CN114189756A - Information updating method, device, equipment and medium for multi-equipment cooperative Internet of things - Google Patents
Information updating method, device, equipment and medium for multi-equipment cooperative Internet of things Download PDFInfo
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Abstract
The application provides an information updating method, device, equipment and medium for a multi-equipment cooperative Internet of things, which comprises the following steps: establishing an information updating system model of a multi-device cooperation Internet of things, wherein the multi-device cooperation Internet of things comprises an edge server and a plurality of associated Internet of things devices; acquiring AoI of each internet of things device, and acquiring AoI of the information updating system model according to each device AoI; constructing a system objective function corresponding to the system AoI; determining AoI updating strategies of the system and data acquisition strategies of the IOT equipment according to the system objective function; and updating information according to the updating strategy of the system AoI and the data acquisition strategy of the Internet of things equipment. Compared with the prior art, the method and the device solve the problem of minimum information freshness of the IOT system for communication scheduling and calculation task unloading of the multiple devices and calculation resource allocation of the edge server, and can effectively improve the information updating efficiency of multi-device cooperation.
Description
Technical Field
The application relates to the technical field of internet of things, in particular to an information updating method, device, equipment and storage medium for a multi-equipment cooperative internet of things.
Background
With the continuous expansion of the deployment range of the 5G commercial network, the development of the Internet of things enters a new development stage. The relevant reports show that by 2023 there will be 147 billion internet devices around the world, and on average there will be 1.8 internet of things devices per person around the world. By 2026, 269 billion internet devices were accessed. Accompanying the access of mass devices is the processing of mass data. For B5G and 6G, in order to meet more complex service requirements, different types of devices in the internet of things need to cooperatively perform environment sensing and data acquisition, and meanwhile, in order to ensure timeliness of data, data needs to be transmitted and processed at the first time after data acquisition, so that effective information in the data is obtained. For example, in a remote plant control system, a control center of a plant needs to jointly make an industrial command according to a plurality of sensors such as temperature, vibration, and a video probe on a production line of industrial equipment. In the internet of vehicles, the device information and road monitoring information of a plurality of vehicles need to be simultaneously transmitted to roadside processing data nodes to judge whether the vehicles can safely run, and particularly, higher requirements on data collection and processing time are put forward for the control of automatic driving vehicles. In the process from the generation of data to the final data processing, the wireless link transmission and the data processing of the data are included, and how the transmission and the processing of different data are coordinated directly influences the instantaneity and the accuracy of the final system decision.
The measurement of information transmission efficiency in the traditional network is often characterized by adopting a transmission delay index, and the delay in the communication network can be subdivided into a plurality of delays such as transmission delay, queuing delay, data processing delay and the like. However, considering the information generation process, the time delay after the information generation alone cannot fully measure the effectiveness of the information. Therefore, the Information freshness (AoI) is used as an index of the Information timeliness in the equipment of the Internet of things. AoI is defined as the time consumed from the collection of the latest information data packet such as environment from the sensor source node to the processing of the data by the server node to obtain the information, and the connotation is more significant than the traditional communication delay from the target end. For example, at the information acquisition node, AoI may reflect the impact of a data update policy, and a lower update frequency may preserve device buffer queue length, but may result in AoI being larger, with less information timeliness, and therefore a larger time difference between updates. AoI, a queue model is generally adopted, when the arrival of service data and data processing are distributed according to a specific manner, the system can be in a stable state, however, in consideration of the distribution characteristic of the service in a certain time period in an actual system, the distribution characteristic is often limited by the current network state and the data processing capacity, and therefore, the actual scheduling problem of data transmission needs to be considered under the condition of long-time statistical characteristic optimization. Under the conditions that the performance of a device processor is continuously enhanced and a data processing algorithm is continuously developed, the data processing capacity of the terminal device is greatly improved, and the device can process data in advance by depending on the processor before transmitting the data, so that the data processing efficiency is improved. Meanwhile, in the process of processing data by the equipment, the equipment can split and send the data to the edge processing terminal for processing the data, so that the flexible data processing capability can avoid the stagnation of data processing when the network is unavailable. In order to meet the objective of optimization AoI, joint optimization of the calculation offload policy of users in multiple timeslots and the transmission communication resources is a key method for improving system performance under the non-statistical distribution characteristic.
Currently, the optimization for AoI is mainly focused on a scenario of joint optimization of data acquisition and transmission, and the research target is often independent AoI of multiple sensor devices in a network, which makes it difficult to optimize AoI when multiple sensor devices cooperate.
Disclosure of Invention
The embodiment of the invention provides an information updating method, device, equipment and medium for a multi-equipment cooperation Internet of things, which are used for solving the problem of information updating of the multi-equipment cooperation Internet of things.
Therefore, a first aspect of the present application provides an information updating method for a multi-device cooperation internet of things, including:
establishing an information updating system model of a multi-device cooperation Internet of things, wherein the multi-device cooperation Internet of things comprises an edge server and a plurality of associated Internet of things devices;
acquiring AoI of each internet of things device, and acquiring AoI of the information updating system model according to each device AoI;
constructing a system objective function corresponding to the system AoI, wherein the system objective function is used for solving the minimum value of the system peak value AoI under various constraints;
determining AoI updating strategies of the system and data acquisition strategies of the IOT equipment according to the system objective function;
and updating information according to the updating strategy of the system AoI and the data acquisition strategy of the Internet of things equipment.
In a possible implementation manner, in the foregoing method provided by the present application, the determining an update policy of the system AoI and a data acquisition policy of the internet of things device according to the system objective function includes:
converting the system objective function into a solvable parameter optimization problem by using a pre-established system AoI optimization model;
and solving the parameter optimization problem by using a preset iterative algorithm to obtain a solution result, wherein the solution result is the update strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
In one possible implementation, in the above method provided by this application, the optimization process of the system AoI on the system objective function by the optimization model is as follows:
taking the system objective function as an original problem P1;
converting the original problem P1 into a problem P2 of a maximum system AoI which is averaged in a plurality of scheduling periods;
the problem P3 is obtained by taking the reduction of the scheduling period required by the Internet of things equipment which completes data processing finally as a target;
problem P3 is transformed into problem P4 by the substitution of variables, the property of a pseudo-convex function, and the property of an integer function.
In a possible implementation manner, in the foregoing method provided by the present application, the system objective function is a MIN-MAX function; the problem P4 is as follows:
wherein alpha represents an unloading decision variable of the equipment of the Internet of things, beta represents a calculation resource distribution coefficient of the edge server to the equipment of the Internet of things, omega represents a bandwidth distribution factor of the equipment of the Internet of things, and c represents a bandwidth distribution factor of the equipment of the Internet of thingsbsRepresenting computing resources of an edge server, t1、t2、t3In order to convert the problem P3 into auxiliary variables introduced by the problem P4, the constraints C1 to C6, C7b and C8b respectively limit resources in the multi-device cooperative Internet of things.
In a possible implementation manner, in the method provided by the present application, the preset iterative algorithm is a greedy algorithm.
The second aspect of the present application provides an information updating apparatus for a multi-device cooperation internet of things, including:
the system comprises an establishing module, a judging module and a judging module, wherein the establishing module is used for establishing an information updating system model of a multi-device cooperation Internet of things, and the multi-device cooperation Internet of things comprises an edge server and a plurality of associated Internet of things devices;
an obtaining module, configured to obtain a device AoI of each internet of things device, and obtain a system AoI of the information updating system model according to each device AoI;
a building module, configured to build a system objective function corresponding to the system AoI, where the system objective function is used to find a minimum value of the system peak AoI under multiple constraints;
the determining module is used for determining an updating strategy of the system AoI and a data acquisition strategy of the internet of things equipment according to the system objective function;
and the updating module is used for updating information according to the updating strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
In a possible implementation manner, in the apparatus provided in the present application, the determining module is specifically configured to:
converting the system objective function into a solvable parameter optimization problem by using a pre-established system AoI optimization model;
and solving the parameter optimization problem by using a preset iterative algorithm to obtain a solution result, wherein the solution result is the update strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
In a possible implementation manner, in the apparatus provided in the present application, the preset iterative algorithm is a greedy algorithm.
A third aspect of the present application provides an electronic device comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the computer program when executing the computer program to perform the method of the first aspect of the application.
A fourth aspect of the present application provides a computer readable storage medium having computer readable instructions stored thereon which are executable by a processor to implement the method of the first aspect of the present application.
The beneficial effect of this application is as follows:
the information updating method, the device, the equipment and the medium for the multi-equipment cooperation Internet of things establish an information updating system model of the multi-equipment cooperation Internet of things, wherein the multi-equipment cooperation Internet of things comprises an edge server and a plurality of associated Internet of things equipment; acquiring AoI of each internet of things device, and acquiring AoI of the information updating system model according to each device AoI; constructing a system objective function corresponding to the system AoI, wherein the system objective function is used for solving the minimum value of the system peak value AoI under various constraints; determining AoI updating strategies of the system and data acquisition strategies of the IOT equipment according to the system objective function; and updating information according to the updating strategy of the system AoI and the data acquisition strategy of the Internet of things equipment. Compared with the prior art, the method and the device solve the problem of minimum information freshness of the Internet of things system for communication scheduling and calculation task unloading of the combined device and calculation resource allocation of the edge server in the Internet of things with multiple device cooperation, and can effectively improve the information updating efficiency of the multiple device cooperation.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating preferred embodiments and are not to be construed as limiting the application. Also, like reference numerals are used to denote like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart of an information updating method of a multi-device cooperative internet of things provided by the present application;
fig. 2 is an architecture diagram of a multi-device cooperative internet of things provided by the present application;
FIG. 3 is a process diagram for iteratively solving a problem P4 using a greedy algorithm as provided herein;
fig. 4 is a schematic diagram of an information updating apparatus of a multi-device cooperation internet of things provided by the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the application provides an information updating method, an information updating device, equipment and a storage medium for a multi-equipment cooperative internet of things, and the following description is given with reference to the accompanying drawings.
Referring to fig. 1, which shows a flowchart of an information updating method for a multi-device cooperative internet of things provided in the present application, as shown in fig. 1, the method may include the following steps S101 to S105:
s101, establishing an information updating system model of a multi-device cooperation Internet of things, wherein the multi-device cooperation Internet of things comprises an edge server and a plurality of associated Internet of things devices;
fig. 2 is a diagram illustrating an architecture of a multi-device cooperative internet of things provided in the present application, and as shown in fig. 2, the internet of things includes a plurality of internet of things devices and an edge server disposed near a base station, and the internet of things devices are in communication connection with the base station and the edge server through an internet of things information transmission link.
S102, obtaining AoI of each Internet of things device, and obtaining a system AoI of the information updating system model according to each device AoI;
s103, constructing a system objective function corresponding to the system AoI, wherein the system objective function is used for solving the minimum value of a system peak value AoI under various constraints;
s104, determining AoI updating strategies of the system and data acquisition strategies of the Internet of things equipment according to the system objective function;
s105, updating information according to the updating strategy of the system AoI and the data acquisition strategy of the Internet of things equipment.
In the information updating method for a multi-device cooperative internet of things provided in the embodiment of the present application, step S104 may be implemented as:
converting the system objective function into a solvable parameter optimization problem by using a pre-established system AoI optimization model;
and solving the parameter optimization problem by using a preset iterative algorithm to obtain a solution result, wherein the solution result is the update strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
In the information updating method for the multi-device cooperative internet of things provided by the embodiment of the application, the optimization process of the system AoI optimization model on the system objective function is as follows:
taking the system objective function as an original problem P1;
converting the original problem P1 into a problem P2 of a maximum system AoI which is averaged in a plurality of scheduling periods;
the problem P3 is obtained by taking the reduction of the scheduling period required by the Internet of things equipment which completes data processing finally as a target;
problem P3 is transformed into problem P4 by the substitution of variables, the property of a pseudo-convex function, and the property of an integer function.
The optimization process of the system AoI optimization model to the system objective function is described in detail below based on the multi-device cooperation internet of things shown in fig. 2.
The objective of the present application is to optimize the system AoI in the multi-device collaborative internet of things, so as to obtain the update policy of the system AoI and the data acquisition policy of the internet of things devices, such as smart sensors. As shown in fig. 2, the safety alarm system composed of a ground base station and a plurality of internet of things devices is constructed, and information timeliness problems in data acquisition and processing processes are analyzed. In an OFDM (orthogonal frequency division multiplexing) access mode, in which there are N internet of things devices that need status update, it is assumed that information collected by IoT N ∈ {1,2, 3.. and N } is represented as a binary set (d) of information amount and calculation amountn,τn) Because the data volume collected by different internet of things devices is different. Generally, the larger the amount of data, the more computing resources that need to be consumed for information processing, and assuming that the data and the computing amount are positively linearly correlated, the correlation coefficient is λn. Each Internet of things device has information processing capacity of cnMeanwhile, the base station side is deployed with the processing capacity of cbsFor accelerating data processing. In this embodiment, the device unload decision variable is defined as αn∈[0,1]. In the long-time information acquisition process, the recently acquired data is processed after the last information processing is completed by the internet of things equipment each time.
Defining uplink rate of each internet of things device as RnThen, it is calculated by the following formula:
wherein σ2The noise power of a receiving end is B, and the total bandwidth shared by all the Internet of things equipment is omeganThe bandwidth allocation factor of the internet of things equipment is expressed. For the internet of things equipment n, the data size is dnData packet, needs to occupy
The transmission is completed for one scheduling period.
The bandwidth allocation factors of all the internet of things devices are not more than 1 in sum. Therefore, the task that the device of the internet of things needs to calculate locally needs to occupy the scheduling period of
Meanwhile, assuming that the edge server has parallel processing capability, the calculation resource which can be distributed to each internet of things device is defined as betancbsThen the edge server processing delay can be calculated as
To ensure that computing resources do not exceed edge server load, constraints are defined
Assume a scheduling period initial time of t0Scheduling period of Δ tms, definition
And if the calculation task at the current moment is 0, the data processing is finished, and at the current scheduling period, the Internet of things equipment generates a new data packet.
defining the associated internet of things device AoI covered by the same information collection center, namely the base station and the matched information processing device, as A (t)j) When the data of different internet of things devices in the same scheduling cycle are processed, the data can be updated AoI, and the updated AoI is determined by the earliest generated data packet in the previous scheduling cycle. Therefore, in this embodiment, the scheduling time when each piece of internet-of-things equipment is periodically updated is defined as
Ai(tj) System AoI representing the ith update cycle:
the system peak AoI can effectively measure the worst performance of the internet of things system, so the peak AoI of the optimized cell can be considered to define AjFor the jth maximum value of AoI, the following optimization problem is established to optimize the information updating strategy, defined as problem P1:
constraints C1-C5 are all linear constraints that respectively limit the resources in the system. Wherein, the constraint C1 is a limit on the proportion of the data volume needing to be unloaded, and C2-C3 limits the uplink bandwidth allocation resource. C4 and C5 limit the allocation of server computing resources.
Considering that the peak value AoI in the problem P1 is actually affected by the device information updating policy and the device computation offloading policy and the communication computation resource allocation policy in each scheduling cycle, the problem is tightly coupled and cannot be directly solved, so that the long-time optimization problem needs to be refined to several scheduling cycles. The original problem is converted into the problem P2 of averaging the maximum AoI in T scheduling periods as follows:
when the weighted average is obtained for the multiple peak values AoI, considering that in a single scheduling period, each scheduling decision is able to process the current data in the minimum scheduling period, and because of the correlation between devices, as can be seen from equation (3), when the data in the current data period of an internet of things device is not processed, AoI of the system is continuously increased, so the embodiment considers reducing the scheduling period required by the device which finally completes data processing, and obtains the problem P3 as follows:
the difficulty of observing the problem P3 mainly exists in the objective function Obj1, because the constraints are linear functions, and the objective function includes the max function and the rounding function, which belong to discontinuous non-convex functions. Considering the use of DQCP in CVXPY to solve the optimization problem, it is necessary to convert problem P3, considering
Rewrite the objective function to Obj 2:
in order to further separate the MAX function in the objective function, considering that the MIN-MAX function is optimized for the worst case of the problem in the system, the converted objective function value Obj2 needs to be larger than the original objective function, and therefore, the objective function value Obj2 needs to be satisfied
Obj1≤Obj2And in accordance with the following inequality,
converting the original objective function into Obj 2:
further consider that
Therefore, the original problem is subjected to variable substitution and constraints C6, C7, C8:
at this time, the original objective function becomes Obj 3:
by using the characteristics of the rounding function, equation (7) is converted into:
for the constraint C7-C8, the convex constraint C7b can be obtained by combining Taylor expansion formula after two sides simultaneously take logarithm:
with the same properties, the C8 constraint was also processed, resulting in C8b:
at this point, the original problem P3 has been transformed into problem P4:
problem P4 is a pseudo-convex planning problem, analyzed as follows:
the rounding function on the outer layer in the target function is a quasi-convex function, and t1-t2-t3And | is a convex function, according to the DCP (partitioned connected conditional mapping) principle, the complex function of the convex problem can be identified by a convex optimization tool package only if a certain condition is met, and the target function can be a quasi-convex function. The constraint conditions are all convex sets, so the whole problem can be solved by means of a convex optimization tool bag CVXPY (continuous variable property X ray)The function uses a two-term search, while the interior needs to be iterated over a loop.
The process of solving the system AoI updating strategy and the internet of things equipment data acquisition strategy according to the problem P4 is as follows:
for the problem P1, the embodiment depends on the solution result of the problem P4, and a greedy algorithm is adopted, so that the data processing delay of the internet of things device is minimized in each information acquisition cycle, and whether the scheduling policy is updated or not is considered in each scheduling cycle by updating the system AoI. In formula (3)
The calculation formula is as follows:
wherein:
the data acquisition strategy of the internet of things device in the embodiment is as follows: when in use
In time, new data is collected.
Fig. 3 shows a process of iteratively solving the problem P4 by using a greedy algorithm, which specifically includes the following steps:
s201, establishing a greedy algorithm simulation model, and inputting a basic simulation parameter pul,B,hul,d,λ,cn,cbs,δ；
S202, initializing equipment AoI to be 0, and initializing system AoI to be 0;
s203, giving an initial value alpha of the unloading ratio(t),v(t),β(t)Solving the scheduling selection sub-problem;
s204, fixing alpha, and solving the optimization problem of local AoI; the iterative formula is as follows:
s205, judging whether convergence is achieved, if not, jumping to S203, and if so, jumping to S206, wherein the judgment conditions are as follows:
s206, outputting the optimal strategy { t } of the current information updating period1,t2,t3}(itr)＝{t1,t2,t3}*；
S207, checking the residual tasks of the equipment, and updating the equipment AoI and the system AoI;
s208, judging whether the system AoI is lowered, if not, skipping to S206, and if so, skipping to S209;
and S209, updating the equipment information and the scheduling strategy.
The updating of the scheduling strategy refers to re-executing the above algorithm, and if the resource allocation parameter calculated by the algorithm is changed, the resource is re-allocated; if the resource allocation parameters output by the algorithm are not changed, the original resource allocation strategy is still executed.
In the information updating method of the multi-device cooperative internet of things in the embodiment of the application, a system objective function is established; converting a system objective function into a solvable parameter optimization problem through variable substitution, a quasi-convex function property and an integer function property; calculating optimal scheduling parameters through an iterative algorithm for information updating time, user data unloading and transmission decisions and edge server computing resource allocation involved in an information updating process in the multi-device cooperative Internet of things; the device AoI and the system AoI under the resource allocation policy are calculated to determine whether the resource scheduling policy needs to be updated.
The information updating method of the multi-device cooperation internet of things in the embodiment of the application comprises wireless communication resource allocation, device and server computing resource allocation and device data segmentation joint scheduling optimization during acquisition and processing of the multi-device cooperation information, and further comprises an information updating strategy during cooperation of the multiple devices.
The information freshness of cooperation of a plurality of devices is considered, and the method is different from the existing single-device information freshness priority resource allocation strategy. The cooperative scheduling of communication and computing resources is considered, which is different from the existing scheduling of communication resources; and a delay strategy during equipment information updating is also considered, and an information updating strategy is improved.
In the foregoing embodiment, an information updating method of a multi-device cooperation internet of things is provided, and correspondingly, an information updating device of a multi-device cooperation internet of things is also provided in the present application.
As shown in fig. 4, an information updating apparatus 10 of a multi-device cooperative internet of things provided by the present application includes:
the establishing module 101 is configured to establish an information updating system model of a multi-device cooperation internet of things, where the multi-device cooperation internet of things includes an edge server and multiple associated internet of things devices;
an obtaining module 102, configured to obtain a device AoI of each internet of things device, and obtain a system AoI of the information updating system model according to each device AoI;
a building module 103, configured to build a system objective function corresponding to the system AoI, where the system objective function is used to find a minimum value of the system peak AoI under multiple constraints;
a determining module 104, configured to determine, according to the system objective function, an update policy of the system AoI and a data acquisition policy of the internet of things device;
the updating module 105 is configured to update information according to the updating policy of the system AoI and the data acquisition policy of the internet of things device.
In some embodiments of the present application, the determining module 104 is specifically configured to:
converting the system objective function into a solvable parameter optimization problem by using a pre-established system AoI optimization model;
and solving the parameter optimization problem by using a preset iterative algorithm to obtain a solution result, wherein the solution result is the update strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
Specifically, the optimization process of the system AoI optimization model on the system objective function is as follows:
taking the system objective function as an original problem P1;
converting the original problem P1 into a problem P2 of a maximum system AoI which is averaged in a plurality of scheduling periods;
the problem P3 is obtained by taking the reduction of the scheduling period required by the Internet of things equipment which completes data processing finally as a target;
problem P3 is transformed into problem P4 by the substitution of variables, the property of a pseudo-convex function, and the property of an integer function.
Specifically, the system objective function is a MIN-MAX function; the problem P4 is as follows:
the constraints C1 to C6, C7b and C8b respectively limit resources in the multi-device cooperation Internet of things.
In some embodiments of the present application, the preset iterative algorithm is a greedy algorithm.
The information updating device of the multi-device cooperation internet of things provided by the embodiment of the application and the information updating method of the multi-device cooperation internet of things provided by the embodiment of the application are based on the same inventive concept and have the same beneficial effects.
The embodiment of the present application further provides an electronic device corresponding to the information updating method of the multi-device cooperative internet of things provided in the foregoing embodiment, where the electronic device includes: the information updating method of the multi-device cooperative Internet of things comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program when running the computer program so as to realize the information updating method of the multi-device cooperative Internet of things. The electronic device can be a mobile phone, a notebook computer, a tablet computer, a desktop computer and the like.
The present application further provides a computer-readable storage medium, such as an optical disc, a usb disc, etc., corresponding to the information updating method for a multi-device cooperation internet of things provided in the foregoing embodiments, where a computer program (i.e., a program product) is stored on the storage medium, and when the computer program is executed by a processor, the computer program performs the information updating method for a multi-device cooperation internet of things provided in any foregoing embodiments.
It should be noted that examples of the computer-readable storage medium may also 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 optical and magnetic storage media, which are not described in detail herein.
The above description is only for the preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. An information updating method for a multi-device cooperation Internet of things is characterized by comprising the following steps:
establishing an information updating system model of a multi-device cooperation Internet of things, wherein the multi-device cooperation Internet of things comprises an edge server and a plurality of associated Internet of things devices;
acquiring AoI of each internet of things device, and acquiring AoI of the information updating system model according to each device AoI;
constructing a system objective function corresponding to the system AoI, wherein the system objective function is used for solving the minimum value of the system peak value AoI under various constraints;
determining AoI updating strategies of the system and data acquisition strategies of the IOT equipment according to the system objective function;
and updating information according to the updating strategy of the system AoI and the data acquisition strategy of the Internet of things equipment.
2. The information updating method of the multi-device cooperative internet of things as claimed in claim 1, wherein the determining AoI updating policy and the data collection policy of the internet of things device according to the system objective function comprises:
converting the system objective function into a solvable parameter optimization problem by using a pre-established system AoI optimization model;
and solving the parameter optimization problem by using a preset iterative algorithm to obtain a solution result, wherein the solution result is the update strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
3. The information updating method of the multi-device cooperative internet of things as claimed in claim 2, wherein the optimization process of the system AoI optimization model on the system objective function is as follows:
taking the system objective function as an original problem P1;
converting the original problem P1 into a problem P2 of a maximum system AoI which is averaged in a plurality of scheduling periods;
the problem P3 is obtained by taking the reduction of the scheduling period required by the Internet of things equipment which completes data processing finally as a target;
problem P3 is transformed into problem P4 by the substitution of variables, the property of a pseudo-convex function, and the property of an integer function.
4. The information updating method of the multi-device cooperative internet of things as claimed in claim 3, wherein the system objective function is a MIN-MAX function; the problem P4 is as follows:
P4：
s.t.C1:0≤αn≤1
C2:βn≥0
C4:ωn≥0
wherein alpha represents an unloading decision variable of the equipment of the Internet of things, beta represents a calculation resource distribution coefficient of the edge server to the equipment of the Internet of things, omega represents a bandwidth distribution factor of the equipment of the Internet of things, and c represents a bandwidth distribution factor of the equipment of the Internet of thingsbsRepresenting computing resources of an edge server, t1、t2、t3In order to convert the problem P3 into auxiliary variables introduced by the problem P4, the constraints C1 to C6, C7b and C8b respectively limit resources in the multi-device cooperative Internet of things.
5. The information updating method of the multi-device cooperative internet of things as claimed in claim 2, wherein the preset iterative algorithm is a greedy algorithm.
6. The utility model provides an information updating device of thing networking is collaborated to multi-equipment which characterized in that includes:
the system comprises an establishing module, a judging module and a judging module, wherein the establishing module is used for establishing an information updating system model of a multi-device cooperation Internet of things, and the multi-device cooperation Internet of things comprises an edge server and a plurality of associated Internet of things devices;
an obtaining module, configured to obtain a device AoI of each internet of things device, and obtain a system AoI of the information updating system model according to each device AoI;
a building module, configured to build a system objective function corresponding to the system AoI, where the system objective function is used to find a minimum value of the system peak AoI under multiple constraints;
the determining module is used for determining an updating strategy of the system AoI and a data acquisition strategy of the internet of things equipment according to the system objective function;
and the updating module is used for updating information according to the updating strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
7. The information updating apparatus of the internet of things with multi-device cooperation according to claim 6, wherein the determining module is specifically configured to:
converting the system objective function into a solvable parameter optimization problem by using a pre-established system AoI optimization model;
and solving the parameter optimization problem by using a preset iterative algorithm to obtain a solution result, wherein the solution result is the update strategy of the system AoI and the data acquisition strategy of the internet of things equipment.
8. The information updating apparatus of the multi-device cooperative internet of things as claimed in claim 7, wherein the preset iterative algorithm is a greedy algorithm.
9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor executes when executing the computer program to implement the method according to any of claims 1 to 5.
10. A computer-readable storage medium having computer-readable instructions stored thereon, the computer-readable instructions being executable by a processor to implement the method of any one of claims 1 to 5.
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