is 0,1, 2, …, n, t represents a vertical coordinate of the feature data, and t is 0,1, 2, …, p, m, n, p represent adjustment constants. FIG. 3 is a schematic structural diagram of a storage model corresponding to feature data, and as shown in FIG. 3, the storage model corresponding to feature data includes at least one storage model corresponding to feature data
The ratio of the time consumption for electronic lock protocol conversion to the cost of the consumed bandwidth is the ratio of the time consumption for electronic lock protocol conversion to the consumed bandwidth.
Step S21, establishing an iterative model, wherein the iterative model comprises:
judging a parameter formula:
iterative evaluation value function formula:
iterative evaluation reference value function formula:
and (3) iterative evaluation conditions: qk≤Rk；
Compounding vectors:
the iterated composite vector:
deep unsupervised learning enhancement factor:
where k represents the number of iterations, k ∈ [1, d ]]D is a predetermined threshold value, ZkRepresenting the judgment parameters corresponding to the characteristic data calculated at the k-th iteration,
representing the network congestion delay parameter of the electronic lock in the characteristic data calculated at the k-th iteration,
representing the ratio of the electronic lock protocol conversion time to the consumed bandwidth cost in the characteristic data calculated at the k-th iteration,
representing the complex vector corresponding to the feature data calculated at the k-th iteration,
represents the composite vector corresponding to the feature data calculated at the (k + 1) th iteration,
indicating a deep unsupervised learning reinforcement factor, L, corresponding to the feature data calculated at the (k + 1) th iterationGminNetwork congestion delay parameter, W, representing a minimum historical electronic lockGminThe ratio of consumed time to consumed bandwidth cost of electronic lock protocol conversion representing the minimum history is shown, k (mod2) represents the remainder of dividing k by 2, k (mod3) represents the remainder of dividing k by 3, theta represents a constant, k (mod3) represents the remainder of dividing k by 3, and Q representskIndicating the current evaluation value, R, corresponding to the characteristic data currently having the smallest decision parameterkDenotes a current evaluation reference value corresponding to feature data currently having the smallest judgment parameter, m, n, and p denote adjustment constants, i, j, and t denote three-dimensional coordinates in a preset storage model corresponding to the feature data, i denotes an abscissa of the feature data, i is 0,1, 2, …, m, j denotes an ordinate of the feature data, j is 0,1, 2, …, n, and t denote vertical coordinates of the feature data, t is 0,1, 2, …, p,
to represent
The variance of the square of (a) is,
to represent
The variance of the square of (a) is,
denotes the base k (mod3) to
Is the logarithm of the number of the true numbers,
to represent
The mathematical expectation of the square of (a) is,
to represent
Mathematical expectation of the square of, LkminRepresents the minimum electronic lock network congestion delay parameter at the k iteration, WkminRepresents the ratio of the minimum electronic lock protocol conversion time consumption to the consumed bandwidth cost at the kth iteration, (k + pi) mod3 represents the remainder of dividing (k + pi) by 3, pi represents a constant, pi is epsilon (0,1), delta represents a constant,
and step S30a, setting the iteration initial parameter k to 0 and the maximum iteration number d.
And step S30b, adding 1 to the current iteration number k.
And step S31, generating current judgment parameters corresponding to each characteristic data according to the current electronic lock network congestion delay parameter, the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio, the electronic lock network congestion delay parameter with the smallest history, and the electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data.
When k is 1, the initial electronic lock network congestion delay parameter of the characteristic data is the current electronic lock network congestion delay parameter of the characteristic data, and the ratio of the initial electronic lock protocol conversion time consumption to the consumed bandwidth cost is the ratio of the current electronic lock protocol conversion time consumption to the consumed bandwidth cost. After each subsequent iteration, the current network congestion delay parameter of the electronic lock, the ratio of the time consumed for converting the electronic lock protocol, and the cost of the consumed bandwidth of each feature data all change, for example, when k is 2, the current network congestion delay parameter of the electronic lock, the ratio of the time consumed for converting the electronic lock protocol, and the cost of the consumed bandwidth calculated at the 2 nd iteration are respectively input as the current network congestion delay parameter of the electronic lock, and the current ratio of the time consumed for converting the electronic lock protocol, and the cost of the consumed bandwidth are respectively input, and step S31 is executed. By analogy, this is not further enumerated here.
Specifically, step S31 includes:
step S31a, according to the current network congestion delay parameter of the electronic lock, the current ratio of the conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, the minimum historical network congestion delay parameter of the electronic lock, the ratio of the conversion time consumption of the minimum historical electronic lock protocol to the consumed bandwidth cost, and the judgment parameter formula:
Wherein, among others,
indicating the current electronic lock network congestion delay parameter,
represents the ratio of the time consumption of the protocol conversion of the current electronic lock to the cost of the consumed bandwidth, LGminNetwork congestion delay parameter, W, representing a minimum historical electronic lockGminRepresenting the ratio of time consumed to cost of consumed bandwidth for the protocol conversion of the electronic lock with the smallest history, ZkRepresenting the current judgment parameter, k representing the current iteration times, k belonging to [1, d ]]D is a preset threshold, k (mod2) represents the remainder of dividing k by 2, k (mod3) represents the remainder of dividing k by 3, m, n, and p represent adjustment constants, i, j, and t represent three-dimensional coordinates in a preset storage model corresponding to feature data, i represents an abscissa of the feature data, i is 0,1, 2, …, m, j represents an ordinate of the feature data, j is 0,1, 2, …, n, t represents a vertical coordinate of the feature data, and t is 0,1，2，…，p。
and step S32, comparing the current judgment parameters corresponding to the characteristic data, and determining the characteristic data with the minimum judgment parameters.
Specifically, according to a judgment parameter formula:
after calculating the current judgment parameters corresponding to each characteristic data, comparing the current judgment parameters Z of each characteristic datakThe value of (c) determines the current minimum judgment parameter ZkCharacteristic data of the value of (a).
Step S33, generating an evaluation value and an evaluation reference value corresponding to the feature data with the minimum judgment parameter according to the current network congestion delay parameter of the electronic lock in the feature data with the minimum judgment parameter, the current ratio of the consumed time of the electronic lock protocol conversion to the consumed bandwidth cost.
Specifically, step S33 includes:
step S33a, according to the current network congestion delay parameter of the electronic lock, the ratio of the current conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, and the iterative evaluation value function formula in the feature data with the minimum judgment parameter:
and calculating an evaluation value corresponding to the feature data with the minimum judgment parameter at present.
Wherein the content of the first and second substances,
to represent
The variance of the square of (a) is,
to represent
OfThe variance of the square or squares of the square or square,
denotes the base k (mod3) to
Is the logarithm of a true number, QkIndicating the current evaluation value corresponding to the feature data currently having the smallest judgment parameter.
Step S33b, according to the current network congestion delay parameter of the electronic lock, the current ratio of the conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, and the iterative evaluation reference value function formula in the feature data with the minimum judgment parameter:
and calculating an evaluation reference value corresponding to the characteristic data with the minimum judgment parameter.
Wherein the content of the first and second substances,
to represent
The mathematical expectation of the square of (a) is,
to represent
Mathematical expectation of the square of RkAnd the evaluation reference value is the current evaluation reference value corresponding to the characteristic data with the minimum judgment parameter.
Step S34, determining whether the evaluation value is less than or equal to the evaluation reference value, if yes, performing step S37, otherwise, performing step S35.
Specifically, step S34 includes:
step S34a, according to the iterative evaluation condition: qk≤RkAnd the evaluation value and the evaluation reference value generated in step S33, and determining the evaluation valueAnd whether the evaluation reference value satisfies the iterative evaluation condition, if so, executing step S37, and if not, executing step S35.
And step S35, generating an iterated electronic lock network congestion delay parameter and an iterated electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data according to the current electronic lock network congestion delay parameter and the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data.
Specifically, step S35 includes:
step S35a, current congestion delay parameter of electronic lock network according to each characteristic data
The ratio of the time consumption of protocol conversion of the current electronic lock to the cost of the consumed bandwidth
Generating a current composite vector corresponding to each feature data
Wherein the content of the first and second substances,
step S35b, current congestion delay parameter of electronic lock network according to each characteristic data
Minimum electronic lock network congestion delay parameter L in k iterationkminRatio of current electronic lock protocol conversion time consumption to consumed bandwidth cost
Ratio W of time consumption to cost of consumed bandwidth of protocol conversion of electronic lock with minimum k iterationkminAnd the formula:
calculating a depth unsupervised learning enhancement factor corresponding to each feature data in the (k + 1) th iteration
Where (k + π) mod3 represents the remainder of (k + π) divided by 3, π represents a constant, π ∈ (0, 1).
Step S35c, a current complex vector corresponding to each feature data
Depth unsupervised learning enhancement factor corresponding to each feature data in (k + 1) th iteration
And the formula:
calculating a composite vector corresponding to each feature data in the k +1 th iteration
Wherein, where, δ represents a constant,
step S35d, according to the compound vector corresponding to each feature data in the k +1 th iteration
Determining the iterated congestion delay parameter of the electronic lock network of each feature data in the (k + 1) th iteration
Ratio of time consumption to bandwidth cost consumed by protocol conversion of electronic lock after iteration
In particular, because
Thus, assume according to
Calculated
Then
Then can derive
Namely the iterated congestion delay parameter of the electronic lock network of each characteristic data in the (k + 1) th iteration
Is determinable, the ratio of the time consumption of electronic lock protocol conversion after iteration of each feature data in the (k + 1) th iteration to the cost of consumed bandwidth
As well as determinable.
In this embodiment, step S35 is followed by:
step S35e, determining whether the value of the current iteration number k is greater than a preset threshold d, if so, executing step S35f, and if not, executing step S36.
In the present embodiment, d is 50.
Step S35f is executed to set the current feature data having the smallest judgment parameter as the optimum feature data, and step S4 is executed.
In this example, d is 50.
Step S36, taking the iterated network congestion delay parameter of the electronic lock of each feature data as the current network congestion delay parameter of the electronic lock of each feature data, taking the iterated ratio of the time consumption of the electronic lock protocol conversion to the cost of the consumed bandwidth of each feature data as the ratio of the time consumption of the electronic lock protocol conversion to the cost of the consumed bandwidth of each feature data, and executing step S31.
Specifically, step S36 includes:
step S36a, electronic lock network congestion delay parameter after iteration of each feature data in the (k + 1) th iteration
As the current congestion delay parameter of the electronic lock network of each feature data, and the ratio of the time consumption of the electronic lock protocol conversion after the iteration of each feature data in the (k + 1) th iteration to the cost of the consumed bandwidth
As the ratio of the consumed time to the consumed bandwidth cost of the current electronic lock protocol conversion of each feature data, step S30b is executed.
Step S37, determining that the feature data having the smallest judgment parameter is the optimum feature data, and executing step S4.
And step S4, taking the electronic lock protocol conversion scheme corresponding to the optimal characteristic data as the current optimal electronic lock protocol conversion scheme, and outputting the current optimal electronic lock protocol conversion scheme.
And determining the optimal characteristic data so as to determine an optimal electronic lock protocol conversion scheme, and outputting the optimal electronic lock protocol conversion scheme to the terminal so as to enable an electronic lock operator to perform protocol conversion on the electronic lock according to the optimal electronic lock protocol conversion scheme, thereby facilitating remote operation of protocol conversion of the electronic lock in different places and realizing low time delay of protocol conversion operation.
In this embodiment, the term "current" appearing in the whole text may also be understood as "the time of the k-th iteration", that is, the term "current" appearing in the whole text, such as "current network congestion delay parameter of the electronic lock", "current ratio of conversion time and consumed bandwidth cost of the electronic lock protocol", "current judgment parameter", "current composite vector", "current evaluation value", "current evaluation reference value", and "feature data with the smallest judgment parameter" refers to "the time of the k-th iteration", and therefore, these quantities of "current" are obtained by correspondingly substituting the quantities calculated at the time of the k-th iteration.
The electronic lock protocol conversion optimization method provided by this embodiment is an electronic lock protocol conversion optimization method based on 5G mobile edge computing, fig. 4 is an application schematic diagram of an electronic lock protocol conversion optimization method provided by a second embodiment of the present invention, and fig. 5 is a schematic diagram of an original protocol and a target protocol to be converted of an electronic lock. As shown in fig. 4, the optimization method for electronic lock protocol conversion based on 5G mobile edge calculation can be applied to the application system shown in fig. 4, and the application system mainly includes five layers: the system comprises a feedback layer, an operator network transmission layer, an electronic lock protocol conversion optimization analysis layer, an edge gateway access layer and an edge data center layer.
The feedback layer comprises an electronic lock and a remote terminal of an electronic lock operator, for example, the remote terminal is a mobile phone, a tablet personal computer and the like, and is used for submitting a protocol conversion requirement of the electronic lock and feeding back a result; an operator network transport layer comprising: the 5G communication base station realizes the access and data transmission of an operator network; the electronic lock protocol conversion optimization analysis layer consists of a plurality of electronic lock protocol conversion optimization analyzers and is used for analyzing and processing the electronic lock protocol conversion requirements; the edge gateway access layer consists of a plurality of edge gateways and is used for realizing the access from an operator network; and the edge data center layer consists of a plurality of edge servers and is used for feeding back the analysis result from the electronic lock protocol conversion optimization analysis layer and transmitting the analysis result to the feedback layer through the operator network transmission layer.
Specifically, a remote terminal corresponding to an electronic lock operator accesses an operator network transmission layer through a 5G communication base station and transmits an electronic lock protocol conversion requirement.
And the 5G communication base station of the operator network transmission layer is used for transmitting the electronic lock protocol conversion requirement to the electronic lock protocol conversion optimization analysis layer by accessing the electronic lock protocol conversion optimization analysis layer.
The electronic lock protocol conversion optimization analyzer of the electronic lock protocol conversion optimization analysis layer obtains an analysis result of the electronic lock protocol conversion requirement, namely an electronic lock protocol conversion scheme corresponding to the optimal characteristic data, by analyzing the electronic lock protocol conversion requirement, and transmits the electronic lock protocol conversion scheme to the edge gateway access layer.
And the edge gateway of the edge gateway access layer is used for accessing an edge server of the edge data center layer and transmitting an electronic lock protocol conversion scheme from the electronic lock protocol conversion optimization analysis layer to the edge server of the edge data center layer.
And the edge server of the edge data center layer transmits the electronic lock protocol conversion scheme from the electronic lock protocol conversion optimization analysis layer to the feedback layer through the operator network transmission layer.
In this embodiment, the electronic lock protocol conversion requirements submitted by each terminal may have different priority levels. After receiving the electronic lock protocol conversion requirement, obtaining characteristic data corresponding to each electronic lock protocol conversion scheme and including an initial electronic lock network congestion delay parameter, initial electronic lock protocol conversion time consumption and consumed bandwidth cost proportion, performing data analysis and judgment on the characteristic data through an iteration model in the embodiment to determine an optimal electronic lock protocol conversion scheme corresponding to the optimal characteristic data, finally outputting the optimal electronic lock protocol conversion scheme, and returning the needed optimal electronic lock protocol conversion scheme to a terminal of an electronic lock operator so as to enable the electronic lock operator to perform protocol conversion on the electronic lock.
The iterative model in the embodiment analyzes the protocol conversion requirement of the electronic lock by combining methods such as multidimensional space, sparse matrix, tree protocol conversion, deep unsupervised learning, probability theory, operation research, machine learning and the like, so that an operator of the electronic lock can conveniently perform protocol conversion operation on the electronic lock in different places, and the iterative model has the advantages of time delay end operation, remote automatic operation and the like.
In the technical scheme of the method for optimizing conversion of the electronic lock protocol provided in this embodiment, the optimal feature data is determined according to the current network congestion delay parameter of the electronic lock of each feature data, the ratio of the current time consumption for conversion of the electronic lock protocol to the consumed bandwidth cost, the electronic lock protocol conversion scheme corresponding to the optimal feature data is used as the current optimal electronic lock protocol conversion scheme, and the current optimal electronic lock protocol conversion scheme is output. Therefore, remote operation of protocol conversion of the electronic lock in different places is facilitated, and low time delay of protocol conversion operation is realized.
Fig. 6 is a schematic structural diagram of an electronic lock protocol conversion optimizer according to a third embodiment of the present invention, as shown in fig. 6, the electronic lock protocol conversion optimizer includes: a receiving module 301, an obtaining module 302, a determining module 303 and an outputting module 304.
The receiving module 301 is configured to receive an electronic lock protocol conversion optimization requirement sent by a terminal; the obtaining module 302 is configured to obtain feature data corresponding to each electronic lock protocol conversion scheme, where the feature data includes a current network congestion delay parameter of the electronic lock, and a ratio of current time consumed for electronic lock protocol conversion to a consumed bandwidth cost; the determining module 303 is configured to determine optimal feature data according to a current network congestion delay parameter of the electronic lock of each feature data, a current ratio of time consumed for electronic lock protocol conversion to a consumed bandwidth cost; the output module 304 is configured to take the electronic lock protocol conversion scheme corresponding to the optimal feature data as a current optimal electronic lock protocol conversion scheme, and output the current optimal electronic lock protocol conversion scheme.
Specifically, the characteristic data further comprises a network congestion delay parameter of the electronic lock with the smallest history, and a ratio of consumed time to consumed bandwidth cost of protocol conversion of the electronic lock with the smallest history; the determining module 303 is specifically configured to perform the following steps: step 31, generating a current judgment parameter corresponding to each feature data according to the current electronic lock network congestion delay parameter, the current ratio of the electronic lock protocol conversion time consumption to the consumed bandwidth cost, the electronic lock network congestion delay parameter with the smallest history, and the ratio of the electronic lock protocol conversion time consumption with the smallest history to the consumed bandwidth cost of each feature data; step 32, comparing the current judgment parameters corresponding to the characteristic data to determine the characteristic data with the minimum judgment parameter; step 33, generating an evaluation value and an evaluation reference value corresponding to the feature data with the minimum judgment parameter according to the current network congestion delay parameter of the electronic lock in the feature data with the minimum judgment parameter, the current conversion time consumption of the electronic lock protocol and the consumed bandwidth cost ratio; step 34, judging whether the evaluation value is less than or equal to the evaluation reference value, if so, executing step 37, otherwise, executing step 35; step 35, generating an iterated electronic lock network congestion delay parameter and an iterated electronic lock protocol conversion time-consuming and consumed bandwidth cost ratio of each characteristic data according to the current electronic lock network congestion delay parameter and the current electronic lock protocol conversion time-consuming and consumed bandwidth cost ratio of each characteristic data; step 36, taking the iterated electronic lock network congestion delay parameter of each feature data as the current electronic lock network congestion delay parameter of each feature data, taking the iterated electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data as the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data, and executing step 31; step 37, determining that the current feature data with the minimum judgment parameter is the optimal feature data, and triggering the output module 304 to execute a step of taking the electronic lock protocol conversion scheme corresponding to the optimal feature data as the current optimal electronic lock protocol conversion scheme, and outputting the current optimal electronic lock protocol conversion scheme.
The electronic lock protocol conversion optimizer provided in this embodiment is used to implement the electronic lock protocol conversion optimization method provided in the second embodiment, and specific description may refer to the second embodiment, which is not repeated here.
Fig. 7 is an application schematic diagram of an electronic lock protocol conversion optimizer according to a third embodiment of the present invention, as shown in fig. 7, after the electronic lock protocol conversion optimizer receives m electronic lock protocol conversion requirements, for each electronic lock protocol conversion requirement, feature data corresponding to each electronic lock protocol conversion scheme and including an initial electronic lock network congestion delay parameter, an initial electronic lock protocol conversion time consumption and a consumed bandwidth cost ratio is obtained, and then data analysis and judgment are performed on the feature data through an iteration model in this embodiment, so as to determine an optimal electronic lock protocol conversion scheme corresponding to the optimal feature data, and finally output the optimal electronic lock protocol conversion scheme. The optimal electronic lock protocol conversion scheme is the final analysis result of the electronic lock protocol conversion requirements, the number of the analysis results is m, the electronic lock protocol conversion requirements are independent and do not interfere with each other, and m is a set number.
In the technical scheme of the electronic lock protocol conversion optimizer provided in this embodiment, an optimal feature data is determined according to a current electronic lock network congestion delay parameter of each feature data, a current ratio of time consumed for electronic lock protocol conversion to a consumed bandwidth cost, an electronic lock protocol conversion scheme corresponding to the optimal feature data is used as a current optimal electronic lock protocol conversion scheme, and the current optimal electronic lock protocol conversion scheme is output. Therefore, remote operation of protocol conversion of the electronic lock in different places is facilitated, and low time delay of protocol conversion operation is realized.
It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.
Claims (8)
1. An electronic lock protocol conversion optimization method is characterized by comprising the following steps:
step S1, receiving the electronic lock protocol conversion requirement sent by the terminal;
step S2, obtaining characteristic data corresponding to each electronic lock protocol conversion scheme, wherein the characteristic data comprises a current electronic lock network congestion delay parameter, and a ratio of current electronic lock protocol conversion time consumption to consumed bandwidth cost;
step S3, determining the optimal feature data according to the current network congestion delay parameter of the electronic lock of each feature data, the current ratio of the conversion time consumption of the electronic lock protocol to the cost of the consumed bandwidth;
step S4, taking the electronic lock protocol conversion scheme corresponding to the optimal characteristic data as the current optimal electronic lock protocol conversion scheme, and outputting the current optimal electronic lock protocol conversion scheme;
the characteristic data also comprises a network congestion delay parameter of the electronic lock with the smallest history, and the ratio of the time consumed for converting the electronic lock protocol with the smallest history to the cost of the consumed bandwidth; step S3 includes:
step S31, generating current judgment parameters corresponding to each characteristic data according to the current electronic lock network congestion delay parameter, the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio, the electronic lock network congestion delay parameter with the smallest history, and the electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data;
step S32, comparing the current judgment parameters corresponding to the characteristic data to determine the characteristic data with the minimum judgment parameters;
step S33, generating an evaluation value and an evaluation reference value corresponding to the feature data with the minimum judgment parameter according to the current network congestion delay parameter of the electronic lock in the feature data with the minimum judgment parameter, the current conversion time consumption of the electronic lock protocol and the consumed bandwidth cost ratio;
step S34, determining whether the evaluation value is less than or equal to the evaluation reference value, if so, performing step S37, otherwise, performing step S35;
step S35, generating an iterated electronic lock network congestion delay parameter and an iterated electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data according to the current electronic lock network congestion delay parameter and the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each characteristic data;
step S36, taking the iterated electronic lock network congestion delay parameter of each feature data as the current electronic lock network congestion delay parameter of each feature data, taking the iterated electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data as the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data, and executing step S31;
step S37, determining that the feature data having the smallest judgment parameter is the optimum feature data, and executing step S4.
2. The electronic lock protocol conversion optimization method of claim 1,
step S31 is preceded by:
step S30a, setting an iteration initial parameter k equal to 0;
step S30b, adding 1 to the current iteration times k;
step S31 includes:
step S31a, according to the current network congestion delay parameter of the electronic lock, the current ratio of the conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, the minimum historical network congestion delay parameter of the electronic lock, the ratio of the conversion time consumption of the minimum historical electronic lock protocol to the consumed bandwidth cost, and the judgment parameter formula:
wherein the content of the first and second substances,
indicating the current electronic lock network congestion delay parameter,
represents the ratio of the time consumption of the protocol conversion of the current electronic lock to the cost of the consumed bandwidth, LGminNetwork congestion delay parameter, W, representing a minimum historical electronic lockGminRepresenting the ratio of time consumed to cost of consumed bandwidth for the protocol conversion of the electronic lock with the smallest history, ZkRepresenting the current judgment parameter, k representing the current iteration times, k belonging to [1, d ]]D is a preset threshold value, k (mod2) represents the remainder of dividing k by 2, k (mod3) represents the remainder of dividing k by 3, m, n and p represent adjustment constants, and i, j and t represent adjustment constantsThe three-dimensional coordinates in the preset storage model corresponding to the feature data are represented by i, i is 0,1, 2, …, m, j is the ordinate of the feature data, j is 0,1, 2, …, n, t is the vertical coordinate of the feature data, and t is 0,1, 2, …, p.
3. The electronic lock protocol conversion optimization method of claim 2, wherein the step S33 includes:
step S33a, according to the current network congestion delay parameter of the electronic lock, the ratio of the current conversion time consumption of the electronic lock protocol to the consumed bandwidth cost, and the iterative evaluation value function formula in the feature data with the minimum judgment parameter:
calculating an evaluation value corresponding to the feature data with the minimum judgment parameter; wherein the content of the first and second substances,
to represent
The variance of the square of (a) is,
to represent
The variance of the square of (a) is,
denotes the base k (mod3) to
Is the logarithm of a true number, QkRepresenting a current evaluation value corresponding to the feature data with the minimum judgment parameter;
step S33b, according to the current minimumJudging a current network congestion delay parameter of the electronic lock, a current ratio of conversion time consumption and consumed bandwidth cost of an electronic lock protocol and an iteration evaluation reference value function formula in the characteristic data of the parameters:
calculating an evaluation reference value corresponding to the feature data with the minimum judgment parameter, wherein,
to represent
The mathematical expectation of the square of (a) is,
to represent
Mathematical expectation of the square of RkAnd the evaluation reference value is the current evaluation reference value corresponding to the characteristic data with the minimum judgment parameter.
4. The electronic lock protocol conversion optimization method of claim 3, wherein the step S34 includes:
step S34a, according to the evaluation value, evaluation reference value, and iterative evaluation condition generated in step S33: qk≤RkAnd judging whether the evaluation value and the evaluation reference value meet the iterative evaluation condition, if so, executing step S37, and if not, executing step S35.
5. The electronic lock protocol conversion optimization method of claim 4, wherein the step S35 includes:
step S35a, current congestion delay parameter of electronic lock network according to each characteristic data
The ratio of the time consumption of protocol conversion of the current electronic lock to the cost of the consumed bandwidth
Generating a current composite vector corresponding to each feature data
Step S35b, current congestion delay parameter of electronic lock network according to each characteristic data
Minimum electronic lock network congestion delay parameter L in k iterationkminRatio of current electronic lock protocol conversion time consumption to consumed bandwidth cost
Ratio W of time consumption to cost of consumed bandwidth of protocol conversion of electronic lock with minimum k iterationkminAnd the formula:
step S35c, a current complex vector corresponding to each feature data
Depth corresponding to each feature data in the (k + 1) th iterationUnsupervised learning enhancement factor
And the formula:
calculating a composite vector corresponding to each feature data in the k +1 th iteration
Wherein, delta represents a constant, and the number of the second electrode,
step S35d, according to the compound vector corresponding to each feature data in the k +1 th iteration
Determining the iterated congestion delay parameter of the electronic lock network of each feature data in the (k + 1) th iteration
Ratio of time consumption to bandwidth cost consumed by protocol conversion of electronic lock after iteration
6. The electronic lock protocol conversion optimization method of claim 5, wherein the step S36 includes: iterative electronic lock network congestion delay parameter of each characteristic data in the (k + 1) th iteration
Current network congestion delay parameters of the electronic lock as characteristic data, andthe ratio of the time consumption of electronic lock protocol conversion after iteration of each characteristic data in the (k + 1) th iteration to the cost of consumed bandwidth
As the ratio of the consumed time to the consumed bandwidth cost of the current electronic lock protocol conversion of each feature data, step S30b is executed.
7. The electronic lock protocol conversion optimization method of claim 6, further comprising, after the step S35:
step S35e, judging whether the value of the current iteration times k is larger than a preset threshold value d, if so, executing step S35f, and if not, executing step S36;
step S35f is executed to set the current feature data having the smallest judgment parameter as the optimum feature data, and step S4 is executed.
8. An electronic lock protocol conversion optimizer, comprising:
the receiving module is used for receiving the electronic lock protocol conversion optimization requirement sent by the terminal;
the acquisition module is used for acquiring characteristic data corresponding to each electronic lock protocol conversion scheme, wherein the characteristic data comprise a current electronic lock network congestion delay parameter, and a ratio of current electronic lock protocol conversion time consumption to consumed bandwidth cost;
the determining module is used for determining optimal characteristic data according to the current network congestion delay parameter of the electronic lock of each characteristic data, the current conversion time consumption of the electronic lock protocol and the consumed bandwidth cost ratio;
the output module is used for taking the electronic lock protocol conversion scheme corresponding to the optimal characteristic data as a current optimal electronic lock protocol conversion scheme and outputting the current optimal electronic lock protocol conversion scheme;
the characteristic data also comprises a network congestion delay parameter of the electronic lock with the smallest history, and the ratio of the time consumed for converting the electronic lock protocol with the smallest history to the cost of the consumed bandwidth; the determining module is specifically configured to perform the following steps:
step 31, generating a current judgment parameter corresponding to each feature data according to the current electronic lock network congestion delay parameter, the current ratio of the electronic lock protocol conversion time consumption to the consumed bandwidth cost, the electronic lock network congestion delay parameter with the smallest history, and the ratio of the electronic lock protocol conversion time consumption with the smallest history to the consumed bandwidth cost of each feature data;
step 32, comparing the current judgment parameters corresponding to the characteristic data to determine the characteristic data with the minimum judgment parameter;
step 33, generating an evaluation value and an evaluation reference value corresponding to the feature data with the minimum judgment parameter according to the current network congestion delay parameter of the electronic lock in the feature data with the minimum judgment parameter, the current conversion time consumption of the electronic lock protocol and the consumed bandwidth cost ratio;
step 34, judging whether the evaluation value is less than or equal to the evaluation reference value, if so, executing step 37, otherwise, executing step 35;
step 35, generating an iterated electronic lock network congestion delay parameter and an iterated electronic lock protocol conversion time-consuming and consumed bandwidth cost ratio of each characteristic data according to the current electronic lock network congestion delay parameter and the current electronic lock protocol conversion time-consuming and consumed bandwidth cost ratio of each characteristic data;
step 36, taking the iterated electronic lock network congestion delay parameter of each feature data as the current electronic lock network congestion delay parameter of each feature data, taking the iterated electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data as the current electronic lock protocol conversion time consumption and consumed bandwidth cost ratio of each feature data, and executing step 31;
and step 37, determining that the current feature data with the minimum judgment parameter is the optimal feature data, and triggering an output module to execute the step of taking the electronic lock protocol conversion scheme corresponding to the optimal feature data as the current optimal electronic lock protocol conversion scheme and outputting the current optimal electronic lock protocol conversion scheme.
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