CN113316211A - Tree growth remote measuring method and system based on directional diffusion protocol - Google Patents

Tree growth remote measuring method and system based on directional diffusion protocol Download PDF

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CN113316211A
CN113316211A CN202110434487.4A CN202110434487A CN113316211A CN 113316211 A CN113316211 A CN 113316211A CN 202110434487 A CN202110434487 A CN 202110434487A CN 113316211 A CN113316211 A CN 113316211A
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CN113316211B (en
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孙渊敬
方陆明
袁方星
孙林豪
郑似青
杨来邦
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Hangzhou Perception Technology Co ltd
Zhejiang A&F University ZAFU
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Zhejiang A&F University ZAFU
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/023—Limited or focused flooding to selected areas of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The invention discloses a tree growth remote measuring method and system based on a directional diffusion protocol, and particularly relates to the field of tree measurement of an artificial forest, which comprises the following steps: the method comprises the steps that interest information is flooded and transmitted to data nodes through base station nodes, the distance between each node and the base station nodes is obtained in the flooding transmission process, and the interest information and the forwarding times of the interest information under each transmission path when the interest information is forwarded to each node are stored in a node list of the corresponding node; acquiring a propagation path with the minimum forwarding times in the propagation paths, and using the propagation path as a data transmission path, wherein the rest propagation paths are used as alternative paths; and screening low-energy nodes and carrying out path replacement. Compared with the traditional DD protocol, the method reduces the gradient establishment process, greatly reduces the network construction time, improves the survival time of the network, and simultaneously improves the utilization rate of network energy.

Description

Tree growth remote measuring method and system based on directional diffusion protocol
Technical Field
The invention relates to the field of tree measurement of artificial forests, in particular to a tree growth remote measuring method and system based on a directional diffusion protocol.
Background
The height and diameter at breast height of tree are important indexes for the growth of tree. The continuous and accurate measurement of the growth amount of the trees in the sample plot not only can reveal the growth rule of the trees and the forest stand, but also is beneficial to ecological research. The traditional single-wood measuring scale has the defects of large labor and time consumption, incapability of continuous measurement, difficulty in integration of measurement and treatment and the like, and cannot meet the requirements of forest resource investigation on multi-party application. With the continuous development of information technology, the continuous and accurate remote measurement of the tree growth amount by using a sensing technology becomes a research hotspot.
At present, the continuous telemetering mainly adopts a mode of arranging a plurality of sensing device nodes in a telemetering sample plot to telemeter the growth amount of trees. Because the sensing device nodes are arranged in the field, even the environment is very complicated, the energy stored in the nodes is limited and is difficult to supplement in time. In order to improve the energy utilization rate and the cooperation efficiency among nodes of the sensing device in the telemetering sample plot as much as possible under the constraint of limited energy, a Wireless Sensing Network (WSN) (wireless Sensor network) technology is applied, and a wireless sensing network for telemetering the continuous growth amount of trees is established by a plurality of micro Sensor nodes in the sample plot and an information collecting base station (Sink) in a self-organizing manner. In the prior art, the WSN technology is used for tree growth amount remote measurement and exploration, but the requirement of a routing protocol is not researched. Meanwhile, the traditional direct diffusion protocol (DD) is a data-centric routing algorithm, which can be used for remote measurement of different data types of tree growth amount, but still has the defects of large node energy consumption and unbalanced energy.
Based on the problems, the DD protocol is optimized aiming at the characteristics that the intervals of trees in an artificial forest are the same and the growth quantity of the trees is continuously telemetered on the basis of the DD protocol, and the DD with energy gradient combining distance and hop which are more suitable for continuously and accurately telemetering a plurality of trees in a sample plot are provided.
Disclosure of Invention
In order to solve the defects of the existing tree growth remote measurement, the invention provides a directional diffusion protocol construction method for tree growth remote measurement, which comprises the following steps:
s1: the method comprises the steps that interest information is flooded and transmitted to data nodes through base station nodes, the distance between each node and the base station nodes is obtained in the flooding transmission process, and the interest information and the forwarding times of the interest information under each transmission path when the interest information is forwarded to each node are stored in a node list of the corresponding node;
s2: acquiring a propagation path with the minimum forwarding times in the propagation paths, and using the propagation path as a data transmission path, wherein the rest propagation paths are used as alternative paths;
s3: judging whether each node in the current data transmission path has a low-energy node or not by taking the preset waiting time of each node as a judgment interval, if so, acquiring the previous node information of the low-energy node and entering the step S4, and if not, performing data transmission by using the current data transmission path; the low-energy node is a node with node energy lower than a preset threshold value;
s4: and the node is used as a propagation starting point, and the alternative path which does not contain the low-energy node and has the least forwarding times is obtained as a data transmission path.
Further, before the determination, the step S3 includes:
setting a preset threshold value of each node through a first preset formula according to the forwarding times and the distance of each node in the current data transmission path; the first preset formula is as follows:
Figure BDA0003032559090000021
in the formula, ETnA preset threshold value for a corresponding node in the current data transmission path, ErIs the node residual energy, h (x, y) is the forwarding times of the corresponding node in the current data transmission path, hmax(x, y) is the maximum number of retransmissions in the flood propagation, hmin(x, y) is the minimum number of times of forwarding in flooding propagation, Sink is a base station node, d (i, Sink) is the distance between the corresponding node and the base station node in the current data transmission path, dmax(i, Sink) is the maximum distance between the node and the base station node in the flooding propagation, dmin(i, Sink) is the minimum value of the distance between the node and the base station node in the flooding propagation, and u is a constant between 0 and 1.
Further, the step S1 is followed by the step of:
s11: and acquiring a node general table of the data nodes after the flooding propagation, and sending the node general table to each node, wherein the node general table comprises the interest information forwarding times and the interest information of each propagation path.
Further, step S3 is preceded by the steps of:
s30: setting the preset waiting time of each node through a second preset formula according to the forwarding times; the second preset formula is as follows:
Tquery＝h(x,y)×t；
in the formula, TqueryAnd the preset waiting time is the forwarding times of the corresponding nodes in the current data transmission path, and t is the time required by the node self-check.
Further, in step S3, if there is a low-energy node, when the data transmission still passes through the low-energy node as the data transmission node, the data transmission path is replaced by the next data transmission passing through step S4.
Furthermore, the trees are artificial forests, and intervals among the trees are equal.
The invention also provides a tree growth remote measuring system based on the directional diffusion protocol, which comprises:
the base station node is used for flooding and transmitting the interest information to the data node;
the intermediate node is used for acquiring the distance from the base station node in the flooding propagation process and storing the interest information and the forwarding times of the interest information under each propagation path to the node list;
the data node is used for acquiring a node general table after flooding propagation and sending the node general table to each intermediate node, wherein the node general table comprises the interest information forwarding times and the interest information of each propagation path;
the path selection unit is used for acquiring the propagation path with the minimum forwarding times in the propagation path, and using the propagation path as a data transmission path, and using the rest propagation paths as alternative paths;
the intermediate node also comprises a judger which is used for judging whether each node in the current data transmission path has a low-energy node or not by taking the preset waiting time of each node as a judgment interval, and if so, sending an alternative signal to the previous node; the low-energy node is a node with node energy lower than a preset threshold value
And the path selection unit acquires an alternative path which does not contain low-energy nodes and has the minimum forwarding times as a data transmission path according to the alternative signal and the node as a propagation starting point.
The system further comprises a threshold setting unit, a threshold setting unit and a data transmission unit, wherein the threshold setting unit is used for setting a preset threshold of each node through a first preset formula according to the forwarding times and the distance of each node in the current data transmission path; the first preset formula is as follows:
Figure BDA0003032559090000031
in the formula, ETnA preset threshold value for a corresponding node in the current data transmission path, ErIs the node residual energy, h (x, y) is the forwarding times of the corresponding node in the current data transmission path, hmax(x, y) is the maximum number of retransmissions in the flood propagation, hmin(x, y) is the minimum number of times of forwarding in flooding propagation, Sink is a base station node, d (i, Sink) is the distance between the corresponding node and the base station node in the current data transmission path, dmax(i, Sink) is a node and a base station node in flood propagationMaximum value of point distance, dmin(i, Sink) is the minimum value of the distance between the node and the base station node in the flooding propagation, and u is a constant between 0 and 1.
Further, the judger sets the preset waiting time of each node through a second preset formula according to the forwarding times; the second preset formula is as follows:
Tquery＝h(x,y)×t；
in the formula, TqueryAnd the preset waiting time is the forwarding times of the corresponding nodes in the current data transmission path, and t is the time required by the node self-check.
Furthermore, the trees are artificial forests, and intervals among the trees are equal.
Compared with the prior art, the invention at least has the following beneficial effects:
(1) the tree growth remote measuring method and system based on the directional diffusion protocol are based on the characteristic that the intervals among trees of an artificial forest are equal, the forwarding times are recorded and stored in the process of flood propagation, and the optimal data transmission path can be obtained by selecting the propagation path with the minimum forwarding times, so that compared with the traditional DD protocol, the process of gradient establishment is reduced, the network construction time is greatly reduced, and the network survival time is prolonged;
(2) by judging the low-energy nodes, after the low-energy nodes are found, the last node of the low-energy nodes in the current transmission path is taken as a transmission starting point, and the alternative path which does not contain the low-energy nodes and has the least forwarding times is selected as a data transmission path, so that the utilization rate of network energy is greatly improved compared with the traditional DD protocol which needs to perform interest diffusion again once the node energy consumption is exhausted;
(3) through the first preset formula, the preset threshold value is set by utilizing the forwarding times and the distance information of each node in the current data transmission path, and the preset threshold value of the node with high utilization rate can be ensured to better meet the actual use requirement.
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FIG. 1 is a method step diagram of a tree growth telemetry method and system based on a directed diffusion protocol;
FIG. 2 is a system diagram of a tree growth telemetry method and system based on a directed diffusion protocol;
FIG. 3 is a diagram of the DD protocol operation;
FIG. 4 is a schematic diagram of DD-DHE protocol "interest" diffusion and gradient setup;
FIG. 5 is a diagram illustrating node forwarding times and distances;
FIG. 6 is a schematic diagram of a network life cycle;
FIG. 7 is a diagram of the total energy remaining in the network;
FIG. 8 is a graph of node remaining average energy;
fig. 9 is a graph showing the data reception amount of the Sink node.
Detailed Description
The following are specific embodiments of the present invention and are further described with reference to the drawings, but the present invention is not limited to these embodiments.
Example one
Telemetry is a method that relies on a proximity sensor to collect data and transmit the data to a remote collection station, and has found good application in the measurement of tree growth. Although telemetry at the present stage has been applied to forestry, the WSN developed in recent years is applied to measurement of tree growth due to its advantages of low cost, rapid and convenient system arrangement, and realization of interactive communication between nodes. A large number of sensor nodes are arranged in a tree sample area to be measured to form a wireless sensing network. When the host sends an instruction to the query node, the node can remotely return corresponding data information, so that a quick and efficient measurement target is realized. The DD protocol is a query-based routing protocol, data-centric. Aiming at the characteristics of the DD protocol, the DD protocol can be applied to the tree growth amount telemetering WSN.
The setup of the DD protocol includes three parts, namely periodic "interest" flooding, data probing and path strengthening. Fig. 3 depicts the operation of the phases of the DD protocol. In fig. 3, a Sink node (corresponding to a base station node in the present invention, and a Source node corresponding to a data node in the present invention) first periodically diffuses an "interest packet" task to all nodes in a network in a flooding manner, where the "interest packet" task includes information such as a data type to be queried. When the interest packet in the graph is diffused, an interest gradient field is established between the Sink node and the data source node, and a plurality of data transmission paths with lower cost are selected. Then, the data source node sends the probe data along the direction of gradient establishment in a low-speed mode, and selects a path with the lowest cost for reinforcement, and the subsequent data transmission is carried out on the reinforced path.
As can be seen from the above description, the DD protocol periodically propagates messages in a flooding manner in the "interest" diffusion stage, which inevitably results in a large amount of energy consumption of the nodes, and in the process of establishing the gradient field, the source node returns a low-rate probe message to the Sink node according to the established inverse gradient, which in turn results in a large amount of energy consumption. After the optimal path is established, the path is used all the time, if a certain node on the path is exhausted or fails, a path reconstruction mechanism needs to be started, which is a great challenge to the overall energy of the network. In order to make the DD protocol better applied to the tree growth telemetering WSN, the invention improves the DD protocol, provides a DD-DHE protocol, and specifically as shown in figure 1, a directional diffusion protocol construction method for tree growth telemetering comprises the following steps:
s1: the method comprises the steps that interest information is flooded and transmitted to data nodes through base station nodes, the distance between each node and the base station nodes is obtained in the flooding transmission process, and the interest information and the forwarding times of the interest information under each transmission path when the interest information is forwarded to each node are stored in a node list of the corresponding node;
s2: acquiring a propagation path with the minimum forwarding times in the propagation paths, and using the propagation path as a data transmission path, wherein the rest propagation paths are used as alternative paths;
s3: judging whether each node in the current data transmission path has a low-energy node or not by taking the preset waiting time of each node as a judgment interval, if so, acquiring the previous node information of the low-energy node and entering the step S4, and if not, performing data transmission by using the current data transmission path; the low-energy node is a node with node energy lower than a preset threshold value;
s4: and the node is used as a propagation starting point, and the alternative path which does not contain the low-energy node and has the least forwarding times is obtained as a data transmission path.
Meanwhile, step S1 is followed by the step of:
s11: and acquiring a node general table of the data nodes after the flooding propagation, and sending the node general table to each node, wherein the node general table comprises the interest information forwarding times and the interest information of each propagation path.
Step S1 is an "interest" diffusion stage of the DD-DHE protocol in the present invention, and since the DD protocol performs "interest" flooding, a large number of data gradients are established between nodes, but in the path enhancement stage, there is only one finally formed path, and there is a phenomenon that the rest of gradients cannot be fully utilized. In the subsequent data transmission process, if the intermediate node exits from the data transmission gradient due to excessive energy consumption, the network needs to perform 'interest' diffusion again to form a new transmission gradient, which causes a large amount of energy consumption on the whole network.
It is important to say that, because the data types measured by the nodes in the tree growth telemetering WSN are the same and are not complicated, based on the data types, a great amount of interest distribution in the whole network area can be carried out in the interest diffusion stage of the DD protocol, each node stores an interest list, a plurality of paths capable of carrying out effective data transmission are established, and the paths can be dynamically adjusted independently after the nodes in the network fail. The energy consumed by re-establishing the gradient by performing 'interest' diffusion after the gradient is failed is saved.
In the measurement of the tree growth amount, the position of the measured tree needs to be positioned, so that the measured sensor node (middle node) can also acquire the position of the sensor node. FIG. 4 depicts the process of DD-DHE protocol "interest" diffusion and gradient setup (solid line for "interest" diffusion and dashed line for gradient setup). Firstly, in an interest diffusion stage, a Sink node distributes interest information to the whole network, and each time the node forwards a message once, the value of the forwarding times in a node list of a corresponding node is added with 1 and added into the node list. The initial forwarding times of the Sink node are 1, and other nodes are 0.
As shown in fig. 4, after the interest information is diffused, the node forwarding times in the network form a layered situation in which the closer the distance from the Sink node is, the smaller the forwarding times are, and the number of forwarding times gradually increases outwards. The node spread to the last node (data node) stores a node summary table of the corresponding forwarding times of each transmission path of all nodes, and the node summary table can be propagated in the whole network in the subsequent detection message sending stage. At the moment, a plurality of transmission paths which can work are established between the Sink node and the source node, and in the subsequent path strengthening, one of the paths with the least forwarding times can be selected for transmission according to the existing information.
However, when a propagation path with the least forwarding times is selected as a data transmission path for data transmission, the intermediate node always forwards data, which causes a phenomenon that the network exits in advance due to too much energy consumption. The nodes in the network automatically inquire the residual energy of the nodes after a period of time T. In order to make the nodes closer to the Sink node perform the query earlier, a waiting time is set for each node in the network query process, so step S3 is preceded by the following steps:
s30: setting the preset waiting time of each node through a second preset formula according to the forwarding times; the second preset formula is as follows:
Tquery＝h(x,y)×t；
in the formula, TqueryAnd the preset waiting time is the forwarding times of the corresponding nodes in the current data transmission path, and t is the time required by the node self-check.
At this time, the node energy self-checking sequence is carried out from less to more according to the forwarding times, if the current node NjIs lower than the preset threshold value, the last forwarding node N of the current data transmission path is informediThe standby path selection mode is turned on and the energy threshold is adjusted. At this time, the node N is temporarily stoppedjAs a relay node for data transmission, and node NjNext forwarding node NkTogether with the ID of the node Ni. It should be noted that, during the data transmission process, the node NjCan still be used as relay node for data transmission, but when next data transmission is carried out, the node NiTaking the node as a propagation starting point, acquiring the alternative path which does not contain the low-energy node and has the least forwarding times in the alternative paths as a data transmission path, returning to step S3, and performing threshold definition and low-energy node determination again until another propagation path having the least forwarding times is acquired as a data transmission path for data transmission.
Considering that the closer the node to the Sink node, the more times the node needs to assume the role of the relay node, which is a challenge to the energy of the node. Therefore, the DD-DHE protocol needs to be subjected to gradient processing when the energy threshold is set, and the closer to the Sink node, the larger the set energy threshold is. Considering that there are nodes in the network with the same node forwarding number but different distances from the Sink node (d1 ≠ d2), as shown in fig. 5. In order to increase the node energy threshold value with the same number of times of forwarding but a shorter distance, step S3 further includes, before the determination, the steps of:
setting a preset threshold value of each node through a first preset formula according to the forwarding times and the distance of each node in the current data transmission path; the first preset formula is as follows:
Figure BDA0003032559090000081
in the formula, ETnA preset threshold value for a corresponding node in the current data transmission path, ErIs the node residual energy, h (x, y) is the forwarding times of the corresponding node in the current data transmission path, hmax(x, y) is the maximum number of retransmissions in the flood propagation, hmin(x, y) is the minimum number of times of forwarding in flooding propagation, Sink is a base station node, d (i, Sink) is the distance between the corresponding node and the base station node in the current data transmission path, dmax(i, Sink) is the maximum distance between the node and the base station node in the flooding propagation, dmin(i, Sink) is the minimum value of the distance between the node and the base station node in the flooding propagationAnd u is a constant between 0 and 1.
Because the nodes in the network all store a node summary table, the nodes can automatically adjust the energy threshold value according to the first preset formula in the network operation process.
Example two
In order to better understand the technical content of the present invention, the present embodiment illustrates the present invention in the form of a system structure, as shown in fig. 2, a tree growth telemetry system based on a directional diffusion protocol, comprising:
the base station node is used for flooding and transmitting the interest information to the data node;
the intermediate nodes (a plurality of) are used for acquiring the distance from the base station node in the flooding propagation process, and storing the interest information and the forwarding times of the interest information under each propagation path to the node list;
the data node is used for acquiring a node general table after flooding propagation and sending the node general table to each intermediate node, wherein the node general table comprises the interest information forwarding times and the interest information of each propagation path;
the path selection unit is used for acquiring the propagation path with the minimum forwarding times in the propagation path, and using the propagation path as a data transmission path, and using the rest propagation paths as alternative paths;
the intermediate node also comprises a judger which is used for judging whether each node in the current data transmission path has a low-energy node or not by taking the preset waiting time of each node as a judgment interval, and if so, sending an alternative signal to the previous node; the low-energy node is a node with node energy lower than a preset threshold value
And the path selection unit acquires an alternative path which does not contain low-energy nodes and has the minimum forwarding times as a data transmission path according to the alternative signal and the node as a propagation starting point.
The system further comprises a threshold setting unit, a threshold setting unit and a data transmission unit, wherein the threshold setting unit is used for setting a preset threshold of each node through a first preset formula according to the forwarding times and the distance of each node in the current data transmission path; the first preset formula is as follows:
Figure BDA0003032559090000091
in the formula, ETnA preset threshold value for a corresponding node in the current data transmission path, ErIs the node residual energy, h (x, y) is the forwarding times of the corresponding node in the current data transmission path, hmax(x, y) is the maximum number of retransmissions in the flood propagation, hmin(x, y) is the minimum number of times of forwarding in flooding propagation, Sink is a base station node, d (i, Sink) is the distance between the corresponding node and the base station node in the current data transmission path, dmax(i, Sink) is the maximum distance between the node and the base station node in the flooding propagation, dmin(i, Sink) is the minimum value of the distance between the node and the base station node in the flooding propagation, and u is a constant between 0 and 1.
Further, the judger sets the preset waiting time of each node through a second preset formula according to the forwarding times; the second preset formula is as follows:
Tquery＝h(x,y)×t；
in the formula, TqueryAnd the preset waiting time is the forwarding times of the corresponding nodes in the current data transmission path, and t is the time required by the node self-check.
Furthermore, the trees are artificial forests, and intervals among the trees are equal.
In summary, the tree growth remote measurement method and system based on the directional diffusion protocol, based on the characteristic that the intervals between trees of the artificial forest are equal, records and stores the forwarding times in the process of flood propagation, and the optimal data transmission path can be obtained by selecting the propagation path with the least forwarding times.
By judging the low-energy nodes, after the low-energy nodes are found, the last node of the low-energy nodes in the current transmission path is taken as a transmission starting point, and the alternative path which does not contain the low-energy nodes and has the least forwarding times is selected as a data transmission path. Through the first preset formula, the preset threshold value is set by utilizing the forwarding times and the distance information of each node in the current data transmission path, and the preset threshold value of the node with high utilization rate can be ensured to better meet the actual use requirement.
EXAMPLE III
In order to better verify the reliability of the technical content of the invention, the invention is verified by using real experimental data. And (3) performing protocol simulation by adopting an MATLAB platform, and comparing the performances of the DD protocol, the IDD protocol (setting a threshold value on the basis of the DD protocol and adjusting according to 1/2) and the DD-DHE protocol under the same experimental condition.
According to the characteristics of the WSN applied to the tree growth remote measurement, the following definitions are made in the simulation:
1) nodes in the network are uniformly distributed, each node has a fixed ID, and the position information of the node is stored in advance;
2) the nodes in the network have the same structure and the initial energy is consistent;
3) the nodes in the network area can communicate with each other;
4) the Sink node is positioned in the geometric center of the network area, the calculation and storage capacity is not limited, and the energy is infinite;
5) the Sink node receives data source data once and takes one round of data acquisition period;
6) the node can perform data fusion processing on different data types sent by the node.
The experimental simulation parameters are shown in table 1:
TABLE 1 simulation experiment parameters
Figure BDA0003032559090000111
In Table 1,. epsilonfsThe energy consumption coefficient of the free space model power amplifying circuit is obtained; epsilonampFor power amplifying circuits of multipath modelsCoefficient of energy consumption; eelscEnergy consumption for transceiving data per bit; eDAThe energy consumed for fusing the data.
Through experiments, a network life cycle comparison chart of the DD, IDD and DD-DHE protocols is obtained and shown in FIG. 6. It can be seen that the death time of the 1 st node of the DD, IDD and DD-DHE protocols in the DD, IDD and DD-DHE protocols is respectively the 105 th, 150 th and 371 th rounds of completing data acquisition, and the total death time of the nodes of the 3 protocols is 727 th, 996 th and 1747 th rounds. Although the IDD protocol is improved on the basis of the DD protocol, the life cycle of the network is prolonged to a certain extent, but the IDD protocol is far from the DD-DHE protocol. Compared with 3 data transmission protocols comprehensively, the DD-DHE protocol effectively delays the death time of the 1 st node and the last 1 node, and obviously improves the life cycle of the network.
And the total energy remaining in the network during the operation of the DD, IDD and DD-DHE protocols is shown in FIG. 7. It can be seen that in the DD protocol, since the data transmission gradient needs to be reestablished after the node is dead and failed, a large amount of node energy is consumed, so that the remaining total energy of the network is rapidly reduced in the operation process. Although the improved IDD protocol is improved on the basis of the DD protocol, the DD-DHE protocol fully utilizes the gradient established previously, so that the link of reestablishing the gradient is avoided, a large amount of network energy is saved, and the energy utilization efficiency of the network is improved.
FIG. 8 depicts the average of the energy remaining for nodes in the network for the DD, IDD, DD-DHE protocols at the same number of dead nodes. It can be seen that the DD-DHE protocol has a higher average value of the energy remaining at nodes in the network than the other two when the number of dead nodes is the same, compared to the DD and IDD protocols. Therefore, compared with the DD and IDD protocols, the DD-DHE protocol can more effectively ensure the balance of network energy consumption.
When the number of dead nodes is the same, the data receiving amount of the Sink nodes of the DD, IDD, DD-DHE protocol is shown in fig. 9. It can be seen that there is a significant gap in Sink node data receiving amount in the DD, IDD, DD-DHE protocols. The receiving amount of the DD-DHE protocol data is close to 224% of the receiving amount of the traditional DD protocol data, and compared with the IDD protocol, the receiving amount of the DD-DHE protocol data is improved by about 69%. Therefore, the DD-DHE protocol can transmit more information data under the same condition.
In conclusion, compared with the DD protocol, the DD-DHE protocol delays the death time of the first node and the death time of the last node in the network by 253% and 140%, so that the survival time of the network is obviously prolonged; the DD-DHE protocol can fully utilize other gradients formed in the network, saves the energy for reestablishing the gradients after the gradients fail, and greatly improves the energy utilization rate of the network; the data receiving amount of the DD-DHE protocol is close to 224% of that of the DD protocol, and the DD-DHE protocol has the characteristic of collecting and transmitting more data.
It should be noted that all the directional indicators (such as up, down, left, right, front, and rear … …) in the embodiment of the present invention are only used to explain the relative position relationship between the components, the movement situation, etc. in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indicator is changed accordingly.
Moreover, descriptions of the present invention as relating to "first," "second," "a," etc. are for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicit ly indicating a number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "connected," "secured," and the like are to be construed broadly, and for example, "secured" may be a fixed connection, a removable connection, or an integral part; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.

Claims (10)

1. A directional diffusion protocol construction method for tree growth remote measurement is characterized by comprising the following steps:
s1: the method comprises the steps that interest information is flooded and transmitted to data nodes through base station nodes, the distance between each node and the base station nodes is obtained in the flooding transmission process, and the interest information and the forwarding times of the interest information under each transmission path when the interest information is forwarded to each node are stored in a node list of the corresponding node;
s2: acquiring a propagation path with the minimum forwarding times in the propagation paths, and using the propagation path as a data transmission path, wherein the rest propagation paths are used as alternative paths;
s3: judging whether each node in the current data transmission path has a low-energy node or not by taking the preset waiting time of each node as a judgment interval, if so, acquiring the previous node information of the low-energy node and entering the step S4, and if not, performing data transmission by using the current data transmission path; the low-energy node is a node with node energy lower than a preset threshold value;
s4: and the node is used as a propagation starting point, and the alternative path which does not contain the low-energy node and has the least forwarding times is obtained as a data transmission path.
2. The tree growth telemetry method based on the directional diffusion protocol as claimed in claim 1, wherein the step S3 further comprises, before the step of determining:
setting a preset threshold value of each node through a first preset formula according to the forwarding times and the distance of each node in the current data transmission path; the first preset formula is as follows:
Figure FDA0003032559080000011
in the formula, ETnA preset threshold value for a corresponding node in the current data transmission path, ErIs the node residual energy, h (x, y) is the forwarding times of the corresponding node in the current data transmission path, hmax(x, y) is the maximum number of retransmissions in the flood propagation, hmin(x, y) is the minimum number of times of forwarding in flooding propagation, Sink is the base station node, d (i, Sin)k) Distance between the corresponding node and the base station node in the current data transmission path, dmax(i, Sink) is the maximum distance between the node and the base station node in the flooding propagation, dmin(i, Sink) is the minimum value of the distance between the node and the base station node in the flooding propagation, and u is a constant between 0 and 1.
3. The tree growth telemetry method of claim 1, wherein the step S1 is further followed by the steps of:
s11: and acquiring a node general table of the data nodes after the flooding propagation, and sending the node general table to each node, wherein the node general table comprises the interest information forwarding times and the interest information of each propagation path.
4. The tree growth telemetry method based on the directional diffusion protocol as claimed in claim 1, wherein the step S3 is preceded by the steps of:
s30: setting the preset waiting time of each node through a second preset formula according to the forwarding times; the second preset formula is as follows:
Tquery＝h(x,y)×t；
in the formula, TqueryAnd the preset waiting time is the forwarding times of the corresponding nodes in the current data transmission path, and t is the time required by the node self-check.
5. The tree growth telemetry method according to claim 1, wherein in step S3, if there is a low energy node, when the data transmission still passes through the low energy node as the data transmission node, the next data transmission is performed to replace the data transmission path through step S4.
6. The method of claim 1, wherein the trees are planted in forest trees with equal spacing between trees.
7. A tree growth telemetry system based on a directed diffusion protocol, comprising:
the base station node is used for flooding and transmitting the interest information to the data node;
the intermediate node is used for acquiring the distance from the base station node in the flooding propagation process and storing the interest information and the forwarding times of the interest information under each propagation path to the node list;
the data node is used for acquiring a node general table after flooding propagation and sending the node general table to each intermediate node, wherein the node general table comprises the interest information forwarding times and the interest information of each propagation path;
the path selection unit is used for acquiring the propagation path with the minimum forwarding times in the propagation path, and using the propagation path as a data transmission path, and using the rest propagation paths as alternative paths;
the intermediate node also comprises a judger which is used for judging whether each node in the current data transmission path has a low-energy node or not by taking the preset waiting time of each node as a judgment interval, and if so, sending an alternative signal to the previous node; the low-energy node is a node with node energy lower than a preset threshold value
And the path selection unit acquires an alternative path which does not contain low-energy nodes and has the minimum forwarding times as a data transmission path according to the alternative signal and the node as a propagation starting point.
8. The tree growth telemetry system according to claim 7, further comprising a threshold setting unit for setting a preset threshold of each node according to the forwarding times and distances of each node in the current data transmission path through a first preset formula; the first preset formula is as follows:
Figure FDA0003032559080000031
in the formula, ETnA preset threshold value for a corresponding node in the current data transmission path, ErIs the node residual energy, h (x, y) isThe number of forwarding times, h, of the corresponding node in the current data transmission pathmax(x, y) is the maximum number of retransmissions in the flood propagation, hmin(x, y) is the minimum number of times of forwarding in flooding propagation, Sink is a base station node, d (i, Sink) is the distance between the corresponding node and the base station node in the current data transmission path, dmax(i, Sink) is the maximum distance between the node and the base station node in the flooding propagation, dmin(i, Sink) is the minimum value of the distance between the node and the base station node in the flooding propagation, and u is a constant between 0 and 1.
9. The tree growth telemetry system of claim 7, wherein the determiner sets the predetermined waiting time of each node according to the forwarding times through a second predetermined formula; the second preset formula is as follows:
Tquery＝h(x,y)×t；
in the formula, TqueryAnd the preset waiting time is the forwarding times of the corresponding nodes in the current data transmission path, and t is the time required by the node self-check.
10. The tree growth telemetry system of claim 7, wherein the trees are planted in forest trees with equal spacing between trees.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20060075797A (en) * 2004-12-29 2006-07-04 한국과학기술정보연구원 Mre-dd sensor network routing algorithm
US20100220653A1 (en) * 2007-11-01 2010-09-02 Hwang So-Young Multi-path routing method in wireless sensor network
CN103078793A (en) * 2012-12-27 2013-05-01 河海大学 Improved directed diffusion routing protocol based on network coding
CN104023367A (en) * 2014-06-17 2014-09-03 河海大学 Directed diffusion protocol based on visual path and promoted evaluation criterion
CN105357731A (en) * 2015-10-14 2016-02-24 国网辽宁省电力有限公司营口供电公司 Energy-efficient wireless sensor network (WSN) routing protocol design method for use in electromagnetic interference environment
CN108112050A (en) * 2018-01-18 2018-06-01 山东大学 Energy balance and deep-controlled Routing Protocol based on underwater wireless sensing network
CN110418390A (en) * 2019-06-17 2019-11-05 华南农业大学 The data transfer optimization method and system of low-altitude remote sensing and earth horizon sensor
CN111510985A (en) * 2020-03-19 2020-08-07 东北电力大学 Wireless sensor network directional diffusion protocol data query method based on cluster bridge

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20060075797A (en) * 2004-12-29 2006-07-04 한국과학기술정보연구원 Mre-dd sensor network routing algorithm
US20100220653A1 (en) * 2007-11-01 2010-09-02 Hwang So-Young Multi-path routing method in wireless sensor network
CN103078793A (en) * 2012-12-27 2013-05-01 河海大学 Improved directed diffusion routing protocol based on network coding
CN104023367A (en) * 2014-06-17 2014-09-03 河海大学 Directed diffusion protocol based on visual path and promoted evaluation criterion
CN105357731A (en) * 2015-10-14 2016-02-24 国网辽宁省电力有限公司营口供电公司 Energy-efficient wireless sensor network (WSN) routing protocol design method for use in electromagnetic interference environment
CN108112050A (en) * 2018-01-18 2018-06-01 山东大学 Energy balance and deep-controlled Routing Protocol based on underwater wireless sensing network
CN110418390A (en) * 2019-06-17 2019-11-05 华南农业大学 The data transfer optimization method and system of low-altitude remote sensing and earth horizon sensor
CN111510985A (en) * 2020-03-19 2020-08-07 东北电力大学 Wireless sensor network directional diffusion protocol data query method based on cluster bridge

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
SHIMAA GAMAL EL-ESAWY: "An Improved Energy-Efficient Directed Diffusion Routing Protocol for Wireless Sensor Network", 《2018 14TH INTERNATIONAL COMPUTER ENGINEERING CONFERENCE (ICENCO)》 *
陈志泊: "一种改进的基于跳数的无线传感器网络路由算法", 《计算机科学》 *

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