CN115712684B - Storage method and system for dynamic information of articles in Internet of things - Google Patents
Storage method and system for dynamic information of articles in Internet of things Download PDFInfo
- Publication number
- CN115712684B CN115712684B CN202211481381.0A CN202211481381A CN115712684B CN 115712684 B CN115712684 B CN 115712684B CN 202211481381 A CN202211481381 A CN 202211481381A CN 115712684 B CN115712684 B CN 115712684B
- Authority
- CN
- China
- Prior art keywords
- article
- information
- node
- dynamic information
- nodes
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000004364 calculation method Methods 0.000 claims description 30
- 238000004422 calculation algorithm Methods 0.000 claims description 20
- 230000006870 function Effects 0.000 claims description 16
- 238000005192 partition Methods 0.000 claims description 10
- 230000004913 activation Effects 0.000 claims description 8
- 230000010354 integration Effects 0.000 claims description 6
- 238000010801 machine learning Methods 0.000 claims description 6
- 230000003213 activating effect Effects 0.000 claims description 3
- 238000010606 normalization Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 13
- 238000005516 engineering process Methods 0.000 abstract description 5
- 238000004891 communication Methods 0.000 description 8
- 230000008569 process Effects 0.000 description 6
- 238000013473 artificial intelligence Methods 0.000 description 4
- 238000004590 computer program Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 3
- 238000005406 washing Methods 0.000 description 3
- 238000004140 cleaning Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 230000000474 nursing effect Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000006835 compression Effects 0.000 description 1
- 238000007906 compression Methods 0.000 description 1
- 239000006071 cream Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000003064 k means clustering Methods 0.000 description 1
- 239000008267 milk Substances 0.000 description 1
- 210000004080 milk Anatomy 0.000 description 1
- 235000013336 milk Nutrition 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000002453 shampoo Substances 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Abstract
The invention relates to a data processing technology, and discloses a method and a system for storing dynamic information of articles in the Internet of things, wherein the method comprises the following steps: acquiring dynamic information of the article, and storing the dynamic information of the article into a database cluster; extracting an article code of the article dynamic information, tracking the article dynamic information according to the article code, and obtaining an article information record; extracting node types from the object information records, and generating a query list according to the node types, the object codes and the object dynamic information, wherein the node types comprise main nodes and sub nodes; according to the query list, the master node is issued and stored to each partial node, and the stored partial nodes are integrated and calculated to obtain an updated master node; and updating the dynamic information of the articles in the database cluster according to the updating master node to obtain the target database cluster. The invention can improve the efficiency of storing the dynamic information of the article.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a method and a system for storing dynamic information of articles in the Internet of things.
Background
In systems such as the internet of things and industrial monitoring, a large amount of data information changing in real time is generated at all times, and the total collection of the data information is complex. In order to process data information generated in real time, the data information is required to be processed in a real-time database with high timeliness and high throughput, equipment is monitored and early-warned in real time according to the data information, historical data information in the real-time database is analyzed and mined, and basis is provided for enterprise decision making and the like.
The current traditional method for processing the historical data information by the real-time database comprises the following steps: 1. the data information is efficiently compressed and stored in a file mode; 2. the method is combined with a relational database, and data information is stored in the relational database, and both the two modes of processing the data information have certain defects. For example, by adopting the efficient data information compression mode, the data information query speed is reduced to a certain extent; the method stored in the relational database has the problems of incapability of large-scale expansion, inadequacy in processing unstructured data information and low efficiency in high concurrency query when processing massive data information. In summary, the existing technology has the problem of low efficiency in storing dynamic information of articles.
Disclosure of Invention
The invention provides a method and a system for storing dynamic information of articles in the Internet of things, and mainly aims to solve the problem of low data integration efficiency.
In order to achieve the above object, the method for storing dynamic information of an article in the internet of things provided by the invention comprises the following steps:
acquiring dynamic information of an article, and storing the dynamic information of the article into a preset database cluster;
extracting an article code of the article dynamic information, and tracking the article dynamic information according to the article code to obtain an article information record;
extracting node types from the article information record, and generating a query list according to the node types, the article codes and the article dynamic information, wherein the node types comprise a main node and a partition node;
according to the query list, the master node is issued and stored to each of the partial nodes, and the stored partial nodes are integrated and calculated to obtain an updated master node;
and updating the dynamic information of the articles in the database cluster according to the updating master node to obtain a target database cluster.
Optionally, the storing the item dynamic information in a preset database cluster includes:
Acquiring a pre-loading information request corresponding to the dynamic information of the article, and analyzing the dynamic information of the article according to the pre-loading information request to obtain a pre-loading information tag;
inquiring a service information area corresponding to the pre-loaded information tag from a preset information pre-loaded data table according to the pre-loaded information tag;
and placing the regional data of the business information region into the database cluster by using a preset SQL statement.
Optionally, the extracting the item code of the item dynamic information includes:
acquiring an information ID of the dynamic information of the article, and positioning an operation area of the dynamic information of the article;
searching a service information area corresponding to the information ID and the operation area from a preset service area definition table;
and inquiring an information label of the dynamic information of the article in the service information area, and numbering the information label to obtain the article code.
Optionally, the tracking the dynamic information of the article according to the article code to obtain an article information record includes:
marking the dynamic information of the article according to the article code to obtain the dynamic information of the marked article;
Recording an information path of the dynamic information of the marked article, and judging whether the information path contains information nodes of the dynamic information of the marked article or not;
and when the information path comprises the information nodes, acquiring the article information in the information nodes, and integrating the article information to obtain article information records.
Optionally, the generating a query list according to the node type, the item code and the item dynamic information includes:
associating the node types by using a preset association algorithm to obtain associated node types;
the article numbers and the article dynamic information corresponding to the article numbers are in one-to-one correspondence, and the corresponding article codes and the article dynamic information are combined to be used as code information;
and constructing a query list by taking the associated node type as a row vector and the coding information as a column vector.
Optionally, the associating the node types by using a preset association algorithm to obtain associated node types includes:
selecting any node type from the node types as a target node type, and taking other node types except the target node type as reference node types;
Performing matching calculation on the target node type and the reference node type by using the association algorithm to obtain a matching value;
the association algorithm is expressed as:
wherein P (v, theta) is expressed as a matching value of the target node type and the reference node type, v is expressed as the target node type, theta is expressed as the reference node type, and Z is expressed as a preset normalization factor;
when the matching value is larger than a preset threshold value, activating the connection point of the target node type and the reference node type by using a preset activation function to obtain an associated node type;
the activation function may be expressed as:
wherein E (v, θ) represents an associated node type of the target node type and the reference node type, v i The method comprises the steps of representing an ith target node type, theta representing a jth reference node type, I representing the number of the target node types, J representing the number of the reference node types, b representing a preset offset vector of the target node type, and a representing a preset offset vector of the reference node type.
Optionally, the step of issuing and storing the master node to each of the partial nodes according to the query list includes:
Inquiring node information of the main node according to the inquiry list;
transmitting the node information to the sub-node through the connection point of the main node and the sub-node, and storing the node information to the sub-node.
Optionally, the integrating calculation is performed on the stored split nodes to obtain an updated master node, which includes:
performing weight assignment on the stored partial nodes to obtain node weights;
performing weighted calculation according to the sub-nodes and the node weights to obtain updated main nodes;
and (3) weighting calculation is carried out by using the following steps to obtain an updated master node:
wherein A represents the update master node, score d Represents the d-th minute node, alpha d And a weight coefficient representing the node weight corresponding to the d-th partial node, wherein n represents the total number of the partial nodes.
Optionally, the updating the dynamic information of the object in the database cluster according to the updating master node to obtain a target database cluster includes:
extracting the main node of the dynamic information of the article by using a preset machine learning algorithm to obtain an information main node;
the machine learning algorithm is expressed as:
wherein h represents the information main node, Y represents the dynamic information of the article, w represents a preset weight of the information main node, and c represents a preset calculation parameter;
Replacing the information main node by using the update main node, and storing the update main node to the dynamic information of the article;
and storing the updated dynamic information of the object into the database cluster to obtain a target database cluster.
In order to solve the above problems, the present invention further provides a system for storing dynamic information of an article in the internet of things, where the system includes:
the article dynamic information storage module is used for acquiring article dynamic information and storing the article dynamic information into a preset database cluster;
the article information record generation module is used for extracting article codes of the article dynamic information, tracking the article dynamic information according to the article codes and obtaining article information records;
the query list generation module is used for extracting node types from the article information records and generating a query list according to the node types, the article codes and the article dynamic information, wherein the node types comprise a main node and a partition node;
the node calculation module is used for issuing and storing the master node to each node according to the query list, and carrying out integration calculation on the stored nodes to obtain an updated master node;
And the database cluster updating module is used for updating the dynamic information of the articles in the database cluster according to the updating master node to obtain a target database cluster.
The embodiment of the invention provides a method and a system for storing dynamic information of articles in the Internet of things, which can distinguish different dynamic information of the articles by storing the dynamic information of the articles into a database cluster; by extracting the article codes of the article dynamic information and tracking the article dynamic information according to the article codes, the accuracy of acquiring the article information record can be improved, and the processing efficiency of a computer can be accelerated; the master node issues and stores the data to each of the partial nodes, and the stored partial nodes are integrated and calculated, so that the data can be ensured to be uniform, and the calculation efficiency is accelerated; and updating the dynamic information of the articles in the database cluster by updating the master node, so that the target database cluster is more accurate, and the efficiency of storing the dynamic information of the articles is improved. Therefore, the method, the system, the electronic equipment and the computer readable storage medium for storing the dynamic information of the articles in the Internet of things can solve the problem of low efficiency in storing the dynamic information of the articles.
Drawings
Fig. 1 is a flow chart of a method for storing dynamic information of an article in the internet of things according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of an article encoding for extracting dynamic information of an article according to an embodiment of the present application;
FIG. 3 is a flow chart of generating a query list according to node type, item code and item dynamic information according to an embodiment of the present application;
FIG. 4 is a functional block diagram of a storage system for dynamic information of an article in the Internet of things according to an embodiment of the present application;
the achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The embodiment of the application provides a method for storing dynamic information of articles in the Internet of things. The execution main body of the method for storing the dynamic information of the object in the internet of things comprises at least one of electronic equipment, such as a server side, a terminal and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the method for storing the dynamic information of the object in the internet of things can be executed by software or hardware installed in the terminal device or the server device, and the software can be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a method for storing dynamic information of an article in the internet of things according to an embodiment of the present invention is shown. In this embodiment, the method for storing dynamic information of an article in the internet of things includes:
s1, acquiring dynamic information of an article, and storing the dynamic information of the article into a preset database cluster;
in the embodiment of the invention, the dynamic information of the article comprises information such as an article number, an article name, an article information record and the like.
In the embodiment of the present invention, the storing the dynamic information of the article in a preset database cluster includes:
acquiring a pre-loading information request corresponding to the dynamic information of the article, and analyzing the dynamic information of the article according to the pre-loading information request to obtain a pre-loading information tag;
inquiring a service information area corresponding to the pre-loaded information tag from a preset information pre-loaded data table according to the pre-loaded information tag;
and placing the regional data of the business information region into the database cluster by using a preset SQL statement.
In the embodiment of the invention, all the preloading information requests are ordered according to the generating time of the preloading information requests, a preloading information request queue is generated, the preloading information request queue comprises a plurality of preloading information requests and preloading information labels corresponding to the preloading information requests, and the preloading information labels corresponding to the dynamic information of the articles are extracted according to the preloading information request queue to obtain a plurality of preloading information labels.
In the embodiment of the invention, the preset information preloading data table contains information data such as preloading information labels, service information areas, dynamic information of articles and the like, each preloading information label is provided with a unique number corresponding to the preloading information label, the number can be represented by a numerical value or a letter, and the service information area corresponding to the preloading information label can be found in the information preloading data table according to the number.
In the embodiment of the invention, the preset SQL statement refers to a structured query language.
In the embodiment of the invention, the area data of the service information area is stored in the database cluster, and different service information areas correspond to different area data, for example, the online shopping commodity can be divided into a skin care area, a washing area and the like, and the data corresponding to the skin care area comprises data such as water, milk and the like, so that the service information area can be utilized to distinguish different dynamic information of the commodity.
S2, extracting an article code of the article dynamic information, and tracking the article dynamic information according to the article code to obtain an article information record;
referring to fig. 2, in an embodiment of the present invention, the extracting an item code of the item dynamic information includes:
S21, acquiring an information ID of the dynamic information of the article, and positioning an operation area of the dynamic information of the article;
s22, searching a service information area corresponding to the information ID and the operation area from a preset service area definition table;
s23, inquiring an information label of the dynamic information of the article in the service information area, and numbering the information label to obtain the article code.
In the embodiment of the invention, an operation area corresponding to the information ID is found according to the information ID of the dynamic information of the article, for example, the corresponding information ID is found in a front page, and the operation area is obtained by positioning the information ID through a mouse cursor; the operation area refers to an area for performing addition, deletion and verification, for example, a certain commodity can be added, deleted and verified on a commodity background page.
In the embodiment of the invention, the service area definition table refers to a relation comparison table between different operation areas and corresponding service information areas in a predefined front-end page according to actual service conditions, a plurality of commodities corresponding to each service information area contain corresponding operation areas, for example, commodity toner in a skin care area, and a background page contains operation areas for adding, deleting and checking toner.
In the embodiment of the invention, the corresponding information labels are searched through the corresponding information IDs in the service information area, each information ID corresponds to a plurality of information labels, the information labels are ordered according to the time of creation of the information labels from long to short, and the article codes are obtained, for example, the time of adding the information labels of the commodity A is 5 days, the time of adding the information labels of the commodity B is 1 day, the number A is 1, the number B is 2, and the like, and the obtained plurality of numbers are used as article numbers.
In the embodiment of the present invention, the tracking the dynamic information of the article according to the article code to obtain an article information record includes:
marking the dynamic information of the article according to the article code to obtain the dynamic information of the marked article;
recording an information path of the dynamic information of the marked article, and judging whether the information path contains information nodes of the dynamic information of the marked article or not;
and when the information path comprises the information nodes, acquiring the article information in the information nodes, and integrating the article information to obtain article information records.
In the embodiment of the invention, different marks are carried out on the dynamic information of the article according to different article codes, for example, if the article code is 100, the dynamic information of the article is marked with a 100 word; specifically, the embodiment of the invention can record the information path of the dynamic information of the article by using a preset Dijkstra algorithm.
In the embodiment of the invention, the corresponding dynamic information of the article can be quickly found in the calculation process by marking the dynamic information of the article, so that the calculation efficiency is accelerated; and by recording the information path, the accuracy of acquiring the dynamic information of the article is improved.
S3, extracting node types from the article information record, and generating a query list according to the node types, the article codes and the article dynamic information, wherein the node types comprise a main node and a sub node;
in the embodiment of the invention, extracting node types from the article information record refers to generating a feature matrix corresponding to a node according to more than two feature information of the node extracted from the article information record, inputting the feature matrix into a preset K-mean value K-means clustering algorithm for clustering, identifying the node types according to a clustering result, and carrying out application type division and extraction on the node types.
In the embodiment of the invention, the node type includes a main node and a sub node, the main node may be a generic name of one major class in the article information record, the sub node refers to a minor class in the corresponding major class, for example, the washing and caring article is used as one major class, the washing and caring article is divided into two minor classes of cleaning article and nursing article, the cleaning article further includes shampoo, shower gel and the like, and the nursing article further includes hair conditioner, body cream and the like.
Referring to fig. 3, in the embodiment of the present invention, the generating a query list according to the node type, the item code, and the item dynamic information includes:
s31, associating the node types by using a preset association algorithm to obtain associated node types;
s32, corresponding the article numbers and the article dynamic information corresponding to the article numbers one by one, and combining the corresponding article codes and the article dynamic information to be used as code information;
s33, constructing a query list by taking the associated node type as a row vector and the coding information as a column vector.
In the embodiment of the present invention, the associating the node types by using a preset association algorithm to obtain associated node types includes:
selecting any node type from the node types as a target node type, and taking other node types except the target node type as reference node types;
performing matching calculation on the target node type and the reference node type by using the association algorithm to obtain a matching value;
the association algorithm is expressed as:
wherein P (v, theta) is expressed as a matching value of the target node type and the reference node type, v is expressed as the target node type, theta is expressed as the reference node type, and Z is expressed as a preset normalization factor;
When the matching value is larger than a preset threshold value, activating the connection point of the target node type and the reference node type by using a preset activation function to obtain an associated node type;
the activation function may be expressed as:
wherein E (v, θ) represents an associated node type of the target node type and the reference node type, v i The method comprises the steps of representing an ith target node type, theta representing a jth reference node type, I representing the number of the target node types, J representing the number of the reference node types, b representing a preset offset vector of the target node type, and a representing a preset offset vector of the reference node type.
In the embodiment of the present invention, after the connection point between the target node type and the reference node type is activated, information included in the target node type after the connection point is activated may be transmitted to the reference node type.
In the embodiment of the present invention, when the matching value is greater than a preset threshold, for example, the threshold is 60%, and when the matching value is greater than 60%, a preset activation function may be used to activate the connection point between the target node type and other node types, where the activation state may be represented by boolean values, for example, 0 and 1, where 0 represents an inactive state and 1 represents an active state. When the connection point is activated, the information contained in the target node type can be transmitted to the reference node type matched with the target node type, and the associated node type is obtained.
In the embodiment of the invention, the node types are associated, so that more data information can be shared, and the calculation efficiency is accelerated.
S4, according to the query list, the master node is issued and stored to each of the partial nodes, and the stored partial nodes are integrated and calculated to obtain an updated master node;
in the embodiment of the invention, the query list comprises the main node and the corresponding sub-nodes, the corresponding sub-nodes in the main node are found through the target sub-nodes according to the corresponding relation in the list, and then the main node is split to obtain the sub-nodes.
In the embodiment of the present invention, the step of storing the master node to each of the partition nodes according to the query list includes:
inquiring node information of the main node according to the inquiry list;
transmitting the node information to the sub-node through the connection point of the main node and the sub-node, and storing the node information to the sub-node.
In the embodiment of the present invention, the integrating calculation is performed on the stored partition nodes to obtain updated master nodes, including:
performing weight assignment on the stored partial nodes to obtain node weights;
Performing weighted calculation according to the sub-nodes and the node weights to obtain updated main nodes;
and (3) weighting calculation is carried out by using the following steps to obtain an updated master node:
wherein A represents the update master node, score d Represents the d-th minute node, alpha d And a weight coefficient representing the node weight corresponding to the d-th partial node, wherein n represents the total number of the partial nodes.
In the embodiment of the invention, the types of the sub-nodes are divided, and the weight is used as node weight according to the ratio of the number of the sub-nodes in the types to the total number of the nodes.
And S5, updating the dynamic information of the objects in the database cluster according to the updating master node to obtain a target database cluster.
In the embodiment of the present invention, the updating the dynamic information of the object in the database cluster according to the updating master node to obtain the target database cluster includes:
extracting the main node of the dynamic information of the article by using a preset machine learning algorithm to obtain an information main node;
the machine learning algorithm is expressed as:
wherein h represents the information main node, Y represents the dynamic information of the article, w represents a preset weight of the information main node, and c represents a preset calculation parameter;
Replacing the information main node by using the update main node, and storing the update main node to the dynamic information of the article;
and storing the updated dynamic information of the object into the database cluster to obtain a target database cluster.
In the embodiment of the invention, the main node of the dynamic information of the object is extracted to realize the update of the main node, thereby realizing the update of the dynamic information of the object and obtaining the target database cluster.
In the embodiment of the invention, the dynamic information of the article is updated through the updating master node, so that the dynamic information of the article can be updated in real time, thereby ensuring the real-time property, uniformity and accuracy of data and being more accurate when the computer processes the information.
The embodiment of the invention provides a method and a system for storing dynamic information of articles in the Internet of things, which can distinguish different dynamic information of the articles by storing the dynamic information of the articles into a database cluster; by extracting the article codes of the article dynamic information and tracking the article dynamic information according to the article codes, the accuracy of acquiring the article information record can be improved, and the processing efficiency of a computer can be accelerated; the master node issues and stores the data to each of the partial nodes, and the stored partial nodes are integrated and calculated, so that the data can be ensured to be uniform, and the calculation efficiency is accelerated; and updating the dynamic information of the articles in the database cluster by updating the master node, so that the target database cluster is more accurate, and the efficiency of storing the dynamic information of the articles is improved. Therefore, the method for storing the dynamic information of the article in the Internet of things can solve the problem of low efficiency in storing the dynamic information of the article.
Fig. 4 is a functional block diagram of a storage system for dynamic information of an article in the internet of things according to an embodiment of the present invention.
The storage system 100 for dynamic information of objects in the internet of things can be installed in electronic equipment. According to the implemented functions, the storage system 100 of the dynamic information of the article in the internet of things may include an article dynamic information storage module 101, an article information record generating module 102, a query list generating module 103, a node calculating module 104 and a database cluster updating module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the article dynamic information storage module 101 is configured to obtain article dynamic information, and store the article dynamic information into a preset database cluster;
the article information record generating module 102 is configured to extract an article code of the article dynamic information, track the article dynamic information according to the article code, and obtain an article information record;
The query list generation module 103 is configured to extract a node type from the item information record, and generate a query list according to the node type, the item code, and the item dynamic information, where the node type includes a master node and a partition node;
the partition node calculation module 104 is configured to issue and store the master node to each partition node according to the query list, and perform integrated calculation on the stored partition nodes to obtain an updated master node;
the database cluster updating module 105 is configured to update the dynamic information of the objects in the database cluster according to the update master node, so as to obtain a target database cluster.
In detail, each module in the storage system 100 for the dynamic information of the object in the internet of things in the embodiment of the present invention adopts the same technical means as the storage method for the dynamic information of the object in the internet of things in the drawings when in use, and can produce the same technical effects, which are not described herein.
The embodiment also provides an electronic device, which may include a processor, a memory, a communication bus, and a communication interface, and may further include a computer program stored in the memory and executable on the processor, such as a guard upgrade program based on information security big data.
The processor may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing Unit, CPU), a microprocessor, a digital processing chip, a graphics processor, a combination of various control chips, and the like. The processor is a Control Unit (Control Unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, and executes various functions of the electronic device and processes data by running or executing programs or modules stored in the memory 11 (for example, executing a program for storing dynamic information of an article in the internet of things, etc.), and calling data stored in the memory.
The memory includes at least one type of readable storage medium including flash memory, removable hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory may in other embodiments also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device. Further, the memory may also include both internal storage units and external storage devices of the electronic device. The memory can be used for storing application software installed in electronic equipment and various data, such as codes of storage programs of dynamic information of articles in the Internet of things, and can also be used for temporarily storing data which are output or are to be output.
The communication bus may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory and at least one processor or the like.
The communication interface is used for communication between the electronic equipment and other equipment, and comprises a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
The storage program of the dynamic information of the article in the internet of things stored in the memory in the electronic device is a combination of a plurality of instructions, and when the storage program runs in the processor, the steps of the storage method of the dynamic information of the article in the internet of things can be realized.
Specifically, the specific implementation method of the above instruction by the processor may refer to descriptions of related steps in the corresponding embodiment of the drawings, which are not repeated herein.
Further, the electronic device integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The invention also provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method of storing dynamic information of an item in the internet of things as described above.
These program code may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows.
Storage media includes both permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media may include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, read only compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.
In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus, system and method may be implemented in other manners. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and other manners of division may be implemented in practice.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. Multiple units or systems as set forth in the system claims may also be implemented by means of one unit or system in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application and not for limiting the same, and although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present application without departing from the spirit and scope of the technical solution of the present application.
Claims (9)
1. The method for storing the dynamic information of the article in the Internet of things is characterized by comprising the following steps:
acquiring dynamic information of an article, and storing the dynamic information of the article into a preset database cluster;
extracting an article code of the article dynamic information, and tracking the article dynamic information according to the article code to obtain an article information record;
extracting node types from the article information record, and generating a query list according to the node types, the article codes and the article dynamic information, wherein the node types comprise a main node and a partition node;
according to the query list, the master node is issued and stored to each of the partial nodes, the stored partial nodes are subjected to integration calculation to obtain an updated master node, wherein the stored partial nodes are subjected to integration calculation to obtain the updated master node, and the method comprises the following steps: performing weight assignment on the stored partial nodes to obtain node weights, performing weight calculation according to the partial nodes and the node weights to obtain updated main nodes, and performing weight calculation by using the following formula to obtain updated main nodes:
wherein ,representing the update master node- >Indicate->Individual node->Indicate->Weight coefficient of node weight corresponding to each partial node, +.>Representing the total number of the sub-nodes;
and updating the dynamic information of the articles in the database cluster according to the updating master node to obtain a target database cluster.
2. The method for storing dynamic information of an article in the internet of things according to claim 1, wherein storing the dynamic information of the article in a preset database cluster comprises:
acquiring a pre-loading information request corresponding to the dynamic information of the article, and analyzing the dynamic information of the article according to the pre-loading information request to obtain a pre-loading information tag;
inquiring a service information area corresponding to the pre-loaded information tag from a preset information pre-loaded data table according to the pre-loaded information tag;
and placing the regional data of the business information region into the database cluster by using a preset SQL statement.
3. The method for storing dynamic information of an item in the internet of things according to claim 1, wherein the extracting the item code of the dynamic information of the item comprises:
acquiring an information ID of the dynamic information of the article, and positioning an operation area of the dynamic information of the article;
Searching a service information area corresponding to the information ID and the operation area from a preset service area definition table;
and inquiring an information label of the dynamic information of the article in the service information area, and numbering the information label to obtain the article code.
4. The method for storing dynamic information of an article in the internet of things according to claim 1, wherein tracking the dynamic information of the article according to the article code to obtain an article information record comprises:
marking the dynamic information of the article according to the article code to obtain the dynamic information of the marked article;
recording an information path of the dynamic information of the marked article, and judging whether the information path contains information nodes of the dynamic information of the marked article or not;
and when the information path comprises the information nodes, acquiring the article information in the information nodes, and integrating the article information to obtain article information records.
5. The method for storing dynamic information of an item in the internet of things according to claim 1, wherein the generating a query list according to the node type, the item code and the dynamic information of the item comprises:
Associating the node types by using a preset association algorithm to obtain associated node types;
the article codes are in one-to-one correspondence with the article dynamic information corresponding to the article codes, and the corresponding article codes and the article dynamic information are combined to be used as coding information;
and constructing a query list by taking the associated node type as a row vector and the coding information as a column vector.
6. The method for storing dynamic information of an article in the internet of things according to claim 5, wherein the associating the node types by using a preset association algorithm to obtain associated node types includes:
selecting any node type from the node types as a target node type, and taking other node types except the target node type as reference node types;
performing matching calculation on the target node type and the reference node type by using the association algorithm to obtain a matching value;
the association algorithm is expressed as:
wherein ,a matching value expressed as the target node type and the reference node type, +.>Representing the target node type->Representing the reference node type- >Representing a preset normalization factor;
when the matching value is larger than a preset threshold value, activating the connection point of the target node type and the reference node type by using a preset activation function to obtain an associated node type;
the activation function may be expressed as:
wherein ,an associated node type representing the target node type and the reference node type, +.>Indicate->Individual target node type->Indicate->A reference node type, I represents the number of the target node types, < >>Representing the number of the reference node types, b representing a preset offset vector of the target node type, and a representing a preset offset vector of the reference node type.
7. The method for storing dynamic information of an article in the internet of things according to claim 1, wherein the step of storing the master node in each of the partial nodes according to the query list includes:
inquiring node information of the main node according to the inquiry list;
transmitting the node information to the sub-node through the connection point of the main node and the sub-node, and storing the node information to the sub-node.
8. The method for storing dynamic information of an item in the internet of things according to any one of claims 1 to 7, wherein updating the dynamic information of the item in the database cluster according to the update master node to obtain a target database cluster includes:
extracting the main node of the dynamic information of the article by using a preset machine learning algorithm to obtain an information main node;
the machine learning algorithm is expressed as:
wherein ,representing the information master node->Representing said item dynamic information,/for>Weight of the information master node expressed as preset,/or->Representing preset calculation parameters;
replacing the information main node by using the update main node, and storing the update main node to the dynamic information of the article;
and storing the updated dynamic information of the object into the database cluster to obtain a target database cluster.
9. A storage system for dynamic information of an article in the internet of things, the system comprising:
the article dynamic information storage module is used for acquiring article dynamic information and storing the article dynamic information into a preset database cluster;
the article information record generation module is used for extracting article codes of the article dynamic information, tracking the article dynamic information according to the article codes and obtaining article information records;
The query list generation module is used for extracting node types from the article information records and generating a query list according to the node types, the article codes and the article dynamic information, wherein the node types comprise a main node and a partition node;
the node calculation module is configured to issue and store the master node to each of the nodes according to the query list, perform an integration calculation on the stored nodes to obtain an updated master node, where the performing the integration calculation on the stored nodes to obtain the updated master node includes: performing weight assignment on the stored partial nodes to obtain node weights, performing weight calculation according to the partial nodes and the node weights to obtain updated main nodes, and performing weight calculation by using the following formula to obtain updated main nodes:
wherein ,representing the update master node->Indicate->Individual node->Indicate->Weight coefficient of node weight corresponding to each partial node, +.>Representing the total number of the sub-nodes;
and the database cluster updating module is used for updating the dynamic information of the articles in the database cluster according to the updating master node to obtain a target database cluster.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211481381.0A CN115712684B (en) | 2022-11-24 | 2022-11-24 | Storage method and system for dynamic information of articles in Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211481381.0A CN115712684B (en) | 2022-11-24 | 2022-11-24 | Storage method and system for dynamic information of articles in Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115712684A CN115712684A (en) | 2023-02-24 |
| CN115712684B true CN115712684B (en) | 2023-10-24 |
Family
ID=85234743
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211481381.0A Active CN115712684B (en) | 2022-11-24 | 2022-11-24 | Storage method and system for dynamic information of articles in Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115712684B (en) |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7716077B1 (en) * | 1999-11-22 | 2010-05-11 | Accenture Global Services Gmbh | Scheduling and planning maintenance and service in a network-based supply chain environment |
| CN101833710A (en) * | 2010-05-07 | 2010-09-15 | 中国科学院自动化研究所 | Semantics-based article information tracking and tracing method for Internet of things |
| CN102014113A (en) * | 2010-07-09 | 2011-04-13 | 北京哈工大计算机网络与信息安全技术研究中心 | Storage method and system of dynamic information of goods in internet of things |
| CN103023970A (en) * | 2012-11-15 | 2013-04-03 | 中国科学院计算机网络信息中心 | Method and system for storing mass data of Internet of Things (IoT) |
| CN104199900A (en) * | 2014-08-26 | 2014-12-10 | 中国航天科工集团第二研究院七〇六所 | Audit and analysis method based on file trajectory tracking trees |
| CN105745675A (en) * | 2013-11-29 | 2016-07-06 | 联邦快递服务公司 | Methods and systems for managing shipment of an item using a wireless node network |
| CN106339843A (en) * | 2016-08-26 | 2017-01-18 | 特斯联（北京）科技有限公司 | A logistics management system based on internet of things |
| CN107428461A (en) * | 2015-02-18 | 2017-12-01 | 联邦快递服务公司 | Use the counter interface display device management logistics information related to logistics counter |
| CN108140009A (en) * | 2015-10-13 | 2018-06-08 | 微软技术许可有限责任公司 | B-tree key assignments manager of the distributed freedom formula based on RDMA |
| KR20200004543A (en) * | 2018-07-04 | 2020-01-14 | 강대웅 | Method for providing authentic data and application based substitute payment service |
| CN112529460A (en) * | 2020-12-23 | 2021-03-19 | 城云科技（中国）有限公司 | Material scheduling method, scheduling system, electronic device and storage medium |
| CN113316118A (en) * | 2021-05-31 | 2021-08-27 | 中国人民解放军国防科技大学 | Unmanned aerial vehicle cluster network self-organizing system and method based on task cognition |
| CN113886434A (en) * | 2021-11-02 | 2022-01-04 | 北京百度网讯科技有限公司 | Database cluster-based query and storage method, device and equipment |
-
2022
- 2022-11-24 CN CN202211481381.0A patent/CN115712684B/en active Active
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7716077B1 (en) * | 1999-11-22 | 2010-05-11 | Accenture Global Services Gmbh | Scheduling and planning maintenance and service in a network-based supply chain environment |
| CN101833710A (en) * | 2010-05-07 | 2010-09-15 | 中国科学院自动化研究所 | Semantics-based article information tracking and tracing method for Internet of things |
| CN102014113A (en) * | 2010-07-09 | 2011-04-13 | 北京哈工大计算机网络与信息安全技术研究中心 | Storage method and system of dynamic information of goods in internet of things |
| CN103023970A (en) * | 2012-11-15 | 2013-04-03 | 中国科学院计算机网络信息中心 | Method and system for storing mass data of Internet of Things (IoT) |
| CN105745675A (en) * | 2013-11-29 | 2016-07-06 | 联邦快递服务公司 | Methods and systems for managing shipment of an item using a wireless node network |
| CN104199900A (en) * | 2014-08-26 | 2014-12-10 | 中国航天科工集团第二研究院七〇六所 | Audit and analysis method based on file trajectory tracking trees |
| CN107428461A (en) * | 2015-02-18 | 2017-12-01 | 联邦快递服务公司 | Use the counter interface display device management logistics information related to logistics counter |
| CN108140009A (en) * | 2015-10-13 | 2018-06-08 | 微软技术许可有限责任公司 | B-tree key assignments manager of the distributed freedom formula based on RDMA |
| CN106339843A (en) * | 2016-08-26 | 2017-01-18 | 特斯联（北京）科技有限公司 | A logistics management system based on internet of things |
| KR20200004543A (en) * | 2018-07-04 | 2020-01-14 | 강대웅 | Method for providing authentic data and application based substitute payment service |
| CN112529460A (en) * | 2020-12-23 | 2021-03-19 | 城云科技（中国）有限公司 | Material scheduling method, scheduling system, electronic device and storage medium |
| CN113316118A (en) * | 2021-05-31 | 2021-08-27 | 中国人民解放军国防科技大学 | Unmanned aerial vehicle cluster network self-organizing system and method based on task cognition |
| CN113886434A (en) * | 2021-11-02 | 2022-01-04 | 北京百度网讯科技有限公司 | Database cluster-based query and storage method, device and equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115712684A (en) | 2023-02-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112115152B (en) | Data increment updating and inquiring method and device, electronic equipment and storage medium | |
| CN115002200B (en) | Message pushing method, device, equipment and storage medium based on user portrait | |
| CN113626607B (en) | Abnormal work order identification method and device, electronic equipment and readable storage medium | |
| CN110930192A (en) | User loss prediction method, system, device and storage medium | |
| CN108241867B (en) | Classification method and device | |
| CN110955690A (en) | Self-service data labeling platform and self-service data labeling method based on big data technology | |
| US20190286724A1 (en) | Data analysis support apparatus and data analysis support method | |
| CN105550270A (en) | Database inquiry method and device | |
| CN114612194A (en) | Product recommendation method and device, electronic equipment and storage medium | |
| CN114186132A (en) | Information recommendation method and device, electronic equipment and storage medium | |
| CN114756669A (en) | Intelligent analysis method and device for problem intention, electronic equipment and storage medium | |
| CN114862140A (en) | Behavior analysis-based potential evaluation method, device, equipment and storage medium | |
| CN113658002A (en) | Decision tree-based transaction result generation method and device, electronic equipment and medium | |
| CN113706253A (en) | Real-time product recommendation method and device, electronic equipment and readable storage medium | |
| CN115712684B (en) | Storage method and system for dynamic information of articles in Internet of things | |
| CN111222923A (en) | Method and device for judging potential customer, electronic equipment and storage medium | |
| CN113722437B (en) | User tag identification method, device, equipment and medium based on artificial intelligence | |
| CN114841165B (en) | User data analysis and display method and device, electronic equipment and storage medium | |
| CN114518993A (en) | System performance monitoring method, device, equipment and medium based on business characteristics | |
| CN114996386A (en) | Business role identification method, device, equipment and storage medium | |
| CN115204971A (en) | Product recommendation method and device, electronic equipment and computer-readable storage medium | |
| CN113806492A (en) | Record generation method, device and equipment based on semantic recognition and storage medium | |
| CN113706019A (en) | Service capability analysis method, device, equipment and medium based on multidimensional data | |
| CN112818215A (en) | Product data processing method, device, equipment and storage medium | |
| CN113656690A (en) | Product recommendation method and device, electronic equipment and readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |