CN110417770B - Wireless remote data real-time transmission method based on deterministic resource scheduling - Google Patents
Wireless remote data real-time transmission method based on deterministic resource scheduling Download PDFInfo
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Abstract
The invention discloses a wireless remote data real-time transmission method based on deterministic resource scheduling. The method is characterized in that: firstly, stamping a time stamp for sampled process data and then wirelessly transmitting the sampled process data; acquiring process data and a delay value of the process data through a cloud server, and estimating network communication quality; and step three, adaptively adjusting the delay value of the technological process data acquired by the cloud server, and ensuring that the cloud server control and decision program can call the same batch of sampling data at the same time. The method meets the requirement of deterministic time processing of the industrial wireless process data by a control and decision program on the cloud server, and realizes the real-time requirement of the industrial Internet of things; and the deterministic acquisition of all data in the same batch is completed, the reliability requirement of the industrial Internet of things is realized, and a technical basis is provided for realizing remote cloud control and decision deployment in the industrial production process based on the industrial Internet of things.
Description
Technical Field
The invention takes an industrial Internet of things as a research background, and particularly relates to a wireless remote data real-time transmission method based on deterministic resource scheduling.
Background
Due to the mobile and deployment advantages brought by the wireless characteristics of the wireless communication, the practical production process is not limited by operation space, operation environment and the like, and the wireless communication becomes an important component of the industrial Internet of things. With the gradual increase of the intelligent degree of a factory, modern industry utilizes the existing high-performance computing technology, virtual simulation application technology and the like to gradually develop towards the information-based industry direction of cloud application, and the information management of the production process enables the enterprise production mode based on mass production data analysis to be gradually accepted and used by more enterprises. However, the data is used and simultaneously the requirement for more strict real-time performance of the data is brought, so that a wireless remote data transmission method meeting the real-time requirement of industrial certainty is urgently needed.
In industrial processes, the real-time nature of wireless network transmission generally means that data transmitted over the network must be transmitted from a source to a destination within a predetermined time, based on periodic industrial control requirements, i.e. it is required that the required data is available at a certain moment. The current cloud control and decision program requires equally-spaced real-time data acquisition, so that the same batch of centralized processing of data is facilitated. If the time interval difference of the same batch of sampled data reaching the cloud end is large and accurate synchronization cannot be realized, the data accessed by the cloud end control and the decision program are not in the same time dimension, so that the problems of control instruction, decision deviation and even errors are caused. However, due to characteristics of wireless transmission, such as channel attenuation and network instability, transmission delay fluctuation is large, so for an industrial internet of things requiring a large amount of real-time industrial process data, it is difficult to obtain real-time data with determined delay and equal intervals, and unstable channel and network states pose a greater challenge for a cloud decision program that needs to remove the real-time data with equal intervals, and cannot effectively support remote processing of the data.
However, at present, an industrial real-time solution under a wireless environment is still incomplete, a wireless remote data transmission method under a cloud computing and big data environment is a new research hotspot, especially for modern industries which need a large amount of computing resources, cannot be completed locally and rely on a large amount of data, the necessity of a wireless remote transmission mode is obviously improved due to the limitation of the spatial position of the computing resources, but the characteristics of large fluctuation and instability of a wireless network always exist, for the production process that a control and decision link is located in a remote cloud server, the wireless transmission mode must provide higher requirements for the industrial real-time performance of data transmission, and the on-time arrival and equal-interval acquisition of data are particularly important.
Disclosure of Invention
The invention provides a wireless remote data real-time transmission method based on deterministic resource scheduling, which aims at the problems that if the time interval difference of the same batch of sampled data in the industrial Internet of things is large and accurate synchronization cannot be realized, the data accessed by a cloud control program and a decision program are not in the same time dimension, so that control instructions and decision deviation even errors are caused, and the like, and the technical scheme is as follows:
a wireless remote data real-time transmission method based on deterministic resource scheduling comprises the following steps:
the method comprises the following steps: the method comprises the following specific steps of performing wireless transmission after time stamping on sampled process data:
1) the method comprises the steps that an industrial field periodically collects process data in real time and sends the process data and current sampling time to a wireless remote transmission terminal;
2) the wireless remote transmission device continuously monitors a designated process data port, receives process data and current sampling time sent by an industrial field in real time, packs the process data and the current sampling time, adds a processing timestamp, establishes a data packet timestamp, and then wirelessly sends the data packet timestamp to a cloud server;
step two: the method comprises the following steps of obtaining technological process data and a delay value of the technological process data through a cloud server, and estimating network communication quality, wherein the method comprises the following specific steps:
1) the wireless remote transmission terminal and the cloud server establish a virtual private network channel for data exchange, and process data, current acquisition time and a data packet timestamp obtained by the wireless remote transmission device are uploaded to the cloud server;
2) calling a packet analysis program in the function library to analyze the current sampling time and the data packet timestamp in each data packet received by the cloud server in the memory of the cloud server, and recording the timestamp obtained when the data in the data packet reaches the cloud server;
3) connecting a database of the cloud server, extracting l pieces of historical data in the same production period from the database of the cloud server, processing the l pieces of historical data, and then obtaining a network transmission delay value of each piece of historical data, wherein the network transmission delay value delay isk-iThe calculation formula of (a) is as follows:
delayk-i＝c_timek-i-pi_timek-i
wherein, delayk-iThe network transmission delay value represents k-i data, k represents latest data, namely current time sampling data, i represents the number of data strips away from the latest data, i is 1,2,3, … l, l represents the number of historical data in the same production period extracted from the cloud server, and k-i represents sampling data at i sampling times before the current time and is recorded as k-i data; c _ timek-iThe timestamp obtained when the kth-i data arrives at the cloud server is represented; pi _ timek-iA packet time stamp indicating the kth-i data;
4) calculating a target maximum network transmission delay value, the target maximum network transmission delay value being delaymax＝max{{delayk-i|i＝1,2,3,…l}、delaydrop、delaythroughtWherein, delayk-iThe network transmission delay value represents k-i data, k represents latest data, namely current time sampling data, i represents the number of data strips away from the latest data, i is 1,2,3, … l, l represents the number of historical data in the same production period extracted from the cloud server, and k-i represents sampling data at i sampling times before the current time and is recorded as k-i data; delaydropDelay value, delay, of network transmission indicating maximum packet loss ratethroughtA network transmission delay value representing a minimum network throughput condition;
5) and evaluating the current network communication quality through network parameters such as network throughput, throughput change rate, loop time delay, time delay jitter, packet loss rate, packet error rate and delay time.
Step three: and the delay value of the technological process data acquired by the cloud server is adjusted in a self-adaptive manner, so that the control and decision program of the cloud server can call the same batch of sampling data at the same time.
The specific steps of adaptively adjusting the delay value of the process data acquired by the cloud server are as follows:
1) if the current network communication quality is better than the worst network in the l network communication qualities corresponding to the l historical dataQuality of the network communication in delaymaxThe target maximum delay of the data received this time; if the current network communication quality is inferior to the worst network communication quality in the l network communication qualities corresponding to the l historical data, the next data cannot arrive on time, and at the moment, the cloud server simulation model directly gives a predicted value to replace a true value without calculating delay;
2) when the target maximum network transmission delay value is delayedmaxAfter the determination, calculating the waiting time delta delay needed by the current process data in the memory after the current process data reaches the memory of the cloud server and before the decision program is calledk-iThe time delta delay required by the current process data to wait in the memory after the current process data reaches the memory of the cloud server and before the decision program is calledk-iThe calculation formula of (a) is as follows:
Δdelayk-i＝delaymax-delayk-i
wherein, Δ delayk-iThe data processing method comprises the steps of representing the waiting time of k-i data, i represents the number of data apart from the latest data, and i is 1,2,3, … l, l represents the number of historical data extracted from a cloud server in the same production period; delaymaxA value representing a target maximum network transmission delay; delayk-iAnd the network transmission delay value of the k-i data is represented.
The invention has the beneficial effects that:
according to the wireless remote data real-time transmission method based on deterministic resource scheduling, the value range of the industrial process data delay is accurately set, the deterministic acquisition of all data in the same batch, the detection of packet loss error sequence and the like are completed on the premise of ensuring the deterministic time processing requirement of the industrial process data, and the reliability requirement of the industrial Internet of things is more favorably realized.
Drawings
Fig. 1 is a flow chart of a method for wireless remote data real-time transmission based on deterministic resource scheduling.
Fig. 2 is a diagram of a typical network architecture of an industrial internet of things.
Fig. 3 is a schematic diagram of a method for real-time wireless remote data transmission based on deterministic resource scheduling, where fig. 3(a) is a diagram of an actual situation during wireless remote data transmission, fig. (b) is a diagram of an ideal situation during wireless remote data transmission, fig. (c) is a diagram of a delay operation during wireless remote data transmission, and fig. (d) is a diagram of an equal-interval reception situation after a delay value is added during wireless remote data transmission.
Detailed Description
The following is a detailed description of the technical solution of the present invention with reference to the accompanying drawings.
As shown in fig. 1, a flowchart of a method for real-time wireless remote data transmission based on deterministic resource scheduling, a method for real-time wireless remote data transmission based on deterministic resource scheduling includes the following steps:
as shown in fig. 2, which is a typical network architecture diagram of the internet of things for industry, the first step: the method comprises the following specific steps of performing wireless transmission after time stamping on sampled process data: 1) siemens S7-300PLC of the bottom industrial field production data acquisition equipment periodically acquires technical process data such as voltage values, current values and the like, and time stamps p _ time corresponding to the latest acquired technical process data and the current sampling timekTogether to the wireless remote transmission device; 2) the router and the raspberry serve as a wireless remote transmission device to continuously monitor a designated process data port, and receive the process data sent by an industrial field in real time and the timestamp p _ time corresponding to the current sampling timekBy time-stamping the process data with the time stamp p _ time corresponding to the current sampling timekAdding a processing time stamp after packaging, and establishing a data packet time stamp pi _ timekThen time stamp pi _ time for the data packetkAnd wirelessly transmitting to a cloud server.
Step two: the method comprises the following steps of obtaining technological process data and a delay value of the technological process data through a cloud server, and estimating network communication quality, wherein the method comprises the following specific steps:
1) the wireless remote transmission terminal and the cloud server establish a Virtual Private Network (VPN) channel for data exchange, and process data acquired by the PLC and a timestamp p _ time corresponding to the current acquisition timekAnd a passage wayTime stamp pi _ time of data packet obtained by device and raspberry groupkUploading to a cloud server for processing;
2) calling a packet analysis program in a function library to analyze a timestamp p _ time corresponding to a timestamp corresponding to the current sampling time in each data packet received by the cloud server in a memory of the cloud serverkAnd packet timestamp pi _ timekAnd recording a timestamp c _ time obtained when the data in the data packet arrives at the cloud serverk；
3) Connecting a database of the cloud server, extracting l pieces of historical data in the same production period from the database of the cloud server, processing the l pieces of historical data, and then obtaining a network transmission delay value delay of each piece of historical datak-iDelay value of network transmissionk-iThe calculation formula of (2) is as follows:
delayk-i＝c_timek-i-pi_timek-i
wherein, delayk-iThe network transmission delay value represents k-i data, k represents latest data, namely current time sampling data, i represents the number of data strips away from the latest data, i is 1,2,3, … l, l represents the number of historical data in the same production period extracted from the cloud server, and k-i represents sampling data at i sampling times before the current time and is recorded as k-i data; c _ timek-iThe timestamp obtained when the kth-i data arrives at the cloud server is represented; pi _ timek-iA packet time stamp indicating the kth-i data;
4) calculating a target maximum network transmission delay value delaymaxDelay value of target maximum network transmissionmax＝max{{delayk-i|i＝1,2,3,…l}、delaydrop、delaythroughtWherein, delayk-iThe network transmission delay value represents k-i data, k represents latest data, namely current time sampling data, i represents the number of data strips away from the latest data, i is 1,2,3, … l, l represents the number of historical data in the same production period extracted from the cloud server, and k-i represents sampling data at i sampling times before the current time and is recorded as k-i data; delaydropDelay value, delay, of network transmission indicating maximum packet loss ratethroughtA network transmission delay value representing a minimum network throughput condition;
5) and evaluating the current network communication quality through network parameters such as network throughput, throughput change rate, loop time delay, time delay jitter, packet loss rate, packet error rate and delay time.
In the transmission process of the second step, the wireless transmission time from the S7-300PLC to the router and the raspberry group is short and always equal, so that the time delay can be regarded as a very small and equal constant value, and when the time delay value from the S7-300PLC to the cloud server is calculated, the transmission delay from the S7-300PLC to the cloud server memory and the transmission delay from the S7-300PLC to the router and the raspberry group both include the constant value, so that the whole wireless network transmission delay value from the S7-300PLC to the cloud server is calculatedk-iTime, timestamp c _ timekAnd a timestamp pi _ timekThe constant value can be offset in the process of difference, so that the wireless transmission delay value from the S7-300PLC to the router and the raspberry group can be ignored, and the timestamp c _ time reaching the cloud server can be obtained in the wireless transmission from the router and the raspberry group to the cloud serverkTime stamp pi _ timekAnd timestamp c _ timekThe interval between the two data is the key for judging whether the data is on time and can be obtained at equal intervals, the time interval between two adjacent data received by the cloud server can be equal and the equal-interval real-time data can be obtained only if each piece of data meets the real-time requirement in the delay time period sent from the router and the raspberry to the cloud server, the time interval between the two adjacent data received by the cloud server always fluctuates and is unequal due to channel fading and instability in the wireless transmission process, and the industrial control and decision process for obtaining the data at equal intervals in the cloud server is very unfavorable, so that the data can be obtained at equal intervals always under the condition of meeting the industrial real-time property by reasonably delaying the data after the cloud server receives the data.
Step three: adaptive adjustment of industrial site acquired by cloud serverA data delay value ensures that the cloud server control and decision program can call the same batch of sampled data at the same time, as shown in a schematic diagram of a wireless remote data real-time transmission method based on deterministic resource scheduling in fig. 3, when the ideal transmission condition of the data is from S7-300PLC to the cloud server, the data is sent at equal time intervals from S7-300PLC, and the cloud server control and decision program can receive the data at equal time intervals, as shown in fig. 3 (b); however, as shown in fig. 3(a), due to the characteristics of unstable wireless network and large fluctuation, the data is sent at intervals of S7-300PLC, but the time intervals between data arriving at the cloud server are not equal, so the processing method shown in fig. 3(c) needs to be adopted, that is, the delay value of the industrial field data is obtained by adaptively adjusting the cloud server, and the specific steps are as follows: 1) if the current network communication quality is better than the worst one of the network communication qualities corresponding to the historical data extracted in the above step, then use delaymaxThe target maximum delay of the data received this time; if the current network communication quality is inferior to the worst network communication quality in the l network communication qualities corresponding to the l historical data, the next data cannot arrive on time, and at the moment, the cloud server simulation model directly gives a predicted value to replace a true value without calculating delay; 2) when the target maximum network transmission delay value is delayedmaxAfter the determination, calculating the waiting time delta delay needed by the current industrial process data in the memory after the current industrial process data reaches the memory of the cloud server and before the control decision program is calledk-iThe calculation formula is as follows:
Δdelayk-i＝delaymax-delayk-i
wherein, Δ delayk-iThe data processing method comprises the steps of representing the waiting time of k-i data, i represents the number of data apart from the latest data, and i is 1,2,3, … l, l represents the number of historical data extracted from a cloud server in the same production period; delaymaxA value representing a target maximum network transmission delay; delayk-iAnd the network transmission delay value of the k-i data is represented. After the self-adaptive adjustment, the industrial field data is transmitted from the PLC at equal intervals and passes through the cloud serverAfter a short delay, the effect of equal time interval between two data can be achieved, as shown in fig. 3 (d).
Claims (2)
1. A wireless remote data real-time transmission method based on deterministic resource scheduling is characterized by comprising the following steps:
the method comprises the following steps: the method comprises the following specific steps of performing wireless transmission after time stamping on sampled process data:
1) the method comprises the steps that an industrial field periodically collects process data in real time and sends the process data and current sampling time to a wireless remote transmission terminal;
2) the wireless remote transmission terminal continuously monitors a designated process data port, receives the process data and the current sampling time sent by the industrial field in real time, packs the process data and the current sampling time, adds a processing timestamp, establishes a data packet timestamp, and then wirelessly sends the data packet timestamp to a cloud server;
step two: the method comprises the following steps of obtaining technological process data and a delay value of the technological process data through a cloud server, and estimating network communication quality, wherein the method comprises the following specific steps:
1) the wireless remote transmission terminal and the cloud server establish a virtual private network channel for data exchange, and upload the process data, the current sampling time and the timestamp of the data packet obtained by the wireless remote transmission terminal to the cloud server;
2) calling a packet analysis program in a function library to analyze the current sampling time and the data packet timestamp in each data packet received by the cloud server in the memory of the cloud server, and recording the timestamp obtained when the data in the data packet reaches the cloud server;
3) connecting a database of the cloud server, extracting l pieces of historical data in the same production period from the database of the cloud server, processing the l pieces of historical data, and then obtaining a network transmission delay value of each piece of historical data, wherein the network transmission delay value delay isk-iThe calculation formula of (a) is as follows:
delayk-i＝c_timek-i-pi_timek-i
wherein, delayk-iThe network transmission delay value represents k-i data, k represents latest data, namely current time sampling data, i represents the number of data strips away from the latest data, i is 1,2,3, … l, l represents the number of historical data in the same production period extracted from the cloud server, and k-i represents sampling data at i sampling times before the current time and is recorded as k-i data; c _ timek-iThe timestamp obtained when the kth-i data arrives at the cloud server is represented; pi _ timek-iA packet time stamp indicating the kth-i data;
4) calculating a target maximum network transmission delay value, the target maximum network transmission delay value being delaymax＝max{{delayk-i|i＝1,2,3,…l}、delaydrop、delaythroughtWherein, delayk-iThe network transmission delay value represents k-i data, k represents latest data, namely current time sampling data, i represents the number of data strips away from the latest data, i is 1,2,3, … l, l represents the number of historical data in the same production period extracted from the cloud server, and k-i represents sampling data at i sampling times before the current time and is recorded as k-i data; delaydropDelay value, delay, of network transmission indicating maximum packet loss ratethroughtA network transmission delay value representing a minimum network throughput condition;
5) evaluating the current network communication quality through network parameters such as network throughput, throughput change rate, loop time delay, time delay jitter, packet loss rate, packet error rate and delay time;
step three: and the delay value of the technological process data acquired by the cloud server is adjusted in a self-adaptive manner, so that the control and decision program of the cloud server can call the same batch of sampling data at the same time.
2. The method according to claim 1, wherein the step three is a specific step of adaptively adjusting a delay value of the process data obtained by the cloud server, and the method comprises the following steps:
1) if the current network communication quality is better than the worst network communication quality in the l network communication qualities corresponding to the l historical data, the delay is usedmaxThe target maximum delay of the data received this time; if the current network communication quality is inferior to the worst network communication quality in the l network communication qualities corresponding to the l historical data, the next data cannot arrive on time, and at the moment, the cloud server simulation model directly gives a predicted value to replace a true value without calculating delay;
2) when the target maximum network transmission delay value is delayedmaxAfter the determination, calculating the waiting time delta delay needed by the current process data in the memory after the current process data reaches the memory of the cloud server and before the decision program is calledk-iThe time delta delay required by the current process data to wait in the memory after the current process data reaches the memory of the cloud server and before the decision program is calledk-iThe calculation formula of (a) is as follows:
Δdelayk-i＝delaymax-delayk-i
wherein, Δ delayk-iThe data processing method comprises the steps of representing the waiting time of k-i data, i represents the number of data apart from the latest data, and i is 1,2,3, … l, l represents the number of historical data extracted from a cloud server in the same production period; delaymaxA value representing a target maximum network transmission delay; delayk-iAnd the network transmission delay value of the k-i data is represented.
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