CN117499395A - Cloud platform deployment method of intelligent lock - Google Patents
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Abstract
The invention discloses a cloud platform deployment method of an intelligent lock, which relates to the technical field of intelligent locks.
Description
Technical Field
The invention relates to the technical field of intelligent locks, in particular to a cloud platform deployment method of an intelligent lock.
Background
The intelligent lock technology is to use a mode of combining software and hardware to realize that the lock has an intelligent function. The intelligent lock can realize the functions of remote control, remote monitoring, data statistics and the like through connection with the cloud platform, so that the cloud platform suitable for deploying the intelligent lock is selected by considering the supporting degree and the performance of the intelligent lock, and therefore, the cloud platform deployment method of the intelligent lock is generated.
However, the cloud platform deployment method of the intelligent lock in the prior art has the defects of single-point fault risk, network delay problem, security problem, expansibility problem, management and maintenance problem and the like, and obviously has at least the following problems: 1. in the traditional technology, comprehensive performances of all cloud platforms are difficult to fully acquire and analyze, so that optimal cloud platforms are difficult to determine to deploy intelligent locks, and the problems of performance reduction, stability reduction and the like can be caused by wrong cloud platform selection.
2. Under the condition that enough performance test data and performance evaluation coefficients are not available in the traditional technology, whether the performance of the intelligent lock is qualified or not is difficult to judge, and the performance is further optimized, so that difficulty is brought to the performance improvement of the intelligent lock, if the performance of the intelligent lock is poor, a user can face the problems of slow response, network delay, unstable operation and the like, the user experience and satisfaction can be reduced, and meanwhile, the problem cannot be found in time and corresponding measures can be taken due to the lack of an early warning prompt function.
Disclosure of Invention
Aiming at the technical defects, the invention aims to provide a cloud platform deployment method of an intelligent lock.
In order to solve the technical problems, the invention adopts the following technical scheme: the invention provides a cloud platform deployment method of an intelligent lock, which comprises the following steps: step one, acquiring expansion data: and acquiring performance data corresponding to each cloud platform, wherein the performance data comprises processor speed, memory capacity and network connection speed.
Step two, analysis of extension data: according to the performance data corresponding to each cloud platform, the performance data corresponding to each cloud platform is analyzed, a performance evaluation coefficient corresponding to each cloud platform performance is obtained, whether each cloud platform is a high-quality cloud platform is judged, and then each high-quality cloud platform is obtained.
Step three, setting a test group: and setting each high-quality cloud platform into a plurality of test groups, so as to test each test group, and further collecting the sending data information and the receiving data information corresponding to each high-quality cloud platform in each test group after the test of each test group is completed, wherein the sending data information comprises the sending response time length and the sending delay time length of each control instruction, and the receiving data information comprises the receiving response time length and the receiving delay time length of each operation instruction.
Fourth, analysis of data information: according to the sending data information and the receiving data information corresponding to the high-quality cloud platforms in each test group, the sending data information and the receiving data information corresponding to the high-quality cloud platforms in each test group are analyzed, and the sending performance evaluation coefficient and the receiving performance evaluation coefficient corresponding to the high-quality cloud platforms are obtained.
Step five, acquiring a comprehensive performance evaluation coefficient: and according to the transmission performance evaluation coefficients and the receiving performance evaluation coefficients corresponding to the high-quality cloud platforms, further obtaining the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms.
Step six, selecting an optimal cloud platform: and selecting an optimal cloud platform according to the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms, and deploying the target intelligent lock into the optimal cloud platform.
Preferably, the performance data corresponding to each cloud platform is analyzed, and the specific analysis process is as follows: respectively marking the processor speed, the memory capacity and the network connection speed corresponding to each cloud platform as s i 、f i And h i Wherein i represents a number corresponding to each cloud platform, i=1, 2, and n, n is any integer greater than 2, and is substituted into a calculation formulaObtaining a performance evaluation coefficient eta corresponding to the performance of each cloud platform i S ', f ', h ' are respectively the standard processor speed, standard memory capacity and standard network connection speed epsilon corresponding to the set cloud platform 1 、ε 2 、ε 3 And e represents a natural constant, wherein the weight factors correspond to the set cloud platform processor speed, the set memory capacity and the set network connection speed respectively.
Preferably, the determining whether each cloud platform is a high-quality cloud platform includes the following specific analysis process: comparing the performance evaluation coefficient corresponding to the performance of each cloud platform with the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, if the performance evaluation coefficient corresponding to the performance of a certain cloud platform is smaller than the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, judging that the cloud platform is not a high-quality cloud platform, and if the performance evaluation coefficient corresponding to the performance of the certain cloud platform is larger than or equal to the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, judging that the cloud platform is a high-quality cloud platform, and judging whether the cloud platforms are high-quality cloud platforms or not in this way.
Preferably, each test group is tested by the following specific test procedure: a1, setting each test group according to the preset quantity of concurrent users, wherein the quantity of concurrent users of each high-quality cloud platform in each test group is the same, further respectively deploying the target intelligent locks in each high-quality cloud platform, sequentially sending each control instruction to the target intelligent locks through each high-quality cloud platform in each test group, and further collecting the sending response time and the sending delay time of each control instruction corresponding to each high-quality cloud platform in each test group.
A2, acquiring receiving response time and receiving delay time of each operation instruction corresponding to each high-quality cloud platform in each test group by carrying out each operation instruction on the target intelligent lock in each test group.
Preferably, the analyzing the data information sent by each high-quality cloud platform in each test group specifically includes the following steps: respectively marking the transmission response time length and the transmission delay time length of each control instruction corresponding to each high-quality cloud platform in each test group as Z j gy And X j gy Wherein g represents a number corresponding to each test group, g=1, 2,..m, y represents a number corresponding to each control instruction, y=1, 2,..p, j represents a number corresponding to each high-quality cloud platform, j=1, 2,..u, m is any integer greater than 2, p is any integer greater than 2, u is any integer greater than 2, and the values are substituted into a calculation formulaObtaining the transmission performance evaluation coefficient phi corresponding to each high-quality cloud platform j Wherein Z 'and X' are respectively the standard sending response time length, the standard sending delay time length and sigma corresponding to the set high-quality cloud platform 1 、σ 2 And respectively sending the weight factors corresponding to the response time and the sending delay time for the set high-quality cloud platform.
Preferably, the analyzing the received data information corresponding to each high-quality cloud platform in each test group specifically includes the following steps: the receiving response time length and the receiving delay time length of each operation instruction corresponding to each high-quality cloud platform in each test group are respectively marked as C j gk And V j gk Wherein k represents a number corresponding to each operation instruction, k=1, 2, w, w is any integer greater than 2, and the integer is substituted into a calculation formulaObtaining the corresponding receiving performance evaluation coefficient of each high-quality cloud platform>Wherein C 'and V' are respectively the standard receiving response time length, the standard receiving delay time length and theta corresponding to the set high-quality cloud platform 1 、θ 2 And respectively setting weight factors corresponding to the high-quality cloud platform receiving response time and the receiving delay time.
Preferably, the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms are obtained by the following specific obtaining process:
substituting the transmission performance evaluation coefficient and the receiving performance evaluation coefficient corresponding to each high-quality cloud platform into a calculation formulaObtaining the comprehensive performance evaluation coefficient corresponding to each high-quality cloud platform>Wherein v 1 、υ 2 Respectively set high-quality cloud platform sending performance evaluation systemNumber, weight factor corresponding to the receiving performance evaluation coefficient.
Preferably, the selecting the optimal cloud platform corresponding to the target intelligent lock specifically includes the following steps: and arranging the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms in order from small to large, and further selecting the high-quality cloud platform corresponding to the largest comprehensive performance evaluation coefficient as the best cloud platform corresponding to the target intelligent lock.
The invention has the beneficial effects that: 1. according to the cloud platform deployment method of the intelligent lock, through data-driven selection and comprehensive performance evaluation, the optimal cloud platform can be selected more accurately, the performance and user experience of the intelligent lock are improved, meanwhile, through screening of high-quality cloud platforms and multi-test-group settings, performance of each cloud platform can be evaluated more comprehensively, and a more basis reference is provided for selection.
2. According to the scheme, the performance level of each cloud platform can be objectively evaluated by acquiring and analyzing the performance data of each cloud platform, so that subjective judgment or blind selection can be avoided, the accuracy of selection is improved, a high-quality cloud platform can be screened out, the high-quality cloud platform generally has higher processor speed, memory capacity and network connection speed, and better performance and stability can be provided.
3. According to the scheme, the high-quality cloud platforms are arranged into a plurality of test groups, comprehensive and careful tests can be conducted, through the arrangement of the test groups, performance performances of different high-quality cloud platforms in different instructions can be compared, performance advantages and disadvantages of the high-quality cloud platforms can be further evaluated, performance performances of the high-quality cloud platforms in terms of data transmission can be known in more detail, the performance of each cloud platform in terms of sending and receiving can be determined, a more targeted basis is provided for final selection, comprehensive performances of the cloud platforms can be evaluated more comprehensively, and accordingly the best cloud platform can be selected, and good user experience and service quality can be provided.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the steps of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment of the invention is shown in fig. 1, and a cloud platform deployment method of an intelligent lock comprises the following steps: step one, acquiring expansion data: and acquiring performance data corresponding to each cloud platform, wherein the performance data comprises processor speed, memory capacity and network connection speed.
It should be noted that, the performance testing tool is installed on each cloud platform, and the processor speed, the memory capacity and the network connection speed corresponding to each cloud platform are further obtained through the performance testing tool installed on each cloud platform.
It should also be noted that the performance test tools include ApacheJMeter, loadRunner and gambling, etc.
Step two, analysis of extension data: according to the performance data corresponding to each cloud platform, the performance data corresponding to each cloud platform is analyzed, a performance evaluation coefficient corresponding to each cloud platform performance is obtained, whether each cloud platform is a high-quality cloud platform is judged, and then each high-quality cloud platform is obtained.
In a specific embodiment, the performance data corresponding to each cloud platform is analyzed, and a specific analysis process is as follows: respectively marking the processor speed, the memory capacity and the network connection speed corresponding to each cloud platform as s i 、f i And h i Wherein i represents the number corresponding to each cloud platformI=1, 2, n, n is any integer greater than 2, substituted into the calculation formulaObtaining a performance evaluation coefficient eta corresponding to the performance of each cloud platform i S ', f ', h ' are respectively the standard processor speed, standard memory capacity and standard network connection speed epsilon corresponding to the set cloud platform 1 、ε 2 、ε 3 And e represents a natural constant, wherein the weight factors correspond to the set cloud platform processor speed, the set memory capacity and the set network connection speed respectively.
Epsilon is the same as epsilon 1 、ε 2 、ε 3 Are all greater than 0 and less than 1.
In another specific embodiment, the determining whether each cloud platform is a good-quality cloud platform includes the following specific analysis process: comparing the performance evaluation coefficient corresponding to the performance of each cloud platform with the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, if the performance evaluation coefficient corresponding to the performance of a certain cloud platform is smaller than the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, judging that the cloud platform is not a high-quality cloud platform, and if the performance evaluation coefficient corresponding to the performance of the certain cloud platform is larger than or equal to the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, judging that the cloud platform is a high-quality cloud platform, and judging whether the cloud platforms are high-quality cloud platforms or not in this way.
According to the scheme, the performance level of each cloud platform can be objectively evaluated by acquiring and analyzing the performance data of each cloud platform, so that subjective judgment or blind selection can be avoided, the accuracy of selection is improved, a high-quality cloud platform can be screened out, the high-quality cloud platform generally has higher processor speed, memory capacity and network connection speed, and better performance and stability can be provided.
Step three, setting a test group: and setting each high-quality cloud platform into a plurality of test groups, so as to test each test group, and further collecting the sending data information and the receiving data information corresponding to each high-quality cloud platform in each test group after the test of each test group is completed, wherein the sending data information comprises the sending response time length and the sending delay time length of each control instruction, and the receiving data information comprises the receiving response time length and the receiving delay time length of each operation instruction.
It should be noted that, through the performance testing tools installed on each cloud platform, performance indexes of cloud instances can be monitored and recorded, the performance testing tools are used for monitoring the sending response time and the sending delay time of the control instructions, and the receiving response time and the receiving delay time of the operation instructions, so as to collect the sending response time and the sending delay time of each control instruction, and the receiving response time and the receiving delay time of each operation instruction.
In a specific embodiment, the test is performed on each test group, and the specific test procedure is as follows: a1, setting each test group according to the preset quantity of concurrent users, wherein the quantity of concurrent users of each high-quality cloud platform in each test group is the same, further respectively deploying the target intelligent locks in each high-quality cloud platform, sequentially sending each control instruction to the target intelligent locks through each high-quality cloud platform in each test group, and further collecting the sending response time and the sending delay time of each control instruction corresponding to each high-quality cloud platform in each test group.
A2, acquiring receiving response time and receiving delay time of each operation instruction corresponding to each high-quality cloud platform in each test group by carrying out each operation instruction on the target intelligent lock in each test group.
It should be noted that, the number of concurrent users is 1,2, 3, and then 3 test groups are set, where the number of concurrent users in the first test group is 1, the number of concurrent users in the second test group is 2, and the number of concurrent users in the third test group is 3.
Fourth, analysis of data information: according to the sending data information and the receiving data information corresponding to the high-quality cloud platforms in each test group, the sending data information and the receiving data information corresponding to the high-quality cloud platforms in each test group are analyzed, and the sending performance evaluation coefficient and the receiving performance evaluation coefficient corresponding to the high-quality cloud platforms are obtained.
In one specific embodiment of the present invention,the data information sent by each high-quality cloud platform in each test group is analyzed, and the specific analysis process is as follows: respectively marking the transmission response time length and the transmission delay time length of each control instruction corresponding to each high-quality cloud platform in each test group as Z j gy And X j gy Wherein g represents a number corresponding to each test group, g=1, 2,..m, y represents a number corresponding to each control instruction, y=1, 2,..p, j represents a number corresponding to each high-quality cloud platform, j=1, 2,..u, m is any integer greater than 2, p is any integer greater than 2, u is any integer greater than 2, and the values are substituted into a calculation formulaObtaining the transmission performance evaluation coefficient phi corresponding to each high-quality cloud platform j Wherein Z 'and X' are respectively the standard sending response time length, the standard sending delay time length and sigma corresponding to the set high-quality cloud platform 1 、σ 2 And respectively sending the weight factors corresponding to the response time and the sending delay time for the set high-quality cloud platform.
Sigma is added to 1 、σ 2 Are all greater than 0 and less than 1.
In another specific embodiment, the analyzing the received data information corresponding to each high-quality cloud platform in each test group specifically includes the following steps: the receiving response time length and the receiving delay time length of each operation instruction corresponding to each high-quality cloud platform in each test group are respectively marked as C j gk And V j gk Wherein k represents a number corresponding to each operation instruction, k=1, 2, w, w is any integer greater than 2, and the integer is substituted into a calculation formulaObtaining the corresponding receiving performance evaluation coefficient of each high-quality cloud platform>Wherein C 'and V' are respectively the standard receiving response time length and standard receiving delay time corresponding to the set high-quality cloud platformLong, θ 1 、θ 2 And respectively setting weight factors corresponding to the high-quality cloud platform receiving response time and the receiving delay time.
Note that θ 1 、θ 2 Are all greater than 0 and less than 1.
Step five, acquiring a comprehensive performance evaluation coefficient: and according to the transmission performance evaluation coefficients and the receiving performance evaluation coefficients corresponding to the high-quality cloud platforms, further obtaining the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms.
In a specific embodiment, the obtaining the comprehensive performance evaluation coefficients corresponding to each high-quality cloud platform specifically includes the following steps: substituting the transmission performance evaluation coefficient and the receiving performance evaluation coefficient corresponding to each high-quality cloud platform into a calculation formulaObtaining the comprehensive performance evaluation coefficient corresponding to each high-quality cloud platform>Wherein v 1 、υ 2 And respectively sending the performance evaluation coefficients and receiving the weight factors corresponding to the performance evaluation coefficients for the set high-quality cloud platform.
Incidentally, v 1 、υ 2 Are all greater than 0 and less than 1.
Step six, selecting an optimal cloud platform: and according to the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms, selecting an optimal cloud platform corresponding to the target intelligent lock, and deploying the target intelligent lock into the optimal cloud platform.
In a specific embodiment, the selecting the optimal cloud platform corresponding to the target smart lock specifically includes the following steps: and arranging the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms in order from small to large, and further selecting the high-quality cloud platform corresponding to the largest comprehensive performance evaluation coefficient as the best cloud platform corresponding to the target intelligent lock.
According to the scheme, the high-quality cloud platforms are arranged into a plurality of test groups, comprehensive and careful tests can be conducted, through the arrangement of the test groups, performance performances of different high-quality cloud platforms in different instructions can be compared, performance advantages and disadvantages of the high-quality cloud platforms can be further evaluated, performance performances of the high-quality cloud platforms in terms of data transmission can be known in more detail, the performance of each cloud platform in terms of sending and receiving can be determined, a more targeted basis is provided for final selection, comprehensive performances of the cloud platforms can be evaluated more comprehensively, and accordingly the best cloud platform can be selected, and good user experience and service quality can be provided.
According to the cloud platform deployment method of the intelligent lock, through data-driven selection and comprehensive performance evaluation, the optimal cloud platform can be selected more accurately, the performance and user experience of the intelligent lock are improved, meanwhile, through screening of high-quality cloud platforms and multi-test-group settings, performance of each cloud platform can be evaluated more comprehensively, and a more basis reference is provided for selection.
The foregoing is merely illustrative and explanatory of the principles of the invention, as various modifications and additions may be made to the specific embodiments described, or similar arrangements may be substituted by those skilled in the art, without departing from the principles of the invention or beyond the scope of the invention as defined in the description.
Claims (8)
1. The cloud platform deployment method of the intelligent lock is characterized by comprising the following steps of:
step one, acquiring expansion data: acquiring performance data corresponding to each cloud platform, wherein the performance data comprises processor speed, memory capacity and network connection speed;
step two, analysis of extension data: according to the performance data corresponding to each cloud platform, analyzing the performance data corresponding to each cloud platform to obtain performance evaluation coefficients corresponding to the performance of each cloud platform, judging whether each cloud platform is a high-quality cloud platform or not, and further obtaining each high-quality cloud platform;
step three, setting a test group: setting each high-quality cloud platform into a plurality of test groups, testing each test group, and further collecting transmission data information and reception data information corresponding to each high-quality cloud platform in each test group after the test of each test group is completed, wherein the transmission data information comprises transmission response time and transmission delay time of each control instruction, and the reception data information comprises reception response time and reception delay time of each operation instruction;
fourth, analysis of data information: according to the sending data information and the receiving data information corresponding to the high-quality cloud platforms in each test group, the sending data information and the receiving data information corresponding to the high-quality cloud platforms in each test group are analyzed, and the sending performance evaluation coefficient and the receiving performance evaluation coefficient corresponding to the high-quality cloud platforms are obtained;
step five, acquiring a comprehensive performance evaluation coefficient: according to the transmission performance evaluation coefficients and the receiving performance evaluation coefficients corresponding to the high-quality cloud platforms, further obtaining comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms;
step six, selecting an optimal cloud platform: and according to the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms, selecting an optimal cloud platform corresponding to the target intelligent lock, and deploying the target intelligent lock into the optimal cloud platform.
2. The cloud platform deployment method of the intelligent lock according to claim 1, wherein the analyzing the performance data corresponding to each cloud platform comprises the following specific analysis process:
respectively marking the processor speed, the memory capacity and the network connection speed corresponding to each cloud platform as s i 、f i And h i Wherein i represents a number corresponding to each cloud platform, i=1, 2, and n, n is any integer greater than 2, and is substituted into a calculation formulaObtaining a performance evaluation coefficient eta corresponding to the performance of each cloud platform i S ', f ', h ' are respectively the standard processor speed, standard memory capacity and standard network connection speed epsilon corresponding to the set cloud platform 1 、ε 2 、ε 3 Are respectively provided withAnd the fixed cloud platform processor speed, the memory capacity and the weight factors corresponding to the network connection speed, and e represents a natural constant.
3. The cloud platform deployment method of the intelligent lock according to claim 2, wherein the specific analysis process for judging whether each cloud platform is a high-quality cloud platform is as follows:
comparing the performance evaluation coefficient corresponding to the performance of each cloud platform with the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, if the performance evaluation coefficient corresponding to the performance of a certain cloud platform is smaller than the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, judging that the cloud platform is not a high-quality cloud platform, and if the performance evaluation coefficient corresponding to the performance of the certain cloud platform is larger than or equal to the performance evaluation coefficient corresponding to the performance of the set standard cloud platform, judging that the cloud platform is a high-quality cloud platform, and judging whether the cloud platforms are high-quality cloud platforms or not in this way.
4. The cloud platform deployment method of the intelligent lock according to claim 1, wherein the testing of each test group is performed by the following specific testing process:
a1, setting each test group according to the preset quantity of concurrent users, wherein the quantity of concurrent users of each high-quality cloud platform in each test group is the same, further respectively deploying the target intelligent locks in each high-quality cloud platform, sequentially sending each control instruction to the target intelligent locks through each high-quality cloud platform in each test group, and further collecting the sending response time and the sending delay time of each control instruction corresponding to each high-quality cloud platform in each test group;
a2, acquiring receiving response time and receiving delay time of each operation instruction corresponding to each high-quality cloud platform in each test group by carrying out each operation instruction on the target intelligent lock in each test group.
5. The cloud platform deployment method of the intelligent lock according to claim 4, wherein the analysis of the data information sent by each high-quality cloud platform in each test group is performed according to the following specific analysis process:
respectively marking the transmission response time length and the transmission delay time length of each control instruction corresponding to each high-quality cloud platform in each test group as Z j gy And X j gy Wherein g represents a number corresponding to each test group, g=1, 2,..m, y represents a number corresponding to each control instruction, y=1, 2,..p, j represents a number corresponding to each high-quality cloud platform, j=1, 2,..u, m is any integer greater than 2, p is any integer greater than 2, u is any integer greater than 2, and the values are substituted into a calculation formulaObtaining the transmission performance evaluation coefficient phi corresponding to each high-quality cloud platform j Wherein Z 'and X' are respectively the standard sending response time length, the standard sending delay time length and sigma corresponding to the set high-quality cloud platform 1 、σ 2 And respectively sending the weight factors corresponding to the response time and the sending delay time for the set high-quality cloud platform.
6. The cloud platform deployment method of the intelligent lock according to claim 5, wherein the analysis of the received data information corresponding to each high-quality cloud platform in each test group is performed by the following specific analysis process:
the receiving response time length and the receiving delay time length of each operation instruction corresponding to each high-quality cloud platform in each test group are respectively marked as C j gk And V j gk Wherein k represents a number corresponding to each operation instruction, k=1, 2, w, w is any integer greater than 2, and the integer is substituted into a calculation formulaObtaining the corresponding receiving performance evaluation coefficient of each high-quality cloud platform>C 'and V' are respectively the standard receiving response time length and standard receiving delay corresponding to the set high-quality cloud platformDuration, θ 1 、θ 2 And respectively setting weight factors corresponding to the high-quality cloud platform receiving response time and the receiving delay time.
7. The cloud platform deployment method of the intelligent lock according to claim 6, wherein the obtaining of the comprehensive performance evaluation coefficients corresponding to each high-quality cloud platform comprises the following specific obtaining process:
substituting the transmission performance evaluation coefficient and the receiving performance evaluation coefficient corresponding to each high-quality cloud platform into a calculation formulaObtaining the comprehensive performance evaluation coefficient corresponding to each high-quality cloud platform>Wherein v 1 、υ 2 And respectively sending the performance evaluation coefficients and receiving the weight factors corresponding to the performance evaluation coefficients for the set high-quality cloud platform.
8. The cloud platform deployment method of the intelligent lock according to claim 7, wherein the selecting the optimal cloud platform corresponding to the target intelligent lock comprises the following specific selecting process:
and arranging the comprehensive performance evaluation coefficients corresponding to the high-quality cloud platforms in order from small to large, and further selecting the high-quality cloud platform corresponding to the largest comprehensive performance evaluation coefficient as the best cloud platform corresponding to the target intelligent lock.
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| CN116700920A (en) * | 2023-05-15 | 2023-09-05 | 中国工商银行股份有限公司 | Cloud primary hybrid deployment cluster resource scheduling method and device |
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