CN112187886B - Service processing method of distributed intelligent analysis equipment system - Google Patents
Service processing method of distributed intelligent analysis equipment system Download PDFInfo
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Abstract
The invention provides a service processing method of a distributed intelligent analysis equipment system, which constructs different application end equipment to form a distributed application end equipment network and unifies the information analysis mode of each application end equipment in the network, thereby ensuring that each application end equipment is the same in information analysis processing performance, and associating all the application end equipment through an information processing linkage triggering relationship, thereby realizing the information processing relevance of all the application end equipment and being convenient for summarizing the information processing results of all the application end equipment, thereby improving the service processing performance and the data processing efficiency of the distributed intelligent analysis equipment system.
Description
Technical Field
The invention relates to the technical field of integrated service processing, in particular to a service processing method of a distributed intelligent analysis equipment system.
Background
At present, a distributed intelligent analysis device system is widely used for realizing parallel integrated service processing, and forms a corresponding distributed device network by performing communication connection on analysis devices with different functions, so that corresponding data information analysis processing can be conveniently performed in different spatial regions, the result of the data information analysis processing is uploaded to a corresponding service terminal, and corresponding comprehensive evaluation is performed through the service terminal. The distributed intelligent analysis equipment system can effectively meet the requirement of multi-object monitoring analysis, but in the prior art, each analysis equipment in the distributed intelligent analysis equipment system can only analyze the received data information, and the analysis equipment can not perform corresponding data association mining processing on the data information received by other analysis equipment, so that the different analysis equipment do not have any data information association, and the business processing performance of the distributed intelligent analysis equipment system is seriously restricted and the data processing efficiency is reduced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a service processing method of a distributed intelligent analysis equipment system, which comprises the steps of acquiring the respective operation state information and storage state information of a plurality of application end equipment, constructing and forming a corresponding distributed application end equipment network according to the operation state information and the storage state information, then carrying out unified processing of an information analysis mode on all the application end equipment in the distributed application end equipment network, constructing information processing linkage triggering relations among all the application end equipment, acquiring an analysis result of any one application end equipment on certain input information through the information analysis mode, simultaneously instructing other application end equipment to carry out data association mining processing on the analysis result through the information processing linkage triggering relations, and finally carrying out data association mining processing according to the data association mining processing result, summarizing and displaying the data results currently output by all application end equipment; therefore, the service processing method of the distributed intelligent analysis equipment system can ensure that each application end equipment is the same in information analysis processing performance by building different application end equipment to form a distributed application end equipment network and unifying the information analysis mode of each application end equipment in the network, and can also associate all the application end equipment through an information processing linkage triggering relationship, so that the information processing association of all the application end equipment is realized, the information processing results of all the application end equipment are convenient to summarize, and the service processing performance and the data processing efficiency of the distributed intelligent analysis equipment system are improved.
The invention provides a service processing method of a distributed intelligent analysis equipment system, which is characterized by comprising the following steps:
step S1, obtaining the respective operation state information and storage state information of a plurality of application terminal devices, and constructing and forming a corresponding distributed application terminal device network according to the operation state information and the storage state information;
step S2, performing unified processing of information analysis mode on all application end equipment in the distributed application end equipment network, and simultaneously constructing information processing linkage triggering relation among all application end equipment;
step S3, acquiring an analysis result of any application terminal device on certain input information through the information analysis mode, and simultaneously indicating other application terminal devices to perform data association mining processing on the analysis result through the information processing linkage triggering relationship;
step S4, summarizing and displaying the data results currently output by all application end equipment according to the data association mining processing results;
further, in the step S1, the obtaining of the operation status information and the storage status information of each of the plurality of application devices specifically includes,
step S101A, acquiring the current actual operation load value, actual operation speed value and actual operation time delay value of each application terminal device, and taking the values as the operation state information;
step S102A, obtaining a nominal value of a storage space, a residual value of an actual storage space and a consumption rate of the storage space of each application terminal device, and taking the values as the storage state information;
further, in the step S1, constructing and forming a corresponding distributed application device network according to the operation state information and the storage state information specifically includes,
step S101B, performing comprehensive evaluation analysis on the operation performance of the application device according to the actual operation load value, the actual operation rate value, and the operation time delay value, so as to determine an operation performance evaluation value of the application device;
step S102B, comprehensively evaluating and analyzing the storage performance of the application terminal equipment according to the nominal value of the storage space, the residual value of the actual storage space and the consumption rate of the storage space, so as to determine the evaluation value of the storage performance of the application terminal equipment;
step S103B, determining respective information processing priority levels of all application end equipment according to the operation performance evaluation value and the storage performance evaluation value, and constructing and forming the distributed application end equipment network according to the information processing priority levels;
further, in the step S2, the performing unified processing of the information analysis mode on all the application devices in the distributed application device network specifically includes,
step S201A, determining an image information analysis mode, a sound information analysis mode, and a text information analysis mode, which correspond to image information, sound information, and text information, respectively, for each application device in the distributed application device network;
step S202A, determining an actual information analysis sensitivity value and an actual information analysis calculation frequency value of each of the image information analysis mode, the sound information analysis mode, and the text information analysis mode corresponding to each application device;
step S203A, according to the actual information analysis sensitivity value and the actual information analysis calculation frequency value, respectively setting a unified information analysis sensitivity value and a unified information analysis calculation frequency value for the image information analysis mode, the sound information analysis mode, and the text information analysis mode corresponding to each application terminal device, thereby implementing unified processing on the image information analysis mode, the sound information analysis mode, and the text information analysis mode;
further, in the step S2, the constructing of the information processing linkage triggering relationship among all the application devices specifically includes,
step S201B, acquiring actual data input clock information of respective data input ports of all application end devices, and calculating a time difference between actual data input clock information corresponding to the application end devices;
step S202B, according to the time difference, the respective data input ports of all the application end devices synchronously coordinate to work under a unified clock;
step S203B, according to the unified clock, synchronizing the respective information processing operations of all the application end devices, so that when any one application end device performs the information processing operation, the other application end devices correspondingly perform the same information processing operation, thereby realizing the information processing linkage triggering relationship;
further, in step S3, the obtaining of the analysis result of any application device on some input information through the information analysis model specifically includes,
step S301A, determining an information type of current input information of any application device, where the information type includes video information, audio information, or text information;
step S302A, according to the information type, calling a matched information analysis mode from a corresponding application terminal device, and analyzing and processing the input information to obtain a corresponding analysis processing result, wherein the analysis processing includes image tone characteristic analysis processing, image texture characteristic analysis processing, sound and voice print characteristic analysis processing or text semantic analysis processing;
further, in the step S3, the indicating, through the information processing linkage triggering relationship, that the other application devices perform data association mining on the analysis result specifically includes,
step S301B, determining processing progress clock information of the input information by any one application device;
step S302B, through the information processing linkage triggering relationship and the processing progress clock information, instructing other application end equipment to perform data association mining processing on the analysis result, wherein the data association mining processing comprises performing information association expansion on the analysis result, and mining other data information matched with the analysis result from other application end equipment according to the result of the information association expansion;
further, in the step S4, according to the result of the data association mining process, the step of summarizing and displaying the data results currently output by all the application end devices specifically includes,
step S401, determining a data type corresponding to the result of the data association mining processing, and dividing the data information obtained by the data association mining processing into a plurality of data sets;
step S402, taking a plurality of data sets as data results currently output by all application terminal equipment, and summarizing and dynamically displaying the data results;
further, a comprehensive evaluation model of operation performance and a comprehensive evaluation model of storage performance are constructed by using formulas to perform comprehensive evaluation analysis on the operation performance of the application end device and the storage performance of the application end device, since the actual operation load value, the actual operation rate value and the operation time delay value have floating changes in each operation process of the application end device, the corresponding changes need to be corrected in the comprehensive evaluation model of operation performance by using data processing, similarly, the storage space consumption rate also has floating change fluctuations in the storage process of the application end device, the corresponding changes need to be corrected in the comprehensive evaluation model of storage performance, and finally, the respective information processing priority levels of all the application end devices are determined by using formulas according to the evaluation values of operation performance and the evaluation values of storage performance, the specific process comprises the following steps of,
firstly, obtaining an input-output expression of the comprehensive evaluation model of the operational performance by using the following formula (1)
In the above formula (1), λiIndicating the comprehensive evaluation value of the operation performance of the ith application terminal equipment,
represents the floating value of the a-th actual operation load of the ith application terminal equipment, Vi aRepresents the floating value of the a-th actual operation rate of the ith application terminal device,
represents the floating value of the a-th operation time delay of the ith application terminal device,
presentation pair
Find the variance, and
u represents the number of changes in the actual computation load value, the actual computation rate value, and the computation time delay value, and n representsThe total number of the application terminal devices;
secondly, obtaining an input-output expression of the storage performance comprehensive evaluation model by using the following formula (2)
In the above formula (2), βiIndicates the storage performance comprehensive evaluation value of the ith application terminal equipment, GiNominal value of storage space, X, representing the ith application deviceiRepresenting the actual storage space surplus value of the ith application device,
a floating value representing the jth memory consumption rate of the ith application device,
presentation pair
Find the variance, and
m represents the number of times of change of the storage space consumption rate of the ith application terminal device;
thirdly, the respective information processing priority decision values of all the application side devices are obtained by using the following formula (3)
In the above formula (3), DiAn information processing priority decision value indicating the ith application terminal device when DiThe larger the value of the distributed application terminal equipment is, the higher the information processing priority of the corresponding application terminal equipment is, and then a distributed application terminal equipment network is constructed and formed according to the information processing priority.
Compared with the prior art, the service processing method of the distributed intelligent analysis equipment system comprises the steps of obtaining the respective operation state information and storage state information of a plurality of application end equipment, and constructing and forming a corresponding distributed application terminal equipment network according to the operation state information and the storage state information, and then carrying out unified processing of an information analysis mode on all application terminal equipment in the distributed application terminal equipment network, simultaneously, the information processing linkage triggering relation among all the application end devices is established, the analysis result of any one application end device on certain input information through the information analysis mode is obtained, meanwhile, the information processing linkage triggering relationship indicates other application end equipment to carry out data association mining processing on the analysis result, and finally, the data results currently output by all the application end equipment are summarized and displayed according to the result of the data association mining processing; therefore, the service processing method of the distributed intelligent analysis equipment system can ensure that each application end equipment is the same in information analysis processing performance by building different application end equipment to form a distributed application end equipment network and unifying the information analysis mode of each application end equipment in the network, and can also associate all the application end equipment through an information processing linkage triggering relationship, so that the information processing association of all the application end equipment is realized, the information processing results of all the application end equipment are convenient to summarize, and the service processing performance and the data processing efficiency of the distributed intelligent analysis equipment system are improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a service processing method of a distributed intelligent analysis device system provided in the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a service processing method of a distributed intelligent analysis device system according to an embodiment of the present invention. The service processing method of the distributed intelligent analysis equipment system comprises the following steps:
step S1, obtaining the respective operation status information and storage status information of a plurality of application end devices, and constructing and forming a corresponding distributed application end device network according to the operation status information and the storage status information;
step S2, performing unified processing of information analysis mode on all application end equipment in the distributed application end equipment network, and simultaneously constructing information processing linkage triggering relation among all application end equipment;
step S3, acquiring an analysis result of any application terminal device on certain input information through the information analysis mode, and simultaneously instructing other application terminal devices to perform data association mining processing on the analysis result through the information processing linkage triggering relationship;
and step S4, summarizing and displaying the data results currently output by all the application end equipment according to the data association mining processing result.
The service processing of the distributed intelligent analysis equipment system is different from that of the distributed intelligent analysis equipment system in the prior art that different application end equipment are isolated and have no information relevance, the different application end equipment originally in an information isolation state is converted into the information processing equipment with corresponding relevance by constructing an information processing linkage triggering relation related to all the application end equipment, and the rest of the application end equipment is indicated to carry out data association mining processing according to an analysis result of any one application end equipment by virtue of the relevance, so that the currently analyzed data information is comprehensively and accurately associated and gathered, and the service processing performance and the data processing efficiency of the distributed intelligent analysis equipment system are improved.
Preferably, in step S1, the obtaining of the operation status information and the storage status information of each of the plurality of application devices specifically includes,
step S101A, acquiring the current actual operation load value, actual operation speed value and actual operation time delay value of each application terminal device, and taking the values as the operation state information;
step S102A, obtaining the nominal value of the storage space, the remaining value of the actual storage space, and the consumption rate of the storage space of each application device as the storage status information.
The operation state information and the storage state information of different application end equipment are not completely the same, and the difference of the operation state and the storage state of different application end equipment can influence the overall data processing performance of a corresponding distributed application end equipment network formed by subsequent construction, and the operation state and the storage state can be comprehensively analyzed comprehensively by acquiring the actual operation load value, the actual operation speed value, the actual operation time delay value, the storage space nominal value, the actual storage space residual value and the storage space consumption rate of each application end equipment, so that the data processing performance of the distributed application end equipment network is optimized.
Preferably, in the step S1, constructing and forming a corresponding distributed application device network according to the operation status information and the storage status information specifically includes,
step S101B, according to the actual operation load value, the actual operation speed value and the operation time delay value, performing comprehensive evaluation analysis on the operation performance of the application terminal equipment, so as to determine the operation performance evaluation value of the application terminal equipment;
step S102B, performing comprehensive evaluation and analysis on the storage performance of the application device according to the nominal value of the storage space, the remaining value of the actual storage space, and the consumption rate of the storage space, so as to determine the evaluation value of the storage performance of the application device;
step S103B, determining respective information processing priority levels of all the application devices according to the operation performance evaluation value and the storage performance evaluation value, and constructing and forming the distributed application device network according to the information processing priority levels; the distributed application end equipment network refers to the communication connection of application end equipment arranged in different position areas, so that a corresponding distributed communication network is formed.
By determining the operation performance evaluation values and the storage performance evaluation values of different application end devices, the application end devices with different priority levels can be accurately and pertinently arranged in a proper area in the process of constructing and forming the distributed application end device network, so that the overall operation performance of the distributed application end device network is greatly improved.
Preferably, in step S2, the uniformly processing the information analysis pattern for all the application devices in the distributed application device network specifically includes,
step S201A, determining an image information analysis mode, a sound information analysis mode, and a text information analysis mode, which correspond to the image information, the sound information, and the text information, respectively, for each application device in the distributed application device network;
step S202A, determining an actual information analysis sensitivity value and an actual information analysis calculation frequency value of each of the image information analysis mode, the sound information analysis mode, and the text information analysis mode corresponding to each application device;
step S203A, according to the actual information analysis sensitivity value and the actual information analysis calculation frequency value, respectively setting a unified information analysis sensitivity value and a unified information analysis calculation frequency value for the image information analysis mode, the sound information analysis mode, and the text information analysis mode corresponding to each application device, thereby implementing unified processing on the image information analysis mode, the sound information analysis mode, and the text information analysis mode; the unified information analysis sensitivity value and the unified information analysis calculation frequency value are set to have the same information analysis sensitivity value and the same information analysis calculation frequency value for each application terminal device, and the unified processing of the image information analysis mode, the sound information analysis mode and the text information analysis mode refers to the same information analysis processing of the image information analysis mode, the sound information analysis mode and the text information analysis mode according to the same information analysis sensitivity value and the same information analysis calculation frequency value.
By uniformly processing the image information analysis mode, the sound information analysis mode and the text information analysis mode in all the application terminal equipment, each application terminal equipment can be ensured to carry out analysis processing with the same precision and sensitivity on the input image information, sound information and text information, and therefore the accuracy and reliability of data information processing of the distributed application terminal equipment network are ensured.
Preferably, in step S2, the constructing of the information processing linkage triggering relationship among all the application devices specifically includes,
step S201B, acquiring actual data input clock information of respective data input ports of all the application end devices, and calculating a time difference between actual data input clock information corresponding to the application end devices;
step S202B, according to the time difference, the respective data input ports of all the application end devices synchronously coordinate to work under a unified clock;
step S203B, according to the unified clock, synchronizing the respective information processing operations of all the application devices, so that when any one of the application devices performs an information processing operation, the other application devices also perform the same information processing operation accordingly, thereby implementing the information processing linkage triggering relationship.
By unifying the clocks of all the application-side devices, the information processing linkage triggering relationship of all the application-side devices can be conveniently constructed subsequently according to the unified clocks, so that the forming difficulty of the information processing linkage triggering relationship is reduced.
Preferably, in step S3, the obtaining of the analysis result of any application device on some input information through the information analysis model specifically includes,
step S301A, determining an information type of current input information of any application device, where the information type includes video information, audio information, or text information;
step S302A, according to the information type, invoking a matched information analysis mode from the corresponding application device, and performing analysis processing on the input information, thereby obtaining a corresponding analysis processing result, where the analysis processing includes image hue feature analysis processing, image texture feature analysis processing, sound and voice print feature analysis processing, or text semantic analysis processing.
The analysis accuracy and effectiveness of the input information can be improved by instructing the application terminal equipment to analyze and process the input information about image tone characteristics, image texture characteristics, sound and sound texture characteristics or text semantics.
In step S3, the step of instructing, through the information processing linkage trigger relationship, the other application devices to perform data association mining processing on the analysis result specifically includes,
step S301B, determining processing progress clock information of the input information by the arbitrary application device;
step S302B, instructing, through the information processing linkage trigger relationship and the processing progress clock information, the other application devices to perform data association mining processing on the analysis result, where the data association mining processing includes performing information association expansion on the analysis result, and mining the other application devices to obtain other data information matched with the analysis result according to the result of the information association expansion.
The data association mining processing is carried out through the information processing linkage triggering relation and the processing progress clock information, so that the accuracy and the thoroughness of data association mining of all application-side equipment can be improved to the maximum extent, and the situations of data mining errors and omissions are avoided.
Preferably, in step S4, according to the result of the data association mining process, the step of summarizing and displaying the data results currently output by all the application devices specifically includes,
step S401, determining a data type corresponding to the result of the data association mining processing, and dividing the data information obtained by the data association mining processing into a plurality of data sets;
and S402, taking a plurality of data sets as the current output data results of all the application terminal equipment, and summarizing and dynamically displaying the data results.
The data information obtained by the data association mining processing is divided into a plurality of data sets, so that the data results can be conveniently and reliably and comprehensively summarized and displayed subsequently, and the convenience of acquiring the data results by a user is improved.
Preferably, a comprehensive evaluation model of operation performance and a comprehensive evaluation model of storage performance are constructed by using formulas to perform comprehensive evaluation analysis on the operation performance of the application end device and the storage performance of the application end device, since the actual operation load value, the actual operation rate value and the operation time delay value of the application end device have floating changes in each operation process, the corresponding changes need to be corrected in the comprehensive evaluation model of operation performance by using data processing, similarly, the storage space consumption rate also has floating change fluctuations in the storage process of the application end device, and the corresponding changes need to be corrected in the comprehensive evaluation model of storage performance, finally, the respective information processing priority levels of all application end devices are determined by using formulas according to the evaluation values of operation performance and storage performance, and the specific process comprises the following steps,
firstly, an input-output expression of the comprehensive evaluation model of the operational performance is obtained by using the following formula (1)
In the above formula (1), λiIndicating the comprehensive evaluation value of the operation performance of the ith application terminal equipment,
represents the floating value of the a-th actual operation load of the ith application terminal equipment, Vi aRepresents the floating value of the a-th actual operation rate of the ith application terminal device,
represents the floating value of the a-th operation time delay of the ith application terminal device,
presentation pair
Find the variance, and
u represents the change times of the actual operation load value, the actual operation speed value and the operation time delay value, and n represents the total number of the application terminal equipment;
secondly, an input-output expression of the storage performance comprehensive evaluation model is obtained by using the following formula (2)
In the above formula (2), βiIndicates the storage performance comprehensive evaluation value of the ith application terminal equipment, GiIndicating the ith application terminal deviceNominal value of the memory space, XiRepresenting the actual storage space surplus value of the ith application device,
a floating value representing the jth memory consumption rate of the ith application device,
presentation pair
Find the variance, and
m represents the number of times of change of the storage space consumption rate of the ith application terminal device;
thirdly, the respective information processing priority decision values of all the application side devices are obtained by using the following formula (3)
In the above formula (3), DiAn information processing priority decision value indicating the ith application terminal device when DiThe larger the value of the distributed application terminal equipment is, the higher the information processing priority of the corresponding application terminal equipment is, and then a distributed application terminal equipment network is constructed and formed according to the information processing priority.
Obtaining an input-output expression of the comprehensive evaluation model of the operational performance by using a formula (1), correcting the floating changes of an actual operational load value, an actual operational speed value and an operational time delay value of the application terminal equipment in each operational process by using the comprehensive evaluation model of the operational performance, and obtaining the comprehensive evaluation value of the operational performance; obtaining an input-output expression of the storage performance comprehensive evaluation model by using a formula (2), and correcting the floating change of the storage space consumption rate by using the storage performance comprehensive evaluation model to obtain a storage performance comprehensive evaluation value; finally, obtaining respective information processing priorities of all application end equipment by using a formula (3), and determining the respective information processing priorities of all application end equipment according to the judgment value; then, constructing and forming the distributed application terminal equipment network according to the information processing priority level; the floating change of each calculation and storage in the process is corrected and an evaluation model is established, so that the whole evaluation model is stable and reliable.
From the content of the above embodiments, the service processing method of the distributed intelligent analysis device system includes obtaining the respective operation state information and storage state information of a plurality of application end devices, and constructing and forming a corresponding distributed application terminal equipment network according to the operation state information and the storage state information, and then carrying out unified processing of an information analysis mode on all application terminal equipment in the distributed application terminal equipment network, simultaneously, the information processing linkage triggering relation among all the application end devices is established, the analysis result of any one application end device on certain input information through the information analysis mode is obtained, meanwhile, the information processing linkage triggering relation indicates other application end equipment to carry out data association mining processing on the analysis result, and finally, the data results currently output by all the application end equipment are summarized and displayed according to the result of the data association mining processing; therefore, the service processing method of the distributed intelligent analysis equipment system can ensure that each application end equipment is the same in information analysis processing performance by building different application end equipment to form a distributed application end equipment network and unifying the information analysis mode of each application end equipment in the network, and can also associate all the application end equipment through an information processing linkage triggering relationship, so that the information processing association of all the application end equipment is realized, the information processing results of all the application end equipment are convenient to summarize, and the service processing performance and the data processing efficiency of the distributed intelligent analysis equipment system are improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. The service processing method of the distributed intelligent analysis equipment system is characterized by comprising the following steps:
step S1, obtaining the respective operation state information and storage state information of a plurality of application terminal devices, and constructing and forming a corresponding distributed application terminal device network according to the operation state information and the storage state information;
step S2, performing unified processing of information analysis mode on all application end equipment in the distributed application end equipment network, and simultaneously constructing information processing linkage triggering relation among all application end equipment;
step S3, acquiring an analysis result of any application terminal device on certain input information through the information analysis mode, and simultaneously indicating other application terminal devices to perform data association mining processing on the analysis result through the information processing linkage triggering relationship;
step S4, summarizing and displaying the data results currently output by all application end equipment according to the data association mining processing results;
wherein, a comprehensive evaluation model of operation performance and a comprehensive evaluation model of storage performance are constructed by using formulas to perform comprehensive evaluation analysis on the operation performance of the application end equipment and the storage performance of the application end equipment, because the actual operation load value, the actual operation rate value and the operation time delay value have floating changes in each operation process of the application end equipment, the corresponding changes need to be corrected by using data processing in the comprehensive evaluation model of operation performance, similarly, the storage space consumption rate also has fluctuation of floating changes in the storage performance storage process of the application end equipment, the corresponding changes need to be corrected in the comprehensive evaluation model of storage performance, and finally, the respective information processing priority levels of all the application end equipment are determined by using formulas according to the evaluation value of operation performance and the evaluation value of storage performance, the specific process comprises the following steps of,
firstly, obtaining an input-output expression of the comprehensive evaluation model of the operational performance by using the following formula (1)
In the above formula (1), λiIndicating the comprehensive evaluation value of the operation performance of the ith application terminal equipment,
represents the floating value of the a-th actual operation load of the ith application terminal equipment, Vi aRepresents the floating value of the a-th actual operation rate of the ith application terminal device,
represents the floating value of the a-th operation time delay of the ith application terminal device,
presentation pair
Find the variance, and
u represents the change times of the actual operation load value, the actual operation speed value and the operation time delay value, and n represents the total number of the application terminal equipment;
secondly, obtaining an input-output expression of the storage performance comprehensive evaluation model by using the following formula (2)
In the above formula (2), βiIndicates the storage performance comprehensive evaluation value of the ith application terminal equipment, GiIndicating the storage of the ith application deviceStoring space nominal value, XiRepresenting the actual storage space surplus value of the ith application device,
a floating value representing the jth memory consumption rate of the ith application device,
presentation pair
Find the variance, and
m represents the number of times of change of the storage space consumption rate of the ith application terminal device;
thirdly, the respective information processing priority decision values of all the application side devices are obtained by using the following formula (3)
In the above formula (3), DiAn information processing priority decision value indicating the ith application terminal device when DiThe larger the value of the distributed application terminal equipment is, the higher the information processing priority of the corresponding application terminal equipment is, and then a distributed application terminal equipment network is constructed and formed according to the information processing priority.
2. The business processing method of the distributed intelligent analysis device system according to claim 1, characterized in that:
in step S1, the obtaining of the operation status information and the storage status information of each of the plurality of application devices specifically includes,
step S101A, acquiring the current actual operation load value, actual operation speed value and actual operation time delay value of each application terminal device, and taking the values as the operation state information;
step S102A, obtaining a nominal value of storage space, a remaining value of actual storage space, and a consumption rate of storage space of each application device as the storage status information.
3. The business processing method of the distributed intelligent analysis device system according to claim 2, characterized in that:
in step S1, the constructing and forming a corresponding distributed application device network according to the operation status information and the storage status information specifically includes,
step S101B, performing comprehensive evaluation analysis on the operation performance of the application device according to the actual operation load value, the actual operation rate value, and the operation time delay value, so as to determine an operation performance evaluation value of the application device;
step S102B, comprehensively evaluating and analyzing the storage performance of the application terminal equipment according to the nominal value of the storage space, the residual value of the actual storage space and the consumption rate of the storage space, so as to determine the evaluation value of the storage performance of the application terminal equipment;
step S103B, determining respective information processing priority levels of all the application devices according to the operation performance evaluation value and the storage performance evaluation value, and then constructing and forming the distributed application device network according to the information processing priority levels.
4. The business processing method of the distributed intelligent analysis device system according to claim 3, characterized in that:
in step S2, the step of uniformly processing the information analysis pattern for all the application devices in the distributed application device network specifically includes,
step S201A, determining an image information analysis mode, a sound information analysis mode, and a text information analysis mode, which correspond to image information, sound information, and text information, respectively, for each application device in the distributed application device network;
step S202A, determining an actual information analysis sensitivity value and an actual information analysis calculation frequency value of each of the image information analysis mode, the sound information analysis mode, and the text information analysis mode corresponding to each application device;
step S203A, according to the actual information analysis sensitivity value and the actual information analysis calculation frequency value, respectively setting a unified information analysis sensitivity value and a unified information analysis calculation frequency value for the image information analysis mode, the sound information analysis mode, and the text information analysis mode corresponding to each application device, thereby implementing unified processing on the image information analysis mode, the sound information analysis mode, and the text information analysis mode.
5. The business processing method of the distributed intelligent analysis device system according to claim 4, wherein:
in step S2, the constructing of the information processing linkage triggering relationship among all the application devices specifically includes,
step S201B, acquiring actual data input clock information of respective data input ports of all application end devices, and calculating a time difference between actual data input clock information corresponding to the application end devices;
step S202B, according to the time difference, the respective data input ports of all the application end devices synchronously coordinate to work under a unified clock;
step S203B, synchronizing the respective information processing operations of all the application devices according to the unified clock, so that when any one of the application devices performs an information processing operation, the other application devices also perform the same information processing operation accordingly, thereby implementing the information processing linkage triggering relationship.
6. The business processing method of the distributed intelligent analysis device system according to claim 5, wherein:
in step S3, the obtaining of the analysis result of any application device on some input information through the information analysis model specifically includes,
step S301A, determining an information type of current input information of any application device, where the information type includes video information, audio information, or text information;
step S302A, according to the information type, invoking a matched information analysis mode from a corresponding application device, and performing analysis processing on the input information, thereby obtaining a corresponding analysis processing result, where the analysis processing includes image hue feature analysis processing, image texture feature analysis processing, sound and voice print feature analysis processing, or text semantic analysis processing.
7. The business processing method of the distributed intelligent analysis device system of claim 6, wherein:
in step S3, the step of instructing, through the information processing linkage trigger relationship, the other application devices to perform data association mining processing on the analysis result specifically includes,
step S301B, determining processing progress clock information of the input information by any one application device;
step S302B, through the information processing linkage triggering relationship and the processing progress clock information, instructing other application end devices to perform data association mining processing on the analysis result, wherein the data association mining processing includes performing information association expansion on the analysis result, and mining other data information matched with the analysis result from other application end devices according to the result of the information association expansion.
8. The business processing method of the distributed intelligent analysis device system according to claim 7, wherein:
in step S4, the step of summarizing and displaying the data results currently output by all the application devices according to the result of the data association mining process specifically includes,
step S401, determining a data type corresponding to the result of the data association mining processing, and dividing the data information obtained by the data association mining processing into a plurality of data sets;
and S402, taking a plurality of data sets as the current output data results of all the application terminal equipment, and summarizing and dynamically displaying the data results.
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