CN114615637A

CN114615637A - High-information timeliness data transmission method based on two-stage polling

Info

Publication number: CN114615637A
Application number: CN202210069960.8A
Authority: CN
Inventors: 朱旭; 黄永高; 蒋宇飞
Original assignee: Shenzhen Graduate School Harbin Institute of Technology
Current assignee: Shenzhen Graduate School Harbin Institute of Technology
Priority date: 2022-01-21
Filing date: 2022-01-21
Publication date: 2022-06-10

Abstract

The invention provides a high information timeliness data transmission method based on double-stage polling, an industrial sensor network model based on double-stage polling and data aggregation comprises a sensor, an aggregator and a monitor, and the high information timeliness data transmission method based on double-stage polling comprises the following steps: step 1: dividing the sensor nodes into K groups according to the spatial correlation among the sensor nodes; step 2: configuring an aggregator for each group of sensors; and step 3: the sensor nodes send information update to the aggregator in a polling mode, the sensor nodes in each group transmit data information to the aggregator according to the polling period of the aggregator, and the polling is primary polling; and 4, step 4: the aggregator collects data of nodes in the group and aggregates the data; and 5: the aggregator forwards the aggregated data to the monitor by polling, which is a secondary poll. The invention effectively improves the timeliness of the sensor network system.

Description

High-information timeliness data transmission method based on double-stage polling

Technical Field

The invention relates to the field of data transmission, in particular to a polling method for data transmission.

Background

Age of information

The age of the information is significantly different from the time delay in conventional communication systems. They measure the timeliness of a system from different perspectives, respectively, the time delay is considered from the perspective of the transmitter, describing the time from generation to completion of transmission of information, and the age of the information quantifies the timeliness of the system at the receiver, which refers to the time that the information received by the receiver passes from generation to the present. In a real-time monitoring system or a control system, the information transmission speed is required to be high, the timeliness of the information received by the terminal is concerned more, and the outdated information cannot provide sufficient effective information for the next decision of the terminal. Therefore, the information age can effectively and quantitatively describe the information timeliness of the terminal, and plays an important role in a real-time system.

Consider an information update system as shown in fig. 1, which consists of three parts, a sender, a channel and a destination node D, wherein the sender comprises an active node S, a sender server and a buffer queue, one each. Suppose that the real-time sampling information generation of the source node obeys the random process x (t), and the destination node needs the real-time information of the source node. Therefore, the source node needs to continuously transmit information update packets through the transmission server and then reach the destination node through the communication link, wherein the data of each information update packet includes the sampling information X (t) of the source node_i) And the generation time t of the ith information update packet_i. When the sending server is in a busy state, namely the current sending server is transmitting the information updating packet, the newly arrived information updating packet enters the buffer queue and sequentially enters the sending server according to the arrival sequence for data transmission. It is assumed that the information update packet is transmitted to the destination node over an error-free communication link after transmission at the source node transmitter is complete. When the information updating package reaches the destination node, it means that the receiving end completes the information updating, i.e. the information age of the system is updated at the same time.

In the information update system in fig. 1, all information update packages i generated by the source node are 1,2, and 3 …, and need to be transmitted to the destination node. It is assumed that the time from the generation of the information update packet to the queue is negligible, i.e. the generation of the information update packet is the same as the meaning of the information update packet arrival queue in this model. The generation of information update packets is modeled as a poisson process with an average rate λ, and the transmission time of data packets follows an exponential random process with an average rate μ.

The information age at any time in the system describes the time elapsed after the latest information update packet word of the destination node is generated. Suppose an information update package is at time t₁,t₂,…,t_i…, respectively, at time t'₁,t'₂,…,t′_i…, when arriving at the destination, at time t, the maximum index of the information update package received by the destination is:

k＝max{i|t′_i∈t} (0-10)

the timestamp generated by the latest update is:

U(t)＝t_k (0-11)

at time t, the mathematical expression for the age of the information is as follows:

Δ(t)＝t-U(t) (0-12)

the age change of the system information corresponding to the system of fig. 1 is shown in fig. 2. The time when the ith information update packet is generated and received is t_iAnd t'_iAnd (4) performing representation. X_iThe arrival intervals of the ith and (i +1) th information update packets are represented, and the sizes of the arrival intervals are related to the arrival rate lambda of the information update packets. S_iThe service time of the ith information update packet is represented, and the size of the service time depends on the service rate of the sending server. Y is_iIndicating the time interval at which the receiving end receives the ith and (i +1) th information update packets. A. the_iIndicating the maximum information age reached by the receiving end when receiving the ith information update packet. Q_iIndicating the trapezoidal area resulting from the acceptance of the ith packet, e.g. shaded Q in FIG. 2₃The area of the trapezoid generated when the third information update packet is received is shown in (a). Delta₀Indicating the age of the system start message.

As can be seen from fig. 2, the information age curve of the system is jagged, and when a new information update package arrives, the information age of the system is updated, and the information age is decreased. In the absence of information update package arrival, the information age has a linear increasing trend.

The mean information age expression for the system is as follows:

round robin scheduling policy

When there are several update sources in the information updating system, all the update sources send information updating packages in turn according to the preset sequence to update information.

In industrial intelligent production and monitoring, real-time acquisition of production environment data needs to be ensured, and control instructions are accurate and reliable. The information age is provided under the application scene of high information timeliness, and compared with time delay, the timeliness of the industrial sensor network can be measured more comprehensively and effectively. Due to the high-density characteristic of the sensor nodes, (the high density is understood that the quantity is as much as possible, the quantity is not wasted, a fixed numerical value is not needed, and a numerical range is selected by a technical person in the technical field according to actual requirements), a large amount of redundancy exists in data acquired by adjacent sensor nodes, and the timeliness of system information is reduced due to the transmission of a large amount of redundant data. Current research on information age is mainly focused on different system models and information transmission strategies and the impact of information update packet loss caused by interference on system information age performance. Moreover, the research in this field is to consider the improvement of system information age performance by using data correlation, and the research is limited to a single-level information updating system.

Disclosure of Invention

In order to solve the problems in the prior art, the invention provides a high-information timeliness data transmission method based on double-stage polling, an industrial sensor network model based on double-stage polling and data aggregation comprises a sensor, an aggregator and a monitor, and the high-information timeliness data transmission method based on double-stage polling comprises the following steps:

step 1: dividing the sensor nodes into K groups according to the spatial correlation among the sensor nodes;

step 2: configuring an aggregator for each group of sensors;

and step 3: the sensor nodes send information update to the aggregator in a polling mode, the sensor nodes in each group transmit data information to the aggregator according to the polling period of the aggregator, and the polling is primary polling; in each aggregator polling period, the selected nodes polled by each group of sensors transmit data information to the aggregator;

and 4, step 4: the aggregator collects data of nodes in the group and aggregates the data;

and 5: the aggregator forwards the aggregated data to the monitor by polling, which is a secondary poll.

As a further improvement of the invention, the method also comprises the following steps of 6: modeling the system into a discrete Markov process of finite state, analyzing detailed parameter information corresponding to the state transition and the Markov process of the system, and solving and analyzing the average information age of the system by means of a stochastic hybrid system theory.

As a further improvement of the invention, the stochastic mixing system models a queuing system as a process of finite state (Q (t), x (t)), where Q (t) e Q ═ {0,1,2, …, m } represents a Markov chain of continuous time finite states describing various queuing conditions of the queuing system, and x (t) [ x ], (t) } x₀(t),x₁(t)...x_n(t)]∈R^1x(n+1)Also a continuous process for recording age changes of the corresponding process at the receiving end; therefore, the information age of the marked source can be tracked at the receiving end by marking the source to be solved and then using x (t) along with the updating of the system state; x (t) is a vector of linearly increasing piecewise functions whose rate of increase can be solved by:

wherein b is_q＝[b_q,0b_q,1…b_q,n]Is a vector in which b_q,jE {0,1}, if in state q, age process x_j(t) linear growth, b_q,jThe value is 1, otherwise, the value is 0;

the Markov chain is represented by graph G (Q, L), where the node Q ∈ Q represents the Markov state Q, and the link L ∈ L represents the state Q'_lTransfer to q'_l(ii) a The difference from the conventional markov process is that there is a possibility of self-transition in this markov chain, i.e. from the current state to the current state; when the information update package arrives or finishes transmission, the state transition occurs, and the continuous state x (t) updates x '(t), that is, x' is xA according to the formula_lFor transfer matrix A_lSolving is carried out;

to solve for the average information age using a stochastic mixture model, the steady-state probability pi for each state of the Markov chain is needed_q(t)And the correlation vector V between discrete states q (t)_q(t)And (3) solving:

π_q(t)＝E[δ_q,q(t)]＝P(q(t)＝q) (0-14)

V_q(t)＝E[x(t)δ_q,q(t)]＝[v_q0(t)…v_qn(t)] (0-15)

from L'_qIndicating all transition links, L, entering state q_qRepresents all transition links going out of state q, i.e.:

L'_q＝{l∈L|q′_l＝q} (0-16)

L_q＝{l∈L|q_l＝q} (0-17)

analysis of information age will follow the ergodic assumption of a Markov chain q (t) with a Markov state vector of π (t) ([ π!)₀(t),π₁(t)…π_m(t)]Will converge to a steady state vector

In the same way as thatTime of flight

The following relation is satisfied:

under the assumption of Markov chain ergodicity, the state related vector v_q(t)Convergence to non-negative limits

For any state q, when t → ∞, the following conclusions hold:

the final mean age of information can be solved by:

as a further development of the invention, the sensors are grouped according to position characteristics.

As a further improvement of the present invention, in step 4, since the data of the same group of sensor nodes has strong correlation, the aggregator aggregates the information by using the collected data information and the stored historical data information every time the aggregator collects the data information of the sensor nodes.

As a further improvement of the invention, the data transmitted by the sensor nodes to the aggregator is transmitted by using short packets.

As a further improvement of the invention, the sensor nodes are deployed at high density.

As a further improvement of the invention, the secondary polling is driven by the primary polling, when the information update package of the primary polling is transmitted to the aggregator, the aggregator processes the received data in time and sends the data to the monitor immediately.

The invention has the beneficial effects that:

the sensor nodes are clustered according to the spatial correlation to obtain an industrial sensor network model based on double-stage polling and data aggregation, and the correlation among the updating sources is utilized to assist a series of related sources to update information, so that the timeliness of the sensor network system can be effectively improved. In addition, the characteristic of small data volume in industrial production is considered, a short packet technology is adopted in the system for data transmission, and three coping strategies of no retransmission, retransmission no resampling and retransmission resampling are considered when data packet transmission has errors. The theoretical expression of the average information age of the system under three retransmission strategies is solved, and the research result can effectively guide engineering practice.

Due to the high-density deployment characteristic of the sensor nodes, data between adjacent nodes have strong correlation, and the double-stage polling industrial sensor information updating system reduces the data transmission amount by utilizing the correlation between the sensor nodes so as to achieve the purpose of reducing the timeliness of the system. The sensor nodes are clustered according to spatial correlation, the aggregator polls to send information updates to the monitor, and the sensor nodes in each cluster are strongly correlated due to data, the aggregator polls to select the nodes in the cluster to send the collected data to the aggregator, and aggregates the received data and the stored data to obtain effective data, and sends the effective data to the monitor.

Drawings

FIG. 1 is a diagram of a single-source single-server information update system model;

FIG. 2 is a schematic diagram of the system's instant message age;

FIG. 3 is a model diagram of a sensor information updating system of a high information timeliness data transmission method based on double-stage polling;

FIG. 4 is a schematic diagram of a model architecture of a dual-level polling information updating system according to the present invention;

FIG. 5 is a age chart of a secondary polling information update system of the present invention;

FIG. 6 is a Markov state transition diagram of the no retransmission policy system of the present invention;

FIG. 7 is a graph of age performance versus information for a dual-level polling and single-level polling system of the present invention;

FIG. 8 is a graph of the impact of retransmission strategies of the present invention on system information age performance;

FIG. 9 is a diagram of system information age simulation under imperfect channel conditions in accordance with the present invention;

FIG. 10 is a graph of the effect of packet length on system information age performance of the present invention;

fig. 11 is a two-level polling information update system model.

Detailed Description

The invention is further described below with reference to the accompanying drawings.

An industrial sensor network model based on dual-stage polling and data aggregation is shown in fig. 3, and consists of a sensor, an aggregator and a monitor, wherein the sensor needs to send collected data information to the monitor as soon as possible. Because the sensor data in the intelligent factory has strong spatial correlation, the sensors are averagely divided into K groups according to the position characteristics. And after aggregating the collected information update and the stored information, the aggregator circularly sends the information update of the sensor group to the monitor by adopting a polling scheduling strategy, and because the sensor nodes in each cluster have strong correlation, the sensor nodes in the clusters circularly send the information update to the aggregator by adopting the polling scheduling strategy. Aggregator polling aggregates the collected sensor data and then passes it to the monitor. When an aggregator-to-monitor transmission is in error, three packet management strategies are considered herein, assuming that the feedback from the monitor back to the aggregator is error-free:

(1) no Retransmission (No Retransmission): when the transmission of the information updating packet is in error, the information updating is directly carried out by the next sensor in turn as if no error occurs.

(2) Retransmission Without Resampling (Retransmission Without sampling): the retransmission non-resampling strategy is only to retransmit the originally acquired data packet, and no resampling is performed, which is a main difference from the retransmission resampling strategy, and similarly, when an information update packet is in error, retransmission is performed until the information update packet is successfully transmitted.

(3) Retransmission Resampling (Retransmission With sampling): and when the transmission of the information updating packet is wrong, the sensor data is collected again to ensure that the latest data is transmitted, and if the transmission of the information updating packet is wrong, the retransmission and resampling strategy is repeated until the transmission of the information updating packet is successful.

In a primary polling information updating system, an aggregator is mainly used for collecting and storing information updates of a certain related sensor group. It is assumed that the aggregator is located in the vicinity of the sensor cluster and can choose a better channel location for placement to ensure that the sensor to aggregator transmission is reliable, i.e., no information update packet loss occurs. Assuming that the sensor has a real-time information collecting capability, that is, the sending server completes sending the last information update packet, it can immediately collect the information of the next information update packet, so that the arrival rate μ of the information update packet is the same as the service rate μ of the sending server, that is, in the system considered herein, the buffer queue of the sending server will always remain idle. Correspondingly, the service time (or transmission time) for the sending server to send an information update package is T_b. Since the information update packet is encoded as a packet with a packet length of m, and the unit can be represented by symbols or channel uses, the transmission time is affected by the packet length, i.e. T_b＝mT_u(T_uRepresenting the duration of a symbol). Because the data volume transmitted by each update is less, the transmitted data packet is very suitable for being transmitted by adopting a short packet. Rate of short packet transmission in white gaussian noise channelThe approximation is:

wherein C-channel capacity under Shannon's formula, i.e. C ═ log₂(1+ γ), related to the signal-to-noise ratio γ;

v-the channel dispersion,

Q^-1inverse function of the equation (-) -Q (-), i.e.

Analyzing and processing the formula (3-1) to obtain the following relations between the error probability of the data packet and the length m of the data packet, the data volume k and the signal-to-noise ratio gamma of the channel:

it can be known from equation (3-2) that, assuming that an information update packet transmits k bits of information in the form of short packets, the probability of packet error will also be related to the destination received noise ratio γ and the packet length of the information update packet. If the probability of packet transmission errors is to be reduced under the condition that the signal-to-noise ratio is kept constant, the packet length of the data packet needs to be increased. Similarly, when the packet length of the information updating packet is fixed, the signal-to-noise ratio of the receiving end can be increased, and the error probability of data packet transmission is reduced. Furthermore, careful observation shows that when the channel conditions are good, for example, the signal-to-noise ratio of the receiving end reaches 10dB, the data packet can be transmitted without errors, and therefore, the position of the aggregator can be adjusted to make the transmission from the sensor to the aggregator error-free.

The two-level information update system model from aggregator to monitor is shown in fig. 11. In a secondary polling information update system, an aggregator polls information collected from a sensor group and sends it to a monitor.The polymerization operation of the polymerizer means: the aggregator aggregates data representing the sensor group according to the current received information updating data and the assistance of historical data. Furthermore, since the aggregation time is extremely small, it is not considered herein, that is, the aggregator has a real-time data aggregation capability, and therefore only the transmission delay of the system is considered herein. Therefore, regardless of the retransmission, the polling period of the system is related to the number of aggregators, denoted as T_s＝KT_b. In the primary polling information updating system, because the aggregator is arranged near the sensor group to collect the sensor information, the distance is short, the channel condition is good, and reliable transmission can be ensured. However, the transmission path from the aggregator to the monitor is far, the channel condition is unstable, and the performance when transmitting the information update packet using a short packet is greatly affected by the channel condition. On the other hand, due to the regular movement of the robot and the equipment in the factory production environment, a certain probability p exists for shielding the transmission path, and in order to qualitatively analyze the influence of the shielding of the information transmission path on the age performance of the system information, it is assumed that a fixed channel attenuation delta exists due to shielding.

Related information sources based on literature research can effectively assist information updating, and the information age performance of an information updating system with a large number of related sources is effectively measured. In addition to the information update after the destination receives the information update packet from the same source, the information of the related update source is also valid within a certain error range, and can be fully utilized by the destination. Thus, the information age of all update sources for the same related information source is the same. For example, in the sensor group of the aggregator 1 in fig. 3, the information update packet from any source in the sensor group arrives at the destination, and the destination updates the information ages of all relevant update sources corresponding to the sensor group.

In summary, in the dual-polling information updating system model shown in fig. 3, since the information update sent by any sensor in the sensor group is valid for the entire sensor group, the sensor polling in the sensor group performs the information update, i.e., the aforementioned first-level polling. The second-level polling is driven by the first-level polling, namely when the information update package of the first-level polling is transmitted to the aggregator, the aggregator processes the received data in time and sends the data to the monitor immediately. Since the data aggregation time is negligible, the overall system model can be simplified to a two-stage information update system as in fig. 4.

Next, the information age performance in the secondary polling information updating system under the non-retransmission strategy is analyzed, and since the information transmission from the aggregator to the monitor is unreliable, although each aggregator sends information updates to the monitor according to a fixed sequence and periodic polling, the information age of the monitor does not change periodically. On one hand, due to the use of short packets for data transmission, the error probability epsilon (k, m, gamma) of a data packet depends on the channel condition, and the error probability rapidly increases when the channel condition is poor, and on the other hand, due to the interference of robots in a factory, a certain probability q is that the channel gain is attenuated by delta. Since the occurrence of a packet error event depends on the mechanism for data transmission using short packets, while the event of channel occlusion depends on the factory environment, these two events are independent. The probability of success of the transmission from the aggregator to the monitor is solved as follows:

the age change of the effective information of the sensor in the monitor is shown in FIG. 5, where Δ₀Represents the initial age of the information update package, i.e. the time elapsed for the information update package to arrive at the aggregator from the sensor. The time that the information update package is transmitted again after being timely aggregated by the aggregator and then reaches the monitor is shown as 2T_b. Since the transmission from the aggregator to the monitor is unreliable, there is a possibility that data update packets will be lost and the age of valid information observed by the monitor will not appear to be updated periodically as the age of information observed at the aggregator, e.g. t in fig. 5₂Information sent from aggregator to monitor at timeNew packets are lost and therefore the age of the available information at the monitor is not updated and will continue to appear linearly increasing.

For the effective information age solution for the sensors monitored by the monitor in fig. 5, a random hybrid system will be employed. For the no retransmission strategy, we can model the information update system as a Markov chain as shown in FIG. 6. In the figure, the state 1 indicates that the cluster where the sensor to be solved is located is updated, and the state 2-K indicates that the clusters where other sensors are located are updated. In FIG. 6, with l_iI-1, 2, …, K +1 indicates that the state of the system has changed, and the transfer rate is denoted as λ^(l)While the system state changes, i.e. x' ═ xA_l. As can be seen from the equations (3-13), in order to solve v_qRequire a state transition matrix A_lThe detailed changes of the parameters during the Markov chain transition in FIG. 6 are analyzed and summarized in Table 3-1.

TABLE 3-1 retransmission policy free state transition case

The physical meanings corresponding to each transfer process in Table 3-1 are:

(1)l₁the information update package of the sensor which indicates the information age is required to be decoded is successfully transmitted, and the information age of the receiving end is updated to be x'₀＝x₁. X 'since a new information update packet will arrive until the next polling period after the transmission of the information update packet of the current sensor is completed'₁＝0。

(2)l₂The information update package of the sensor requiring to solve the information age fails to be transmitted, and the information age of the receiving end is not updated and continues to keep linear increase, namely x'₀＝x₀. After the information update package of the current sensor is transmitted, the next information update package is neededOnly in the polling period will a new information update packet arrive, so x'₁＝0。

(3)l_iAnd indicating that the information update packages of other sensors are transmitted, wherein i is more than or equal to 2 and less than or equal to K. Since the transmission of these sensor information update packets does not affect the information age of the sensor to be solved, and the transmission failure is the same as the state before and after the successful transition, the successful transmission and the transmission error are considered together. The receiving end information age is not updated, and the linear growth is continuously kept, namely x'₀＝x₀. X 'since the information update packet of the sensor requiring solution does not arrive after the transmission of the information update packet of the sensor is completed'₁＝0。

(4)l_K+1The information update package representing the irrelevant sensor completes transmission, does not influence the information age of the sensor to be solved, and also considers the successful transmission and the transmission error. The receiving end information age is not updated, and linear growth is continuously kept, namely x'₀＝x₀. Since the information update packet to be solved arrives at the transmission server at this time, the age is 0, that is, x'₁＝0。

From the equation (3-5), it can be known that the information age x (t) at the receiving end increases depending on b_qI.e. x' ═ b_q. Because the age of the information to be solved consists of x₀(t) real-time tracking with b in all states_q11. If the information update package being transmitted is from a sensor requiring a solution, b _q21, because when the information update package transmission of the sensor to be solved is completed, the information age of the receiving end is updated to x₁(t), that is to say b_q2And x₁(t) has the effect of recording the transmission time of the information update packet to be resolved, as follows:

through the analysis of the transition process, the information age tracking process x 'after the state transition is obtained, and then the information age tracking process x' can be obtained through x ═ xA_lFind out in Table 3-1A of (A)_l. Finally, the last column v in Table 3-1 can be obtained by simple calculation_qlA_l。

The corresponding data in the table are taken into equations (3-10) and (3-11), and the Markov chain steady-state probability can be obtained as follows:

by bringing formulae (3-15) and (3-16) into formula (3-12), it is possible to obtain information on v_qlThe equation of (a) is as follows:

by solving the system of equations expressed by the equations (3-17), v can be obtained_q0：

The mean information age Delta of the system under the strategy of no retransmission can be obtained by substituting the formula (3-18) into the formula (3-13)_{Without retransmission}The expression is as follows:

similar system average information age expressions under available retransmission non-resampling strategy and retransmission resampling strategy:

theory of random mixing system

Since there is a possibility of error in information update from the aggregator to the monitor, in order to simplify the computational complexity of the information age solving process, this section will adopt a random hybrid system to solve the information age of the dual-stage polling system. Therefore, this section will make a brief introduction to the random mixing system.

The stochastic mixing system models a queuing system as a change process of finite state (Q (t), x (t)), wherein Q (t) epsilon Q ═ {0,1,2, …, m } represents a Markov chain of continuous time finite state for describing various queuing conditions of the queuing system, and x (t) [ [ x (t) } x₀(t),x₁(t)...x_n(t)]∈R^1x(n+1)R represents a vector space of 1 x (n +1), which is also a continuous process, and is used to record the age change of the corresponding process at the receiving end. It is therefore possible to keep track of the age of the information of the source marked at the receiving end with x (t) by marking the source to be solved and then following the update of the system state [59,60 ]]. x (t) is a vector of linearly increasing piecewise functions whose rate of increase can be solved by:

wherein b is_q＝[b_q,0b_q,1…b_q,n]Is a vector in which b_q,jE {0,1}, if in state q, age process x_j(t) linear growth, b_q,jThe value is 1, otherwise 0.

The Markov chain is represented by graph G (Q, L), where the node qeQ represents the Markov state Q and the connecting line leL represents the state from Q_lTransfer to q'_l. The difference with the conventional markov process is that there is a possibility of self-transition in this markov chain, i.e. from the current state to the current state. When the information update package arrives or finishes transmission, the state transition occurs, and the continuous state x (t) updates x '(t), that is, x' is xA according to the formula_lFor transfer matrix A_lAnd (6) solving.

To solve for the average information age using a stochastic hybrid model, one needs to do a Markov chainSteady state probability of each state_q(t)And the correlation vector V between discrete states q (t)_q(t)And (3) solving:

π_q(t)＝E[δ_q,q(t)]＝P(q(t)＝q) (3-6)

V_q(t)＝E[x(t)δ_q,q(t)]＝[v_q0(t)…v_qn(t)] (3-7)

from L'_qIndicating all transition links, L, into state q_qRepresents all transition links going out of state q, i.e.:

L'_q＝{l∈L|q′_l＝q} (3-8)

L_q＝{l∈L|q_l＝q} (3-9)

analysis of information age will follow the ergodic assumption of Markov chain q (t) [8]Markov state vector pi (t) ═ pi₀(t),π₁(t)…π_m(t)]Will converge to a steady state vector

At the same time

The following relation is satisfied:

it is available from literature that the state-related vector v is under the assumption of markov chain ergodicity_q(t)Convergence to a non-negative limit

For any state q, when t → ∞, the following conclusions hold:

the final mean information age can be solved by the following equation [8 ]:

in order to compare the average information age performance difference between the double-stage polling system and the single-stage polling system and highlight the superiority of the double-stage polling system, the number of sensors in the two systems is assumed to be 10-3000 in simulation, the data volume of each transmission is 150bits, the length of an information update packet is 200 channels uses, the number of groups is 5, and other simulation parameters are set to be gamma-10 dB, p-0.1, delta-5 dB, T_u0.006ms, some of which are referred to in the literature.

Fig. 7 shows the simulation analysis and comparison of the age performance of the dual-polling system and the single-polling information, from which it can be seen that the age of the system information is approximately linear with the number of sensors, consistent with the conclusions of equations (3-19). Compared with the information timeliness in multi-source information updating based on polling scheduling in documents, the double-stage polling strategy aggregates data by utilizing the correlation after the first-stage polling, reduces the transmission of redundant data, and shortens the overall polling time of a system, so that the double-stage polling scheduling strategy based on aggregator assistance is remarkably improved in the information timeliness, and the information timeliness improvement effect of the method adopted in the research is more obvious along with the increase of information updating sources.

Fig. 8 is a simulation analysis of the influence of three retransmission strategies, namely no retransmission, retransmission resampling and retransmission no resampling, on the age performance of the information of the dual-stage polling system. In the simulation process, the parameters are set to be N100, K5, K150 bit, m 200channel uses, gamma 10dB, p 0.1, sigma 5dB, T_u0.006 ms. It can be known from fig. 8 that when the channel condition is good, even if a certain transmission is erroneous, the transmission will be successful with a high probability in the next polling, and the information age performance of the system is not greatly affected, so the information age performance of the system under the three policies is basically the same. In addition, due to retransmissionThe sampling strategy is used for resampling in each retransmission, so the performance of the retransmission resampling strategy is slightly superior to that of the retransmission non-resampling strategy. When the channel condition is poor, the retransmission strategy is adopted to ensure that the information updating packet can be transmitted in time, and the age performance of the system information is effectively improved.

Fig. 9 shows a simulation analysis of the influence of channel conditions on the age of system information in actual industrial production, where parameters in the simulation process are set to N3000, K5, K150 bit, m 200channel uses, γ 10dB, p {0.1, 0.2, 0.3, 0.4}, δ 0-20dB, T_u0.006 ms. As can be seen from fig. 9, when the channel interference probability p is constant, the average information age of the system is hardly affected when the channel gain loss is small, the information age of the system rapidly increases when the channel loss reaches 6dB, and the information age of the system does not change with the channel gain attenuation when the channel loss approaches 9 dB. The fundamental reason for the above phenomenon is that the second stage of the dual-stage polling information updating system uses short packets for data transmission, and since the success rate of data transmission using short packets changes rapidly when the channel condition reaches a critical value, when the channel condition drops to a certain threshold, the error probability of the data packet rises rapidly, thereby causing the information age of the system to increase rapidly.

Fig. 10 is a simulation analysis of the influence of the packet length on the system effective information age, and the experiment is performed on the system effective information age under different packet lengths, where the parameters are set to N3000, K5, K150 bit, m 150 channel uses, γ 10dB, p 0.2, δ 5dB, T_u0.006 ms. It can be seen from the figure that the information age performance of the system is less affected by the channel conditions when the packet length is large, and the system timeliness is drastically reduced as the channel conditions become worse when the packet length is small. In addition, as the signal-to-noise ratio increases, the packet length of the transmission data packet which causes the system to have the lowest timeliness gradually decreases. The root cause of the above phenomenon is found from the equations (3-2) and (3-19), and in the system using short packets for data transmission, when the packet length increases, on the one hand, the transmission error probability of the information update packet can be reduced, thereby reducing the average information age of the system,on the other hand, when the number of data packets increases, the transmission time of the data update packets and the polling time increase, thereby improving the average information age of the system. Therefore, the optimal packet length will depend on the information transmission conditions in the actual scenario.

The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.

Claims

1. A high information timeliness data transmission method based on double-stage polling is characterized in that: the industrial sensor network model based on the double-stage polling and the data aggregation comprises sensors, an aggregator and a monitor, and the high-information timeliness data transmission method based on the double-stage polling comprises the following steps:

step 2: configuring an aggregator for each group of sensors;

2. The method for transmitting data with high information timeliness based on dual-stage polling of claim 1, characterized in that: further comprising the step 6: modeling the system into a discrete Markov process of finite state, analyzing detailed parameter information corresponding to the state transition and the Markov process of the system, and solving and analyzing the average information age of the system by means of a stochastic hybrid system theory.

3. The method for transmitting data with high information timeliness based on dual-stage polling of claim 2, characterized in that:

the stochastic mixing system models a queuing system as a change process of finite state (Q (t), x (t)), wherein Q (t) epsilon Q ═ {0,1,2, …, m } represents a Markov chain of continuous time finite state for describing various queuing conditions of the queuing system, and x (t) [ [ x (t) } x₀(t),x₁(t)...x_n(t)]∈R^1x(n+1)Also a continuous process for recording age changes of the corresponding process at the receiving end; therefore, the information age of the marked source can be tracked at the receiving end by marking the source to be solved and then using x (t) along with the updating of the system state; x (t) is a vector of linearly increasing piecewise functions whose rate of increase can be solved by:

the Markov chain is represented by graph G (Q, L), where the node qeQ represents the Markov state Q and the connecting line leL represents the state from Q_lTransfer to q'_l(ii) a The difference from the conventional markov process is that there is a possibility of self-transition in this markov chain, i.e. from the current state to the current state; when the information update package arrives or finishes transmission, the state transition occurs, and the continuous state x (t) updates x '(t), that is, x' is xA according to the formula_lFor transfer matrix A_lSolving is carried out;

π_q(t)＝E[δ_q,q(t)]＝P(q(t)＝q) (0-2)

V_q(t)＝E[x(t)δ_q,q(t)]＝[v_q0(t)…v_qn(t)] (0-3)

L′_q＝{l∈L|q′_l＝q} (0-4)

L_q＝{l∈L|q_l＝q} (0-5)

At the same time π (t) satisfies the following relation:

under the assumption of Markov chain ergodicity, the state related vector v_q(t)Convergence to a non-negative limit

For any state q, when t → ∞, the following conclusions hold:

the final mean age of information can be solved by:

4. the method for transmitting data with high information timeliness based on double-stage polling according to any one of claims 1 to 3, characterized in that: the sensors are grouped by location characteristics.

5. The method for transmitting data with high information timeliness based on double-stage polling according to any one of claims 1 to 3, characterized in that: in step 4, since the data of the same group of sensor nodes has strong correlation, the aggregator aggregates the information by using the collected data information and the stored historical data information every time the aggregator collects the data information of the sensor nodes.

6. The method for transmitting data with high information timeliness based on double-stage polling according to any one of claims 1 to 3, characterized in that: and the data transmitted to the aggregator by the sensor nodes is transmitted by adopting short packets.

7. The method for transmitting data with high information timeliness based on double-stage polling according to any one of claims 1 to 3, characterized in that: the sensor nodes are deployed at high density.

8. The method for transmitting data with high information timeliness based on double-stage polling according to any one of claims 1 to 3, characterized in that: and the secondary polling is driven by the primary polling, when an information updating packet of the primary polling is transmitted to the aggregator, the aggregator processes the received data in time and sends the data to the monitor immediately.