CN110972230B - Method for LEACH two-stage clustering routing protocol based on cuckoo algorithm - Google Patents
Method for LEACH two-stage clustering routing protocol based on cuckoo algorithm Download PDFInfo
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Abstract
The invention discloses a method for an LEACH two-level clustering routing protocol based on a cuckoo algorithm, which comprises the following steps: s1, broadcasting first-level cluster head election information to nodes, and selecting first-level cluster head nodes and common nodes; s2, broadcasting information to all common nodes by the primary cluster head nodes, and selecting the primary cluster head node with the strongest signal and adding the primary cluster head node into the cluster by the common nodes according to the strength of the signal of the received information; s3, screening the primary cluster head nodes with the largest number of common nodes in the primary cluster head nodes and the primary cluster head nodes which are farthest from the base station in the primary cluster head nodes, and determining the secondary cluster head nodes through a valley-laying bird algorithm; s4, the common node transmits data to a secondary cluster head node, and the secondary cluster head node transmits the received data to a primary cluster head node; s5, updating the position information of all the common nodes, judging whether the secondary cluster head node is the required secondary cluster head node, and if so, executing the step S6; s6, calculating the energy of all nodes for transmitting data, judging whether the energy reaches a preset threshold value, and if not, continuing to execute S1-S5.
Description
Technical Field
The invention relates to the technical field of wireless sensors, in particular to a method of an LEACH secondary clustering routing protocol based on a cuckoo algorithm.
Background
The thought of the wireless Sensor network WSN (Wireless Sensor network) is from the beginning of the 70 th 20 th century, the scale of the wireless Sensor network is not large at first, but the Sensor is found to have strong environmental adaptability to collect external original information, so that the wireless Sensor network has good research significance; by the late 20 th century, the wireless sensor technology is becoming mature, and has strong sensing capability, computing capability and communication capability. Until the appearance of the scientific review in the american journal in 2003, the technology started the research booming and WSN work was carried out around canada, uk, japan, and other countries.
The wireless sensor network has the characteristics of high fault tolerance, strong self-organizing capability and self-sufficient work, is more and more applied to different fields in actual life, such as ecological environment, anti-terrorism, medical sanitation, military defense and the like, and is greatly convenient for the life of people.
When the sensor works, the limited energy of the node is one of the main reasons for limiting the development of the wireless sensor network, wherein the proportion of energy consumed by data transmission is large, and a plurality of experts reduce the energy consumption of the node from the perspective of a routing algorithm, but the traditional routing algorithm can not meet the larger requirements of people, so that how to provide an efficient and energy-saving routing algorithm and enable the whole wireless sensor network to achieve energy balance becomes important, and the effect of long service life becomes important. Therefore, the invention provides a method for an LEACH clustering routing protocol based on a cuckoo algorithm, which aims to solve the technical problems that the random selectivity of cluster heads causes the uneven distribution of the cluster heads and the generation of 'hot spots' is easy, and to realize the energy consumption balance of nodes in the whole wireless sensor network in order to reduce the defects of excessive energy consumption and larger time delay during data transmission as much as possible, the invention provides the improved algorithm to solve the problems.
Disclosure of Invention
The invention aims to provide a method of an LEACH two-level clustering routing protocol based on a cuckoo algorithm aiming at the defects of the prior art, which can prolong the service life of all nodes in the whole network, improve the network performance and achieve high-efficiency data transmission.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method of an LEACH clustering routing protocol based on a cuckoo algorithm comprises the following steps:
s1, broadcasting first-level cluster head election information to wireless sensor nodes, and selecting a plurality of first-level cluster head nodes and a plurality of common nodes;
s2, the primary cluster head nodes broadcast information related to the primary cluster head nodes to all common nodes in the network, the common nodes select the primary cluster head nodes with the strongest signals according to the received signal strength of the broadcast information of the primary cluster head nodes and add the primary cluster head nodes into the selected cluster, and step S3 is executed until all the common nodes are added into the cluster;
s3, screening the primary cluster head node with the largest number of common nodes in the primary cluster head nodes and the primary cluster head node which is farthest from the base station in the primary cluster head nodes, and determining the secondary cluster head node by the aid of a valley-laying bird algorithm according to the screened primary cluster head node with the largest number of common nodes and the primary cluster head node which is farthest from the base station;
s4, the common node transmits data to a secondary cluster head node, and the secondary cluster head node transmits the received data to a primary cluster head node;
s5, updating the position information of all the common nodes in the primary cluster head node with the largest number of common nodes and the primary cluster head node farthest from the base station, judging whether the determined secondary cluster head node is the required secondary cluster head node, and if so, executing the step S6;
s6, calculating the energy of the common node, the secondary cluster head node and the primary cluster head node of the transmission data, judging whether the energy reaches a preset threshold value according to the calculated energy, and if so, finishing data transmission; if not, the steps S1-S5 are continued.
Further, after the step S1 of broadcasting the first-level cluster election information to the wireless sensor nodes, the method further includes collecting geographic locations of all the wireless sensor nodes and calculating distances between any two nodes.
Further, the step S1 selects a plurality of primary cluster head nodes by comparing the random number with a threshold value; the random number is generated by each node.
Further, the calculation formula of the threshold is as follows:
wherein t (n) represents a threshold value; p represents the ratio of the number of the first-level cluster head nodes in the network to all the nodes in the network, r represents the number of currently experienced rounds, GrThe first r-1 round is not selected as the set of the first-level cluster head nodes.
Further, after all the common nodes are added into the cluster in step S2, the method further includes that each primary cluster head node establishes a TDMA slot table according to the number of the common nodes in the cluster, and allocates data transmission time of the common nodes in the cluster.
Further, the step S4 includes that if there is no secondary cluster head node in the cluster, the normal node directly transmits data to the primary cluster head node through the established TDMA slot table.
Further, in step S4, the normal node transmits the data to the secondary cluster head node, and the secondary cluster head node transmits the received data to the primary cluster head node through the established TDMA time slot table.
Further, the determining of the secondary cluster head node in step S3 specifically includes:
determining the secondary cluster head nodes in the primary cluster head node cluster with the largest number of screened common nodes, wherein the formula is as follows:
wherein E isiFor the ith node, residual energy, E0An initial energy for each node; determining the common node with the most residual energy as a secondary cluster head node;
determining secondary cluster head nodes in the screened primary cluster head node cluster farthest from the base station, wherein the specific formula is as follows:
wherein D isi,BSThe distance between the ith node and the base station is obtained; and determining the common node closest to the base station as a secondary cluster head node.
Further, the step S5 includes updating the determined secondary cluster head node if the determined secondary cluster head node is not the required secondary cluster head node.
Further, in the step S5, the location information of all the common nodes is updated, and the specific formula is as follows:
v～N(0,1)
wherein the content of the first and second substances,
representing the position of the ith cuckoo found at the t +1 th search; pbest (i)(t)Denotes the position of the ith cuckoo t times, gbest(t)Representing the positions of all cuckoos at t times, taking alpha as a step size, taking 0.01, enabling mu and v to obey standard normal distribution, and taking gamma (1+ beta) as a standard gamma function; β is 1.5.
Compared with the prior art, the cuckoo algorithm adopted by the invention has the advantages of high search efficiency, high speed, simple algorithm, good search effect and the like, is applied to cluster head selection of the LEACH protocol, combines the selection of the optimal node of the network performance index 'accuracy' to ensure that the probability of selecting the cluster head from the nodes with high energy and short distance is high, fully ensures that the nodes can not be selected as the cluster head due to the adverse conditions of low energy or long distance, effectively relieves the problem of 'energy holes', can be obviously improved in energy consumption compared with the basic LEACH protocol no matter compared with the energy formula or in simulation results, and has great effect on improving the stability of the wireless sensor network.
Drawings
Fig. 1 is a flowchart of a method of a LEACH secondary clustering routing protocol based on a cuckoo algorithm according to an embodiment;
FIG. 2 is a schematic diagram of a wireless sensor node distribution diagram according to an embodiment;
FIG. 3 is a diagram illustrating the relationship between the death number of nodes and the number of rounds provided in the first embodiment;
fig. 4 is a schematic diagram illustrating a relationship between a network remaining energy and a number of wheels according to an embodiment;
fig. 5 is a schematic structural diagram of an actual wireless sensor network according to an embodiment.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
The invention aims to provide a method for an LEACH two-level clustering routing protocol based on a cuckoo algorithm aiming at the defects of the prior art.
Example one
The embodiment provides a method of a LEACH secondary clustering routing protocol based on a cuckoo algorithm, as shown in fig. 1 to 5, including the steps of:
s11, broadcasting first-level cluster head election information to the wireless sensor nodes, and selecting a plurality of first-level cluster head nodes and a plurality of common nodes;
s12, the primary cluster head nodes broadcast information related to the primary cluster head nodes to all common nodes in the network, the common nodes select the primary cluster head nodes with the strongest signals according to the received signal strength of the broadcast information of the primary cluster head nodes and add the primary cluster head nodes into the selected cluster, and step S13 is executed until all the common nodes are added into the cluster;
s13, screening the primary cluster head node with the largest number of common nodes in the primary cluster head nodes and the primary cluster head node which is farthest from the base station in the primary cluster head nodes, and determining the secondary cluster head node by the aid of a valley-laying bird algorithm according to the screened primary cluster head node with the largest number of common nodes and the primary cluster head node which is farthest from the base station;
s14, the common node transmits data to a secondary cluster head node, and the secondary cluster head node transmits the received data to a primary cluster head node;
s15, updating the position information of all the common nodes in the primary cluster head node with the largest number of common nodes and the primary cluster head node farthest from the base station, judging whether the determined secondary cluster head node is the required secondary cluster head node, and if so, executing the step S16;
s16, calculating the energy of the common node, the secondary cluster head node and the primary cluster head node of the transmission data, judging whether the energy reaches a preset threshold value according to the calculated energy, and if so, finishing data transmission; if not, the steps S11-S15 are continued.
In step S11, primary cluster election information is broadcasted to the wireless sensor nodes, and a plurality of primary cluster nodes and a plurality of common nodes are selected.
In this embodiment, assume that N wireless sensor nodes are randomly deployed in an M × M square area, wireless sensor node parameters are initialized, a base station broadcasts primary cluster election information to all sensor nodes in the area, collects geographical locations of all nodes, and calculates a distance d between any two nodesij. As shown in fig. 2.
In this embodiment, a specific method for initializing the node parameters of the wireless sensor is as follows:
assume that N wireless sensor nodes are randomly deployed within an M × M square area and that the sensor network has the following constraints:
1. each sensor node is kept still and is powered by only one battery with the same initial energy, and no additional charging is needed in the whole work;
2. all the sensor nodes have the capabilities of sending data, receiving data and sensing data and unique identification IDs;
3. each sensor node can judge the distance between the sensor node and a sender according to the received signal strength;
4. the base station is fixed in position and is not limited in energy.
In this embodiment, dijCalculated from the following equation:
wherein (x)i,yi) Is the coordinate of node i, (x)j,yj) Is the coordinate of node j.
In this embodiment, selecting a plurality of first-level cluster head nodes is specifically selected by comparing the random number with the threshold value; the random number is generated by each node.
Firstly, calculating a threshold value T (n), and generating a random number of 0-1 by each node; and comparing the value of T (n) with the value of the random number, if the random number of the node is smaller than a threshold value, the node is selected as a first-level cluster head node, and otherwise, the node becomes a common node.
Wherein the threshold t (n) is determined by the formula:
wherein: p is the ratio of the number of first-level cluster head nodes in the whole network to all the nodes, r is the number of currently experienced rounds, GrThe first r-1 round is not selected as the set of the first-level cluster head nodes.
In step S12, the multiple first-level cluster head nodes broadcast information related to the first-level cluster head nodes to all common nodes in the network, and the common nodes select the first-level cluster head node with the strongest signal according to the received signal strength of the broadcast information of the multiple first-level cluster head nodes and join the selected cluster, and step S13 is executed until all common nodes join the cluster.
The node selected as the first-level cluster head broadcasts self information to all nodes in the network, wherein the self information comprises a node id; and the common node selects the primary cluster head node with the strongest signal to join the cluster according to the strength of the received signal, and after all the nodes are clustered, each primary cluster head node establishes a TDMA time slot table according to the number of the nodes in the cluster, and allocates the data transmission time of the nodes in the cluster.
In step S13, the first-level cluster head node with the largest number of common nodes among the first-level cluster head nodes and the first-level cluster head node farthest from the base station among the first-level cluster head nodes are screened, and the second-level cluster head node is determined by the valley-distribution bird algorithm with respect to the first-level cluster head node with the largest number of common nodes and the first-level cluster head node farthest from the base station.
After the first-level cluster head nodes are selected, the first-level cluster head with the most nodes in the cluster is selected from the first-level cluster head node set, a second-level cluster head mechanism is implemented, in addition, the first-level cluster head nodes which are farthest from the base station are selected from all the first-level cluster head nodes, and the second-level cluster head mechanism is also implemented.
The secondary cluster head node mechanism is specifically realized as follows: the primary cluster head nodes are elected according to a threshold formula, secondary cluster head nodes are selected for clusters with the most nodes in the clusters, the election of the secondary cluster head nodes is realized through a valley-laying bird algorithm, the fitness function mainly considers energy factors, and the formula is as follows:
wherein E isiFor the ith node, residual energy, E0For the initial energy of each node, the node with the most residual energy in the common node set serves as a secondary cluster head to share the energy load of a single cluster head.
For the primary cluster head node farthest from the base station, a secondary cluster head node also needs to be selected, and at the moment, the distance from the base station is considered by the fitness function, and the specific formula is as follows:
wherein D isi,BSAnd selecting the node closest to the base station as a secondary cluster head node for the distance between the ith node and the base station.
In step S14, the regular node transmits the data to the secondary cluster head node, which transmits the received data to the primary cluster head node.
The method comprises the steps that target data are collected and preprocessed by common nodes, if no secondary cluster head node exists in a current cluster, the target data are directly transmitted to the primary cluster head node in a pre-allocated time slot, and the primary cluster head node singly fuses all intra-cluster node data and then reaches a base station through forwarding of a plurality of other primary cluster head nodes;
if a secondary cluster head node exists in a current cluster, the common node transmits data to the secondary cluster head node, then the secondary cluster head node transmits the data to a primary cluster head node, multi-hop transmission is carried out between the primary cluster head node and a base station, the primary cluster head node optimally forwarded each time is determined by an improved valley laying bird algorithm, and then single-hop transmission is directly carried out. And if the secondary cluster head node exists in the current cluster, the data transmission is also transmitted through the established TDMA time slot table.
In step S15, the position information of all the ordinary nodes in the primary cluster head node with the largest number of ordinary nodes and the primary cluster head node farthest from the base station is updated, and it is determined whether the determined secondary cluster head node is the required secondary cluster head node, if yes, step S16 is executed.
The method comprises the steps that a Valley bird algorithm determines historical individual optimal node positions pbest and global optimal node positions gbest, the individual optimal node positions pbest are determined by fitness functions when the nodes are located at updated positions, if the updated fitness functions are superior to fitness functions before the nodes, the pbest is replaced, otherwise, the pbest is kept unchanged, the same is true, the updated global optimal node fitness functions are superior to the fitness functions before the nodes, the pbest is replaced, otherwise, the node is kept unchanged, and the selected nodes after each updating are guaranteed to be optimal.
The specific flow of the improved cuckoo algorithm adopted in the embodiment is as follows:
1. taking the position of a first-stage cluster head node as the position of an initial cuckoo, initializing parameters including a fitness function F, an initial node individual optimal position pbest, an initial global optimal position gbest, a particle position Si, a step length control quantity alpha and a constant beta, wherein the initial pbest is the position of the first-stage cluster head node, and the gbest is the position of the node with the maximum fitness in all the first-stage cluster head nodes;
2. the position of the node is denoted as S (i) { S (i) } { (i)1,S2…SN0|i＝1,2…N0The fitness function of the node is denoted as F (i), F (i) ═ F (1), F (2) … F (N)0)|i＝1,2…N0Selecting a node with the maximum fitness function from the common node set as a gbest (second-level cluster head node);
3. after each selection, the node updates the position of the node, and the specific formula is as follows, the current fitness function is calculated and compared to re-determine the optimal position pbest and the global optimal position gbest of the individual; if the fitness value of each updated node is better than that of the previous node, replacing the historical individual optimal position pbest as the current position, otherwise keeping the current position unchanged, if the global optimal position of the updated node is better than that of the previous node, replacing the current position with the global optimal position of the updated node, and otherwise keeping the global optimal position of the updated node unchanged;
v～N(0,1)
wherein
Is the position found by the ith cuckoo at the t +1 th search, pbest (i)(t)Expressed as the optimal position of the ith cuckoo t times, gbest(t)Expressing the optimal positions of all cuckoos at t times, taking alpha as a step size, taking 0.01, enabling mu and v to obey standard normal distribution, and taking gamma (1+ beta) as a standard gamma function; β is 1.5.
In step S16, calculating the energy of the common node, the secondary cluster head node, and the primary cluster head node of the transmission data, and determining whether a preset threshold is reached according to the calculated energy, if yes, ending the data transmission; if not, the steps S11-S15 are continued.
In this embodiment, the threshold may be a preset number of cycles, an energy loss threshold, or a threshold set to no energy, and the threshold may be set according to actual conditions, and is not limited herein.
The nodes perform energy calculation according to the wireless communication energy consumption model, and repeatedly perform the steps from S11 to S15 to complete data transmission of each round, so that a secondary clustering mechanism of the LEACH protocol based on the Cuckoo algorithm can be obtained to prolong the network life cycle and balance energy consumption better than the traditional LEACH protocol.
The wireless communication energy consumption model is specifically defined as follows:
the energy calculation formula consumed by the sensor node to send M-bit data to the node with the distance d is as follows:
where M is the total number of bits for data transmission, EelecEnergy consumed by the circuit to transmit 1-bit data, d is the node transmission distance, d0Is a threshold value, if d<d0The loss model of the power amplifier adopts a free space model, and if d is less than or equal to d0Using a multipath fading model, epsilonfsThe amplification factor of the power amplifier in the free space model.
The energy calculation formula consumed by the sensor node to receive the M-bit data from the node with the distance d is as follows:
ERX(M,d)＝M*Eelec
the energy consumed by the first-level cluster head node fusing the M-bit data from the C nodes is calculated as follows:
Emix＝(C+1)*M*EDA
wherein EDAFor the fusion coefficient, C is the number of all nodes in a certain cluster.
This embodiment is characterized by energy loss: each wireless sensor node must follow the following energy loss rule:
Esum＝ERX+Efusion+ETX
ERX＝n*Eelec
The primary cluster head node comprises:
Efusion＝n*EDA
The beneficial effects produced by the embodiment are as follows: the cuckoo algorithm has the advantages of high searching efficiency, high speed, simple algorithm, good searching effect and the like, is applied to cluster head selection of the LEACH protocol, selects the optimal node in combination with the index of network performance to enable the probability that the node with high energy and short distance is selected as the cluster head to be high, fully ensures that the node cannot be selected as the cluster head due to the adverse conditions of low energy or long distance, effectively relieves the problem of 'energy holes', can be obviously improved in comparison with the energy formula and simulation results compared with the basic LEACH protocol in energy consumption, and has a great effect on improving the stability of the wireless sensor network.
The nouns referred to in this embodiment are:
cuckoo algorithm: cuckoo Search (CS abbreviation): is an algorithm that effectively solves the optimization problem by simulating parasitic brooding (BroodParasitism) of certain species of cuckoo. Meanwhile, the CS also adopts a related Levy flight search mechanism. Studies have shown that cuckoo search is more efficient than other population optimization algorithms.
The LEACH protocol: the network routing protocol is called a Low power consumption Adaptive Clustering hierarchical protocol (Low Energy Adaptive Clustering Hierarchy) and is a wireless sensor network routing protocol. Algorithms based on the LEACH protocol are called LEACH algorithms. The basic idea of the algorithm is as follows: and randomly selecting cluster head nodes in a circulating mode, and evenly distributing the energy load of the whole network to each sensor node, thereby achieving the purposes of reducing the energy consumption of the network and improving the overall survival time of the network. Simulation shows that compared with a general plane multi-hop routing protocol and a static layering algorithm, the LEACH clustering protocol can prolong the life cycle of a network by 15%.
TDMA: time Division Multiple Access (Time Division Multiple Access) is to divide Time into periodic frames (frames), each Frame is divided into several Time slots to transmit signals to the base station, and the base station can receive the signals of each mobile terminal in each Time slot without mixing under the condition of satisfying timing and synchronization. Meanwhile, the signals sent by the base station to a plurality of mobile terminals are all arranged in a predetermined time slot in sequence for transmission, and each mobile terminal can distinguish and receive the signals sent to the mobile terminal in the combined signals as long as the mobile terminal receives the signals in the designated time slot.
The embodiment provides a new clustering algorithm, effectively avoids the problem of 'hot spots' and 'islands' of the whole network, reduces energy consumption as much as possible, achieves the effects of high efficiency, energy saving and prolonging the life cycle of a wireless network; in addition, a new clustering mode is defined in the embodiment from the stage of the largest energy consumption of the sensor, an improved cuckoo algorithm is introduced, a secondary clustering mechanism is combined, and by simulation, how to design a good clustering method has great influence on the network performance and the survival time, and the effectiveness of the algorithm is also verified.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method of LEACH two-level clustering routing protocol based on cuckoo algorithm is characterized by comprising the following steps:
s1, broadcasting first-level cluster head election information to wireless sensor nodes, and selecting a plurality of first-level cluster head nodes and a plurality of common nodes;
s2, the primary cluster head nodes broadcast information related to the primary cluster head nodes to all common nodes in the network, the common nodes select the primary cluster head nodes with the strongest signals according to the received signal strength of the broadcast information of the primary cluster head nodes and add the primary cluster head nodes into the selected cluster, and step S3 is executed until all the common nodes are added into the cluster;
s3, screening the primary cluster head node with the largest number of common nodes in the primary cluster head nodes and the primary cluster head node which is farthest from the base station in the primary cluster head nodes, and determining the secondary cluster head node by the aid of a valley-laying bird algorithm according to the screened primary cluster head node with the largest number of common nodes and the primary cluster head node which is farthest from the base station;
s4, the common node transmits data to a secondary cluster head node, and the secondary cluster head node transmits the received data to a primary cluster head node;
s5, updating the position information of all the common nodes in the primary cluster head node with the largest number of common nodes and the primary cluster head node farthest from the base station, judging whether the determined secondary cluster head node is the required secondary cluster head node, and if so, executing the step S6;
s6, calculating the energy of the common node, the secondary cluster head node and the primary cluster head node of the transmission data, judging whether the energy reaches a preset threshold value according to the calculated energy, and if so, finishing data transmission; if not, the steps S1-S5 are continued.
2. The method of claim 1, wherein the step S1 of broadcasting the first-level cluster election information to the wireless sensor nodes further comprises collecting geographical locations of all wireless sensor nodes and calculating distances between any two wireless sensor nodes.
3. The method according to claim 2, wherein the step S1 of selecting the first-level cluster head nodes is specifically selecting by comparing random numbers with a threshold value; the random number is generated by each node.
4. The method of the LEACH second-level clustering routing protocol based on the Cuckoo algorithm as claimed in claim 3, wherein the threshold is calculated by the following formula:
wherein t (n) represents a threshold value; p represents the ratio of the number of the first-level cluster head nodes in the network to all the nodes in the network, r represents the number of currently experienced rounds, GrThe first r-1 round is not selected as the set of the first-level cluster head nodes.
5. The method according to claim 1, wherein the step S2, after all the normal nodes are added into the cluster, further comprises each primary cluster head node establishing a TDMA slot table according to the number of the normal nodes in the cluster and allocating the data transmission time of the normal nodes in the cluster.
6. The method of claim 5, wherein the step S4 further includes the step of transmitting data to the primary clusterhead node directly through the established TDMA slot table if there is no secondary clusterhead node in the cluster.
7. The method of claim 5, wherein the ordinary node transmits data to the secondary clusterhead node in step S4, and the secondary clusterhead node transmits the received data to the primary clusterhead node through the established TDMA slot table.
8. The method of the LEACH secondary clustering routing protocol based on the cuckoo algorithm of claim 1, wherein the determining the secondary cluster head node in step S3 specifically includes:
determining the secondary cluster head nodes in the primary cluster head node cluster with the largest number of screened common nodes, wherein the formula is as follows:
wherein E isiFor the ith node, residual energy, E0An initial energy for each node; determining the common node with the most residual energy as a secondary cluster head node;
determining secondary cluster head nodes in the screened primary cluster head node cluster farthest from the base station, wherein the specific formula is as follows:
wherein D isi,BSThe distance between the ith node and the base station is obtained; and determining the common node closest to the base station as a secondary cluster head node.
9. The method according to claim 1, wherein the step S5 further includes updating the determined secondary cluster head node if the determined secondary cluster head node is not the required secondary cluster head node.
10. The method according to claim 9, wherein the step S5 of updating the location information of all the common nodes is implemented by using the following specific formula:
v～N(0,1)
wherein the content of the first and second substances,
representing the position of the ith cuckoo found at the t +1 th search; pbest (i)(t)Denotes the position of the ith cuckoo t times, gbest(t)Representing the positions of all cuckoos at t times, taking alpha as a step size, taking 0.01, enabling mu and v to obey standard normal distribution, and taking gamma (1+ beta) as a standard gamma function; β is 1.5.
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