CN116319967B - Data storage expansion method, device and equipment based on Internet of things and storage medium - Google Patents

Data storage expansion method, device and equipment based on Internet of things and storage medium Download PDF

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Publication number
CN116319967B
CN116319967B CN202310561133.5A CN202310561133A CN116319967B CN 116319967 B CN116319967 B CN 116319967B CN 202310561133 A CN202310561133 A CN 202310561133A CN 116319967 B CN116319967 B CN 116319967B
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memory
equipment
internet
things
preset
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CN116319967A (en
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余道德
孙海涛
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Shenzhen Ruiai Electronics Co ltd
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Shenzhen Ruiai Electronics Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0628—Interfaces specially adapted for storage systems making use of a particular technique
    • G06F3/0638—Organizing or formatting or addressing of data
    • G06F3/0644—Management of space entities, e.g. partitions, extents, pools
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
    • G06F3/0601—Interfaces specially adapted for storage systems
    • G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
    • G06F3/0671—In-line storage system
    • G06F3/0683—Plurality of storage devices
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
    • H04L67/1004—Server selection for load balancing
    • H04L67/1008—Server selection for load balancing based on parameters of servers, e.g. available memory or workload
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
    • H04L67/1031—Controlling of the operation of servers by a load balancer, e.g. adding or removing servers that serve requests
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/0215—Traffic management, e.g. flow control or congestion control based on user or device properties, e.g. MTC-capable devices
    • H04W28/0221—Traffic management, e.g. flow control or congestion control based on user or device properties, e.g. MTC-capable devices power availability or consumption
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/08—Load balancing or load distribution
    • H04W28/09—Management thereof
    • H04W28/0917—Management thereof based on the energy state of entities
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

The invention relates to an artificial intelligence technology, and discloses a data storage expansion method based on the Internet of things, which comprises the following steps: acquiring the number of devices and the device memory, and screening an available device set from the internet-of-things device set according to the number of the devices and the device memory; when the residual memory of the stirring equipment to be stored is smaller than or equal to the preset required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory; calculating an allocated memory according to the used memory and the equipment memory, and screening an allocable equipment set from the available equipment sets according to the allocated memory; performing storage expansion according to the memory with additional requirements; acquiring user information of stirring equipment to be stored, and performing storage expansion according to the user information; and acquiring the wireless type of the assignable equipment set, and performing storage expansion according to the wireless type. The invention further provides a data storage expansion device based on the Internet of things, electronic equipment and a storage medium. The invention can improve the data expansion efficiency of the stirring system.

Description

Data storage expansion method, device and equipment based on Internet of things and storage medium
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a data storage expansion method, a device, electronic equipment and a computer readable storage medium based on the internet of things.
Background
Along with the development of information technology, more and more traditional electrical appliances are digitalized gradually, for example, a digitalized stirrer can break food and juice fruits, different stirring preferences of different users can be recorded, the stirring mode is switched more intelligently, a large amount of user information needs to be stored by the stirrer for realizing the digitalization of the stirrer, and data storage expansion needs to be carried out on the stirrer for storing more user data.
The existing data storage expansion method of the stirrer is mainly based on an external data storage, and further performs data expansion, for example, the data storage expansion is based on a flash memory card (SD card, secure Digital Memory Card), in practical application, the data storage expansion based on the external data storage requires additional funds to purchase the flash memory card, the plugging operation of the flash memory card is inconvenient, the flash memory card is easy to damage, and therefore the efficiency of performing data expansion on a stirring system is low.
Disclosure of Invention
The invention provides a data storage expansion method and device based on the Internet of things and a computer readable storage medium, and mainly aims to solve the problem of low efficiency when data expansion is performed on a stirring system.
In order to achieve the above object, the data storage expansion method based on the internet of things provided by the invention comprises the following steps:
acquiring the number of devices of an Internet of things device set and the device memory of each Internet of things device in the Internet of things device set in a preset network domain, and screening the Internet of things devices in the Internet of things device set according to the number of the devices and the device memory to obtain an available device set;
when the available equipment set is not an empty set, judging whether the residual memory of the stirring equipment to be stored is larger than a preset required memory or not;
when the residual memory of the stirring equipment to be expanded is larger than the required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending data storage expansion;
when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
Calculating the allocated memory of each Internet of things device in the available device set according to the used memory and the device memory, and screening the Internet of things devices in the available device set according to the allocated memory to obtain an allocable device set;
performing storage expansion on the assignable equipment set according to the extra-demand memory by using a preset equipartition algorithm;
when the storage expansion of the equipartition algorithm fails, acquiring user information of the stirring equipment to be expanded, and carrying out storage expansion on the allocatable equipment set according to the user information by utilizing a preset frequency allocation algorithm;
when the frequency allocation algorithm fails to perform storage expansion, acquiring the wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by utilizing a preset signal allocation algorithm.
Optionally, the screening, according to the number of devices and the device memory, the internet of things devices in the internet of things device set to obtain an available device set includes:
judging whether the number of the devices is larger than a preset number threshold;
when the number of the devices is larger than the number threshold, selecting one of the Internet of things devices in the Internet of things device set one by one as a target device, and judging whether the device memory of the target device is larger than a preset memory threshold;
When the device memory of the target device is greater than the memory threshold, adding the target device to the set of available devices;
returning to the step of selecting one internet of things device in the internet of things device set one by one as a target device when the device memory of the target device is smaller than or equal to the memory threshold;
when the number of devices is less than or equal to the number threshold, the set of available devices is set to an empty set.
Optionally, the calculating the allocated memory of each of the devices in the set of available devices according to the used memory and the device memory includes:
one internet of things device in the available device set is selected one by one to serve as a device to be distributed;
subtracting the used memory of the equipment to be allocated from the equipment memory of the equipment to be allocated to obtain the spare memory of the equipment to be allocated;
dividing the spare memory by a preset distribution coefficient to obtain the distribution memory of the equipment to be distributed.
Optionally, the obtaining the user information of the stirring device to be stored includes:
processing the fingerprint component and the voiceprint component of the stirring equipment to be stored by a preset double identification algorithm to obtain the user name of the user;
Inquiring in a database of the stirring equipment to be stored in a expanding manner according to the user name to obtain the frequency of use, the recording gear, the recording rotating speed and the stirring time length corresponding to the user name;
and integrating the user name, the frequency of use, the recording gear, the recording rotating speed and the stirring time length into the user information.
Optionally, the storing and expanding the allocable device set according to the user information by using a preset frequency allocation algorithm includes:
extracting the frequency of use, the recording gear, the recording rotating speed and the stirring time from the user information;
calculating a maximum storage capacity according to the use frequency, the recording gear, the recording rotating speed and the stirring time length by using a frequency distribution algorithm of the following formula (1):
formula (1)
In the formula (1), d refers to the maximum storage capacity, ceiling is an upward rounding symbol, q refers to the use frequency, g refers to the recording gear, β is a preset gear coefficient, p refers to the recording rotation speed, h refers to the stirring time period, α is a preset frequency coefficient, R is a preset capacity coefficient, and γ is a preset stirring coefficient;
And selecting the Internet of things equipment with the allocation memory matched with the maximum storage capacity from the allocable equipment set as target expansion equipment, and taking the spare storage space of the target expansion equipment as the expansion memory of the stirring equipment to be expanded.
Optionally, the acquiring the wireless type of the assignable device set includes:
one internet of things device in the assignable device set is selected one by one to serve as a target wireless device;
acquiring a unit power spectrum of the target wireless equipment, and acquiring a power peak sequence and a power peak sequence from the unit power spectrum;
extracting target edge characteristics from the unit power spectrum, and normalizing the target edge characteristics to obtain a target edge code;
calculating the matching distance between the unit power spectrum and various wireless spectrums in a preset wireless power spectrum library according to the target edge code, the power edge sequence and the power edge sequence by using a spectrum distance algorithm as shown in the following formula (2):
formula (2)
In the formula (2), Y refers to the matching distance, V refers to the target spike code, V refers to the spike code of the wireless spectrum, i refers to the ith bit, m is the total spike bit number of the power spike sequence of the unit power spectrum, A i Refers to the power spike of the ith bit in the power spike sequence of the unit power spectrum, A refers to the power spike sequence of the unit power spectrum, a i Refers to the ith power peak in the power peak sequence of the wireless spectrum, a refers to the power peak sequence of the wireless spectrum, B i Refers to the power peak frequency of the ith bit in the power peak frequency sequence of the unit power spectrum, B refers to the power peak frequency sequence of the unit power spectrum, B i Refers to the power peak frequency of the ith position in the power peak frequency sequence of the wireless spectrum, and b refers to the power of the wireless spectrumA spike sequence;
and selecting the signal type of the corresponding wireless map when the value of the matching distance is minimum as the wireless type of the target wireless device.
Optionally, the storing and expanding the set of assignable devices according to the wireless type by using a preset signal allocation algorithm includes:
ordering the internet of things equipment in the allocable equipment set according to the signal intensity of the wireless type from strong to weak to obtain an allocable equipment sequence;
selecting the Internet of things equipment from the assignable equipment sequence one by one according to the sequence from the small sequence number to the large sequence number as target signal equipment;
And selecting a memory area with the same memory size as the classified memory of the target signal equipment from the spare memory space of the target signal equipment as an expansion memory of the stirring equipment to be expanded.
In order to solve the above problems, the present invention further provides a data storage expansion device based on the internet of things, the device comprising:
the device screening module is used for acquiring the number of devices of the Internet of things device set in a preset network domain and the device memory of each Internet of things device in the Internet of things device set, and screening the Internet of things devices in the Internet of things device set according to the number of the devices and the device memory to obtain an available device set;
the required storage calculation module is used for judging whether the residual memory of the stirring equipment to be stored is larger than a preset required memory when the available equipment set is not an empty set; when the residual memory of the stirring equipment to be expanded is larger than the required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending data storage expansion; when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
The expansion screening module is used for calculating the distribution memory of each piece of internet of things equipment in the available equipment set according to the used memory and the equipment memory, and screening the internet of things equipment in the available equipment set according to the distribution memory to obtain an allocable equipment set;
the memory expansion decision module is used for carrying out memory expansion on the assignable equipment set according to the extra-demand memory by utilizing a preset equipartition algorithm, wherein:
when the storage expansion of the equipartition algorithm fails, acquiring user information of the stirring equipment to be expanded, and carrying out storage expansion on the allocatable equipment set according to the user information by utilizing a preset frequency allocation algorithm;
when the frequency allocation algorithm fails to perform storage expansion, acquiring the wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by utilizing a preset signal allocation algorithm.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the data storage expansion method based on the internet of things.
In order to solve the above problems, the present invention further provides a computer readable storage medium, where at least one computer program is stored, where the at least one computer program is executed by a processor in an electronic device to implement the data storage expansion method based on the internet of things.
The invention can screen the Internet of things equipment in the Internet of things equipment set according to the equipment quantity and the equipment memory to obtain an available equipment set, screen equipment with larger storage capacity from the Internet of things equipment set as equipment for storage expansion, thereby improving the efficiency of storage expansion, calculate the extra required memory of the stirring equipment to be expanded, acquire the used memory of each Internet of things equipment in the available equipment set, provide reference parameters for subsequent memory allocation, screen the Internet of things equipment in the available equipment set according to the allocation memory to obtain an allocatable equipment set, ensure that each Internet of things equipment in the allocatable equipment set has enough memory space for data storage expansion of the stirring equipment to be expanded, avoid the problems of a machine, delay response, heating and the like of the Internet of things equipment in the allocatable equipment set due to the small available memory capacity, simplify the allocation of the equipment according to the extra required memory by using a preset equipartition algorithm, realize the characteristic feature vector expansion of the fingerprint feature of the fingerprint input device in the fingerprint input system, improve the fingerprint feature vector expansion, improve the fingerprint feature of the user, the method comprises the steps of carrying out storage expansion on the allocable equipment set according to user information by using a preset frequency allocation algorithm, selecting the internet of things equipment with different sizes for memory allocation as equipment for memory expansion according to different users, thereby ensuring the on-demand allocation of the storage expansion and improving the efficiency of the storage expansion. Therefore, the data storage expansion method, the data storage expansion device, the electronic equipment and the computer readable storage medium based on the Internet of things can solve the problem of low efficiency when the stirring system is subjected to data expansion.
Drawings
Fig. 1 is a flow chart of a data storage expansion method based on the internet of things according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of acquiring wireless types of an assignable device set according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a memory expansion process according to a signal allocation algorithm according to an embodiment of the present invention;
FIG. 4 is a flow chart illustrating a method for screening a set of available devices according to an embodiment of the present invention;
FIG. 5 is a functional block diagram of a data storage expansion device based on the Internet of things according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device for implementing the data storage expansion method based on the internet of things according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention 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 invention.
The embodiment of the application provides a data storage expansion method based on the Internet of things. The execution subject of the data storage expansion method based on the internet of things comprises at least one of electronic equipment, such as a server, a terminal and the like, which can be configured to execute the method provided by the embodiment of the application. In other words, the data storage expansion method based on the internet of things can be executed by software or hardware installed in a terminal device or a 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 (ContentDelivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of a data storage expansion method based on the internet of things according to an embodiment of the present invention is shown. In this embodiment, the data storage expansion method based on the internet of things includes:
s1, acquiring the number of devices of an Internet of things device set in a preset network domain and the device memory of each Internet of things device in the Internet of things device set, and screening the Internet of things devices in the Internet of things device set according to the number of the devices and the device memory to obtain an available device set;
in the embodiment of the invention, the internet of things device set refers to all networking devices connected with the preset network domain, such as a router, a network camera, an intelligent terminal, an intelligent sound box and other devices.
In the embodiment of the present invention, the obtaining the number of devices in the internet of things device set in the preset network domain and the device memory of each internet of things device in the internet of things device set includes:
acquiring a device list of the Internet of things device set by utilizing a cloud server of the preset network domain, and counting the number of devices of the Internet of things device in the device list;
one internet of things device in the device list is selected one by one to serve as a device to be queried, and a query request is sent to the device to be queried;
And acquiring the return data of the equipment to be queried aiming at the query request, and extracting the equipment memory from the return data.
Specifically, the device list includes an IP address, a device name, and a device type of each of the devices in the set of devices.
In detail, the NetServerEnum function or the thinsbard platform of the cloud server may be utilized to obtain the device list of the internet of things device set.
In detail, a query request may be sent to the target device by means of a transmission handshake (TCP, transmission Control Protocol), where the query request may be an instruction such as cat/proc/meminfo or df-h.
In detail, the device memory may be extracted from the return data using a select statement or regular expression.
In detail, referring to fig. 4, the screening, according to the number of devices and the device memory, the internet of things devices in the internet of things device set to obtain an available device set includes:
s41, judging whether the number of the devices is larger than a preset number threshold;
s42, when the number of the devices is larger than the number threshold, selecting one of the Internet of things devices in the Internet of things device set one by one as a target device;
S43, judging whether the equipment memory of the target equipment is larger than a preset memory threshold value;
s44, when the equipment memory of the target equipment is larger than the memory threshold value, adding the target equipment into the available equipment set;
s45, returning to the step of selecting one of the Internet of things devices in the Internet of things device set one by one as the target device when the device memory of the target device is smaller than or equal to the memory threshold;
s46, when the number of the devices is smaller than or equal to the number threshold, setting the available device set as an empty set.
In particular, the number threshold may be 1 or 2.
In detail, the memory threshold may be 100B or 150B.
In the embodiment of the invention, the available equipment set is obtained by screening the Internet of things equipment in the Internet of things equipment set according to the equipment number and the equipment memory, and the equipment with larger storage capacity can be screened out from the Internet of things equipment set to serve as storage expansion equipment, so that the efficiency of storage expansion is improved.
S2, when the available equipment set is not an empty set, judging whether the residual memory of the stirring equipment to be stored is larger than a preset required memory or not;
In the embodiment of the invention, the stirring equipment to be stored can be an intelligent stirrer of the internet of things or an intelligent juicer of the internet of things.
In detail, the required memory refers to the size of data to be stored in the stirring device to be expanded, where the data to be stored may be data such as system update data and stirring data.
Specifically, the remaining memory refers to the memory remaining after subtracting the occupied memory from the total memory of the device in the memory expansion and stirring device, so as to obtain the total memory and occupied memory of the device to be memory expansion and stirring device, and subtracting the occupied memory from the total memory of the device to obtain the remaining memory.
In the embodiment of the invention, whether the stirring equipment to be expanded needs to be expanded by using the available equipment set can be analyzed by judging whether the residual memory of the stirring equipment to be expanded is larger than the preset required memory.
S3, when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
in the embodiment of the present invention, calculating the additional required memory of the stirring device to be expanded refers to subtracting the remaining memory from the required memory to obtain the additional required memory.
Specifically, the method for obtaining the used memory of each of the internet of things devices in the available device set is consistent with the number of devices in the internet of things device set in the preset network domain and the method for obtaining the device memory of each of the internet of things devices in the internet of things device set in the step S1, which are not described herein.
In the embodiment of the invention, the reference parameters can be provided for subsequent memory allocation by calculating the extra required memory of the stirring equipment to be stored and acquiring the used memory of each of the internet of things equipment in the available equipment set.
S4, calculating the distribution memory of each piece of Internet of things equipment in the available equipment set according to the used memory and the equipment memory, and screening the pieces of Internet of things equipment in the available equipment set according to the distribution memory to obtain an allocable equipment set;
in the embodiment of the present invention, the allocated memory refers to a memory size of the available device set that can be used for memory expansion of other devices.
In the embodiment of the present invention, the calculating, according to the used memory and the device memory, the allocated memory of each of the devices in the set of available devices includes:
One internet of things device in the available device set is selected one by one to serve as a device to be distributed;
subtracting the used memory of the equipment to be allocated from the equipment memory of the equipment to be allocated to obtain the spare memory of the equipment to be allocated;
dividing the spare memory by a preset distribution coefficient to obtain the distribution memory of the equipment to be distributed.
In particular, the distribution coefficient may be 2 or 2.5.
In detail, the allocation memory of the equipment to be allocated is obtained by dividing the spare memory by a preset allocation coefficient, so that the equipment to be allocated can be ensured to have sufficient storage space for daily function operation after the data of the stirring equipment to be expanded are stored.
In detail, the screening, according to the allocation memory, the internet of things devices in the set of available devices to obtain the set of allocable devices includes:
one internet of things device in the available device set is selected one by one to serve as target distribution equipment;
judging whether the used memory of the target distribution equipment is larger than the distribution memory of the target distribution equipment or not;
returning to the step of selecting one internet of things device in the set of available devices one by one as a target distribution device when the used memory of the target distribution device is smaller than or equal to the distribution memory of the target distribution device;
And adding the target allocation device to the allocatable device set when the used memory of the target allocation device is greater than the allocated memory of the target allocation device.
Specifically, the internet of things equipment in the available equipment set is screened according to the allocated memory to obtain an allocable equipment set, so that each internet of things equipment in the allocable equipment set can be ensured to have sufficient memory space for data storage expansion of the stirring equipment to be expanded, and the problems of downtime, delayed response, heating, scalding and the like of the internet of things equipment in the allocable equipment set due to the fact that the available memory capacity is too small after the subsequent data storage expansion is finished are avoided.
S5, using a preset equipartition algorithm to store and expand the assignable equipment set according to the extra-demand memory;
in the embodiment of the present invention, the storing and expanding the assignable device set according to the extra-demand memory by using a preset equipartition algorithm includes:
acquiring the equipment stock of the allocable equipment set;
dividing the extra required memory by the equipment stock to obtain an average memory;
and selecting a spare storage space with the same size as the equipartition memory from each internet of things device of the allocatable device set as an expansion memory of the stirring device to be expanded.
In detail, the device stock refers to the number of the internet of things devices in the assignable device set.
In the embodiment of the invention, the memory expansion of the allocable equipment set is carried out according to the extra-demand memory by utilizing the preset equipartition algorithm, so that the effect of simplifying the memory expansion step can be achieved when the allocated memory of the internet of things equipment in the allocable equipment set is larger and the equipartition memory is smaller, and the memory expansion efficiency is improved.
S6, when the equipartition algorithm fails to store and expand, acquiring user information of the stirring equipment to be stored, and storing and expanding the assignable equipment set according to the user information by using a preset frequency allocation algorithm;
in the embodiment of the present invention, when the storage expansion of the equipartition algorithm fails, the storage expansion refers to when the classified memory of at least one internet of things device in the assignable device set is less than or equal to the equipartition memory.
In detail, the user information includes information such as user name information, user use frequency, stirring times record of various food materials by a user, user gear use record, user rotation speed use record, user stirring time record and the like.
In the embodiment of the present invention, the obtaining the user information of the stirring device to be stored includes:
processing the fingerprint component and the voiceprint component of the stirring equipment to be stored by a preset double identification algorithm to obtain the user name of the user;
inquiring in a database of the stirring equipment to be stored in a expanding manner according to the user name to obtain the frequency of use, the recording gear, the recording rotating speed and the stirring time length corresponding to the user name;
and integrating the user name, the frequency of use, the recording gear, the recording rotating speed and the stirring time length into the user information.
In detail, the fingerprint component may be a fingerprint identifier integrated on the stirring key, such as a sub-slightly CID5000 fingerprint collector and a shield FP-220 type fingerprint collector.
Specifically, the voiceprint component can signal the intelligent zd-403v2.0 voiceprint collector and the TMC104 voiceprint data collection terminal.
Specifically, the processing, by a preset dual recognition algorithm, the fingerprint component and the voiceprint component of the stirring apparatus to be stored to obtain the user name of the user includes:
acquiring fingerprint information of the user by utilizing the fingerprint component, and extracting features of the fingerprint information to obtain a fingerprint feature vector;
Acquiring voiceprint information of the user by utilizing the voiceprint component, and extracting features of the voiceprint information to obtain voiceprint feature vectors;
selecting one user account number from the database one by one as a target account number, selecting fingerprint features corresponding to the target account number from the database as target fingerprint features, and selecting voiceprint features corresponding to the target account number from the database as target voiceprint features;
calculating the matching degree of the user and the target account number according to the fingerprint feature vector, the voiceprint feature vector, the target fingerprint feature and the target voiceprint feature by using a double recognition algorithm in the following formula (3):
formula (3)
In the formula (3), L refers to the matching degree, arccos is an inverse cosine function, F refers to the fingerprint feature vector, F refers to the target fingerprint feature, S refers to the fingerprint feature vector, and S refers to the target fingerprint feature;
and selecting the corresponding target account number as the user name of the user when the value of the matching degree is minimum.
In detail, the fingerprint information may be feature extracted using a radial basis function network (RBF, radial basis function) to obtain a fingerprint feature vector.
Specifically, a Back Propagation (BP) can be used to perform feature extraction on the voiceprint information to obtain a voiceprint feature vector.
In the embodiment of the invention, the matching degree of the user and the target account number is calculated according to the fingerprint feature vector, the voiceprint feature vector, the target fingerprint feature and the target voiceprint feature by utilizing the double recognition algorithm, so that the matching of the character features with double dimensions of fingerprints and voiceprints can be realized, and the accuracy of character information recognition is improved.
In detail, referring to fig. 2, the storing and expanding the set of allocable devices according to the user information by using a preset frequency allocation algorithm includes:
s21, extracting the use frequency, the recording gear, the recording rotating speed and the stirring time from the user information;
s22, calculating the maximum storage capacity according to the use frequency, the recording gear, the recording rotating speed and the stirring duration by using a frequency distribution algorithm in the following formula (1):
formula (1)
In the formula (1), d refers to the maximum storage capacity, ceiling is an upward rounding symbol, q refers to the use frequency, g refers to the recording gear, β is a preset gear coefficient, p refers to the recording rotation speed, h refers to the stirring time period, α is a preset frequency coefficient, R is a preset capacity coefficient, and γ is a preset stirring coefficient;
S23, selecting the Internet of things equipment with the allocation memory matched with the maximum storage capacity from the allocatable equipment set as target expansion equipment, and taking the spare storage space of the target expansion equipment as the expansion memory of the stirring equipment to be expanded.
Specifically, the gear coefficient may be 1 or 2, the frequency coefficient may be 0.05 or 0.06, the capacity coefficient may be 500 or 1000, and the stirring coefficient may be 36000 or 40000.
In the embodiment of the invention, the storage expansion is carried out on the allocatable equipment set according to the user information by utilizing the preset frequency allocation algorithm, and the internet of things equipment with different sizes for allocating the memory can be selected as equipment for expanding the memory according to different users, so that the on-demand allocation of the storage expansion is ensured, and the efficiency of the storage expansion is improved.
S7, when the frequency allocation algorithm fails to perform storage expansion, acquiring a wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by using a preset signal allocation algorithm;
in the embodiment of the present invention, when the storage expansion of the frequency allocation algorithm fails, the maximum storage capacity is larger than the classified memory of any one of the internet of things devices in the allocable device set.
In an embodiment of the present invention, the obtaining the wireless type of the allocable device set includes:
one internet of things device in the assignable device set is selected one by one to serve as a target wireless device;
acquiring a unit power spectrum of the target wireless equipment, and acquiring a power peak sequence and a power peak sequence from the unit power spectrum;
extracting target edge characteristics from the unit power spectrum, and normalizing the target edge characteristics to obtain a target edge code;
calculating the matching distance between the unit power spectrum and various wireless spectrums in a preset wireless power spectrum library according to the target edge code, the power edge sequence and the power edge sequence by using a spectrum distance algorithm as shown in the following formula (2):
formula (2)
In the formula (2), Y refers to the matching distance, V refers to the target spike code, V refers to the spike code of the wireless spectrum, i refers to the ith bit, m is the total spike bit number of the power spike sequence of the unit power spectrum, A i Refers to the power spike of the ith bit in the power spike sequence of the unit power spectrum, A refers toThe power peak sequence of the unit power spectrum, a i Refers to the ith power peak in the power peak sequence of the wireless spectrum, a refers to the power peak sequence of the wireless spectrum, B i Refers to the power peak frequency of the ith bit in the power peak frequency sequence of the unit power spectrum, B refers to the power peak frequency sequence of the unit power spectrum, B i The power peak frequency of the ith position in the power peak frequency sequence of the wireless spectrum is referred to, and b refers to the power peak frequency sequence of the wireless spectrum;
and selecting the signal type of the corresponding wireless map when the value of the matching distance is minimum as the wireless type of the target wireless device.
According to the embodiment of the invention, the spectrum matching can be performed from three directions of waveform characteristics, peak characteristics and frequency characteristics by calculating the matching distances between the unit power spectrum and various wireless spectrums in a preset wireless power spectrum library according to the target edge code, the power edge sequence and the power edge sequence by using the following spectrum distance algorithm, so that the accuracy of wireless type matching is improved.
Specifically, a WiFi frequency meter may be utilized to obtain a unit power spectrum of the target wireless device.
In detail, a depth residual shrinkage network may be used to extract a target edge feature from the unit power spectrum, and a sigmoid function may be used to normalize the target edge feature to obtain a target edge code.
Specifically, the spike refers to the value of the peak point in the waveform curve.
Specifically, the spike frequency refers to a frequency value corresponding to a curve maximum value on a spectrum curve of one pulse wave, and represents a frequency of the most energetic simple harmonic component among all the simple harmonic components constituting the pulse wave.
In detail, referring to fig. 3, the storing and expanding the set of allocable devices according to the wireless type by using a preset signal allocation algorithm includes:
s31, sorting the Internet of things equipment in the assignable equipment set according to the strength of the wireless type signals from strong to weak to obtain an assignable equipment sequence;
s32, selecting the Internet of things equipment from the assignable equipment sequence one by one according to the sequence from the small sequence number to the large sequence number as target signal equipment;
s33, selecting a memory area with the same memory size as the classified memory of the target signal equipment from the spare memory space of the target signal equipment as an expansion memory of the stirring equipment to be expanded.
According to the embodiment of the invention, the storage expansion is carried out on the distributable equipment set according to the wireless type by utilizing the preset signal distribution algorithm, so that the storage expansion of the Internet of things equipment with better transmission signals can be preferentially selected during the data storage expansion, the safety and stability of data transmission during the storage expansion are ensured, and the efficiency of the data storage expansion is improved.
And S8, when the residual memory of the stirring equipment to be expanded is larger than the preset required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending the data storage expansion.
According to the embodiment of the invention, the internet of things equipment in the internet of things equipment set is screened according to the equipment quantity and the equipment memory to obtain an available equipment set, equipment with larger storage capacity can be screened from the internet of things equipment set to serve as equipment for storage expansion, so that the efficiency of storage expansion is improved, the extra required memory of the stirring equipment to be expanded is calculated, the used memory of each internet of things equipment in the available equipment set is obtained, reference parameters can be provided for subsequent memory allocation, the internet of things equipment in the available equipment set is screened according to the allocation memory, an allocatable equipment set is obtained, each internet of things equipment in the allocatable equipment set is ensured to have sufficient memory space for data storage expansion of the stirring equipment to be expanded, the problems of a character expansion, delay response, heating equipartition and the like of the internet of things equipment in the allocatable equipment set are avoided after the storage expansion of the subsequent data storage expansion is finished because the available memory capacity is too small, the characteristic of the character expansion is calculated by using a preset algorithm, the fingerprint expansion algorithm can be realized by using the characteristic of the fingerprint, the fingerprint expansion algorithm is improved, the fingerprint characteristic of the fingerprint expansion is realized by matching with the fingerprint information in the user, the fingerprint expansion system is realized, the method comprises the steps of carrying out storage expansion on the allocable equipment set according to user information by using a preset frequency allocation algorithm, selecting the internet of things equipment with different sizes for memory allocation as equipment for memory expansion according to different users, thereby ensuring the on-demand allocation of the storage expansion and improving the efficiency of the storage expansion. Therefore, the data storage expansion method based on the Internet of things can solve the problem of low efficiency when the stirring system is subjected to data expansion.
Fig. 5 is a functional block diagram of a data storage expansion device based on the internet of things according to an embodiment of the present invention.
The data storage expansion device 100 based on the internet of things can be installed in electronic equipment. According to the implemented functions, the data storage expansion device 100 based on the internet of things may include a device screening module 101, a storage-needed calculating module 102, a storage-expanding screening module 103, and a storage-expanding decision module 104. 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 device screening module 101 is configured to obtain the number of devices in an internet of things device set in a preset network domain and a device memory of each internet of things device in the internet of things device set, and screen the internet of things devices in the internet of things device set according to the number of devices and the device memory to obtain an available device set;
the required memory calculating module 102 is configured to determine whether a remaining memory of the stirring device to be stored is greater than a preset required memory when the available device set is not an empty set; when the residual memory of the stirring equipment to be expanded is larger than the required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending data storage expansion; when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
The extension screening module 103 is configured to calculate an allocated memory of each of the devices in the set of available devices according to the used memory and the device memory, and screen the devices in the set of available devices according to the allocated memory, so as to obtain a set of allocable devices;
the memory expansion decision module 104 is configured to utilize a preset equipartition algorithm to expand the memory of the assignable device set according to the extra-demand memory, where: when the storage expansion of the equipartition algorithm fails, acquiring user information of the stirring equipment to be expanded, and carrying out storage expansion on the allocatable equipment set according to the user information by utilizing a preset frequency allocation algorithm;
when the frequency allocation algorithm fails to perform storage expansion, acquiring the wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by utilizing a preset signal allocation algorithm.
In detail, each module in the data storage expansion device 100 based on the internet of things in the embodiment of the present invention adopts the same technical means as the data storage expansion method based on the internet of things described in the above fig. 1 to 3 when in use, and can produce the same technical effects, which are not described herein.
Fig. 6 is a schematic structural diagram of an electronic device for implementing a data storage expansion method based on the internet of things according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as a data storage expansion program based on the internet of things.
The processor 10 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 so on. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the entire electronic device using various interfaces and lines, executes or executes programs or modules stored in the memory 11 (for example, executes a data storage expansion program based on the internet of things, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device and process data.
The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 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 11 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 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used to store not only application software installed in an electronic device and various data, such as codes of a data storage expansion program based on the internet of things, but also temporarily store data that has been output or is to be output.
The communication bus 12 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 11 and at least one processor 10 etc.
The communication interface 13 is used for communication between the electronic device and other devices, including 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.
Only an electronic device having components is shown, and it will be understood by those skilled in the art that the structures shown in the figures do not limit the electronic device, and may include fewer or more components than shown, or may combine certain components, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device may further include various sensors, bluetooth modules, wi-Fi modules, etc., which are not described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The data storage expansion program stored in the memory 11 of the electronic device 1 and based on the internet of things is a combination of a plurality of instructions, and when running in the processor 10, the implementation may be:
acquiring the number of devices of an Internet of things device set and the device memory of each Internet of things device in the Internet of things device set in a preset network domain, and screening the Internet of things devices in the Internet of things device set according to the number of the devices and the device memory to obtain an available device set;
When the available equipment set is not an empty set, judging whether the residual memory of the stirring equipment to be stored is larger than a preset required memory or not;
when the residual memory of the stirring equipment to be expanded is larger than the required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending data storage expansion;
when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
calculating the allocated memory of each Internet of things device in the available device set according to the used memory and the device memory, and screening the Internet of things devices in the available device set according to the allocated memory to obtain an allocable device set;
and storing and expanding the assignable equipment set according to the extra-demand memory by using a preset equipartition algorithm, wherein:
when the storage expansion of the equipartition algorithm fails, acquiring user information of the stirring equipment to be expanded, and carrying out storage expansion on the allocatable equipment set according to the user information by utilizing a preset frequency allocation algorithm;
When the frequency allocation algorithm fails to perform storage expansion, acquiring the wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by utilizing a preset signal allocation algorithm.
In particular, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of the drawings, which is not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device 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 present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
Acquiring the number of devices of an Internet of things device set and the device memory of each Internet of things device in the Internet of things device set in a preset network domain, and screening the Internet of things devices in the Internet of things device set according to the number of the devices and the device memory to obtain an available device set;
when the available equipment set is not an empty set, judging whether the residual memory of the stirring equipment to be stored is larger than a preset required memory or not;
when the residual memory of the stirring equipment to be expanded is larger than the required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending data storage expansion;
when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
calculating the allocated memory of each Internet of things device in the available device set according to the used memory and the device memory, and screening the Internet of things devices in the available device set according to the allocated memory to obtain an allocable device set;
performing storage expansion on the assignable equipment set according to the extra-demand memory by using a preset equipartition algorithm;
When the storage expansion of the equipartition algorithm fails, acquiring user information of the stirring equipment to be expanded, and carrying out storage expansion on the allocatable equipment set according to the user information by utilizing a preset frequency allocation algorithm;
when the frequency allocation algorithm fails to perform storage expansion, acquiring the wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by utilizing a preset signal allocation algorithm.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
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 invention 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. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. 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 invention and not for limiting the same, and although the present invention 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 invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (10)

1. The data storage expansion method based on the Internet of things is characterized by comprising the following steps of:
acquiring the number of devices of an Internet of things device set and the device memory of each Internet of things device in the Internet of things device set in a preset network domain, and screening the Internet of things devices in the Internet of things device set according to the number of the devices and the device memory to obtain an available device set;
when the available equipment set is not an empty set, judging whether the residual memory of the stirring equipment to be stored is larger than a preset required memory or not;
When the residual memory of the stirring equipment to be expanded is larger than the required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending data storage expansion;
when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
calculating the allocated memory of each Internet of things device in the available device set according to the used memory and the device memory, and screening the Internet of things devices in the available device set according to the allocated memory to obtain an allocable device set;
and storing and expanding the assignable equipment set according to the extra-demand memory by using a preset equipartition algorithm, wherein: when the storage expansion of the equipartition algorithm fails, acquiring user information of the stirring equipment to be expanded, and carrying out storage expansion on the allocatable equipment set according to the user information by utilizing a preset frequency allocation algorithm; when the frequency allocation algorithm fails to perform storage expansion, acquiring the wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by utilizing a preset signal allocation algorithm.
2. The method for expanding data storage based on the internet of things according to claim 1, wherein the screening the internet of things devices in the internet of things device set according to the number of devices and the device memory to obtain the available device set comprises:
judging whether the number of the devices is larger than a preset number threshold;
when the number of the devices is larger than the number threshold, selecting one of the Internet of things devices in the Internet of things device set one by one as a target device, and judging whether the device memory of the target device is larger than a preset memory threshold; when the device memory of the target device is greater than the memory threshold, adding the target device to the set of available devices; returning to the step of selecting one internet of things device in the internet of things device set one by one as a target device when the device memory of the target device is smaller than or equal to the memory threshold;
when the number of devices is less than or equal to the number threshold, the set of available devices is set to an empty set.
3. The method for expanding data storage based on the internet of things according to claim 1, wherein the calculating the allocated memory of each internet of things device in the set of available devices according to the used memory and the device memory comprises:
One internet of things device in the available device set is selected one by one to serve as a device to be distributed;
subtracting the used memory of the equipment to be allocated from the equipment memory of the equipment to be allocated to obtain the spare memory of the equipment to be allocated;
dividing the spare memory by a preset distribution coefficient to obtain the distribution memory of the equipment to be distributed.
4. The method for expanding data storage based on the internet of things according to claim 1, wherein the step of obtaining the user information of the stirring device to be expanded comprises the steps of:
processing the fingerprint component and the voiceprint component of the stirring equipment to be stored by a preset double identification algorithm to obtain the user name of the user;
inquiring in a database of the stirring equipment to be stored in a expanding manner according to the user name to obtain the frequency of use, the recording gear, the recording rotating speed and the stirring time length corresponding to the user name;
and integrating the user name, the frequency of use, the recording gear, the recording rotating speed and the stirring time length into the user information.
5. The method for expanding data storage based on the internet of things according to claim 4, wherein the storing and expanding the set of allocable devices according to the user information by using a preset frequency allocation algorithm comprises:
Extracting the frequency of use, the recording gear, the recording rotating speed and the stirring time from the user information;
calculating a maximum storage capacity according to the use frequency, the recording gear, the recording rotating speed and the stirring time length by using a frequency distribution algorithm of the following formula (1):
formula (1)
In the formula (1), d refers to the maximum storage capacity, ceiling is an upward rounding symbol, q refers to the use frequency, g refers to the recording gear, β is a preset gear coefficient, p refers to the recording rotation speed, h refers to the stirring time period, α is a preset frequency coefficient, R is a preset capacity coefficient, and γ is a preset stirring coefficient;
and selecting the Internet of things equipment with the allocation memory matched with the maximum storage capacity from the allocable equipment set as target expansion equipment, and taking the spare storage space of the target expansion equipment as the expansion memory of the stirring equipment to be expanded.
6. The method for expanding data storage based on the internet of things according to claim 1, wherein the obtaining the wireless type of the assignable device set comprises:
one internet of things device in the assignable device set is selected one by one to serve as a target wireless device;
Acquiring a unit power spectrum of the target wireless equipment, and acquiring a power peak sequence and a power peak sequence from the unit power spectrum;
extracting target edge characteristics from the unit power spectrum, and normalizing the target edge characteristics to obtain a target edge code;
calculating the matching distance between the unit power spectrum and various wireless spectrums in a preset wireless power spectrum library according to the target edge code, the power edge sequence and the power edge sequence by using a spectrum distance algorithm as shown in the following formula (2):
formula (2)
In the formula (2), Y refers to the matching distance, V refers to the target spike code, V refers to the spike code of the wireless spectrum, i refers to the ith bit, m is the total spike bit number of the power spike sequence of the unit power spectrum, A i Refers to the power spike of the ith bit in the power spike sequence of the unit power spectrum, A refers to the power spike sequence of the unit power spectrum, a i Refers to the ith power peak in the power peak sequence of the wireless spectrum, a refers to the power peak sequence of the wireless spectrum, B i Refers to the power of the unit power spectrum The power peak frequency of the ith bit in the peak frequency sequence, B refers to the power peak frequency sequence of the unit power spectrum, B i The power peak frequency of the ith position in the power peak frequency sequence of the wireless spectrum is referred to, and b refers to the power peak frequency sequence of the wireless spectrum;
and selecting the signal type of the corresponding wireless map when the value of the matching distance is minimum as the wireless type of the target wireless device.
7. The method for expanding data storage based on the internet of things according to claim 1, wherein the storing and expanding the set of allocable devices according to the wireless type by using a preset signal allocation algorithm comprises:
ordering the internet of things equipment in the allocable equipment set according to the signal intensity of the wireless type from strong to weak to obtain an allocable equipment sequence;
selecting the Internet of things equipment from the assignable equipment sequence one by one according to the sequence from the small sequence number to the large sequence number as target signal equipment;
and selecting a memory area with the same memory size as the classified memory of the target signal equipment from the spare memory space of the target signal equipment as an expansion memory of the stirring equipment to be expanded.
8. Data storage expansion device based on thing networking, its characterized in that, the device includes:
The device screening module is used for acquiring the number of devices of the Internet of things device set in a preset network domain and the device memory of each Internet of things device in the Internet of things device set, and screening the Internet of things devices in the Internet of things device set according to the number of the devices and the device memory to obtain an available device set;
the required storage calculation module is used for judging whether the residual memory of the stirring equipment to be stored is larger than a preset required memory when the available equipment set is not an empty set; when the residual memory of the stirring equipment to be expanded is larger than the required memory, determining that the memory of the stirring equipment to be expanded is sufficient, and ending data storage expansion; when the residual memory of the stirring equipment to be stored is smaller than or equal to the required memory, calculating the additional required memory of the stirring equipment to be stored, and acquiring the used memory of each Internet of things equipment in the available equipment set;
the expansion screening module is used for calculating the distribution memory of each piece of internet of things equipment in the available equipment set according to the used memory and the equipment memory, and screening the internet of things equipment in the available equipment set according to the distribution memory to obtain an allocable equipment set;
The memory expansion decision module is used for utilizing a preset equipartition algorithm to store and expand the assignable equipment set according to the extra-demand memory, wherein:
when the storage expansion of the equipartition algorithm fails, acquiring user information of the stirring equipment to be expanded, and carrying out storage expansion on the allocatable equipment set according to the user information by utilizing a preset frequency allocation algorithm;
when the frequency allocation algorithm fails to perform storage expansion, acquiring the wireless type of the allocable equipment set, and performing storage expansion on the allocable equipment set according to the wireless type by utilizing a preset signal allocation algorithm.
9. An electronic device, the electronic device comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the internet of things-based data storage expansion method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the data storage expansion method based on the internet of things according to any one of claims 1 to 7.
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104052770A (en) * 2013-03-13 2014-09-17 鸿富锦精密工业（深圳）有限公司 Storage space expansion system and method
CN116048643A (en) * 2023-03-08 2023-05-02 苏州浪潮智能科技有限公司 Equipment operation method, system, device, storage medium and electronic equipment

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8122421B2 (en) * 2008-08-14 2012-02-21 Omnivision Technologies, Inc. System, and method, and computer readable medium for designing a scalable clustered storage integrated circuit for multi-media processing
US10768820B2 (en) * 2017-11-16 2020-09-08 Samsung Electronics Co., Ltd. On-demand storage provisioning using distributed and virtual namespace management

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104052770A (en) * 2013-03-13 2014-09-17 鸿富锦精密工业（深圳）有限公司 Storage space expansion system and method
CN116048643A (en) * 2023-03-08 2023-05-02 苏州浪潮智能科技有限公司 Equipment operation method, system, device, storage medium and electronic equipment

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
去中心化云存储网络的存储任务分配算法;申圳等;计算机科学;全文 *

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