CN114025404A - Wireless sensor network routing protocol method, wireless sensor and storage medium - Google Patents
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- 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract
The invention discloses a wireless sensor network routing protocol method, a wireless sensor and a storage medium, wherein the routing protocol method comprises the following steps: acquiring an energy span upper limit and an energy span lower limit of a surviving node in the ith round, and a distance span upper limit and a distance span lower limit of the surviving node; acquiring the state of the surviving node according to the energy span upper limit, the energy span lower limit, the distance span upper limit and the distance span lower limit; calculating a grading threshold value of the survival node according to the state; judging whether the surviving node can be used as a cluster head node or not according to the grading threshold value; repeating the steps until all the survival nodes are judged; and acquiring a routing path from the cluster head node to the base station by using a genetic algorithm, and transmitting data. The invention aims to provide a routing protocol method of a wireless sensor network, a wireless sensor and a storage medium, wherein the service life of the wireless sensor network can be prolonged by using the routing protocol method of the wireless sensor network.
Description
Technical Field
The present invention relates to the field of wireless sensor network technologies, and in particular, to a wireless sensor network routing protocol method, a wireless sensor, and a storage medium.
Background
Wireless sensors, as a new type of sensor emerging in recent years, may eliminate power and signal cables. The application of the wireless sensor network to the nuclear power device can greatly enhance the flexibility of sensor arrangement and greatly reduce the workload of cable laying and termination in the construction process of the nuclear power device.
However, the wireless sensor in the prior art consumes energy quickly, and when the wireless sensor is applied to the field of nuclear power, due to the particularity of the environment of the nuclear power device, the battery of the wireless sensor cannot be charged or replaced regularly, so that the wireless sensor network cannot be guaranteed to work stably and reliably for a long time.
Disclosure of Invention
The invention aims to provide a routing protocol method of a wireless sensor network, a wireless sensor and a storage medium, wherein the service life of the wireless sensor network can be prolonged by using the routing protocol method of the wireless sensor network.
The invention is realized by the following technical scheme:
in a first aspect of the present application, there is provided a wireless sensor network routing protocol method, including the steps of:
s1: acquiring an energy span upper limit and an energy span lower limit of a surviving node in an ith round, and a distance span upper limit and a distance span lower limit of the surviving node;
s2: acquiring the state of the surviving node according to the energy span upper limit, the energy span lower limit, the distance span upper limit and the distance span lower limit;
s3: calculating a classification threshold of the surviving node according to the state;
s4: judging whether the surviving node can be used as a cluster head node or not according to the grading threshold value;
s5: repeating the steps S1-S4 until all the survival nodes are judged to be finished;
s6: and acquiring a routing path from the cluster head node to a base station by using a genetic algorithm, and transmitting data.
Preferably, the S1 includes the following substeps:
s11: acquiring the residual energy of each surviving node in the ith round and the distance from each surviving node to a base station;
s12: calculating a residual energy average value and a residual energy standard deviation of the surviving node according to the residual energy, and calculating a distance average value and a distance standard deviation of a distance from the surviving node to a base station according to the distance;
wherein avg _ E (i) is the average value of the remaining energy in the ith round, std _ E (i) is the standard deviation of the remaining energy in the ith round, avg _ D (i) is the average value of the distance in the ith round, std _ D (i) is the standard deviation of the distance in the ith round, D (N) is the distance from the nth surviving node to the base station, E (N) is the remaining energy of the nth surviving node, and N is the total number of surviving nodes;
s13: calculating the energy span upper limit and the energy span lower limit according to the residual energy average value and the residual energy standard deviation, and calculating the distance span upper limit and the distance span lower limit according to the distance average value and the distance standard deviation;
span_distance_low(i)＝avg_D(i)-std_D(i)；
span_distance_high(i)＝avg_D(i)+std_D(i)；
span_energy_low(i)＝avg_E(i)-std_E(i)；
span_energy_high(i)＝avg_E(i)+std_E(i)；
wherein span _ distance _ low (i) is a distance span lower limit in the ith wheel, span _ distance _ high (i) is a distance span upper limit in the ith wheel, span _ energy _ low (i) is an energy span lower limit in the ith wheel, and span _ energy _ high (i) is an energy span upper limit in the ith wheel.
Preferably, the states of the surviving nodes include:
state 1: the remaining energy of the surviving node is larger than the energy span upper limit, and the distance from the surviving node to the base station is larger than the distance span upper limit;
state 2: the remaining energy of the surviving node is larger than the energy span upper limit, and the distance from the surviving node to the base station is between the distance span upper limit and the distance span lower limit;
state 3: the remaining energy of the surviving node is larger than the energy span upper limit, and the distance from the surviving node to the base station is smaller than the distance span lower limit;
and 4: the remaining energy of the surviving node is located between the upper energy span limit and the lower energy span limit, and the distance from the surviving node to the base station is greater than the upper distance span limit;
and state 5: the remaining energy of the surviving node is between the upper energy span limit and the lower energy span limit, and the surviving node-to-base station distance is between the upper distance span limit and the lower distance span limit;
and 6: the remaining energy of the surviving node is located between the energy span upper limit and the energy span lower limit, and the distance from the surviving node to the base station is smaller than the distance span lower limit;
and state 7: the remaining energy of the surviving node is smaller than the energy span lower limit, and the distance from the surviving node to the base station is larger than the distance span upper limit; (ii) a
State 8: the remaining energy of the surviving node is smaller than the energy span lower limit, and the distance from the surviving node to a base station is between the distance span upper limit and the distance span lower limit;
state 9: the remaining energy of the surviving node is less than the energy span lower limit, and the distance from the surviving node to the base station is less than the distance span lower limit.
Preferably, the classification threshold is obtained by:
when the status of the surviving node is status 1, the grading threshold is T1(n)：
When the status of the surviving node is status 2, the grading threshold is T2(n)：
When the status of the surviving node is status 3, the grading threshold is T3(n)：
T3(n)＝pc×1；
When the status of the surviving node is status 4, the grading threshold is T4(n)：
T4(n)＝0；
When the status of the surviving node is status 5, the grading threshold is T5(n)：
When the status of the surviving node is status 6, the grading threshold is T6(n)：
When the status of the surviving node is status 7, the grading threshold is T7(n)：
T7(n)＝0；
When the status of the surviving node is status 8, the grading threshold is T8(n)：
When the status of the surviving node is status 9, the grading threshold is T9(n)：
Wherein p iscFor the expected percentage of the surviving nodes becoming cluster head nodes, 0<pc<1, d (n) is the distance from the surviving node to the base station, e (n) is the remaining energy of the surviving node, span _ distance _ low (i) is the distance span lower limit in the ith round, span _ distance _ high (i) is the distance span upper limit in the ith round, span _ energy _ low (i) is the energy span lower limit in the ith round, and span _ energy _ high (i) is the energy span upper limit in the ith round.
Preferably, the S4 includes the following substeps:
s41: the surviving node generates a random number between 0 and 1;
s42: when the grading threshold value of the survival node is larger than or equal to the random number, the survival node is used as the cluster head node;
and when the grading threshold value of the survival node is smaller than the random number, the survival node is used as a common node.
Preferably, the fitness function of the genetic algorithm is:
ERX(k)＝k×Erx-ele；
wherein m is the total number of cluster head nodes in the path, di is the distance between the cluster head node i and the cluster head node i +1, ETX(k, d) is the energy required to transmit k bits of data over a distance d, ERX(k) Is the energy required to receive the k bit data, EfsAnd EmpEnergy of the amplifier in free space and multipath fading models, respectively, Etx-eleAnd Erx-eleEnergy consumed by the circuit when transmitting and receiving 1bit data, respectively, EDaTo fuse the energy consumed by 1bit data, ETx-ampAnd (k, d) represents the energy that the amplifier can consume when the transmission data amount is k bit and the distance is d.
Preferably, before genetic manipulation, the average energy of the cluster head nodes is calculated, and the cluster head nodes with the residual energy greater than the average energy are selected to generate the next generation.
Preferably, all intermediate cluster head nodes are included in only one of said routing paths.
In a second aspect of the present application, there is provided a wireless sensor for data transmission based on the above wireless sensor network routing protocol method.
In a third aspect of the present application, there is provided a computer readable storage medium comprising a stored computer program which when executed performs a wireless sensor network routing protocol method as described above.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. when the cluster head node of the wireless sensor is selected, the average value, the variance (standard deviation) and the distance from the base station of the node energy are considered at the same time, so that the energy balance of the whole wireless sensor network is better;
2. a cluster head node selection hierarchical threshold mechanism is established, and the critical states of nodes in the network, including the conditions that the energy of the nodes is very low or the distance from the nodes to a base station is very large, are considered, so that more accurate cluster head selection is realized, and the service life of the network is prolonged;
3. aiming at the narrow closed space blocked by multiple metals of the nuclear power plant, some nodes may not directly transmit the actual situation of a base station, after the cluster head nodes are determined, on the basis of the traditional genetic algorithm, the initial path chromosome selection is improved through filtering pretreatment, the path chromosome length is minimized, and the genetic algorithm efficiency is improved;
4. when each round of route is selected, the route with the repeated middle cluster head nodes except the source cluster head node in each multi-hop route is removed, so that the excessive energy exhaustion of some nodes is prevented, the overall efficiency of the network is further improved, and the service life of the network is prolonged.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a diagram of a typical clustered routing protocol network in the prior art;
FIG. 2 is a schematic diagram of the energy consumption span of the present invention;
FIG. 3 is a schematic view of the distance span of the present invention;
FIG. 4 is a schematic flow chart of the present invention;
FIG. 5 is a simulation graph comparing the lifetime of a wireless sensor network node according to the present invention;
FIG. 6 is a graph comparing the impact of the number of wireless sensor network nodes on the network lifetime;
FIG. 7 is a graph comparing the effect of the number of wireless sensor network nodes on the lifetime of the network.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1
A routing protocol method of a wireless sensor network, as shown in fig. 4, includes the following steps:
step 1: network parameters are initialized as shown in table 1:
TABLE 1 Wireless sensor network parameters
Step 2: acquiring an upper energy span limit and a lower energy span limit of the surviving node in each round, as shown in fig. 2, and a lower distance span limit of the surviving node, as shown in fig. 3, specifically, the method includes:
acquiring the residual energy of each surviving node in each round and the distance from each surviving node to a base station;
wherein the residual energy of each surviving node in the ith round is:
S(n).Ei＝S(n).Ei-1-(ETX(k,d)+ERX(k))；
ERX(k)＝k×Erx-ele；
wherein, S (n) EiThe residual energy of node n in the ith round, S (n)i-1For the remaining energy of node n in round i-1, ETX(k, d) is the energy required to transmit k bits of data over a distance d, ERX(k) The energy required for receiving the kbit data, BS.xd and BS.yd are respectively the position abscissa and ordinate of the base station, S (n), xd and S (n), yd are the position abscissa and ordinate of the node n, EfsAnd EmpRespectively amplifiers in free space and in multipleEnergy in radial decay model, Etx-eleAnd Erx-eleEnergy consumed by the circuit when transmitting and receiving 1bit data, respectively, EDaTo fuse the energy consumed by 1bit data, ETx-ampAnd (k, d) represents the energy that the amplifier can consume when the transmission data amount is k bit and the distance is d.
Calculating the average value and standard deviation of the residual energy of the surviving node according to the residual energy, and calculating the average value and standard deviation of the distance from the surviving node to the base station according to the distance;
wherein avg _ E (i) is the average value of the remaining energy in the ith round, std _ E (i) is the standard deviation of the remaining energy in the ith round, avg _ D (i) is the average value of the distance in the ith round, std _ D (i) is the standard deviation of the distance in the ith round, D (N) is the distance from the nth surviving node to the base station, E (N) is the remaining energy of the nth surviving node, and N is the total number of surviving nodes;
calculating an energy span upper limit and an energy span lower limit according to the residual energy average value and the residual energy standard deviation, and calculating a distance span upper limit and a distance span lower limit according to the distance average value and the distance standard deviation;
span_distance_low(i)＝avg_D(i)-std_D(i)；
span_distance_high(i)＝avg_D(i)+std_D(i)；
span_energy_low(i)＝avg_E(i)-std_E(i)；
span_energy_high(i)＝avg_E(i)+std_E(i)；
wherein span _ distance _ low (i) is a distance span lower limit in the ith wheel, span _ distance _ high (i) is a distance span upper limit in the ith wheel, span _ energy _ low (i) is an energy span lower limit in the ith wheel, and span _ energy _ high (i) is an energy span upper limit in the ith wheel.
And step 3: acquiring the state of the surviving node according to the energy span upper limit, the energy span lower limit, the distance span upper limit and the distance span lower limit of the surviving node;
specifically, in this embodiment, the states of the surviving nodes are divided into 9 types according to the relationship between the remaining energy and the upper limit and the lower limit of the energy span, and the relationship between the distance from the surviving node to the base station and the upper limit and the lower limit of the distance span, and when the state of the current surviving node is obtained, the corresponding state is selected from the 9 states according to the upper limit of the energy span, the lower limit of the energy span, the upper limit of the distance span, and the lower limit of the distance span of the current surviving node, as shown in table 2:
TABLE 2 node status Table
Wherein A represents that the residual energy of the surviving node is greater than the energy span upper limit, B represents that the residual energy of the surviving node is between the energy span upper limit and the energy span lower limit, C represents that the residual energy of the surviving node is less than the energy span lower limit, A ' represents that the distance from the surviving node to the base station is greater than the distance span upper limit, B ' represents that the distance from the surviving node to the base station is between the distance span upper limit and the distance span lower limit, and C ' represents that the distance from the surviving node to the base station is less than the distance span lower limit;
and 4, step 4: calculating a grading threshold value of the survival node according to the state;
as can be seen from table 2, any one of the states corresponds to a corresponding threshold calculation equation, and after the states of the surviving nodes are obtained according to the energy span upper limit, the energy span lower limit, the distance span upper limit, and the distance span lower limit of the current energy, the hierarchical threshold calculation is performed according to the corresponding threshold calculation equation.
And 5: judging whether the surviving node can be used as a cluster head node or not according to the grading threshold value; specifically, the method comprises the following steps:
the survival node generates a random number between 0 and 1;
when the grading threshold value of the survival node is larger than or equal to the random number, the survival node is used as a cluster head node;
and when the grading threshold value of the survival node is smaller than the random number, the survival node is used as a common node.
Step 6: repeating the step 2 to the step 5 until all the survival nodes are judged;
and 7: and after all cluster head nodes of the current round are determined, acquiring a routing path from the cluster head nodes to the base station by using a genetic algorithm, and transmitting data.
It should be noted that the step 7 of obtaining the routing path according to the genetic algorithm is prior art, and the embodiment does not relate to the improvement thereof, and therefore, the principle thereof is not described.
The embodiment is an improvement of a traditional clustering routing protocol Leach (the clustering routing protocol belongs to a layered routing protocol, the network is divided into separate clusters, each cluster is provided with a Cluster Head (CH), other nodes in the clusters serve as cluster members, a typical clustering network is shown in fig. 1), a threshold selection mechanism is optimized on the basis of the protocol Leach, the proposed protocol uses a plurality of hierarchical thresholds instead of one threshold, the variance (standard deviation) and the average of the residual energy of the nodes and the distance between the nodes and a base station are fully considered in threshold calculation, the node state is determined by calculating the energy span and the distance span of the nodes, more accurate cluster head selection is realized, and the service life of the network is prolonged. In addition, in the embodiment, the threshold is normalized to the number of nodes, the energy efficiency of the wireless network does not depend on the number of nodes, the attenuation phenomenon does not occur along with the increase of the number of nodes, and the energy efficiency of the network has the advantage of consistency.
Example 2
Considering that the application field of the application is the nuclear field, and the nuclear power device in the nuclear field has a plurality of metal barrier closed spaces, there is a practical situation that some nodes cannot directly transmit data to a base station. Based on this, this embodiment improves step 7 on the basis of embodiment 1, specifically:
before starting genetic manipulation, in order to improve the quality of chromosomes in genetic algorithms, a "filtering" pre-process is first performed to select the best chromosome according to its energy level. Namely: calculating the average energy of all cluster head nodes, selecting the cluster head nodes with the node energy larger than the average energy to participate in the generation of the next generation, wherein each cluster head node and the base station generate a specified number of routing paths (chromosomes) in a binary mode (each cluster head represents a gene), and in each chromosome, a gene 1 represents that the intermediate cluster head is contained in the multi-hop routing path, otherwise, the intermediate cluster head is not contained in the multi-hop routing path. Then, the chromosome after the filtering processing is subjected to copying, crossing and mutation operations, and then, the intermediate cluster head repeated paths except the source cluster head nodes and the base station in the multi-hop routing path are removed, so that the intermediate cluster heads in the multi-hop routing path can not be repeated, and the energy of some intermediate cluster heads can be prevented from being consumed too fast. And finally, calculating an energy consumption fitness function according to the number of middle cluster heads in the multi-hop routing path and an energy consumption model, updating the genetic algorithm parameters, recording the ID of the middle cluster heads in the path until all cluster head nodes in the current round complete data transmission, wherein simulation comparison graphs are shown in figures 5-7, and LEACH-HT is as follows: a Hierarchical Threshold (HT) routing protocol based on LEACH protocol optimization, LEACH-IGAHT is as follows: a Hierarchical Threshold (HT) routing protocol optimized using an Improved Genetic Algorithm (IGA) is used based on the LEACH protocol.
The energy consumption fitness function in this embodiment is:
wherein m is roadNumber of nodes of cluster head in diameter, diThe distance between the cluster head node i and the cluster head node i +1 is defined.
Aiming at a multi-metal barrier closed space of a nuclear power plant, after a cluster head node is determined, on the basis of a traditional genetic algorithm, initial path chromosome selection is improved through filtering pretreatment, the path chromosome length is minimized, and the genetic algorithm efficiency is improved; meanwhile, when each round of route is selected, the route with the repeated middle cluster head nodes except the source cluster head node in each multi-hop route is removed, so that the excessive energy exhaustion of some nodes is prevented, the overall efficiency of the network is further improved, and the service life of the network is prolonged.
Example 3
In this embodiment, on the basis of embodiment 1 and embodiment 2, a wireless sensor is provided, and the wireless sensor performs data transmission based on the routing protocol method of the wireless sensor network provided in embodiment 1 and embodiment 2.
Example 4
The present embodiment provides a computer-readable storage medium on the basis of embodiment 1 and embodiment 2, where the computer-readable storage medium includes a stored computer program, and the computer program executes the wireless sensor network routing protocol method provided in embodiment 1 and embodiment 2.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A routing protocol method of a wireless sensor network is characterized by comprising the following steps:
s1: acquiring an energy span upper limit and an energy span lower limit of a surviving node in an ith round, and a distance span upper limit and a distance span lower limit of the surviving node;
s2: acquiring the state of the surviving node according to the energy span upper limit, the energy span lower limit, the distance span upper limit and the distance span lower limit;
s3: calculating a classification threshold of the surviving node according to the state;
s4: judging whether the surviving node can be used as a cluster head node or not according to the grading threshold value;
s5: repeating the steps S1-S4 until all the survival nodes are judged to be finished;
s6: and acquiring a routing path from the cluster head node to a base station by using a genetic algorithm, and transmitting data.
2. The wireless sensor network routing protocol method according to claim 1, wherein the S1 includes the following sub-steps:
s11: acquiring the residual energy of each surviving node in the ith round and the distance from each surviving node to a base station;
s12: calculating a residual energy average value and a residual energy standard deviation of the surviving node according to the residual energy, and calculating a distance average value and a distance standard deviation of a distance from the surviving node to a base station according to the distance;
wherein avg _ E (i) is the average value of the remaining energy in the ith round, std _ E (i) is the standard deviation of the remaining energy in the ith round, avg _ D (i) is the average value of the distance in the ith round, std _ D (i) is the standard deviation of the distance in the ith round, D (N) is the distance from the nth surviving node to the base station, E (N) is the remaining energy of the nth surviving node, and N is the total number of surviving nodes;
s13: calculating the energy span upper limit and the energy span lower limit according to the residual energy average value and the residual energy standard deviation, and calculating the distance span upper limit and the distance span lower limit according to the distance average value and the distance standard deviation;
span_distance_low(i)＝avg_D(i)-std_D(i)；
span_distance_high(i)＝avg_D(i)+std_D(i)；
span_energy_low(i)＝avg_E(i)-std_E(i)；
span_energy_high(i)＝avg_E(i)+std_E(i)；
wherein span _ distance _ low (i) is a distance span lower limit in the ith wheel, span _ distance _ high (i) is a distance span upper limit in the ith wheel, span _ energy _ low (i) is an energy span lower limit in the ith wheel, and span _ energy _ high (i) is an energy span upper limit in the ith wheel.
3. The method according to claim 1, wherein the status of the surviving node comprises:
state 1: the remaining energy of the surviving node is larger than the energy span upper limit, and the distance from the surviving node to the base station is larger than the distance span upper limit;
state 2: the remaining energy of the surviving node is larger than the energy span upper limit, and the distance from the surviving node to the base station is between the distance span upper limit and the distance span lower limit;
state 3: the remaining energy of the surviving node is larger than the energy span upper limit, and the distance from the surviving node to the base station is smaller than the distance span lower limit;
and 4: the remaining energy of the surviving node is located between the upper energy span limit and the lower energy span limit, and the distance from the surviving node to the base station is greater than the upper distance span limit;
and state 5: the remaining energy of the surviving node is between the upper energy span limit and the lower energy span limit, and the surviving node-to-base station distance is between the upper distance span limit and the lower distance span limit;
and 6: the remaining energy of the surviving node is located between the energy span upper limit and the energy span lower limit, and the distance from the surviving node to the base station is smaller than the distance span lower limit;
and state 7: the remaining energy of the surviving node is smaller than the energy span lower limit, and the distance from the surviving node to the base station is larger than the distance span upper limit;
state 8: the remaining energy of the surviving node is smaller than the energy span lower limit, and the distance from the surviving node to a base station is between the distance span upper limit and the distance span lower limit;
state 9: the remaining energy of the surviving node is less than the energy span lower limit, and the distance from the surviving node to the base station is less than the distance span lower limit.
4. The method of claim 1, wherein the classification threshold is obtained by the following formula:
when the status of the surviving node is status 1, the grading threshold is T1(n)：
When the status of the surviving node is status 2, the grading threshold is T2(n)：
When the status of the surviving node is status 3, the grading threshold is T3(n)：
T3(n)＝pc×1；
When the status of the surviving node is status 4, the grading threshold is T4(n)：
T4(n)＝0；
When the status of the surviving node is status 5, the grading threshold is T5(n)：
When the status of the surviving node is status 6, the grading threshold is T6(n)：
When the status of the surviving node is status 7, the grading threshold is T7(n)：
T7(n)＝0；
When the status of the surviving node is status 8, the grading threshold is T8(n)：
When the status of the surviving node is status 9, the grading threshold is T9(n)：
Wherein p iscFor the expected percentage of the surviving nodes becoming cluster head nodes, 0<pc<1, D (n) from the surviving node to the base stationDistance, e (n) is the remaining energy of the surviving node, span _ distance _ low (i) is the distance span lower limit in the ith round, span _ distance _ high (i) is the distance span upper limit in the ith round, span _ energy _ low (i) is the energy span lower limit in the ith round, and span _ energy _ high (i) is the energy span upper limit in the ith round.
5. The wireless sensor network routing protocol method according to claim 1, wherein the S4 includes the following sub-steps:
s41: the surviving node generates a random number between 0 and 1;
s42: when the grading threshold value of the survival node is larger than or equal to the random number, the survival node is used as the cluster head node;
and when the grading threshold value of the survival node is smaller than the random number, the survival node is used as a common node.
6. The method according to claim 1, wherein the fitness function of the genetic algorithm is:
ERX(k)＝k×Erx-ele；
wherein m is the total number of cluster head nodes in the path, di is the distance between the cluster head node i and the cluster head node i +1, ETX(k, d) is the energy required to transmit k bits of data over a distance d, ERX(k) Is the energy required for receiving k bit dataAmount, EfsAnd EmpEnergy of the amplifier in free space and multipath fading models, respectively, Etx-eleAnd Erx-eleEnergy consumed by the circuit when transmitting and receiving 1bit data, respectively, EDaTo fuse the energy consumed by 1bit data, ETx-ampAnd (k, d) represents the energy that the amplifier can consume when the transmission data amount is k bit and the distance is d.
7. The method of claim 1, wherein an average energy of the cluster head nodes is calculated before genetic manipulation, and the cluster head nodes with the remaining energy greater than the average energy are selected to generate a next generation.
8. The method of claim 1, wherein all intermediate cluster head nodes are included in only one of the routing paths.
9. A wireless sensor, wherein the wireless sensor performs data transmission based on a wireless sensor network routing protocol method as claimed in any one of claims 1 to 8.
10. A computer-readable storage medium comprising a stored computer program that when executed performs a wireless sensor network routing protocol method according to any one of claims 1-8.
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