A method and device for controlling the timeliness of an environmental monitoring system under current storage scheduling

Abstract

The present invention discloses a method and device for regulating the timeliness of an environmental monitoring system under flow storage scheduling, which belongs to the technical field of timeliness detection of environmental monitoring systems. The method includes obtaining the flow storage scheduling period and the real-time data packet generation probability of the environmental monitoring system; calculating the flow storage information age according to the flow storage scheduling period and the real-time data packet generation probability, and the flow storage information age is the information age of the environmental monitoring system under flow storage scheduling; if the flow storage information age is greater than a preset timeliness threshold, the flow storage scheduling period is regulated until the flow storage information age is less than or equal to the preset timeliness threshold, and the timeliness regulation is completed. The present invention quantitatively analyzes the timeliness of the environmental monitoring system under flow storage scheduling by introducing the flow storage information age, judges the level of timeliness according to the size of the flow storage information age, accurately reflects the timeliness, and thereby realizes accurate regulation of the timeliness of the environmental monitoring system by regulating the flow storage information age.

Description

Technical Field

[0001] The invention relates to a method and a device for regulating the timeliness of an environmental monitoring system under current storage dispatching, and belongs to the technical field of timeliness detection of environmental monitoring systems. Background Art

[0002] In the environmental monitoring system of the Internet of Things (IoT), many scenarios have high requirements for real-time data, such as water pollution detection and air pollution monitoring. Uncontrollable delays may affect the efficiency and accuracy of the environmental monitoring system. However, current research lacks effective methods to achieve the timeliness regulation of environmental monitoring systems in the Internet of Things. Summary of the invention

[0003] The purpose of the present invention is to provide a method and device for regulating the timeliness of an environmental monitoring system under current storage scheduling, so as to achieve effective regulation of the timeliness of an environmental monitoring system in the Internet of Things.

[0004] To achieve the above objectives, the present invention is implemented by adopting the following technical solutions:

[0005] In a first aspect, the present invention provides a method for controlling the timeliness of an environmental monitoring system under current storage scheduling, comprising:

[0006] Obtain the storage flow scheduling period and real-time data packet generation probability of the environmental monitoring system;

[0007] Calculate the storage flow information age according to the storage flow scheduling cycle and the real-time data packet generation probability, wherein the storage flow information age is the information age of the environmental monitoring system under the storage flow scheduling;

[0008] If the age of the current storage information is greater than a preset timeliness threshold, the current storage scheduling period is regulated until the age of the current storage information is less than or equal to the preset timeliness threshold, and the timeliness regulation is completed.

[0009] Furthermore, the real-time data packet generation probability is obtained by the following method:

[0010] Obtain the time slots corresponding to each data packet collected by the environmental monitoring system under the storage flow scheduling, as well as the total number of data packets collected in the current time slot, and calculate the real-time data packet collection probability according to the time slots corresponding to each data packet and the total number of data packets collected in the current time slot;

[0011] Obtain all data packet generation intervals, group multiple data packet generation intervals corresponding to multiple recently generated data packets into adjacent generation interval groups, obtain the statistical distribution of the adjacent generation interval groups, calculate the probability distribution of all data packet generation intervals, compare whether the statistical distribution and the probability distribution are consistent, if they are consistent, use the real-time data packet collection probability as the real-time data packet generation probability, if not, recalculate the real-time data packet collection probability and perform the comparison until the comparison result is consistent.

[0012] Furthermore, the real-time data packet collection probability is calculated according to the time slots corresponding to each data packet and the total number of data packets collected in the current time slot, and is performed by the following formula:

[0013] ;

[0014] Among them, p ga is the real-time packet acquisition probability, S is the total number of data packets collected in the current time slot, n l is the time slot corresponding to the lth data packet.

[0015] Furthermore, the probability distribution of all data packet generation intervals is calculated using the following formula:

[0016] ;

[0017] Among them, X i is the i-th packet generation interval, slt is the duration of the time slot occupied by the preset packet generation interval, P(X i =slt) is the interval X between the i-th data packet generation i The probability distribution of ga is the real-time packet acquisition probability, N + Represents the set of positive integers.

[0018] Furthermore, the comparison of whether the statistical distribution is consistent with the probability distribution is performed by the following method:

[0019] The consistency index of the statistical distribution and the probability distribution is calculated by the following formula:

[0020] ;

[0021] Where O(o) is the consistency index, o is the range factor, slt is the duration corresponding to the number of time slots occupied by the preset packet generation interval, P(X i =slt) is the interval X between the i-th data packet generation i The probability distribution of P(X ner-Z =slt) is the statistical distribution of the adjacent generation interval group, X ner-Zis the neighboring generation interval group;

[0022] X ner-Z The expression is:

[0023] ;

[0024] Among them, X S Indicates the packet generation interval between the latest packet generated in the current time slot and the last packet generated. The latest packet generated in the current time slot is the first packet in history. S-Z+1 Indicates the packet generation interval corresponding to the Z+1th packet in history, X S-Z+2 Indicates the data packet generation interval corresponding to the historical Z+2 data packet;

[0025] If the consistency index is less than or equal to a preset consistency threshold, the statistical distribution is consistent with the probability distribution; otherwise, the statistical distribution is inconsistent with the probability distribution.

[0026] Furthermore, the calculation of the storage flow information age according to the storage flow scheduling cycle and the real-time data packet generation probability is performed by the following formula:

[0027] ;

[0028] Where Δ is the storage information age, B is the storage scheduling period, and p ge is the real-time packet generation probability.

[0029] Furthermore, the regulating the current storage scheduling period includes a first-level regulation, and the first-level regulation includes:

[0030] Adjust the storage scheduling period to the interval [1, B max ]Inside;

[0031] Among them, B max is the maximum storage current dispatch period, which is calculated by the following formula:

[0032] ;

[0033] Among them, p ge is the real-time packet generation probability, Δ max is the preset maximum value of the storage current information age, Indicates rounding down.

[0034] Furthermore, the regulating the current storage scheduling period also includes a second layer of regulation provided after the first layer of regulation, and the second layer of regulation includes:

[0035] If after the first level of regulation, the storage information age is in the interval [Δ L , ΔH ], adjust the storage scheduling period to the interval [B L-max , B H-max ]Inside;

[0036] Among them, Δ L is the low timeliness threshold of the environmental monitoring system, Δ H is the high timeliness threshold of the environmental monitoring system, B L-max is the lower limit of the storage scheduling cycle when the environmental monitoring system is in the low timeliness mode, B H-max It is the upper limit of the storage scheduling cycle when the environmental monitoring system is in the low timeliness mode;

[0037] The lower limit of the storage scheduling period is calculated by the following formula:

[0038] ;

[0039] The upper limit of the storage scheduling period is calculated by the following formula:

[0040] .

[0041] Furthermore, the regulating the current storage scheduling period also includes a third layer of regulation arranged after the second layer of regulation, and the third layer of regulation includes:

[0042] If after the second layer of regulation, the storage information age is in the interval [Δ E , Δ L ], adjust the storage scheduling period to the interval [B E-max , B L-max ]Inside;

[0043] Among them, Δ E is the ultimate timeliness of the environmental monitoring system, B E-max is the lower limit of energy consumption during the storage scheduling period;

[0044] The lower limit of energy consumption during the storage scheduling period is calculated by the following formula:

[0045] .

[0046] In a second aspect, the present invention provides a timeliness control device for an environmental monitoring system under current storage scheduling, comprising:

[0047] The data acquisition module is configured to: acquire the storage flow scheduling period and real-time data packet generation probability of the environmental monitoring system;

[0048] The storage flow information age calculation module is configured to: calculate the storage flow information age according to the storage flow scheduling cycle and the real-time data packet generation probability, wherein the storage flow information age is the information age of the environmental monitoring system under the storage flow scheduling;

[0049] The timeliness regulation module is configured to: if the age of the current storage information is greater than a preset timeliness threshold, regulate the current storage scheduling period until the age of the current storage information is less than or equal to the preset timeliness threshold, thereby completing the timeliness regulation.

[0050] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0051] The present invention provides a method and device for regulating the timeliness of an environmental monitoring system under flow storage scheduling. The timeliness of the environmental monitoring system under flow storage scheduling is quantitatively analyzed by introducing the flow storage information age. The timeliness is judged by the size of the flow storage information age, and the timeliness is accurately reflected. Thus, the timeliness of the environmental monitoring system is accurately regulated by regulating the flow storage information age. A simple and effective method for regulating the timeliness of an environmental monitoring system is provided, which improves the response speed of the environmental monitoring system, enables the environmental monitoring system to be applied in a variety of Internet of Things environments, and is particularly suitable for water pollution detection, air pollution monitoring and other scenarios with high real-time requirements, and further promotes the development of Internet of Things environmental monitoring technology.

[0052] By performing statistical analysis on packet generation intervals, verifying the accuracy of real-time packet collection probability and other operations, timely data collection and transmission are guaranteed, which helps reduce system latency and improve the response speed and real-time performance of the entire environmental monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flow chart of a method for timeliness control of an environmental monitoring system under current storage scheduling corresponding to Embodiment 1 of the present invention;

[0054] Figure 2 It is a flow chart of a method for timeliness control of an environmental monitoring system under current storage scheduling corresponding to Embodiment 2 of the present invention;

[0055] Figure 3 Schematic diagram of the relationship between the storage information age and the storage scheduling period of the environmental monitoring system under the storage scheduling provided by the embodiment of the present invention; wherein, p ge is the real-time packet generation probability, B is the storage scheduling period, SAoI is the storage information age, B and SAoI are characterized by the number of time slots, and each grid in the figure represents the corresponding number of time slots;

[0056] Figure 4 Schematic diagram of the relationship between the storage flow information age and the real-time data packet generation probability of the environmental monitoring system under the storage flow scheduling provided by the embodiment of the present invention;

[0057] Figure 5is a schematic diagram of the relationship between different real-time data packet generation probabilities and the maximum storage flow scheduling period under the storage flow scheduling provided by an embodiment of the present invention; wherein, B max It is the maximum storage flow scheduling period, which is also represented by the number of time slots. DETAILED DESCRIPTION

[0058] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the protection scope of the present invention.

[0059] Example 1

[0060] like Figure 1 As shown, the present invention provides a method for controlling the timeliness of an environmental monitoring system under current storage scheduling, comprising:

[0061] Obtain the storage flow scheduling period and real-time data packet generation probability of the environmental monitoring system;

[0062] Calculate the storage flow information age according to the storage flow scheduling cycle and the real-time data packet generation probability; the storage flow information age is the information age of the environmental monitoring system under the storage flow scheduling;

[0063] If the age of the current storage information is greater than a preset timeliness threshold, the current storage scheduling period is regulated until the age of the current storage information is less than or equal to the preset timeliness threshold, and the timeliness regulation is completed.

[0064] The present invention introduces the storage flow information age to conduct quantitative analysis on the timeliness of the environmental monitoring system under storage flow scheduling, judges the timeliness by the size of the storage flow information age, and accurately reflects the timeliness, thereby realizing accurate regulation of the timeliness of the environmental monitoring system by regulating the storage flow information age, providing a simple and effective method for regulating the timeliness of the environmental monitoring system, improving the response speed of the environmental monitoring system, and enabling the environmental monitoring system to be applied in a variety of Internet of Things environments, especially suitable for water pollution detection, air pollution monitoring and other scenarios with high real-time requirements, further promoting the development of Internet of Things environmental monitoring technology.

[0065] Example 2

[0066] like Figure 2 As shown, the present invention provides a method for timeliness control of an environmental monitoring system under current storage scheduling, and its specific implementation includes the following steps S1 to S8.

[0067] S1. Define the storage flow scheduling mode and set the real-time data packet collection probability of the environmental monitoring system to detect the real-time data packet generation probability of the environmental monitoring system in real time.

[0068] Storage flow scheduling refers to the information scheduling mode in which the environmental monitoring system in the Internet of Things completes the transmission of all A data packets at once in the next transmission time slot after collecting A data packets. It is widely used in environmental monitoring systems in the Internet of Things. This paper defines and explains the relevant parameters of the information transmission mode of the environmental monitoring system in the Internet of Things under storage flow scheduling, and paves the way for the subsequent application of the SAoI (Storage Age of Information) formula and system timeliness regulation of the environmental monitoring system under storage flow scheduling: the sensor has the probability of monitoring environmental changes and collecting environmental status information in each time slot, and composing the environmental status information into data packets. According to the speed of environmental changes and system requirements, the real-time upload rate of the sensor (i.e., the real-time data packet collection probability p) ga ) is dynamically changing.

[0069] In the environmental monitoring system, p is calculated according to the following formula ga Values:

[0070] ;

[0071] Among them, p ga is the real-time packet acquisition probability, S is the total number of data packets collected in the current time slot, n l is the time slot corresponding to the lth data packet.

[0072] S2. Calculate the fixed network overhead time interval of the environmental monitoring system, and then obtain the current storage scheduling interval time of the environmental monitoring system.

[0073] Each collected data packet will be transmitted to the central server of the environmental monitoring system through the dispatching control module in the environmental monitoring system, and the collected data packets will be numbered and recorded as: , where n 1 、n 2 、n A 、n A+1 、n kA They represent the time slots corresponding to the 1st, 2nd, A, A+1, and kA data packets (data packets containing collected information), respectively. k is an integer, indicating the kth flow storage scheduling. Whenever A data packets are generated, the environmental monitoring system will transmit these A data packets from the sensor local buffer to the central server in the next time slot. Multiple sensor nodes store their collected data packets in the node's local buffer. When the number of data packets reaches A, the environmental monitoring system will trigger the flow storage scheduling and send these data packets to the central server in the next time slot, and the cycle will repeat. The interval for generating the i-th data packet is recorded as X i ,and , N + represents a set of positive integers, ni 、n i+1 They represent the time slots corresponding to the i-th and i+1-th data packets respectively.

[0074] According to the transmission difference of the environmental monitoring system, the fixed network overhead time interval T of the environmental monitoring system under storage scheduling is calculated. net , and its calculation formula is as follows:

[0075] ;

[0076] Among them, n ss (k) represents the time slot corresponding to the kth triggering of the current storage scheduling, M represents the total number of current storage scheduling, n 0 Indicates the start time slot of the first storage scheduling cycle, n ss (0) represents the time slot number when the environmental monitoring system is in the initial state. The subscript 0 corresponds to the initial position of the environmental monitoring system. At this time, the interpretation of the corresponding symbols does not apply to the above general explanation.

[0077] The fixed network overhead transmission time interval includes the handshake and connection establishment time between devices in information transmission. The storage scheduling interval time of the kth storage scheduling cycle of the environmental monitoring system is obtained, which is recorded as Y k , and its calculation formula is:

[0078] ;

[0079] Among them, n (k-1)A represents the time slot corresponding to the (k-1)Ath data packet (the data packet containing the collected information), n ss (k-1) represents the time slot corresponding to the k-1th triggering of current storage scheduling.

[0080] The flow storage scheduling interval in each flow storage scheduling week depends on the size of the flow storage scheduling cycle and the real-time data packet collection probability of the sensors in the environmental monitoring system.

[0081] S3. Count the probability distribution of the real-time data packet generation interval, verify whether the real-time data packet collection probability is accurate through the probability distribution formula, and finally output the real-time data packet generation probability.

[0082] The environmental monitoring system records the data packet generation interval in real time, and records the data packet generation intervals corresponding to the most recently generated Z+1 data packets to form an adjacent generation interval group, denoted as X ner-Z , whose expression is:

[0083] ;

[0084] Among them, X SIndicates the packet generation interval corresponding to the latest packet generated in the current time slot (the packet generation interval between this packet and the last generated packet). The latest packet generated in the current time slot is the first packet in history. S-Z+1 Indicates the packet generation interval corresponding to the Z+1th packet in history (the packet generation interval between this packet and the last generated packet), X S-Z+2 represents the data packet generation interval corresponding to the Z+2th data packet in history. The adjacent generation interval group is composed of the Z nearest data packet generation intervals. Through the function of the environmental monitoring system itself, after recording the data packet generation interval, the environmental monitoring system counts the statistical distribution of the data packet generation interval corresponding to the adjacent generation interval group, which is recorded as P(X ner-Z =slt).

[0085] The probability distribution of the packet generation interval is given by the following formula:

[0086] ; Among them, X i is the i-th packet generation interval, slt is the duration corresponding to the number of time slots occupied by the preset packet generation interval, P(X i =slt) is the interval X between the i-th data packet generation i The probability distribution of X i The probability of being equal to slt, p ga is the real-time packet acquisition probability, N + Represents the set of positive integers.

[0087] The statistical distribution indicates the probability that a certain data packet generation interval measured by the environmental monitoring system is equal to slt, which is measured by the environmental monitoring system itself. The probability distribution indicates the probability that a certain data packet generation interval is equal to slt calculated by the formula, which is calculated by the above calculation formula. This is equivalent to the statistical distribution being the result of the measurement, and the probability distribution being the result of the prediction. The statistical distribution and the probability distribution will be compared later.

[0088] Comparing the statistical distribution of the adjacent generation interval group and the probability distribution of the data packet generation interval to see if they are consistent is performed by the following method:

[0089] The consistency index of the statistical distribution of the adjacent generation interval group and the probability distribution of the packet generation interval is calculated by the following formula:

[0090] ;

[0091] Where O(o) is the consistency index, o is the range factor, slt is the duration of the time slot occupied by the preset data packet generation interval, P(X i =slt) is the interval X between the i-th data packet generation iThe probability distribution of P(X ner-Z =slt) is the statistical distribution of the adjacent generation interval group, X ner-Z is the neighboring generation interval group;

[0092] If the consistency index is less than or equal to the preset consistency threshold, which can be set to 0.15, the statistical distribution of the adjacent generation interval group and the probability distribution of the data packet generation interval are consistent, otherwise the statistical distribution of the adjacent generation interval group and the probability distribution of the data packet generation interval are inconsistent; if they are consistent, the real-time data packet collection probability is used as the real-time data packet generation probability; if they are inconsistent, the real-time data packet collection probability is recalculated and the above comparison is performed until the result of the above comparison is consistent.

[0093] S4. Introduce the storage information age, and concretize the universal formula into the SAoI (storage information age) formula to describe the timeliness of the system (i.e. calculate the storage information age).

[0094] The age of information (AoI) is a quantitative indicator that describes the timeliness of information. It is used to measure the freshness of information at the destination node. For the environmental monitoring system in the Internet of Things under storage scheduling, a corresponding timeliness measurement indicator is creatively proposed: SAoI (Storage Age of Information).

[0095] The calculation formula of storage information age is defined as:

[0096] ;

[0097] Among them, Δ( t ) indicates the t The storage information age of the environmental monitoring system at each time slot is calculated by dividing the time slot from the start time of the first storage scheduling cycle to the time slot corresponding to the first triggering of storage scheduling. n ss The area under the information age curve in the time interval (1) is denoted as Q 0 .

[0098] The calculation formula of the storage information age of the environmental monitoring system under storage scheduling can be converted and derived as follows:

[0099] ;

[0100] ;

[0101] ;

[0102] in, Abbreviation for because and so, Δ τrepresents the average storage information age of the environmental monitoring system in the τ time interval, and the storage information age of the environmental monitoring system (i.e., Δ) is the extreme value of the ratio of the area enclosed by the information age curve and the time axis to the time length when τ tends to infinity. N(τ) represents the total number of storage dispatches triggered in the τ time interval. E () indicates the mean value. Q Refers to Q 1 , Q 2 , …, Q N(τ) , E ( Q ) means to ask Q 1 , Q 2 , …, Q N(τ) The mean of λ B Indicates the frequency of triggering current storage scheduling, Y represents the interval time of storage flow scheduling, represents the residual value of the last storage flow scheduling, B is the storage scheduling period, X i+1 It is i +1 packet generation interval, X i+(B-1) It is i +( B -1) packet generation interval.

[0103] The universal formula is concretized into the calculation formula of SAoI, which is used to quantify the timeliness of the environmental monitoring system under flow storage scheduling. The SAoI value of the environmental monitoring system directly reflects the timeliness of the system data transmission: the larger the SAoI value, the worse the system timeliness under flow storage scheduling; the smaller the SAoI value, the better the system timeliness under flow storage scheduling.

[0104] like Figure 3 As shown, it shows p ge When it is equal to 0.2, 0.5 and 0.8, the relationship between the SAoI of the environmental monitoring system under the storage flow scheduling and the storage flow scheduling period B can be obtained according to the SAoI formula under the storage flow scheduling. ge The SAoI value of the system under Figure 3 Table 1 is obtained by sampling:

[0105] Table 1 - Relationship between SAoI of environmental monitoring system and storage scheduling cycle B

[0106]

[0107] From Table 1 and Figure 3 It can be seen that the SAoI of the environmental monitoring system under flow storage scheduling is closely related to the flow storage scheduling period B. Under the same real-time data packet generation probability, the larger the flow storage scheduling period, the larger the SAoI value of the system, and the worse the timeliness of the system. This shows that when the real-time data packet generation rate remains unchanged, reducing the flow storage scheduling period as much as possible can significantly improve the timeliness of the system.

[0108] like Figure 4 As shown in the figure, the SAoI of the environmental monitoring system under the storage flow scheduling and the real-time data packet generation probability p are shown when B is equal to 5, 50, and 500. ge According to the SAoI formula under the above storage scheduling, we can get any storage scheduling period B and the real-time data packet generation probability p ge The SAoI values ​​of the systems under are sampled from Table 2:

[0109] Table 2 - SAoI and real-time packet generation probability p of environmental monitoring system ge Relationship table

[0110]

[0111] From Table 2 and Figure 4 It can be seen that the SAoI of the environmental monitoring system under storage flow scheduling is related to the probability of packet generation p ge There is a close relationship between them. Under the same flow storage scheduling cycle, the greater the probability of real-time data packet generation, the smaller the SAoI value of the environmental monitoring system, and the better the timeliness of the environmental monitoring system. This shows that when the flow storage scheduling cycle remains unchanged, increasing the real-time data packet acquisition rate as much as possible can significantly improve the timeliness of the environmental monitoring system. It also further reflects the advantages of flow storage scheduling in dealing with high-speed transmission of environmental monitoring systems.

[0112] S5. According to the SAoI formula, the formula for the real-time maximum storage flow scheduling period of the system is obtained, and then the value range of the storage flow scheduling period B of the environmental monitoring system in the Internet of Things is obtained.

[0113] Set the timeliness threshold of the environmental monitoring system in the Internet of Things (the preset maximum age of the storage information) to Δ max , the maximum storage scheduling period B of the system can be obtained from the SAoI formula under storage scheduling max The calculation formula is as follows:

[0114] ;

[0115] Among them, p ge is the real-time packet generation probability, Δ max is the preset maximum value of the storage current information age, Indicates rounding down.

[0116] The value range of the storage flow scheduling period B that meets the timeliness requirements of the environmental monitoring system can be obtained as follows:

[0117] ;

[0118] Among them, B rg is the value range of the storage scheduling period B.

[0119] The environmental monitoring system in the Internet of Things under storage flow scheduling can be realized under different timeliness thresholds through the SAoI formula under storage flow scheduling and the maximum storage flow scheduling cycle B of the system. max The calculation formula is used to obtain the value range of the storage current scheduling period B.

[0120] like Figure 5 As shown, it shows , when the timeliness threshold of the environmental monitoring system Δ max =20, according to the above maximum storage current scheduling cycle B max The maximum storage flow scheduling cycle dot diagram obtained by the calculation formula, the corresponding maximum storage flow scheduling cycle for:

[0121] ;

[0122] Depend on Figure 5 It can be seen that the maximum current storage scheduling period under different timeliness thresholds of the environmental monitoring system in the Internet of Things can be easily obtained through the provided formula. By adjusting the current storage scheduling period of the environmental monitoring system to be no greater than the maximum current storage scheduling period, the environmental monitoring system can be effectively controlled to ensure that the system timeliness meets the requirements when transmitting data.

[0123] S6. When the environmental monitoring system is in the low timeliness mode, the low timeliness interval of the environmental monitoring system is recorded, and the value range of the low timeliness storage scheduling period B and the optimal storage scheduling period are calculated.

[0124] When the environmental monitoring system is in low timeliness mode, the low timeliness interval of the recording system is: ,in, Indicates the low timeliness threshold of the environmental monitoring system, It represents the high timeliness threshold of the environmental monitoring system. The value range of the low timeliness storage flow scheduling period B is calculated by the real-time data packet generation probability and the maximum storage flow scheduling period formula:

[0125] ;

[0126] ;

[0127] ;

[0128] in, represents the lower limit of the storage scheduling period, represents the upper limit of the storage scheduling period, Represents the value range of the current storage scheduling period B in the low timeliness mode; among them, the optimal current storage scheduling period is the one with the lowest scheduling energy consumption while meeting the system timeliness requirements.

[0129] S7. When the environmental monitoring system is in high timeliness mode, record the high timeliness interval of the environmental monitoring system, calculate the value range of the high timeliness current storage scheduling period B, the optimal current storage scheduling period, and the system's extreme timeliness and extreme current storage scheduling period.

[0130] When the environmental monitoring system is in high timeliness mode, the high timeliness threshold of the environmental monitoring system is recorded: ,in, is the energy consumption load threshold of the environmental monitoring system; the value range of the high-timeliness storage flow scheduling period B is calculated by the real-time data packet generation probability and the maximum storage flow scheduling period formula:

[0131] ;

[0132] ;

[0133] in, Indicates the lower limit of energy consumption during the storage scheduling period; represents the value range of the storage scheduling period B in the high timeliness mode; among them, the optimal storage scheduling period is , the scheduling energy consumption is the lowest while meeting the timeliness requirements of the environmental monitoring system; the ultimate timeliness of the environmental monitoring system is , in the limit mode, the limit current storage scheduling period of the environmental monitoring system is .

[0134] S8, regulating according to each interval calculated by S5, S6, and S7.

[0135] Including the first level of regulation:

[0136] Adjust the storage scheduling period to the interval [1, B max ]Inside.

[0137] It also includes a second layer of regulation set after the first layer of regulation, and the second layer of regulation includes:

[0138] If after the first level of regulation, the storage information age is in the interval [Δ L , Δ H], adjust the storage scheduling period to the interval [B L-max , B H-max ]Inside.

[0139] It also includes a third-level regulation that is set after the second-level regulation. The third-level regulation includes:

[0140] If the storage information age after the second layer of regulation is in the interval [Δ E , Δ L ], adjust the storage scheduling period to the interval [B E-max , B L-max ]Inside.

[0141] In summary, the beneficial effects of the present invention are embodied in the following aspects:

[0142] Accurately control the timeliness: By clarifying the storage flow scheduling mode and dynamically adjusting the storage flow scheduling cycle of the environmental monitoring system, it is helpful to accurately control the timeliness of the environmental monitoring system and make it better adapt to different environments and needs;

[0143] Scientifically quantify timeliness: Introduce the storage age of information (SAoI), a timeliness measurement indicator specifically for environmental monitoring systems under storage scheduling, to facilitate intuitive understanding of the timeliness of system data transmission, and then judge the timeliness based on the size of the SAoI value;

[0144] Improve system response speed: By conducting statistical analysis on packet generation intervals, verifying the accuracy of real-time packet collection probability, and other operations, timely data collection and transmission are guaranteed, which helps reduce system latency and improve the response speed and real-time performance of the entire environmental monitoring system.

[0145] Optimize resource allocation: Consider factors such as the fixed network overhead time interval of transmission to obtain the storage flow scheduling interval, and through a series of control methods of the present invention, on the basis of ensuring the timeliness of the system, reasonably arrange the storage flow scheduling, reduce unnecessary transmission, reduce the occupation of communication resources, and achieve the effect of saving communication resources and optimizing the use of system resources;

[0146] Through these beneficial effects, the present invention demonstrates significant advantages in the timeliness regulation of environmental monitoring systems, providing effective technical support for improving system performance, optimizing resource utilization, and promoting industry development.

[0147] Example 3

[0148] The present invention provides a time-effectiveness control device for an environmental monitoring system under current storage scheduling, comprising:

[0149] The data acquisition module is configured to: acquire the storage flow scheduling period and real-time data packet generation probability of the environmental monitoring system;

[0150] The storage flow information age calculation module is configured to: calculate the storage flow information age according to the storage flow scheduling cycle and the real-time data packet generation probability, wherein the storage flow information age is the information age of the environmental monitoring system under the storage flow scheduling;

[0151] The timeliness regulation module is configured to: if the age of the current storage information is greater than a preset timeliness threshold, regulate the current storage scheduling period until the age of the current storage information is less than or equal to the preset timeliness threshold, thereby completing the timeliness regulation.

[0152] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0153] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0154] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0155] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1The steps for the functions specified in one or more boxes.

[0156] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for controlling the timeliness of an environmental monitoring system under current storage scheduling, characterized in that: include: Obtain the storage flow scheduling period and real-time data packet generation probability of the environmental monitoring system; Calculate the storage flow information age according to the storage flow scheduling cycle and the real-time data packet generation probability, wherein the storage flow information age is the information age of the environmental monitoring system under the storage flow scheduling; If the age of the current storage information is greater than the preset timeliness threshold, the current storage scheduling period is regulated until the age of the current storage information is less than or equal to the preset timeliness threshold, and the timeliness regulation is completed; The calculation formula of the storage current information age is: ； ； ； in, Abbreviation for because and so, Δ τ Indicated in τ The average storage information age of the environmental monitoring system in the time interval, τ represents a set time interval, Δ is the storage information age, and the storage information age of the environmental monitoring system is τ When the information age curve approaches infinity, the ratio of the area enclosed by the time axis to the length of time is at its extreme value. N ( τ ) means in τ The total number of storage dispatches triggered in the time interval, E () indicates the mean value. Q Refers to Q 1. Q 2. … Q N(τ) , Q 0 represents the time slot from the start of the first storage scheduling cycle to the time slot corresponding to the first triggering of storage scheduling n ss The area under the information age curve in the time interval (1), E ( Q ) means to ask Q 1. Q 2. … Q N(τ) The mean of λ B Indicates the frequency of triggering current storage scheduling, Y Indicates the storage scheduling interval time, represents the residual value of the last storage scheduling, B is the storage scheduling period, X i+1 It is i +1 packet generation interval, X i+(B-1) It is i +( B -1) packet generation interval, p ge is the real-time packet generation probability, n 1 indicates the time slot corresponding to the first data packet. Indicates The time slot corresponding to the data packet.

2. The timeliness control method of the environmental monitoring system under current storage scheduling according to claim 1 is characterized in that: The real-time data packet generation probability is obtained by the following method: Obtain the time slots corresponding to each data packet collected by the environmental monitoring system under the storage flow scheduling, as well as the total number of data packets collected in the current time slot, and calculate the real-time data packet collection probability according to the time slots corresponding to each data packet and the total number of data packets collected in the current time slot; Obtain all data packet generation intervals, group multiple data packet generation intervals corresponding to multiple recently generated data packets into adjacent generation interval groups, obtain the statistical distribution of the adjacent generation interval groups, calculate the probability distribution of all data packet generation intervals, compare whether the statistical distribution and the probability distribution are consistent, if they are consistent, use the real-time data packet collection probability as the real-time data packet generation probability, if not, recalculate the real-time data packet collection probability and perform the comparison until the comparison result is consistent.

3. The timeliness control method of the environmental monitoring system under current storage scheduling according to claim 2 is characterized in that: The real-time data packet collection probability is calculated according to the time slot corresponding to each data packet and the total number of data packets collected in the current time slot, and is performed by the following formula: ； Among them, p ga is the real-time packet acquisition probability, S is the total number of data packets collected in the current time slot, n l is the time slot corresponding to the lth data packet.

4. The timeliness control method of the environmental monitoring system under current storage scheduling according to claim 2 is characterized in that: The probability distribution of all data packet generation intervals is calculated using the following formula: ； Among them, X i is the i-th packet generation interval, slt is the duration of the time slot occupied by the preset packet generation interval, P(X i =slt) is the interval X between the i-th data packet generation i The probability distribution of ga is the real-time packet acquisition probability, N + Represents the set of positive integers.

5. The timeliness control method of the environmental monitoring system under current storage scheduling according to claim 2 is characterized in that: The comparison of whether the statistical distribution is consistent with the probability distribution is performed by the following method: The consistency index of the statistical distribution and the probability distribution is calculated by the following formula: ； Where O(o) is the consistency index, o is the range factor, slt is the duration of the preset packet generation interval corresponding to the number of time slots, P(X i =slt) is the interval X between the i-th data packet generation i The probability distribution of P(X ner-Z =slt) is the statistical distribution of the adjacent generation interval group, X ner-Z is the neighboring generation interval group; X ner-Z The expression is: ； Among them, X S Indicates the packet generation interval between the latest packet generated in the current time slot and the last packet generated. The latest packet generated in the current time slot is the first packet in history. S-Z+1 Indicates the packet generation interval corresponding to the Z+1th packet in history, X S-Z+2 Indicates the data packet generation interval corresponding to the historical Z+2 data packet; If the consistency index is less than or equal to a preset consistency threshold, the statistical distribution is consistent with the probability distribution; otherwise, the statistical distribution is inconsistent with the probability distribution.

6. The timeliness control method of the environmental monitoring system under current storage scheduling according to claim 1 is characterized in that: The regulating the current storage scheduling period includes a first-level regulation, and the first-level regulation includes: Adjust the storage scheduling period to the interval [1, B max ]Inside; Among them, B max is the maximum storage current dispatch period, which is calculated by the following formula: ； Among them, p ge is the real-time packet generation probability, Δ max is the preset maximum value of the storage current information age, Indicates rounding down.

7. The timeliness control method of the environmental monitoring system under current storage dispatching according to claim 6 is characterized in that: The regulating the current storage scheduling period also includes a second layer of regulation arranged after the first layer of regulation, and the second layer of regulation includes: If after the first level of regulation, the storage information age is in the interval [Δ L , Δ H ], adjust the storage scheduling period to the interval [B L-max , B H-max ]Inside; Among them, Δ L is the low timeliness threshold of the environmental monitoring system, Δ H is the high timeliness threshold of the environmental monitoring system, B L-max is the lower limit of the storage scheduling cycle when the environmental monitoring system is in the low timeliness mode, B H-max It is the upper limit of the storage scheduling cycle when the environmental monitoring system is in the low timeliness mode; The lower limit of the storage scheduling period is calculated by the following formula: ； The upper limit of the storage scheduling period is calculated by the following formula: 。 8. The timeliness control method of the environmental monitoring system under current storage dispatching according to claim 7 is characterized in that: The regulating the current storage scheduling period further includes a third layer of regulation arranged after the second layer of regulation, and the third layer of regulation includes: If after the second layer of regulation, the storage information age is in the interval [Δ E , Δ L ], adjust the storage scheduling period to the interval [B E-max , B L-max ]Inside; Among them, Δ E is the ultimate timeliness of the environmental monitoring system, B E-max is the lower limit of energy consumption during the storage scheduling period; The lower limit of energy consumption during the storage scheduling period is calculated by the following formula: 。 9. A time-effectiveness control device for an environmental monitoring system under current storage scheduling, characterized in that: include: The data acquisition module is configured to: acquire the storage flow scheduling period and real-time data packet generation probability of the environmental monitoring system; The storage flow information age calculation module is configured to: calculate the storage flow information age according to the storage flow scheduling cycle and the real-time data packet generation probability, wherein the storage flow information age is the information age of the environmental monitoring system under the storage flow scheduling; The timeliness control module is configured to: if the age of the current storage information is greater than a preset timeliness threshold, control the current storage scheduling period until the age of the current storage information is less than or equal to the preset timeliness threshold, thereby completing the timeliness control; The calculation formula of the current storage information age is: ； ； ； in, Abbreviation for because and so, Δ τ Indicated in τ The average storage information age of the environmental monitoring system in the time interval, τ represents a set time interval, Δ is the storage information age, and the storage information age of the environmental monitoring system is τ When the information age curve approaches infinity, the ratio of the area enclosed by the time axis to the length of time is at its extreme value. N ( τ ) means in τ The total number of storage dispatches triggered in the time interval, E () indicates the mean value. Q Refers to Q 1. Q 2. … Q N(τ) , Q 0 represents the time slot from the start of the first storage scheduling cycle to the time slot corresponding to the first triggering of storage scheduling n ss The area under the information age curve in the time interval (1), E ( Q ) means to ask Q 1. Q 2. … Q N(τ) The mean of λ B Indicates the frequency of triggering current storage scheduling, Y Indicates the storage scheduling interval time, represents the residual value of the last storage scheduling, B is the storage scheduling period, X i+1 It is i +1 packet generation interval, X i+(B-1) It is i +( B -1) packet generation interval, p ge is the real-time packet generation probability, n 1 indicates the time slot corresponding to the first data packet. Indicates The time slot corresponding to the data packet.

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