CN113811007A - Method and device for scheduling equipment and allocating resources, electronic equipment and storage medium - Google Patents

Method and device for scheduling equipment and allocating resources, electronic equipment and storage medium Download PDF

Info

Publication number
CN113811007A
CN113811007A CN202111007418.1A CN202111007418A CN113811007A CN 113811007 A CN113811007 A CN 113811007A CN 202111007418 A CN202111007418 A CN 202111007418A CN 113811007 A CN113811007 A CN 113811007A
Authority
CN
China
Prior art keywords
information
scheduling
equipment
time slot
resource allocation
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111007418.1A
Other languages
Chinese (zh)
Other versions
CN113811007B (en
Inventor
王莹
赵俊伟
费子轩
王雪
张秋阳
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing University of Posts and Telecommunications
Original Assignee
Beijing University of Posts and Telecommunications
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing University of Posts and Telecommunications filed Critical Beijing University of Posts and Telecommunications
Priority to CN202111007418.1A priority Critical patent/CN113811007B/en
Publication of CN113811007A publication Critical patent/CN113811007A/en
Application granted granted Critical
Publication of CN113811007B publication Critical patent/CN113811007B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • 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
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention provides a method and a device for scheduling equipment and allocating resources, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring equipment information, transmission information and computing resources of a wireless monitoring system; determining an optimization problem of equipment scheduling and resource allocation of the wireless monitoring system based on the equipment information, the transmission information and the computing resources; and solving the determined optimization problem of the equipment scheduling and the resource allocation so as to determine the equipment scheduling and resource allocation information of the wireless monitoring system. According to the method provided by the invention, the total information age of the wireless monitoring system in a monitoring period is minimized by jointly optimizing the equipment information, the transmission information and the allocation of computing resources, and the timeliness of the equipment state information in the wireless monitoring system is improved.

Description

Method and device for scheduling equipment and allocating resources, electronic equipment and storage medium
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for device scheduling and resource allocation, an electronic device, and a storage medium.
Background
With the continuous application of the Internet of Things in an Industrial communication system, an Industrial Internet of Things (IIoT) provides a customized architecture and a standardized interface for the acquisition and transmission of Industrial system data, and by continuously acquiring and processing Industrial equipment state information in the production practice of the Industrial system, the Industrial application can realize equipment state monitoring, production process optimization, platform safety management and the like. Taking an industrial equipment monitoring application as an example, each industrial equipment generates 20-100MB of data per second for real-time monitoring of equipment status. However, such huge data volume provides a huge challenge for the wireless monitoring system of the industrial internet equipment, and due to the fact that wireless communication resources and computing resources are limited, simultaneous transmission of a large amount of equipment data inevitably causes network congestion and information transmission delay is increased rapidly; meanwhile, if a large amount of device data is not processed in time, the delay of data queuing is increased, and the timeliness of the obtained device state information of the industrial system is poor.
Therefore, how to improve the timeliness of the device status information in the device wireless monitoring system is an important issue to be solved in the industry.
Disclosure of Invention
The invention provides a method and a device for equipment scheduling and resource allocation, electronic equipment and a storage medium, which are used for solving the problem of poor timeliness of equipment state information in a wireless monitoring system.
The invention provides a method for scheduling equipment and allocating resources, which comprises the following steps:
acquiring equipment information, transmission information and computing resources of a wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server;
determining an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information and the computing resources; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period;
and solving the optimization problem of the equipment scheduling and resource allocation, and determining the equipment scheduling and resource allocation information of the wireless monitoring system.
According to the method for scheduling equipment and allocating resources provided by the invention, the optimization problem of the equipment scheduling and the resource allocation is represented as follows:
P0：
Figure BDA0003237694940000021
s.t.C1:
Figure BDA0003237694940000022
C2:
Figure BDA0003237694940000023
C3:
Figure BDA0003237694940000024
C4:
Figure BDA0003237694940000025
C5:
Figure BDA0003237694940000026
C6:
Figure BDA0003237694940000027
C7:
Figure BDA0003237694940000028
wherein P0 is an objective function of the optimization problem of the device scheduling and resource allocation, and C1 to C7 are constraints of the objective function P0; c3 is access restriction of communication system, in any time of communication systemThe access quantity of the equipment does not exceed the total number of the sub-channels included in the communication system; c4 is the transmit power limit of the device; c5 denotes a channel interference limit for guaranteeing the success rate of information transmission; c6 shows that the information transmitted to the network side network element by any equipment in any time slot can be processed by the information processing server at the next moment; c7 is system computing resource constraints; the wireless monitoring system comprises K devices, at least one network side network element and an information processing server; m is the total number of orthogonal sub-channels included in the communication system; n is a time slot number, and n is a time slot number,
Figure BDA0003237694940000031
n is the number of time slots included in one monitoring period; pik(n)＝{αk.n,βk,n}；αk,nIndicating the information gathering status of device k at time slot n,
Figure BDA0003237694940000032
Figure BDA0003237694940000033
αk,n＝{0,1,2}，αk,nwith 0 denotes that the buffer of device k is empty and device k does not collect information at slot n, α k,n1 denotes that at time slot n device k collects information and stores it in the buffer of device k, α k,n2 means that the buffer of device k is not empty and device k does not collect information at slot n; beta is ak,nIndicating the scheduling of device k in time slot n, betak,n＝{0,1}，βk,n0 means that device k does not transmit information in time slot n, β k,n1 indicates that device k transmits information in time slot n; l iskThe amount of information to be transmitted for device k; rk,nFor the amount of information transmitted by device k in slot n,
Figure BDA0003237694940000034
pk,ntransmit power for device k at time slot n; p is the maximum transmit power of the device; h iskChannel gain of a subchannel occupied for device k; n is a radical of0Single-sided power spectral density; b is the channel bandwidth of the subchannel; gamma raythIs a channel signal-to-interference-and-noise ratio threshold;
Figure BDA0003237694940000035
dkis the distance between the device k and the base station, c is the speed of light, fcIs the carrier frequency; t is the time slot length; skThe number of CPU cycles required for the information processing server to process 1bit data; f. ofk,n+1Computing resources allocated to the device k for the information processing server in the time slot n + 1; f is the total amount of computing resources available for the information processing server; a. thes,k(n) is the information age of device k at the beginning of time slot n,
Figure BDA0003237694940000041
Qk(n) is the amount of buffered data for device k at the beginning of slot n,
Figure BDA0003237694940000042
Ad,k(n) is the information age of the device k at the information processing server at the end of the time slot n,
Figure BDA0003237694940000043
according to the method for scheduling and allocating resources of the device provided by the invention, the method for solving the optimization problem of the scheduling and allocating resources of the device and determining the scheduling and allocating resources information of the device of the wireless monitoring system comprises the following steps:
converting the optimization problem of the equipment scheduling and resource allocation into a convex optimization problem:
Px:
Figure BDA0003237694940000044
s.t.C8:
Figure BDA0003237694940000045
C9:
Figure BDA0003237694940000046
C10:
Figure BDA0003237694940000047
C11:
Figure BDA0003237694940000048
C12:
Figure BDA0003237694940000049
C13:
Figure BDA00032376949400000410
C14:
Figure BDA00032376949400000411
C15:
Figure BDA00032376949400000412
where Px is an objective function of the convex optimization problem, and C8 to C15 are constraint conditions of Px:
Figure BDA00032376949400000413
representing a set of equipment to be scheduled by a network element at a time slot n; f. ofn+1Computing resources available to the information processing server at time slot n + 1;
Figure BDA0003237694940000051
Figure BDA0003237694940000052
ε is an infinitesimal quantity greater than 0; χ is a penalty factor, χ > 1;
Figure BDA0003237694940000053
j is the number of iterations,
Figure BDA0003237694940000054
beta to satisfy the restrictions C8 and C9k,nAny value of (a); mnTime slot for network side network elementn number of channels available;
Figure BDA0003237694940000055
and solving the convex optimization problem, and determining equipment scheduling and resource allocation information of the wireless monitoring system.
According to the method for scheduling equipment and allocating resources provided by the invention, the solving of the convex optimization problem and the determination of the equipment scheduling and resource allocation information of the wireless monitoring system comprise the following steps:
for all time slots in the monitoring period, the following steps are repeatedly executed for each time slot in sequence according to the time sequence:
solving the convex optimization problem by adopting an iterative calculation mode and based on a continuous convex approximation algorithm SCA until the total average information age gain of the wireless monitoring system in a time slot is converged to obtain betak,nFeasible solution of
Figure BDA0003237694940000056
rk,nFeasible solution of
Figure BDA0003237694940000057
And
Figure BDA0003237694940000058
feasible solution of
Figure BDA0003237694940000059
Wherein E isnThe total average information age gain of the wireless monitoring system in a time slot; based on
Figure BDA00032376949400000510
Calculating betak,nOf (2) an optimal solution
Figure BDA00032376949400000511
Based on
Figure BDA00032376949400000512
And
Figure BDA00032376949400000513
calculating pk,nOf (2) an optimal solution
Figure BDA00032376949400000514
Based on
Figure BDA00032376949400000515
Calculating to obtain alphak,nOf (2) an optimal solution
Figure BDA00032376949400000516
Based on
Figure BDA00032376949400000517
And
Figure BDA00032376949400000518
calculating fk,n+1Of (2) an optimal solution
Figure BDA00032376949400000519
Based on
Figure BDA00032376949400000520
And
Figure BDA00032376949400000521
calculation of As,k(n) and Ad,k(n); based on
Figure BDA00032376949400000522
And
Figure BDA00032376949400000523
calculating fn+1(ii) a Based on
Figure BDA00032376949400000524
Calculating Mn。
The method for scheduling equipment and allocating resources provided by the invention is based on
Figure BDA0003237694940000061
Computingβk,nOf (2) an optimal solution
Figure BDA0003237694940000062
Based on
Figure BDA0003237694940000063
And
Figure BDA0003237694940000064
calculating pk,nOf (2) an optimal solution
Figure BDA0003237694940000065
Based on
Figure BDA0003237694940000066
Calculating to obtain alphak,nOf (2) an optimal solution
Figure BDA0003237694940000067
Based on
Figure BDA0003237694940000068
And
Figure BDA0003237694940000069
calculating fk,n+1Of (2) an optimal solution
Figure BDA00032376949400000610
The method comprises the following steps:
based on
Figure BDA00032376949400000611
Beta is calculated by adopting a formula C16k,nOf (2) an optimal solution
Figure BDA00032376949400000612
C16：
Figure BDA00032376949400000613
Based on
Figure BDA00032376949400000614
And
Figure BDA00032376949400000615
p is calculated by adopting a formula C17-C20k,nOf (2) an optimal solution
Figure BDA00032376949400000616
C17：
Figure BDA00032376949400000617
C18：
Figure BDA00032376949400000618
C19：
Figure BDA00032376949400000619
C20：
Figure BDA00032376949400000620
Based on
Figure BDA00032376949400000621
And
Figure BDA00032376949400000622
f is calculated by the formula C21k,n+1Of (2) an optimal solution
Figure BDA00032376949400000623
C21：
Figure BDA00032376949400000624
Based on
Figure BDA00032376949400000625
Alpha is calculated by adopting a formula C22k,nOf (2) an optimal solution
Figure BDA00032376949400000626
C22：
Figure BDA00032376949400000627
According to a method for scheduling and allocating resources for a device provided by the present invention, the device scheduling and resource allocation information includes at least one of the following:
the information collection state, the scheduling state and the transmitting power of each device in each time slot in the wireless monitoring system, and the computing resources distributed to each device by the information processing server in each time slot.
The invention also provides a device for scheduling equipment and allocating resources, which comprises:
the acquisition module is used for acquiring equipment information, transmission information and computing resources of the wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server;
a determining module, configured to determine an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information, and the computing resource; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period;
and the solving module is used for solving the optimization problem of the equipment scheduling and resource allocation, determining the information collection state, the scheduling state and the transmitting power of each equipment in each time slot in the wireless monitoring system, and determining the computing resources allocated to each equipment by the information processing server in each time slot.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the device scheduling and resource allocation method according to any one of the above items.
The invention also provides a non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method for scheduling and resource allocation of a device as described in any one of the above.
The equipment scheduling and resource allocation method, the equipment scheduling and resource allocation device, the electronic equipment and the storage medium provided by the invention have the advantages that the total information age of the wireless monitoring system in a monitoring period is minimized by jointly optimizing the equipment information acquisition, scheduling, transmitting power and communication and computing resource allocation, and the timeliness of the equipment state information in the wireless monitoring system is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario of the method for scheduling devices and allocating resources according to the present invention;
FIG. 2 is a flowchart illustrating a method for scheduling devices and allocating resources according to the present invention;
FIG. 3 is a schematic diagram of an information update cycle of the apparatus provided by the present invention;
fig. 4 is a schematic structural diagram of an apparatus for scheduling and allocating resources according to the present invention;
fig. 5 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a method for scheduling equipment and allocating resources, which comprises the following steps: acquiring equipment information, transmission information and computing resources of a wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server; determining an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information and the computing resources; the optimization problem of the device scheduling and resource allocation is a problem of minimizing the total Information Age (AoI) of a wireless monitoring system in a monitoring period; and solving the optimization problem of the equipment scheduling and resource allocation, and determining the equipment scheduling and resource allocation information of the wireless monitoring system. The equipment scheduling and resource allocation method provided by the invention has the advantages that the total information age of the wireless monitoring system in a monitoring period is minimized by jointly optimizing the equipment information acquisition, scheduling, transmitting power and communication and resource allocation calculation, and the timeliness of the equipment state information in the wireless monitoring system is improved.
The equipment scheduling and resource allocation method provided by the invention can be applied to a wireless monitoring system of the industrial Internet. Fig. 1 is a schematic view of an application scenario of the method for scheduling devices and allocating resources according to the present invention. As shown in fig. 1, the wireless monitoring system includes: the system comprises equipment 101, a network side network element 102 and an information processing server 103; wherein: the device 101 may comprise any kind of industrial device that can normally access the industrial internet; the network element 102 on the network side may include a base station or a core network device in the communication system; the information processing server 103 may include a desktop computer or the like.
It should be noted that the invention is not limited to the specific type and number of devices 101. The device 101 accesses the network side network element 102 in an Orthogonal Frequency Division Multiple Access (OFDMA) manner, and the device 101 sends device status information of itself to the network side network element 102 through a wireless transmission channel; the device status information may include information such as an operation status, a wear level, or an execution frequency of the device. The information processing server 103 is connected to the network side network element 102, the network side network element 102 sends the device state information reported by each device to the information processing server 103, and the information processing server 103 processes the device state information to obtain the device state information.
It should be noted that, in the present invention, the information acquisition, transmission and processing for a plurality of devices in the wireless monitoring system are mainly performed in one monitoring period. Meanwhile, in order to ensure the timeliness of the state information of the equipment, the multiple pieces of equipment continuously repeat data acquisition, transmission and processing in one monitoring period.
Next, the method for scheduling devices and allocating resources provided by the present invention will be described.
Fig. 2 is a schematic flow chart of a device scheduling and resource allocation method provided by the present invention, as shown in fig. 2, the method includes:
step 110, acquiring equipment information, transmission information and computing resources of the wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources include computing resources available to the information handling server.
Step 120, determining an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information and the computing resources; the optimization problem of the device scheduling and resource allocation is the problem of minimizing the total information age of the wireless monitoring system in one monitoring period.
Alternatively, AoI refers to the period of time that elapses since the device information was generated until it was received by the information processing server. AoI the timeliness of the device information is measured from the information processing server, and is influenced by the time consumed in the process of multiple information transmission processes, such as device information sampling time, transmission time, queuing time and processing time. AoI, the larger the time spent by the equipment information from the equipment to the information processing server, the worse the timeliness of the equipment information; AoI, the smaller the time spent by the equipment information from the equipment to the information processing server is, the better the timeliness of the equipment information is; the smaller the AoI of the device, the better the system performance.
Step 130, solving the optimization problem of the device scheduling and resource allocation, and determining the device scheduling and resource allocation information of the wireless monitoring system.
Optionally, the device scheduling and resource allocation information includes at least one of: the information collection state, the scheduling state and the transmitting power of each device in each time slot in the wireless monitoring system, and the computing resources distributed to each device by the information processing server in each time slot.
The method provided by the invention minimizes the total information age of the wireless monitoring system in a monitoring period by jointly optimizing the information acquisition, scheduling, transmitting power and communication and calculation resource distribution of the equipment, and improves the timeliness of the equipment state information in the wireless monitoring system.
Fig. 3 is a schematic diagram of an information update cycle of a device provided in the present invention, and as shown in fig. 3, an information update cycle of a device includes: waiting for collection, waiting for scheduling, transmitting data, processing data and the like. One data update of the device begins after the last data transmission is finished. As shown in FIG. 3, the device is at t1To t2Waits for information collection at time t2Information is collected at a time, assuming that the device completes information collection immediately at the time of collecting information, i.e. the device is at t2The time-to-time information collection time is 0. The device stores the collected information in a buffer (buffer) of the device, and the buffer of the device only stores the information collected last time, that is, the device information stored in the buffer of the device is the latest device state information of the device. Is provided withIs prepared at t2To t3Waiting for the scheduling of the network side network element at all times, wherein the network side network element is at t3And the network side network element immediately finishes equipment scheduling at the scheduling time, namely the equipment scheduling time is 0, and simultaneously, the information collected by the equipment is transmitted to the network side network element and the information processing server through a wireless transmission channel, and the information collected by the equipment is further processed at the information processing server. In order to ensure the timeliness of the information, the information collected by the device is processed synchronously, that is, the information transmitted by the current time slot is processed in the next time slot.
Assume that the position coordinates of the network-side network element and the information processing server in the wireless monitoring system shown in fig. 1 are (0,0, H) and (0,0,0), respectively, H is the height of the network-side network element, and the position coordinate of the industrial equipment is Dk＝(xk,yk,0). L is the amount of information that device k needs to transmitkAnd (4) showing. The transmission power of the device k in the time slot n is pk,nThe maximum transmitting power of the equipment is P, n is the time slot serial number,
Figure BDA0003237694940000111
the communication system comprises a total number of orthogonal sub-channels, denoted M
Figure BDA0003237694940000112
Wherein, the channel width of each sub-channel is B, and the length of one time slot is T. Each device is allowed to occupy only one sub-channel to transmit data in any time slot, and each sub-channel can only accommodate one device. The invention adopts a free space path loss model, and the channel gain of a subchannel occupied by equipment k is
Figure BDA0003237694940000121
Where c is the speed of light, fcIs the carrier frequency. dkIs the distance between the device k and the network element on the network side,
Figure BDA0003237694940000122
assuming negligible interference between different sub-channels, the amount of information transmitted by device k in time slot nComprises the following steps:
Figure BDA0003237694940000123
wherein N is0Is a single-sided power spectral density. During the information transmission process, the transmission power of the device k is kept consistent every time, and the information transmission is not interrupted. In addition, in order to prevent data transmission failure caused by poor channel quality and influence the timeliness of information, information transmission needs to ensure that:
Figure BDA0003237694940000124
wherein, γthAnd the signal-to-interference-and-noise ratio threshold value of the channel is used for ensuring the successful information transmission.
The number of CPU cycles required for the information processing server to process 1bit data of the device k is sk. The computing resource f allocated by the information processing server to the device k in the time slot n isk,n. In order to meet the information processing requirements, for information transmitted by device k in slot n, the information processing server must process the completion in n +1 slots, and therefore,
Figure BDA0003237694940000125
meanwhile, the total computing resources allocated by the information processing server to each device at any time slot should be less than the total amount of computing resources available to the information processing server, that is, the total amount of computing resources allocated by the information processing server
Figure BDA0003237694940000126
fk,nIndicating the computing resources allocated by the information processing server to the device k in the time slot n, and f is the total amount of computing resources available to the information processing server.
At each time slot, the network side network element needs to decide which device is to be scheduled to collect information or transmit information. For device k, the information collection status of device k in time slot n is represented by αk,nIs represented byk,n＝{0,1,2}，αk,nWith 0 denotes that the buffer of device k is empty and device k does not collect information at slot n, α k,n1 denotes that at time slot n device k collects information and stores it in the buffer of device k, α k,n2 indicates that the buffer of device k at slot n is notEmpty and device k does not collect information. Beta for scheduling of device k in time slot nk,nIs represented by betak,n＝{0,1}，βk,n0 means that device k does not transmit information in time slot n, β k,n1 indicates that device k transmits information in slot n. Since the device k communicates with the network side network element by using the OFDMA access mode, the device k can communicate with the network side network element by using the OFDMA access mode
Figure BDA0003237694940000131
The scheduling strategy of the device k in the time slot n is expressed as pik(n)＝{αk.n,βk,nAt any one time, the scheduling policies selectable by the device k are (0,0), (0,1), (1,0), (1,1), (2,0), (2, 1). For strategy pikWhen (n) — (0,1), since the amount of information is 0 in the buffer of the slot n device k, information cannot be transmitted, and thus pikAnd (n) ═ 0,1 is an invalid strategy. And pikThe case where (n) — (1,0) indicates that the information collected by device k at time slot n is not transmitted immediately, which does not contribute to the reduction AoI, can be considered as an invalid policy. In addition, the transmission of data cannot be interrupted, so that pik(n) ≠ (2, 0). In summary, the selectable scheduling policy of device k in slot n is pik(n)＝{(0,0),(1,1),(2,1)}。
The invention adopts AoI as a key index for measuring the timeliness of the equipment state information of the system. Let As,k(n) AoI for device k at the beginning of time slot n; a. thed,k(n) AoI for device k at the information processing server at the end of time slot n; qk(n) represents the amount of buffered data in the buffer of device k at the beginning of slot n. According to a scheduling policy pik(n), the amount of buffered data of device k in different time slots can be expressed as:
C23:
Figure BDA0003237694940000141
by definition of AoI, if device k collects information at slot n, AoI for device k will drop to 1; otherwise, AoI for device k would be increased by 1. Thus, AoI for device k may be expressed as:
C24:
Figure BDA0003237694940000142
if the device k completes the transmission of the information in the buffer at the end of the time slot n, the AoI of the device k at the information processing server will drop to AoI and 2 of the device k at the time slot n; one time slot is used for information transmission, and the information processing server processes the information transmitted from the device k to the network element at the network side in the next time slot after the data transmission is finished. Otherwise, device k will increment by 1 at AoI of the information processing server.
Thus, the device k at the end of time slot n +1 is denoted A at AoI of the information processing serverd,k(n +1) in which,
C25:
Figure BDA0003237694940000143
the invention adopts AoI to measure the timeliness of the equipment information of the wireless monitoring system, and AoI is influenced by the time consumed in the process of a plurality of information transmission processes such as the sampling time, the transmission time, the queuing time, the processing time and the like of the equipment information.
The invention minimizes AoI of the wireless monitoring system of the industrial equipment in a monitoring period by jointly optimizing information acquisition and transmission power of the industrial equipment and allocation of communication and computing resources, and accordingly, the optimization problem of determining equipment scheduling and resource allocation of the wireless monitoring system based on equipment information, transmission information and computing resources in fig. 2 can be expressed as:
P0：
Figure BDA0003237694940000144
s.t.C1:
Figure BDA0003237694940000151
C2:
Figure BDA0003237694940000152
C3:
Figure BDA0003237694940000153
C4:
Figure BDA0003237694940000154
C5:
Figure BDA0003237694940000155
C6:
Figure BDA0003237694940000156
C7:
Figure BDA0003237694940000157
wherein P0 is an objective function of the optimization problem of the device scheduling and resource allocation, and C1 to C7 are constraints of the objective function P0; c3 is the access limit of the communication system, the access amount of the device in the communication system does not exceed the total number of sub-channels included in the communication system at any time; c4 is the transmit power limit of the device; c5 denotes a channel interference limit for guaranteeing the success rate of information transmission; c6 shows that the information transmitted to the network side network element by any equipment in any time slot can be processed by the information processing server at the next moment; c7 is system computing resource constraints; the wireless monitoring system comprises K devices, at least one network side network element and an information processing server; m is the total number of orthogonal sub-channels included in the communication system; n is a time slot number, and n is a time slot number,
Figure BDA0003237694940000158
n is the number of time slots included in one monitoring period; pik(n)＝{αk.n,βk,n}；αk,nIndicating the information gathering status of device k at time slot n,
Figure BDA0003237694940000159
Figure BDA00032376949400001510
αk,n＝{0,1,2}，αk,nwith 0 denotes that the buffer of device k is empty and device k does not collect information at slot n, αk,n1 denotes that at time slot n device k collects information and stores it in the buffer of device k, αk,n2 means that the buffer of device k is not empty and device k does not collect information at slot n; beta is ak,nIndicating the scheduling of device k in time slot n, betak,n＝{0,1}，βk,n0 means that device k does not transmit information in time slot n, βk,n1 indicates that device k transmits information in time slot n; l iskThe amount of information to be transmitted for device k; rk,nFor the amount of information transmitted by device k in slot n,
Figure BDA0003237694940000161
pk,ntransmit power for device k at time slot n; p is the maximum transmit power of device k; h iskChannel gain of a subchannel occupied for device k; n is a radical of0Single-sided power spectral density; b is the channel bandwidth of the subchannel; gamma raythIs a channel signal-to-interference-and-noise ratio threshold;
Figure BDA0003237694940000162
dkis the distance between the device k and the network element on the network side, c is the speed of light, fcIs the carrier frequency; t is the time slot length; skThe number of CPU cycles required for the information processing server to process 1bit data; f. ofk,n+1Computing resources allocated to the device k for the information processing server in the time slot n + 1; f is the total amount of computing resources available for the information processing server; a. thes,k(n) is the information age of device k at the beginning of time slot n,
Figure BDA0003237694940000163
Qk(n) is the amount of buffered data for device k at the beginning of slot n,
Figure BDA0003237694940000164
Ad,k(n) is the information age of the device k at the information processing server at the end of the time slot n,
Figure BDA0003237694940000165
for the objective function P0, αk,n，βk,nIs an integer variable, pk,n，fk,nIs a continuous variable with a variable betak,nAnd pk,nThe constraints C5 and C6 in the objective function P0 are coupled to each other, and the same variables are also coupled to each other between different time slots. Therefore, the problem P0 is a mixed integer nonlinear non-convex optimization problem. At the same time, Ad,k(n) is a variable αk,n，βk,n，pk,nAnd fk,nWith implicit expression of joint decision, the traditional optimization method cannot obtain a closed-form solution of the problem P0. In view of this, the present invention converts the nonlinear non-convex optimization problem P0 into a convex optimization problem and then solves the convex optimization problem.
Specifically, an optimization problem P0 of device scheduling and resource allocation is converted into a convex optimization problem, and the convex optimization problem is solved to determine device scheduling and resource allocation information of the wireless monitoring system; wherein: the convex optimization problem can be expressed as:
Px:
Figure BDA0003237694940000171
s.t.C8:
Figure BDA0003237694940000172
C9:
Figure BDA0003237694940000173
C10:
Figure BDA0003237694940000174
C11:
Figure BDA0003237694940000175
C12:
Figure BDA0003237694940000176
C13:
Figure BDA0003237694940000177
C14:
Figure BDA0003237694940000178
C15:
Figure BDA0003237694940000179
where Px is an objective function of the convex optimization problem, and C8 to C15 are constraint conditions of Px:
Figure BDA00032376949400001710
representing a set of equipment to be scheduled by a network element at a time slot n; f. ofn+1Computing resources available to the information processing server at time slot n + 1;
Figure BDA00032376949400001711
Figure BDA00032376949400001712
ε is an infinitesimal quantity greater than 0; χ is a penalty factor, χ > 1;
Figure BDA00032376949400001713
j is the number of iterations,
Figure BDA00032376949400001714
beta to satisfy the restrictions C8 and C9k,nAny value of (a); mnThe number of channels available in the time slot n for the network element at the network side;
Figure BDA00032376949400001715
the process of converting the optimization problem P0 of device scheduling and resource allocation into the convex optimization problem Px is described here:
first, in order to describe the transformation of the optimization problem P0 of device scheduling and resource allocation into the convex optimization problem Px, the present invention introduces a parameter by analyzing the AoI variation of the device: average AoI revenue; and performing equivalent substitution on the objective function of the problem P0 based on the average AoI profit to realize the replanning of the problem P0.
Specifically, the average AoI benefit for device k at time slot n may be expressed as:
C26:
Figure BDA0003237694940000181
wherein the content of the first and second substances,
Figure BDA0003237694940000182
indicating AoI degradation of device k after the end of the slot n schedule. Since the transmission power of the device is constant during one scheduling,
Figure BDA0003237694940000183
indicating the time of transmission of the information.
Maximizing AoI the total droop is equivalent to maximizing AoI per slot droop, i.e., average AoI revenue, when the monitoring period time length is fixed. By optimizing device scheduling and resource allocation, the maximum total average AoI benefit is obtained, and the minimization of the system total AoI is realized. Problem P0 can thus translate into problem P1:
p1:
Figure BDA0003237694940000184
the constraint conditions of the problem P1 are the constraint conditions C1 to C7 of the objective function P0.
Aiming at the characteristic of mutual coupling among different time slots in the problem P1, the method decouples the problem into a plurality of continuous short-term optimal problems, namely, a sub-problem of equipment scheduling and resource allocation optimization which decouples P1 into N different time slots is solved sequentially according to the time sequence, and the optimal solution of the problem P1 is approximately obtained.
Without loss of generality, the device scheduling and resource allocation optimization problem of time slot n needs to be considered, and in this case, the problem P1 can be expressed as:
P2：
Figure BDA0003237694940000191
s.t.C27:
Figure BDA0003237694940000192
C28:
Figure BDA0003237694940000193
C29:
Figure BDA0003237694940000194
C30:
Figure BDA0003237694940000195
C31:
Figure BDA0003237694940000196
C32:
Figure BDA0003237694940000197
C33:
Figure BDA0003237694940000198
wherein the content of the first and second substances,
Figure BDA0003237694940000199
device set M for indicating network side network element to be scheduled in time slot nnNumber of channels, f, available in time slot n for network side network elementsn+1The computing resources available at time slot n +1 for the information processing server.
Based on the relevant analysis of data acquisition, transmission and processing, problem P2 presents the following properties: 1) when the problem P2 obtains an optimal solution, the constraint condition C32 is a tight constraint; 2) for the
Figure BDA00032376949400001910
Figure BDA00032376949400001911
And
Figure BDA00032376949400001912
are related to each other. Wherein the content of the first and second substances,
Figure BDA00032376949400001913
is alphak.nThe optimum solution of (a) to (b),
Figure BDA00032376949400001914
is betak,nThe optimal solution of (1). Thus, constraints C32 and C33 may be re-formulated as:
Figure BDA00032376949400001915
introducing variables
Figure BDA00032376949400001916
Problem P2 is transformed into problem P3:
P3：
Figure BDA0003237694940000201
s.t.C35:
Figure BDA0003237694940000202
C36:
Figure BDA0003237694940000203
C37:
Figure BDA0003237694940000204
C38:
Figure BDA0003237694940000205
C39:
Figure BDA0003237694940000206
wherein A iss,k(n-1) is a known quantity, the problem P3 is a mixed integer non-convex optimization problem, and the solving challenge of P3 mainly comes from two aspects: 1, discrete variable betak,nAnd a continuous variable rk,nNon-convexity of the target function and the constraints due to coupling; and 2, non-convexity caused by the integer function in the objective function.
Taking into account betak,nThe objective function of P3 can be re-expressed as:
Figure BDA0003237694940000207
where ε is an infinitesimal quantity greater than 0.
Beta in the objective function re-expressed for solving the constraints C38, C39 and problem P3k,n·rk,nIs coupled to introduce a variable
Figure BDA0003237694940000208
Thereafter, constraints C41-C44 were introduced to solve the coupling problem by applying the associated mathematical method to re-program.
C41:
Figure BDA0003237694940000209
C42:
Figure BDA00032376949400002010
C43:
Figure BDA00032376949400002011
C44:
Figure BDA0003237694940000211
Converting the integer variable betak,nSerialization, and equivalently writing the formula C35 as formula C45-C46:
C45:
Figure BDA0003237694940000212
C46:
Figure BDA0003237694940000213
where formula C46 is a reverse convex constraint, i.e., a non-convex set, with non-convexity. To solve the non-convexity of the formula C46, let χ (β)k,n-(βk,n)2) χ > 1 is introduced as a penalty term into the objective function, therefore, the problem P3 can be equivalently transformed into P4:
P4：
Figure BDA0003237694940000214
the constraint condition of the target function of P4 is in formulas C8-C15. χ > 1 is a penalty factor to ensure βk,nThe value is close to 0 or 1, and in order to deal with the rounding function in the P4 optimization target, the value is used
Figure BDA0003237694940000215
Substitution
Figure BDA0003237694940000216
Further, the objective function of P4 is a difference of concave functions, and therefore, the problem P4 still has non-convexity. Using successive convex approximation algorithm (SCA) to convert betak,n-(βk,n)2The relaxation deals with the non-convexity of the objective function. In particular, for a given feasible point
Figure BDA0003237694940000217
Will betak,n-(βk,n)2At this point a first order Taylor expansion is performed, taking betak,n-(βk,n)2Is approximated as a linear function
Figure BDA0003237694940000218
Wherein a linear function
Figure BDA0003237694940000219
Expressed as:
C47:
Figure BDA00032376949400002110
since the first-order Taylor expansion of the concave function at any point is the global upper bound of the function, we will be dividing β intok,n-(βk,n)2Is approximated as a linear function
Figure BDA00032376949400002111
This approximation does not extend the range of problem P4, so problem P4 can be translated into problem Px. Obviously, the problem Px is a convex optimization problem.
Optionally, solving the convex optimization problem Px to determine an implementation manner of the device scheduling and resource allocation information of the wireless monitoring system may include:
for all time slots in the monitoring period, the following steps are repeatedly executed for each time slot in sequence according to the time sequence:
solving the convex optimization problem based on a sequential convex approximation algorithm (SCA) by adopting an iterative calculation mode until the total average information age gain of the wireless monitoring system in a time slot is converged to obtain betak,nFeasible solution of
Figure BDA0003237694940000221
Feasible solution of
Figure BDA0003237694940000222
And
Figure BDA0003237694940000223
feasible solution of
Figure BDA0003237694940000224
Wherein E isnThe total average information age gain of the wireless monitoring system in a time slot; based on
Figure BDA0003237694940000225
Calculating betak,nOf (2) an optimal solution
Figure BDA0003237694940000226
Based on
Figure BDA0003237694940000227
And
Figure BDA0003237694940000228
calculating pk,nOf (2) an optimal solution
Figure BDA0003237694940000229
Based on
Figure BDA00032376949400002210
Calculating to obtain alphak,nOf (2) an optimal solution
Figure BDA00032376949400002211
Based on
Figure BDA00032376949400002212
And
Figure BDA00032376949400002213
calculating fk,n+1Of (2) an optimal solution
Figure BDA00032376949400002214
Based on
Figure BDA00032376949400002215
Figure BDA00032376949400002216
And
Figure BDA00032376949400002217
calculation of As,k(n) and Ad,k(n); based on
Figure BDA00032376949400002218
And
Figure BDA00032376949400002219
calculating fn+1(ii) a Based on
Figure BDA00032376949400002220
Calculating Mn(ii) a Wherein E isnRepresenting the total average information age gain of the wireless monitoring system in one time slot.
Specifically, the specific solving algorithm for solving the convex optimization problem Px based on the SCA in the iterative computation manner includes algorithm 1 and algorithm 2, which are respectively introduced as follows:
and the algorithm 1 is used for realizing single-time-slot equipment scheduling and resource allocation optimization.
The input parameters involved in algorithm 1 include:
Figure BDA00032376949400002221
Mn，fn，As,k(n-1)，P，B，T，N0，dk，Lk，γthε, χ; the output parameters include:
Figure BDA00032376949400002222
solving the problem Px by an iterative calculation method based on the algorithm 1, which may include steps a) to c):
step a), obtaining a problem Px through a formula C40-C47, and setting a threshold psi and a maximum iteration number jmaxLet j equal 1, choose an arbitrary variable in the feasible domain of the problem Px, and note it as
Figure BDA0003237694940000231
Wherein, the feasible region refers to a linear function in the objective function of the problem Px
Figure BDA0003237694940000232
The maximum range of values that can be taken.
Step b) for a given value
Figure BDA0003237694940000233
Calculated according to the formula C47
Figure BDA0003237694940000234
Substituting the problem Px into the problem Px, and then solving the problem Px by using CVX to obtain a group of suboptimal solutions
Figure BDA0003237694940000235
And target value
Figure BDA0003237694940000236
Let j +1 become j, let
Figure BDA0003237694940000237
Step c), repeatedly executing step b); up to the target value
Figure BDA0003237694940000238
Satisfies the condition | En j-1-En jPhi is less than or equal to psi or j is equal to jmaxA set of sub-optimal solutions obtained at this time
Figure BDA0003237694940000239
And target value
Figure BDA00032376949400002310
Are each betak,nFeasible solution of
Figure BDA00032376949400002311
rk,nFeasible solution of
Figure BDA00032376949400002312
And
Figure BDA00032376949400002313
feasible solution of
Figure BDA00032376949400002314
In view of
Figure BDA00032376949400002315
Substitution
Figure BDA00032376949400002316
The influence on the transmission power and resource allocation is determined by formula
Figure BDA00032376949400002317
And
Figure BDA00032376949400002318
adjusting variables
Figure BDA00032376949400002319
The optimum value of (d);
Figure BDA00032376949400002320
the number of slots required for user k to transmit data when slot n is scheduled.
Due to the fact that
Figure BDA00032376949400002321
The constraints of the problem Px can still be met, so that this adjustment does not change the scheduling policy
Figure BDA00032376949400002322
The number of slots actually occupied by the device data transmission and the AoI of the device will not change compared to before the adjustment. The advantage of this adjustment is that the optimal allocation of device transmission power and computational resources for the current time slot is reduced after the adjustment, which is beneficial to the next time slot system to obtain greater AoI benefits. After adjustment, based on
Figure BDA00032376949400002323
Beta is calculated by adopting a formula C16k,nOf (2) an optimal solution
Figure BDA0003237694940000241
C16：
Figure BDA0003237694940000242
Based on
Figure BDA0003237694940000243
And
Figure BDA0003237694940000244
p is calculated by adopting a formula C17-C20k,nOf (2) an optimal solution
Figure BDA0003237694940000245
C17：
Figure BDA0003237694940000246
C18：
Figure BDA0003237694940000247
C19：
Figure BDA0003237694940000248
C20：
Figure BDA0003237694940000249
Based on
Figure BDA00032376949400002410
And
Figure BDA00032376949400002411
f is calculated by the formula C21k,n+1Of (2) an optimal solution
Figure BDA00032376949400002412
C21：
Figure BDA00032376949400002413
Based on
Figure BDA00032376949400002414
Alpha is calculated by adopting a formula C22k,nOf (2) an optimal solution
Figure BDA00032376949400002415
C22：
Figure BDA00032376949400002416
And the algorithm 2 is used for realizing time slot-by-time slot equipment scheduling and resource allocation optimization.
Algorithm 2 combines with algorithm 1 to implement slot-by-slot device scheduling and resource allocation optimization for the problem Px. The input parameters of algorithm 2 include:
Figure BDA00032376949400002417
K,N,M,P,f,B,T,N0,dk,Lk,sk,γthε, χ; the output parameters include:
Figure BDA00032376949400002418
As，k(n)，Ad，k(n)
Figure BDA00032376949400002420
algorithm 2 may include the following steps 1) to 8):
step 1):
initialization: the time slot n is 1, the initial AoI of the different device is as,k(0) And Ad,k(0) Schedulable user set
Figure BDA0003237694940000251
Number of available channels M1As M, channel resources f can be utilized1＝f。
Step 2):
for time slot n, solving problem Px based on algorithm 1 to obtain betak,nFeasible solution of
Figure BDA0003237694940000252
rk,nFeasible solution of
Figure BDA0003237694940000253
And
Figure BDA0003237694940000254
feasible solution of
Figure BDA0003237694940000255
According to the formula
Figure BDA0003237694940000256
And
Figure BDA0003237694940000257
computing
Figure BDA0003237694940000258
And
Figure BDA0003237694940000259
calculated according to the formula C16
Figure BDA00032376949400002510
P is calculated according to the formula C17-C20k,nOf (2) an optimal solution
Figure BDA00032376949400002511
Calculating f according to the formula C21k,n+1Of (2) an optimal solution
Figure BDA00032376949400002512
Step 3):
if it is not
Figure BDA00032376949400002513
And is
Figure BDA00032376949400002514
Then:
C48:
Figure BDA00032376949400002515
C49:
Figure BDA00032376949400002516
C50:
Figure BDA00032376949400002517
C51:
Figure BDA00032376949400002518
where n' is a time slot after time slot n,
Figure BDA00032376949400002519
step 4):
based on
Figure BDA00032376949400002520
And
Figure BDA00032376949400002521
calculation of As,k(n) and Ad,k(n) update A of the device at time slot n' using the formula C23-C25s,k(n) and Ad,k(n)。
Step 5):
let n be n + 1.
Step 6):
if it is
Figure BDA0003237694940000261
The network element at the network side needs to schedule the device set in the time slot n
Figure BDA0003237694940000262
Is the set after the device K is rejected in the current K device sets.
Step 7):
based on
Figure BDA0003237694940000263
Calculating the number M of channels available to network side network element in time slot nn：
C52:
Figure BDA0003237694940000264
Based on
Figure BDA0003237694940000265
And
Figure BDA0003237694940000266
calculating the number f of available calculation resources of the information processing server in the time slot n +1n+1：
Figure BDA0003237694940000267
Wherein the content of the first and second substances,
Figure BDA00032376949400002610
to indicate a function when
Figure BDA0003237694940000268
When the utility model is in use,
Figure BDA00032376949400002611
has a value of 1; when in use
Figure BDA0003237694940000269
When the state is not satisfied,
Figure BDA00032376949400002612
the value of (d) is 0.
Step 8): and repeatedly executing the step 2) to the step 7) until N is equal to N.
As can be seen from the algorithm 2, the optimal strategy of each time slot is approximately replaced by the optimal strategy of the whole monitoring period, and the algorithm only needs the state of the system in the current time slot and does not need the long-term state information of the system, so that the algorithm can be effectively adapted to the time-varying industrial system and is suitable for monitoring the equipment state in the time-varying system facing the long-term target. In addition, the algorithm adopts a time slot-by-time slot solving mode, so that the complexity of the algorithm is greatly reduced, and the process is more suitable for being actually applied to a time-varying industrial internet equipment state monitoring system.
The equipment scheduling and resource allocation method provided by the invention is characterized in that the equipment information, the transmission information and the computing resource of the wireless monitoring system are obtained, the optimization problem of the equipment scheduling and resource allocation of the wireless monitoring system is determined according to the obtained equipment information, the obtained transmission information and the obtained computing resource, and the determined optimization problem of the equipment scheduling and resource allocation is solved to determine the equipment scheduling and resource allocation information of the wireless monitoring system. According to the invention, through jointly optimizing the equipment information, the transmission information and the calculation resources, the optimization of equipment scheduling and resource allocation of the wireless monitoring system in a single time slot can be realized, and the optimization of equipment scheduling and resource allocation in multiple time slots can be realized, so that the reasonable allocation of the equipment scheduling and the resources is realized, the total information age of the wireless detection system in a monitoring period is minimized, and the timeliness of the equipment state information in the wireless monitoring system is improved.
The device scheduling and resource allocating apparatus provided in the present invention is described below, and the device scheduling and resource allocating apparatus described below and the device scheduling and resource allocating method described above may be referred to in correspondence with each other.
Fig. 4 is a schematic structural diagram of an apparatus for scheduling and allocating devices according to the present invention, as shown in fig. 4, the apparatus includes: an acquisition module 401, a determination module 402 and a solving module 403; wherein the content of the first and second substances,
an obtaining module 401, configured to obtain device information, transmission information, and computing resources of a wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server;
a determining module 402, configured to determine an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information, and the computing resource; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period;
a solving module 403, configured to solve the optimization problem of device scheduling and resource allocation, and determine an information collection state, a scheduling state, and a transmission power of each device in the wireless monitoring system at each time slot, and a computing resource allocated by the information processing server to each device at each time slot.
The device provided by the invention has the advantages that the total information age of the wireless monitoring system in a monitoring period is minimized by jointly optimizing the information acquisition, scheduling, transmitting power and communication and calculation resource distribution of the equipment, and the timeliness of the equipment state information in the wireless monitoring system is improved.
Optionally, the optimization problem of device scheduling and resource allocation is represented as:
P0：
Figure BDA0003237694940000281
s.t.C1:
Figure BDA0003237694940000282
C2:
Figure BDA0003237694940000283
C3:
Figure BDA0003237694940000284
C4:
Figure BDA0003237694940000285
C5:
Figure BDA0003237694940000286
C6:
Figure BDA0003237694940000287
C7:
Figure BDA0003237694940000288
wherein P0 is an objective function of the optimization problem of the device scheduling and resource allocation, and C1 to C7 are constraints of the objective function P0; c3 is the access limit of the communication system, the access amount of the device in the communication system does not exceed the total number of sub-channels included in the communication system at any time; c4 is the transmit power limit of the device; c5 denotes a channel interference limit for guaranteeing the success rate of information transmission; c6 shows that the information transmitted to the network side network element by any equipment in any time slot can be processed by the information processing server at the next moment; c7 is system computing resource constraints; the wireless monitoring system comprises K devices, at least one network side network element and an information processing server; m is the total number of orthogonal sub-channels included in the communication system; n is a time slot number, and n is a time slot number,
Figure BDA0003237694940000289
n is the number of time slots included in one monitoring period; pik(n)＝{αk.n,βk,n}；αk,nIndicating the information gathering status of device k at time slot n,
Figure BDA0003237694940000291
Figure BDA0003237694940000292
αk,n＝{0,1,2}，αk,nwith 0 denotes that the buffer of device k is empty and device k does not collect information at slot n, αk,n1 denotes that at time slot n device k collects information and stores it in the buffer of device k, αk,n2 means that the buffer of device k is not empty and device k does not collect information at slot n; beta is ak,nIndicating the scheduling of device k in time slot n, betak,n＝{0,1}，βk,n0 means that device k does not transmit information in time slot n, βk,n1 indicates that device k transmits information in time slot n; l iskThe amount of information to be transmitted for device k; rk,nFor the amount of information transmitted by device k in slot n,
Figure BDA0003237694940000293
pk,ntransmit power for device k at time slot n; p is the maximum transmit power of the device; h iskChannel gain of a subchannel occupied for device k; n is a radical of0Single-sided power spectral density; b is the channel bandwidth of the subchannel; gamma raythIs a channel signal-to-interference-and-noise ratio threshold;
Figure BDA0003237694940000294
dkis the distance between the device k and the base station, c is the speed of light, fcIs the carrier frequency; t is the time slot length; skThe number of CPU cycles required for the information processing server to process 1bit data; f. ofk,n+1Computing resources allocated to the device k for the information processing server in the time slot n + 1; f is the total amount of computing resources available for the information processing server; a. thes,k(n) is the information age of device k at the beginning of time slot n,
Figure BDA0003237694940000295
Qk(n) is the amount of buffered data for device k at the beginning of slot n,
Figure BDA0003237694940000296
Ad,k(n) is the information age of the device k at the information processing server at the end of the time slot n,
Figure BDA0003237694940000301
optionally, the solving module 403 is specifically configured to:
converting the optimization problem of the equipment scheduling and resource allocation into a convex optimization problem:
Px:
Figure BDA0003237694940000302
s.t.C8:
Figure BDA0003237694940000303
C9:
Figure BDA0003237694940000304
C10:
Figure BDA0003237694940000305
C11:
Figure BDA0003237694940000306
C12:
Figure BDA0003237694940000307
C13:
Figure BDA0003237694940000308
C14:
Figure BDA0003237694940000309
C15:
Figure BDA00032376949400003010
where Px is an objective function of the convex optimization problem, and C8 to C15 are constraint conditions of Px:
Figure BDA00032376949400003011
representing a set of equipment to be scheduled by a network element at a time slot n; f. ofn+1Computing resources available to the information processing server at time slot n + 1;
Figure BDA00032376949400003012
Figure BDA00032376949400003013
ε is an infinitesimal quantity greater than 0; χ is a penalty factor, χ > 1;
Figure BDA00032376949400003014
j is the number of iterationsThe number of the first and second groups is,
Figure BDA00032376949400003015
beta to satisfy the restrictions C8 and C9k,nAny value of (a); mnThe number of channels available in the time slot n for the network element at the network side;
Figure BDA00032376949400003016
and solving the convex optimization problem, and determining equipment scheduling and resource allocation information of the wireless monitoring system.
Optionally, the solving the convex optimization problem to determine the device scheduling and resource allocation information of the wireless monitoring system includes:
for all time slots in the monitoring period, the following steps are repeatedly executed for each time slot in sequence according to the time sequence:
solving the convex optimization problem by adopting an iterative calculation mode and based on a continuous convex approximation algorithm SCA until the total average information age gain of the wireless monitoring system in a time slot is converged to obtain betak,nFeasible solution of
Figure BDA0003237694940000311
rk,nFeasible solution of
Figure BDA0003237694940000312
And
Figure BDA0003237694940000313
feasible solution of
Figure BDA0003237694940000314
Wherein E isnThe total average information age gain of the wireless monitoring system in a time slot; based on
Figure BDA0003237694940000315
Calculating betak,nOf (2) an optimal solution
Figure BDA0003237694940000316
Based on
Figure BDA0003237694940000317
And
Figure BDA0003237694940000318
calculating pk,nOf (2) an optimal solution
Figure BDA0003237694940000319
Based on
Figure BDA00032376949400003110
Calculating to obtain alphak,nOf (2) an optimal solution
Figure BDA00032376949400003111
Based on
Figure BDA00032376949400003112
And
Figure BDA00032376949400003113
calculating fk,n+1Of (2) an optimal solution
Figure BDA00032376949400003114
Based on
Figure BDA00032376949400003115
Figure BDA00032376949400003116
And
Figure BDA00032376949400003117
calculation of As,k(n) and Ad,k(n); based on
Figure BDA00032376949400003118
And
Figure BDA00032376949400003119
calculating fn+1(ii) a Based on
Figure BDA00032376949400003120
Calculating Mn。
Optionally, the base is
Figure BDA00032376949400003121
Calculating betak,nOf (2) an optimal solution
Figure BDA00032376949400003122
Based on
Figure BDA00032376949400003123
And
Figure BDA00032376949400003124
calculating pk,nOf (2) an optimal solution
Figure BDA00032376949400003125
Based on
Figure BDA00032376949400003126
Calculating to obtain alphak,nOf (2) an optimal solution
Figure BDA00032376949400003127
Based on
Figure BDA00032376949400003128
And
Figure BDA00032376949400003129
calculating fk,n+1Of (2) an optimal solution
Figure BDA00032376949400003130
The method comprises the following steps:
based on
Figure BDA00032376949400003131
Beta is calculated by adopting a formula C16k,nOf (2) an optimal solution
Figure BDA00032376949400003132
C16：
Figure BDA00032376949400003133
Based on
Figure BDA00032376949400003134
And
Figure BDA00032376949400003135
p is calculated by adopting a formula C17-C20k,nOf (2) an optimal solution
Figure BDA00032376949400003136
C17：
Figure BDA00032376949400003137
C18：
Figure BDA00032376949400003138
C19：
Figure BDA0003237694940000321
C20：
Figure BDA0003237694940000322
Based on
Figure BDA0003237694940000323
And
Figure BDA0003237694940000324
f is calculated by the formula C21k,n+1Of (2) an optimal solution
Figure BDA0003237694940000325
C21：
Figure BDA0003237694940000326
Based on
Figure BDA0003237694940000327
Alpha is calculated by adopting a formula C22k,nOf (2) an optimal solution
Figure BDA0003237694940000328
C22：
Figure BDA0003237694940000329
Optionally, the device scheduling and resource allocation information includes at least one of: the information collection state, the scheduling state and the transmitting power of each device in each time slot in the wireless monitoring system, and the computing resources distributed to each device by the information processing server in each time slot.
Fig. 5 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 5: a processor (processor)510, a communication Interface (Communications Interface)520, a memory (memory)530 and a communication bus 540, wherein the processor 510, the communication Interface 520 and the memory 530 communicate with each other via the communication bus 540. Processor 510 may invoke logic instructions in memory 530 to perform a device scheduling and resource allocation method comprising: acquiring equipment information, transmission information and computing resources of a wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server; determining an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information and the computing resources; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period; and solving the optimization problem of the equipment scheduling and resource allocation, and determining the equipment scheduling and resource allocation information of the wireless monitoring system.
Furthermore, the logic instructions in the memory 530 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer being capable of executing the device scheduling and resource allocation method provided by the above methods, the method including: acquiring equipment information, transmission information and computing resources of a wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server; determining an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information and the computing resources; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period; and solving the optimization problem of the equipment scheduling and resource allocation, and determining the equipment scheduling and resource allocation information of the wireless monitoring system.
In yet another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program, when executed by a processor, implements the method for scheduling and allocating resources and performing the device scheduling and resource allocation provided by the foregoing embodiments, the method including: acquiring equipment information, transmission information and computing resources of a wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server; determining an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information and the computing resources; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period; and solving the optimization problem of the equipment scheduling and resource allocation, and determining the equipment scheduling and resource allocation information of the wireless monitoring system.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (9)

1. A method for scheduling and allocating resources for a device, comprising:
acquiring equipment information, transmission information and computing resources of a wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server;
determining an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information and the computing resources; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period;
and solving the optimization problem of the equipment scheduling and resource allocation, and determining the equipment scheduling and resource allocation information of the wireless monitoring system.
2. The method of claim 1, wherein the optimization problem of device scheduling and resource allocation is expressed as:
P0：
Figure FDA0003237694930000011
s.t.C1：
Figure FDA0003237694930000012
C2：
Figure FDA0003237694930000013
C3：
Figure FDA0003237694930000014
C4：
Figure FDA0003237694930000015
C5：
Figure FDA0003237694930000016
C6：
Figure FDA0003237694930000017
C7：
Figure FDA0003237694930000018
wherein P0 is an objective function of the optimization problem of the device scheduling and resource allocation, and C1 to C7 are constraints of the objective function P0; c3 is the access limit of the communication system, the access amount of the device in the communication system does not exceed the total number of sub-channels included in the communication system at any time; c4 is the transmit power limit of the device; c5 denotes a channel interference limit for guaranteeing the success rate of information transmission; c6 shows that the information transmitted to the network side network element by any equipment in any time slot can be processed by the information processing server at the next moment; c7 is a system meterCalculating resource constraints; the wireless monitoring system comprises K devices, at least one network side network element and an information processing server; m is the total number of orthogonal sub-channels included in the communication system; n is a time slot number, and n is a time slot number,
Figure FDA0003237694930000021
n is the number of time slots included in one monitoring period; pik(n)＝{αk.n,βk,n}；αk,nIndicating the information gathering status of device k at time slot n,
Figure FDA0003237694930000025
Figure FDA0003237694930000022
αk,n＝{0,1,2}，αk,nwith 0 denotes that the buffer of device k is empty and device k does not collect information at slot n, αk,n1 denotes that at time slot n device k collects information and stores it in the buffer of device k, αk,n2 means that the buffer of device k is not empty and device k does not collect information at slot n; beta is ak,nIndicating the scheduling of device k in time slot n, betak,n＝{0,1}，βk,n0 means that device k does not transmit information in time slot n, βk,n1 indicates that device k transmits information in time slot n; l iskThe amount of information to be transmitted for device k; rk,nFor the amount of information transmitted by device k in slot n,
Figure FDA0003237694930000023
pk,ntransmit power for device k at time slot n; p is the maximum transmit power of the device; h iskChannel gain of a subchannel occupied for device k; n is a radical of0Single-sided power spectral density; b is the channel bandwidth of the subchannel; gamma raythIs a channel signal-to-interference-and-noise ratio threshold;
Figure FDA0003237694930000024
dkis the distance between the device k and the base station, c is the speed of light, fcIs the carrier frequency; t is the time slot length;skthe number of CPU cycles required for the information processing server to process 1bit data; f. ofk,n+1Computing resources allocated to the device k for the information processing server in the time slot n + 1; f is the total amount of computing resources available for the information processing server; a. thes,k(n) is the information age of device k at the beginning of time slot n,
Figure FDA0003237694930000031
Qk(n) is the amount of buffered data for device k at the beginning of slot n,
Figure FDA0003237694930000032
Ad,k(n) is the information age of the device k at the information processing server at the end of the time slot n,
Figure FDA0003237694930000033
3. the method of claim 2, wherein the solving the optimization problem of the device scheduling and resource allocation to determine the device scheduling and resource allocation information of the wireless monitoring system comprises:
converting the optimization problem of the equipment scheduling and resource allocation into a convex optimization problem:
Px：
Figure FDA0003237694930000034
s.t.C8：
Figure FDA0003237694930000035
C9：
Figure FDA0003237694930000036
C10：
Figure FDA0003237694930000037
C11：
Figure FDA0003237694930000038
C12：
Figure FDA0003237694930000039
C13：
Figure FDA00032376949300000310
C14：
Figure FDA00032376949300000311
C15：
Figure FDA00032376949300000312
where Px is an objective function of the convex optimization problem, and C8 to C15 are constraint conditions of Px:
Figure FDA00032376949300000313
representing a set of equipment to be scheduled by a network element at a time slot n; f. ofn+1Computing resources available to the information processing server at time slot n + 1;
Figure FDA00032376949300000314
Figure FDA0003237694930000041
ε is an infinitesimal quantity greater than 0; χ is a penalty factor, χ > 1;
Figure FDA0003237694930000042
j is the number of iterations,
Figure FDA0003237694930000043
beta to satisfy the restrictions C8 and C9k,nAny one of (1) to (2)A value; mnThe number of channels available in the time slot n for the network element at the network side;
Figure FDA0003237694930000044
and solving the convex optimization problem, and determining equipment scheduling and resource allocation information of the wireless monitoring system.
4. The method of claim 3, wherein the solving the convex optimization problem to determine the device scheduling and resource allocation information of the wireless monitoring system comprises:
for all time slots in the monitoring period, the following steps are repeatedly executed for each time slot in sequence according to the time sequence:
solving the convex optimization problem by adopting an iterative calculation mode and based on a continuous convex approximation algorithm SCA until the total average information age gain of the wireless monitoring system in a time slot is converged to obtain betak,nFeasible solution of
Figure FDA0003237694930000045
rk,nFeasible solution of
Figure FDA0003237694930000046
And
Figure FDA0003237694930000047
feasible solution of
Figure FDA0003237694930000048
Wherein E isnThe total average information age gain of the wireless monitoring system in a time slot; based on
Figure FDA0003237694930000049
Calculating betak,nOf (2) an optimal solution
Figure FDA00032376949300000410
Based on
Figure FDA00032376949300000411
And
Figure FDA00032376949300000412
calculating pk,nOf (2) an optimal solution
Figure FDA00032376949300000413
Based on
Figure FDA00032376949300000414
Calculating to obtain alphak,nOf (2) an optimal solution
Figure FDA00032376949300000415
Based on
Figure FDA00032376949300000416
And
Figure FDA00032376949300000417
calculating fk,n+1Of (2) an optimal solution
Figure FDA00032376949300000418
Based on
Figure FDA00032376949300000419
And
Figure FDA00032376949300000420
calculation of As,k(n) and Ad,k(n); based on
Figure FDA00032376949300000421
And
Figure FDA00032376949300000422
calculating fn+1(ii) a Based on
Figure FDA00032376949300000423
Calculating Mn。
5. The method of claim 4, wherein the base station is based on
Figure FDA00032376949300000424
Calculating betak,nOf (2) an optimal solution
Figure FDA00032376949300000425
Based on
Figure FDA00032376949300000426
And
Figure FDA00032376949300000427
calculating pk,nOf (2) an optimal solution
Figure FDA0003237694930000051
Based on
Figure FDA0003237694930000052
Calculating to obtain alphak,nOf (2) an optimal solution
Figure FDA0003237694930000053
Based on
Figure FDA0003237694930000054
And
Figure FDA0003237694930000055
calculating fk,n+1Of (2) an optimal solution
Figure FDA0003237694930000056
The method comprises the following steps:
based on
Figure FDA0003237694930000057
Beta is calculated by adopting a formula C16k,nOf (2) an optimal solution
Figure FDA0003237694930000058
C16：
Figure FDA0003237694930000059
Based on
Figure FDA00032376949300000510
And
Figure FDA00032376949300000511
p is calculated by adopting a formula C17-C20k,nOf (2) an optimal solution
Figure FDA00032376949300000512
C17：
Figure FDA00032376949300000513
C18：
Figure FDA00032376949300000514
C19：
Figure FDA00032376949300000515
C20：
Figure FDA00032376949300000516
Based on
Figure FDA00032376949300000517
And
Figure FDA00032376949300000518
f is calculated by the formula C21k,n+1Of (2) an optimal solution
Figure FDA00032376949300000519
C21：
Figure FDA00032376949300000520
Based on
Figure FDA00032376949300000521
Alpha is calculated by adopting a formula C22k,nOf (2) an optimal solution
Figure FDA00032376949300000522
C22：
Figure FDA00032376949300000523
6. The device scheduling and resource allocation method according to any one of claims 1 to 5, wherein the device scheduling and resource allocation information comprises at least one of:
the information collection state, the scheduling state and the transmitting power of each device in each time slot in the wireless monitoring system, and the computing resources distributed to each device by the information processing server in each time slot.
7. An apparatus for scheduling and allocating resources, comprising:
the acquisition module is used for acquiring equipment information, transmission information and computing resources of the wireless monitoring system; wherein the device information includes: the distance between the equipment and a network element at the network side, the maximum transmitting power of the equipment, the transmission information content of the equipment and the unilateral power spectrum density; the transmission information includes: time slot length, channel bandwidth of sub-channel, carrier frequency and channel signal-to-interference-and-noise ratio threshold; the computing resources comprise computing resources available to an information processing server;
a determining module, configured to determine an optimization problem of device scheduling and resource allocation of the wireless monitoring system based on the device information, the transmission information, and the computing resource; the optimization problem of the equipment scheduling and the resource allocation is the problem of minimizing the total information age of a wireless monitoring system in a monitoring period;
and the solving module is used for solving the optimization problem of the equipment scheduling and resource allocation, determining the information collection state, the scheduling state and the transmitting power of each equipment in each time slot in the wireless monitoring system, and determining the computing resources allocated to each equipment by the information processing server in each time slot.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the device scheduling and resource allocation method according to any of claims 1 to 6.
9. A non-transitory computer readable storage medium, having stored thereon a computer program, when being executed by a processor, for implementing the steps of the method for scheduling and resource allocation of a device according to any one of claims 1 to 6.
CN202111007418.1A 2021-08-30 2021-08-30 Equipment scheduling and resource allocation method and device, electronic equipment and storage medium Active CN113811007B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111007418.1A CN113811007B (en) 2021-08-30 2021-08-30 Equipment scheduling and resource allocation method and device, electronic equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111007418.1A CN113811007B (en) 2021-08-30 2021-08-30 Equipment scheduling and resource allocation method and device, electronic equipment and storage medium

Publications (2)

Publication Number Publication Date
CN113811007A true CN113811007A (en) 2021-12-17
CN113811007B CN113811007B (en) 2023-07-28

Family

ID=78941908

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111007418.1A Active CN113811007B (en) 2021-08-30 2021-08-30 Equipment scheduling and resource allocation method and device, electronic equipment and storage medium

Country Status (1)

Country Link
CN (1) CN113811007B (en)

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070297327A1 (en) * 2006-06-27 2007-12-27 International Business Machines Corporation Method for applying stochastic control optimization for messaging systems
US20110046837A1 (en) * 2009-08-19 2011-02-24 Deepak Khosla System and method for resource allocation and management
RU2015125820A (en) * 2015-06-30 2017-01-10 Общество С Ограниченной Ответственностью "Яндекс" METHOD AND SERVER FOR PROCESSING USER REQUEST FOR PROVIDING RECOMMENDED AREA OF INTEREST
CN110380773A (en) * 2019-06-13 2019-10-25 广东工业大学 A kind of track optimizing and resource allocation methods of unmanned plane multi-hop relay communication system
CN111328144A (en) * 2020-01-20 2020-06-23 赣江新区智慧物联研究院有限公司 Wireless resource allocation method, device, readable storage medium and computer equipment
US20200214009A1 (en) * 2017-09-15 2020-07-02 Huawei Technologies Co., Ltd. Transmission resource allocation method and apparatus
CN112509684A (en) * 2020-12-31 2021-03-16 曜立科技(北京)有限公司 Medical resource allocation method and system based on big data
CN112911555A (en) * 2021-01-28 2021-06-04 上海交通大学 Wireless network communication resource scheduling method and system based on information age
US20210266834A1 (en) * 2020-02-25 2021-08-26 South China University Of Technology METHOD OF MULTI-ACCESS EDGE COMPUTING TASK OFFLOADING BASED ON D2D IN INTERNET OF VEHICLES (IoV) ENVIRONMENT

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070297327A1 (en) * 2006-06-27 2007-12-27 International Business Machines Corporation Method for applying stochastic control optimization for messaging systems
US20110046837A1 (en) * 2009-08-19 2011-02-24 Deepak Khosla System and method for resource allocation and management
RU2015125820A (en) * 2015-06-30 2017-01-10 Общество С Ограниченной Ответственностью "Яндекс" METHOD AND SERVER FOR PROCESSING USER REQUEST FOR PROVIDING RECOMMENDED AREA OF INTEREST
US20200214009A1 (en) * 2017-09-15 2020-07-02 Huawei Technologies Co., Ltd. Transmission resource allocation method and apparatus
CN110380773A (en) * 2019-06-13 2019-10-25 广东工业大学 A kind of track optimizing and resource allocation methods of unmanned plane multi-hop relay communication system
CN111328144A (en) * 2020-01-20 2020-06-23 赣江新区智慧物联研究院有限公司 Wireless resource allocation method, device, readable storage medium and computer equipment
US20210266834A1 (en) * 2020-02-25 2021-08-26 South China University Of Technology METHOD OF MULTI-ACCESS EDGE COMPUTING TASK OFFLOADING BASED ON D2D IN INTERNET OF VEHICLES (IoV) ENVIRONMENT
CN112509684A (en) * 2020-12-31 2021-03-16 曜立科技(北京)有限公司 Medical resource allocation method and system based on big data
CN112911555A (en) * 2021-01-28 2021-06-04 上海交通大学 Wireless network communication resource scheduling method and system based on information age

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
MINGYAN LI等: "Learning-Based Autonomous Scheduling for AoI-Aware Industrial Wireless Networks", IEEE INTERNET OF THINGS JOURNAL *
左雨星;郭爱煌;黄博;王露;: "基于网络效用最大化的车联网功率控制算法", 计算机应用, no. 12 *
李世超;王秋云;寇为刚;贺国庆;: "基于车辆边缘计算的用户能耗最小化资源分配研究", 电子科技大学学报, no. 02 *

Also Published As

Publication number Publication date
CN113811007B (en) 2023-07-28

Similar Documents

Publication Publication Date Title
Alsenwi et al. Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond: A deep reinforcement learning based approach
CN103699446B (en) Quantum-behaved particle swarm optimization (QPSO) algorithm based multi-objective dynamic workflow scheduling method
CN112105062B (en) Mobile edge computing network energy consumption minimization strategy method under time-sensitive condition
CN104901989B (en) A kind of Site Service offer system and method
CN100576177C (en) Bidirectional grade gridding resource scheduling method based on the QoS constraint
CN105379412B (en) A kind of system and method controlling multiple radio access nodes
CN105718479A (en) Execution strategy generation method and device under cross-IDC (Internet Data Center) big data processing architecture
CN107748696A (en) The method and terminal device of a kind of task scheduling
CN110096362A (en) A kind of multitask discharging method based on Edge Server cooperation
CN111866954A (en) User selection and resource allocation method based on federal learning
CN111385142B (en) Kubernetes-based adaptive web container stretching method
CN111328146B (en) Service scheduling method for optimizing transmission rate weight based on genetic algorithm
Zhang et al. Joint spectrum reservation and on-demand request for mobile virtual network operators
Kopras et al. Task allocation for energy optimization in fog computing networks with latency constraints
CN116366576A (en) Method, device, equipment and medium for scheduling computing power network resources
CN112867162B (en) Slice resource allocation method and device
Wang et al. Joint service caching, resource allocation and computation offloading in three-tier cooperative mobile edge computing system
CN113811007A (en) Method and device for scheduling equipment and allocating resources, electronic equipment and storage medium
CN114222371A (en) Flow scheduling method for coexistence of eMBB (enhanced multimedia broadcast/multicast service) and uRLLC (unified radio link control) equipment
CN113840333A (en) Power grid resource allocation method and device, electronic equipment and storage medium
WO2023222061A1 (en) Intent-driven wireless network resource conflict resolution method and apparatus
Sun et al. Bandwidth estimation for aggregate traffic under delay QoS constraint based on supermartingale theory
WO2018072259A1 (en) Resource scheduling method and device
Wang et al. A virtual control layer resource allocation framework for heterogeneous cognitive radio network
WO2021185194A1 (en) Electronic device and method for wireless communication, and computer readable storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant