CN111935664B - Network data real-time collection method based on dynamic feedback - Google Patents

Network data real-time collection method based on dynamic feedback Download PDF

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CN111935664B
CN111935664B CN202010698152.9A CN202010698152A CN111935664B CN 111935664 B CN111935664 B CN 111935664B CN 202010698152 A CN202010698152 A CN 202010698152A CN 111935664 B CN111935664 B CN 111935664B
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CN111935664A (en
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张伟
柏洋洋
司华友
姚晔
李霞瑞
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Hangzhou Dianzi University
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    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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Abstract

The invention discloses a network data real-time collection method based on dynamic feedback, which comprises the steps of arranging nodes to a detection area, calculating a feedback time by a source node according to environment configuration, layering a transfer node, initializing a coding degree value by the source node and the transfer node, randomly selecting a code word in a cache area by the source node for coding operation, executing early strict filtering and later probability filtering according to a feedback data packet to obtain a sending candidate packet set, obtaining a value to be sent in the current round in a new degree time conversion sequence, selecting a code word from the filtered code word for coding and forwarding, decoding the code word by the transfer node, detecting whether the current round needs feedback, and sending a feedback packet if the current round needs feedback; and detecting whether the current round reaches the delay effect moment, and if the current round reaches the delay effect moment, switching to a Pull mode for carrying out data packet exchange. The invention improves the collection efficiency of real-time data packets, reduces invalid code words in the network and improves the effective utilization rate of channels by combining dynamic feedback, pull mode and the like.

Description

Network data real-time collection method based on dynamic feedback
Technical Field
The invention belongs to the field of near real-time data transmission of a wireless sensor network, relates to a rapid real-time data collecting method in a point-to-multipoint oriented diffusion network, and particularly relates to a network data real-time collecting method based on dynamic feedback.
Background
The wireless sensor network is a network formed by randomly distributing a large number of sensor nodes in a certain area in a self-organizing manner through a wireless communication technology, and aims to cooperatively sense, collect and process the environment and events in the coverage area of the network. The method has the characteristics of flexible deployment, distributed type, low cost and the like, and is widely applied to civil fields of military, industry, medical treatment and the like, such as ecological environment monitoring, infrastructure protection, event positioning, target tracking and the like. The wireless sensor network is flexible and convenient in deployment mode and powerful in function, and the core function of the wireless sensor network is the collection of sensing data in the network, so that the wireless sensor network is often deployed in severe or special environments to collect monitoring data.
Network coding is widely applied to data collection of erasure channels, particularly wireless sensor networks, for example, coding modes such as Random Network Coding (RNC), LT Codes, growth Codes and the like, people generally utilize network coding to improve the efficiency of data collection and network throughput, and rateless coding is proved to be suitable for data collection in scenarios of erasure channel or lossy channel data transmission. In a multicast scene, random linear coding is added, and the collection success probability and robustness can be improved by utilizing the redundant network capacity; for some P2P medium content distribution scenes, network coding under a random strategy is also applied.
Data collection protocols based on network coding technology are generally divided into two types according to the collection timeliness, one type is a delay data collection protocol, and the other type is a rapid data collection protocol. The delayed collection protocol is represented by LT Code, and the delayed collection protocol focuses on the safe storage and recovery of data; the fast data collection protocol is represented by Growth Codes, and focuses on the safe collection and recovery of data. The network coding protocols are suitable for a network model with multi-point perception and single-point collection, and have poor adaptability under the network model with single-point data diffusion and multi-point collection. Currently, there is less research on collection protocols under such a network model, and there is less research on collection protocols for real-time data under such a network model. The traditional point-to-multipoint wireless communication network generally comprises a central monitoring node (source node) and a plurality of remote terminal nodes (receiving nodes), wherein a plurality of forwarding layer nodes (transfer nodes) are used as transfer stations between the central monitoring node and the remote terminal nodes. Since the design of the conventional network coding protocol is not suitable for the point-to-multipoint network collection model, if the network coding protocol such as LT Code and Growth Codes is used, there are disadvantages of inefficient data collection, excessive redundant data packets, etc., and the "coupon collection" problem at the end of collection increases the collection delay of data.
Disclosure of Invention
The invention aims to provide a network data real-time collection method based on dynamic feedback, which has low collection delay and high collection efficiency and is suitable for a point-to-multipoint network collection model.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
the invention relates to a network real-time data collection method based on dynamic feedback, which comprises the following steps:
s1, arranging nodes to a detection area, wherein the nodes comprise a source node, a receiving end node and a transfer node, a hierarchical data packet is arranged in the source node, and a simple code word cache X and a complex code word cache Y are arranged in the transfer node;
s2, the source node calculates feedback time according to environment configuration and stores the feedback time in a feedback sequence;
s3, adding the feedback sequence into the layered data packet and sending the layered data packet by the source node, and layering after receiving the layered data packet by the transit node;
s4, initializing the coding degree value d by the source node and the transfer node, initializing a simple code word cache X and a complex code word cache Y by the transfer node, generating source data by the source node and dividing the source data into N code words;
s5, a source node randomly selects a code word of a cache area to perform coding operation, randomly selects a neighbor node for exchanging a coded data packet, obtains a feedback data packet of a transfer node in the exchange, performs early-stage strict filtering and later-stage probability filtering according to the feedback data packet to obtain a sending candidate packet set C, and obtains a value d to be sent in the current round in a new degree time conversion sequence;
s6, the source node randomly generates a candidate value Sigma, if the candidate value Sigma is smaller than or equal to d, the Sigma value is unchanged, otherwise, the Sigma = d, and the source node randomly selects non-repeated code words in the code word set C according to the candidate value Sigma to carry out coding, and randomly selects the neighbor nodes to carry out code word exchange;
s7, after receiving the code word sent by the source node, the transfer node decodes the code word and caches the decoding result in an X cache or a Y cache;
s8, judging whether the current round reaches the delay effect moment, if the current round reaches the delay effect moment, the transfer node changes the data packet exchange mode into a Pull mode, exchanges with a neighbor node and enters the next step, if the delay effect moment is not reached, the transfer node selects a value to encode the data packet and forwards the data packet, judging whether the transfer round reaches the feedback moment or not, if the delay effect moment is not reached, returning to S5, and if the feedback moment is reached, entering the next step;
and S9, when the receiving end node does not receive all the code word packets, returning to S5, and when the receiving end node receives all the code word packets, finishing the collection process.
Preferably, in step S2, the source node calculates the feedback time according to an environment configuration, where the environment configuration includes the number of the source nodes, the number of the receiving end nodes, and the number of the data packets.
Preferably, in step S2, the feedback opportunity is calculated by using a markov algorithm and a feedback opportunity probability matrix, and the method specifically includes the steps of:
s2.1, assuming that the hierarchy of the current forwarding layer is l, the average neighbor number of the forwarding node is n, the neighbor number of the neighbor node with the hierarchy higher than that of the neighbor node is k, and after the r round of exchange, the arrival hierarchy of the feedback packet is X r Obtaining the transition probability of the Markov chain
Figure BDA0002592026410000031
Comprises the following steps:
Figure BDA0002592026410000032
and calculating to obtain a state equation matrix p:
Figure BDA0002592026410000033
wherein eta is i,j Indicating a transition of state and indicating the probability of state i transitioning to state j.
S2.2, after unit turns are calculated, expected change (P-I) X of each code word propagation level is as follows:
Figure BDA0002592026410000034
when the transmitted layer 0 is 1, the current data packet is transmitted to the source end node;
and S2.3, solving the equation to obtain a code word feedback time sequence required by the forwarding layer.
Preferably, in step S3, the layering of the transit node specifically includes:
s3.1, a source node generates a hierarchical data packet, wherein incremental hierarchical data i is carried in the hierarchical data packet and is sent to a neighbor node;
s3.2, taking out i in the hierarchical data packet by the neighbor node, setting the hierarchy of the neighbor node as i, updating the hierarchical data packet, setting hierarchy information i = i +1 in the data packet, and broadcasting the data packet to the neighbor node of the neighbor node;
s3.3, if the neighbor node already receives the hierarchical data packet, directly discarding the data packet, otherwise, executing the step S3.2;
and S3.4, repeating the steps S3.2 and S3.3 until all the forwarding layer nodes obtain the hierarchy information.
Preferably, when the source node randomly selects a code word in the buffer area for encoding operation in S5, the selecting step includes:
s5.1, setting the network packet loss rate in the current network model as alpha and the number of source end nodes as S n ，S n Default is 1, source data packet number N and transfer node number F n Calculating to obtain the probability rho of successfully decoding a data packet with one degree d received by the transit node when the transit node successfully decodes r r′,d ，
Figure BDA0002592026410000041
S5.2. Calculating the expected decoding sequence R d Comprises the following steps:
Figure BDA0002592026410000042
s5.3, after the feedback information is added, according to the early-stage strict filtering and the later-stage probability filtering criteria, the number of the ideal code words needed when the acquisition degree is j is A j And calculating to obtain a degree conversion time sequence as follows:
Figure BDA0002592026410000043
k is the corresponding forwarding round, fn is the number of the transit nodes, the epsilon is the strength coefficient,
Figure BDA0002592026410000044
the method adjusts the code word sending number of the source node to adapt to the requirement of data packet collection under different environments, and when the element is the minimum value>
Figure BDA0002592026410000045
Then, the multiplication coefficient e is calculated as 1, namely, the data packet is sent according to the original data volume, and the enhancement flow is 0; when the e is the maximum value 1, the multiplication coefficient e is calculated as Fn, the number of the code words transmitted in each round is positively correlated with the number of forwarding layer nodes, and the value is based on the sum of the values of the multiplication coefficient e and the value of the multiplication coefficient Fn>
Figure BDA0002592026410000046
For the probability of failure of each decoding round, <' >>
Figure BDA0002592026410000047
S5.3, the source node randomly selects the coded data packet S, and the degree of the data packet S meets the condition that degree (S) is less than or equal to j.
Preferably, in S8, the deriving step of the delay effect time is as follows:
s8.1, setting the independent storage and forwarding space in each transfer node as C, the number of missing code words of the neighbor nodes exchanged in the round as m, and the degree randomly selected in the degree distribution as d, wherein when d is less than or equal to C-m, the probability that the code words coded in the round are useless data packets is obtained as follows:
Figure BDA0002592026410000048
/>
s8.2. Decoding sequence by ideal
Figure BDA0002592026410000049
Can be obtained when: >>
Figure BDA00025920264100000410
Figure BDA00025920264100000411
The delay effect is emphasized, i.e. the delay effect moment is reached.
Preferably, in S1, when the nodes are arranged to the detection area, the source node is placed at an edge position of the area, the sink node is deployed at the other side of the area, and the transit node is randomly arranged between the source node and the sink node.
Compared with the prior art, the invention has the following beneficial effects:
the invention utilizes the feedback channel in the wireless sensor network to generate feedback information and dynamically act on the central node and the forwarding layer node, optimizes the feedback opportunity by utilizing the Markov algorithm, reduces the flooding effect brought by the feedback information, and uses a new degree time conversion sequence to optimize the data packet value in the network, thereby improving the transmission and collection efficiency of real-time data, reducing the delay effect, improving the utilization rate of the channel and reducing the number of redundant code words in the network. Meanwhile, the system robustness is increased by means of dynamic adjustment, and the adaptability to different environments is improved compared with the traditional method.
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FIG. 1 is a block diagram of a general implementation of the method of the present invention.
FIG. 2 is an abstract network model architecture diagram.
Fig. 3 is a network feedback hierarchy.
Fig. 4 is a diagram of a forwarding layer-source feedback packet structure.
Fig. 5 is a diagram of a forwarding layer-forwarding layer Pull packet structure.
FIG. 6 is a diagram of a source hierarchical packet structure.
Detailed Description
For further understanding of the present invention, the present invention will be described in detail with reference to examples, which are provided for illustration of the present invention but are not intended to limit the scope of the present invention. The embodiment is directed to rapid collection of real-time data under a point-to-multipoint network model in wireless network transmission.
Referring to fig. 1, the method for collecting network real-time data based on dynamic feedback according to the present invention includes the following steps:
s1, arranging nodes to a detection area, wherein the nodes comprise source nodes, receiving end nodes and transit nodes, a layered data packet is arranged in the source nodes, the source nodes are placed at the edge of the area, the receiving end nodes are arranged at the other side of the area, and the transit nodes are randomly arranged between the source nodes and the receiving end nodes, which is shown in the attached figure 2; wherein, a simple code word cache X and a complex code word cache Y are arranged in the transit node.
S2, the source node calculates feedback opportunity according to environment configuration, the environment configuration comprises the number of the source nodes, the number of the receiving end nodes and the number of data packets, the source node stores the feedback opportunity in a feedback sequence, the feedback opportunity is calculated by using a Markov algorithm and a feedback opportunity probability matrix, and the method specifically comprises the following steps:
s2.1, assuming that the hierarchy of the current forwarding layer is l, the average neighbor number of the forwarding node is n, the neighbor number of the neighbor node with the hierarchy higher than that of the neighbor node is k, and after the r round of exchange, the arrival hierarchy of the feedback packet is X r Obtaining the transition probability of the Markov chain
Figure BDA0002592026410000061
Comprises the following steps:
Figure BDA0002592026410000062
/>
and calculating to obtain a state equation matrix p:
Figure BDA0002592026410000063
wherein eta is i,j Indicating the transition of state and indicating the probability of state i transitioning to state j.
S2.2, after unit turns are calculated, expected change (P-I) X of each code word propagation level is as follows:
Figure BDA0002592026410000064
when the transmitted layer 0 is 1, the current data packet is transmitted to the source end node;
and S2.3, solving the equation to obtain a code word feedback time sequence required by the forwarding layer.
S3, in order to accelerate the feedback speed of the feedback data packet, the embodiment adds a concept of network feedback layering, a source node adds a feedback sequence into the layered data packet and sends the layered data packet, a transit node performs layering after receiving the layered data packet, and the layering of the transit node specifically comprises:
s3.1, a source node generates a hierarchical data packet, wherein the structure of the hierarchical data packet is shown in figure 6, incremental hierarchical data i is carried in the hierarchical data packet and is sent to a neighbor node;
s3.2, taking out i in the hierarchical data packet by the neighbor node, setting the hierarchy of the neighbor node as i, updating the hierarchical data packet, setting hierarchy information i = i +1 in the data packet, and broadcasting the data packet to the neighbor node of the neighbor node;
s3.3, if the neighbor node already receives the layered data packet, the data packet is directly discarded, otherwise, the step S3.2 is executed;
and S3.4, repeating the steps S3.2 and S3.3 until all the forwarding layer nodes obtain the hierarchy information, and finally obtaining the network feedback hierarchy relation graph shown in the figure 3.
S4. Source node and transit node pairInitializing a coding degree value d, wherein the initialized value d is 1, initializing a simple code word cache X and a complex code word cache Y by a transfer node, generating source data by a source node, dividing the source data into N code words, and setting one code word as N i 。
S5, the source node randomly selects the code words of the cache area to perform coding operation, and the selection step comprises the following steps:
s5.1, setting the network packet loss rate in the current network model as alpha and the number of source end nodes as S n ，S n Default is 1, source data packet number N and transfer node number F n Calculating the probability rho of successfully decoding a data packet with one degree d received by the transit node when the transit node successfully decodes r r′,d ，
Figure BDA0002592026410000071
S5.2. Calculating the expected decoding sequence R d Comprises the following steps:
Figure BDA0002592026410000072
s5.3, after the feedback information is added, according to the early-stage strict filtering and the later-stage probability filtering criteria, the number of the ideal code words needed when the acquisition degree is j is A j And calculating to obtain a degree conversion time sequence as follows:
Figure BDA0002592026410000073
/>
k is the corresponding forwarding round, fn is the number of the transit nodes, the epsilon is the strength coefficient,
Figure BDA0002592026410000074
the method adjusts the code word sending number of the source node to adapt to the requirement of data packet collection in different environments, and when the element is the minimum value>
Figure BDA0002592026410000075
Then, the multiplication coefficient e is calculated as 1, namely, the data packet is sent according to the original data volume, and the enhancement flow is 0; when e is the maximum value 1, the multiplication coefficient e is calculated as Fn, the number of code words transmitted in each turn is positively correlated with the number of forwarding layer nodes, and the value of Fn is determined by the maximum value of>
Figure BDA0002592026410000076
For the probability of failure of each decoding round, <' >>
Figure BDA0002592026410000077
S5.3, the source node randomly selects the coded data packet S, and the degree of the data packet S meets the condition that degree (S) is less than or equal to j.
The source node randomly selects a neighbor node for exchanging the data packet after being coded, obtains a feedback data packet of the transfer node in the exchange, performs early strict filtering and later probability filtering according to the feedback data packet to obtain a sending candidate packet set C, and obtains a value d to be sent in the current round in a new degree moment conversion sequence;
s6, the source node randomly generates a candidate value Sigma, if the candidate value Sigma is smaller than or equal to d, the Sigma value is unchanged, otherwise, the Sigma = d, and the source node randomly selects non-repeated code words in the code word set C according to the candidate value Sigma to carry out coding, and randomly selects the neighbor nodes to carry out code word exchange;
s7, after receiving the code word sent by the source node, the transfer node executes a D-type decoder to decode the code word, and caches the decoding result in an X cache or a Y cache;
s8, judging whether the current round reaches the delay effect time, wherein the delay effect time is deduced according to the following steps:
s8.1, setting the independent storage and forwarding space in each transfer node as C, the number of missing code words of the neighbor nodes exchanged in the round as m, and the degree randomly selected in the degree distribution as d, wherein when d is less than or equal to C-m, the probability that the code words coded in the round are useless data packets is obtained as follows:
Figure BDA0002592026410000081
s8.2. Decoding sequence by ideal
Figure BDA0002592026410000082
Can be obtained when: >>
Figure BDA0002592026410000083
Figure BDA0002592026410000084
When the delay effect is increased, namely the delay effect moment is reached;
if the delay effect moment is reached, the transfer node changes the data packet exchange mode into a Pull mode and exchanges with the neighbor node, as shown in fig. 5, the transfer node is a Pull data packet structure diagram, when the transfer node is changed into the Pull mode, the request type is changed into 1, the position of the request data packet id is set as the id required by the request, and then the next step is carried out;
if the delay effect moment is not reached, the transit node is in a common mode, the transit node selects a value-coded data packet and forwards the data packet, namely the request type is 0, the id position of the request data packet is replaced by a placeholder, if the neighbor node receives the request packet in the current round, nbit corresponds to the data packet corresponding to the request id carried in the request data packet, then whether the forwarding round reaches the feedback moment or not is judged, if the feedback moment does not reach the feedback moment, S5 is returned, if the feedback moment reaches, the decoding condition of the neighbor node is fed back, the feedback is carried out according to the reverse feedback of the hierarchy, the feedback speed is improved, the structure of the feedback data packet is shown in figure 4, the decoding conditions of the hierarchy and Nbit are included, when the data packet is forwarded to the hierarchy higher than the current hierarchy, the current hierarchy level value is changed and continuously forwarded to the source end, the source end updates the own filter screen, the data packet is used in the next round of forwarding, and then the next round is carried out;
and S9, when the receiving end node does not collect all the code word packets, returning to S5, and when the receiving end node collects all the code word packets, ending the collection process and stopping the transmission of the data of the current generation.
The present invention has been described in detail with reference to the embodiments, but the description is only for the preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.

Claims (6)

1. A network real-time data collection method based on dynamic feedback is characterized in that: which comprises the following steps:
s1, arranging nodes to a detection area, wherein the nodes comprise a source node, a receiving end node and a transfer node, a hierarchical data packet is arranged in the source node, and a simple code word cache X and a complex code word cache Y are arranged in the transfer node;
s2, the source node calculates feedback time according to environment configuration and stores the feedback time in a feedback sequence;
s3, adding the feedback sequence into the layered data packet and sending the layered data packet by the source node, and layering after receiving the layered data packet by the transit node;
s4, initializing the coding degree value d by the source node and the transfer node, initializing a simple code word cache X and a complex code word cache Y by the transfer node, generating source data by the source node and dividing the source data into N code words;
s5, a source node randomly selects a code word of a cache area to perform coding operation, randomly selects a neighbor node for exchanging a coded data packet, obtains a feedback data packet of a transfer node in the exchange, performs early-stage strict filtering and later-stage probability filtering according to the feedback data packet to obtain a sending candidate packet set C, and obtains a value d to be sent in the current round in a new degree time conversion sequence;
s6, the source node randomly generates a candidate value Sigma, if the candidate value Sigma is smaller than or equal to d, the value Sigma is unchanged, otherwise, the value Sigma = d, and the source node randomly selects non-repeated code words in the code word set C according to the candidate value Sigma to carry out coding, and randomly selects the neighbor nodes to carry out code word exchange;
s7, after receiving the code word sent by the source node, the transfer node decodes the code word and caches the decoding result in an X cache or a Y cache;
s8, judging whether the current round reaches the delay effect time, if so, changing the data packet exchange mode into a Pull mode by the transfer node, exchanging with a neighbor node and entering the next step, if not, selecting the value-coded data packet and forwarding by the transfer node, judging whether the transfer round reaches the feedback time, if not, returning to S5, and if so, entering the next step;
and S9, when the receiving end node does not receive all the code word packets, returning to S5, and when the receiving end node receives all the code word packets, finishing the collection process.
2. The method for collecting network real-time data based on dynamic feedback according to claim 1, wherein: in step S2, the source node calculates the feedback time according to the environment configuration, where the environment configuration includes the number of source nodes, the number of receiving end nodes, and the number of data packets.
3. The method for collecting network real-time data based on dynamic feedback according to claim 1, wherein: in step S3, the layering of the transit node specifically includes:
s3.1, a source node generates a hierarchical data packet, wherein incremental hierarchical data i are carried in the hierarchical data packet and are sent to a neighbor node;
s3.2, the neighbor node takes out the i in the hierarchical data packet, sets the hierarchy of the neighbor node as i, updates the hierarchical data packet, sets the hierarchy information i = i +1 in the data packet, and broadcasts the data packet to the neighbor node of the neighbor node;
s3.3, if the neighbor node already receives the layered data packet, the data packet is directly discarded, otherwise, the step S3.2 is executed;
and S3.4, repeating the steps S3.2 and S3.3 until all the forwarding layer nodes obtain the hierarchy information.
4. The method for collecting network real-time data based on dynamic feedback according to claim 1, wherein: when the source node randomly selects the code words in the cache area for coding operation in the S5, the selecting step includes:
s5.1, setting the network packet loss rate in the current network model as alpha and the number of source end nodes as S n ，S n Default is 1, source data packet number N and transfer node number F n Calculating to obtain the probability of successfully decoding a data packet with one degree d when the relay node successfully decodes r
Figure QLYQS_1
r′,d ，
Figure QLYQS_2
S5.2. Calculating the expected decoding sequence R d Comprises the following steps:
Figure QLYQS_3
s5.3, after adding the feedback information, according to the early-stage strict filtering and the later-stage probability filtering criteria, the number of the ideal code words needed when the obtained degree is j is A j And calculating to obtain a degree conversion time sequence as follows:
Figure QLYQS_4
k is the corresponding forwarding round, fn is the number of the transit nodes, the epsilon is the strength coefficient,
Figure QLYQS_5
for the probability of failure of each decoding round, <' >>
Figure QLYQS_6
S5.3, the source node randomly selects the coded data packet S, and the degree of the data packet S meets the condition that degree (S) is less than or equal to j.
5. The method for network real-time data collection based on dynamic feedback according to claim 4, wherein: in S8, the deriving step of the delay effect time is as follows:
s8.1, setting the independent storage and forwarding space in each transfer node as C, the number of missing code words of the neighbor nodes exchanged in the round as m, and the degree randomly selected in the degree distribution as d, wherein when d is less than or equal to C-m, the probability that the code words coded in the round are useless data packets is obtained as follows:
Figure QLYQS_7
s8.2. Decoding sequence by ideal
Figure QLYQS_8
Can be obtained when the condition is satisfied>
Figure QLYQS_9
Figure QLYQS_10
The delay effect is emphasized, i.e. the delay effect moment is reached.
6. The method for collecting network real-time data based on dynamic feedback according to claim 4, wherein: in S1, when nodes are arranged to a detection area, a source node is placed at the edge position of the area, a receiving end node is arranged at the other side of the area, and a transit node is randomly arranged between the source node and the receiving end node.
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