CN110072265B - Method for realizing energy heterogeneous wireless sensor network clustering protocol - Google Patents
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Abstract
The invention provides a method for realizing an energy heterogeneous wireless sensor network clustering protocol, which comprises the following steps: firstly, establishing a system energy consumption model, and determining the optimal cluster number of the system under the condition of considering the minimum energy consumption, thereby determining the number of nodes in each cluster. And then selecting cluster head nodes under the condition of ensuring the maximum cluster head coverage rate, replacing the cluster head nodes with larger energy consumption in the current round of communication according to a certain proportion, and preparing for the next round of communication. And the rest member nodes of each cluster are added into the cluster in a nearby clustering mode, the data of the rest member nodes are firstly sent to the cluster head node, and the cluster head node fuses the data of all the member nodes and then sends the data to the base station, so that one round of communication is completed. The algorithm provided by the invention has obvious advantages in network service life in energy heterogeneous network application, and the cluster heads with larger energy consumption in the round are replaced according to a certain proportion in the cluster head selection process, so that the whole energy consumption of the network is reduced, the network load is balanced, and the network service life is prolonged.
Description
[ technical field ] A
The invention relates to the technical field of communication technology, in particular to a method for realizing an energy heterogeneous wireless sensor network clustering protocol.
[ background ] A method for producing a semiconductor device
The wireless sensor network needs a large number of nodes to cooperatively complete a measurement task and faces a complex and variable working environment. And the nodes are reasonably selected and arranged according to different environments and the parameters are optimized, so that the working efficiency of the wireless sensor network is improved and the cost is reduced. In recent years, researchers have tried to solve the problem of lifetime optimization of wireless sensor networks from different perspectives, and many effective methods have been proposed. The layering mechanism can optimize data delay to achieve the purpose of increasing network upgradability, and meanwhile, data are integrated in a layering mode, so that data redundancy can be reduced, communication load can be reduced, and the purpose of optimizing network service life can be achieved. The hierarchical routing protocol is called as low-power consumption self-adaptive clustering hierarchical protocol, and 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. The LEACH algorithm is divided into three parts: firstly, selecting cluster heads; secondly, adding cluster members into a cluster; routing of clusters. During election, each node generates a random number between 0 and 1, and if the number is smaller than a threshold value T (n), the node becomes a cluster head. The threshold value T (n) is calculated by
Wherein p represents the proportion of cluster heads in the network, r represents the number of current running rounds, and the set G represents the node set of which no elected cluster head exists in the previous 1/p rounds. From the equation (1), all nodes have an opportunity to be selected as cluster heads, and the energy consumption of all nodes in the system is balanced, so that the life cycle of the system is prolonged. However, the LEACH algorithm has the following disadvantages: firstly, the election of cluster heads of the LEACH algorithm is completely random, so that the cluster heads are possibly unevenly distributed in a monitoring area, the overall energy consumption is unevenly distributed, and particularly, nodes far away from a base station are easy to die prematurely; secondly, the expansibility is poor, and the cluster head and the base station adopt a single-hop communication mode, so that the cluster head is not suitable for large-scale network application; adaptability is poor, application occasions of the wireless sensor network are various, requirements of each application may not be identical, and the LEACH algorithm adopts a sampling and transmission period which is uniform in the whole network, so that the LEACH algorithm cannot be suitable for a heterogeneous network.
In response to the deficiency of LEACH algorithm, a great deal of research has also made some improvements, for example
1. A distributed algorithm is adopted, and a simulation experiment is carried out as an extension of the LEACH clustering algorithm. Although the network life is prolonged compared with the LEACH network, the algorithm is only suitable for the problems of unit circle and non-unit circle and has limitation;
2. an energy adaptive protocol NEAP (novel energy adaptive protocol) is adopted. Unlike the LEACH protocol, the NEAP threshold is a function of the node's remaining energy, as shown in equation (2)
Wherein: e cur 、E ini Respectively representing the current energy and the initial energy of the node; r is a radical of hydrogen s Indicating the number of consecutive rounds that the node has not been selected as a cluster head. Compared with the LEACH protocol, the NEAP protocol has better performance in the aspect of selecting the cluster heads, but energy optimization in each round of cluster head selection is not discussed;
3. a distributed energy efficient-clustering (DEEC) protocol is employed. The DEEC protocol adopts a heterogeneous network model of a two-stage energy structure, and each node selects a cluster head according to the residual energy of the node. The DEEC protocol only selects the cluster head from the residual energy of the DEEC protocol, and does not consider the problem of system energy balance. Or a DEEC modified algorithm DDEEC (modified DEEC) protocol. The protocol dynamically changes the standard of selecting the cluster head, thereby balancing the energy consumption of the nodes; or a stable election protocol, which is referred to as SEP (stable election protocol) protocol. The SEP has the basic idea that the nodes are set into two types of common nodes and advanced nodes according to different initial energies of the nodes. The advanced nodes have higher initial energy than the common nodes, the probability of being selected as the cluster head is higher, but the SEP protocol does not adjust the threshold value of the cluster head according to the energy level of the nodes.
[ summary of the invention ]
The invention aims to solve the problems in the prior art, and provides a method for realizing an energy heterogeneous wireless sensor network clustering protocol, which can balance cluster head selection as much as possible on the basis of considering that the energy consumption of each round of communication is as small as possible and the coverage rate of the selected cluster head is as large as possible, so that the energy load of a system is balanced, and the aim of prolonging the life cycle of the system is fulfilled.
In order to achieve the above object, the present invention provides a method for implementing an energy heterogeneous wireless sensor network clustering protocol, which includes the following steps:
s1, firstly, establishing a system energy consumption model, and determining the optimal cluster number of a system under the condition of considering minimum energy consumption so as to determine the due node number in each cluster;
s2, selecting cluster head nodes under the condition of ensuring the maximum cluster head coverage rate, replacing the cluster head nodes with higher energy consumption in the current communication according to a certain proportion, and preparing for the next communication;
and S3, adding the rest member nodes of each cluster into the cluster in a nearby clustering mode, sending the data of the rest member nodes to the cluster head node, fusing the data of each member node by the cluster head node, and sending the data to the base station, thereby completing one round of communication.
Preferably, the step S1 specifically includes the following steps:
s1.1, system time sequence division: dividing a system time sequence into a plurality of periods, wherein one period is designed into one round, each round is internally provided with an initial stage and a working stage, the initial stage is used for selecting a cluster head and forming a cluster, and the working stage is used for finishing data transmission;
s1.2, establishing an energy model: the transmitting end of the wireless energy consumption model consumes energy when operating the transmitter element and the power amplifier, and the receiving end consumes energy when operating the transmitter element; the distance between the receiving end and the transmitting end is d m, if d is smaller, a free space transmission model is adopted, and if d is larger, a multipath fading channel model is adopted;
the energy consumed to transmit the qbit message between the transmitting end and the receiving end at distance d m is:
e in the formula (3) el Representing the energy consumed per bit when operating the transmitter element; e frs 、E tworay Represents the energy consumption of the transmitter in the free space and the unit power amplifier of the dual path propagation model, respectively, and d 0 Comprises the following steps:
h in formula (4) t 、h r Respectively is the ground clearance between the sending end and the receiving end, and lambda is the wavelength; the energy consumed to receive the q-bit message is:
E re (q)＝q×E el (5)；
s1.3, determining the optimal cluster number: the number of nodes in the network is N, and the initial energy of each node is different; assuming that C cluster heads CH are generated in the r-th round, there is an average in each cluster
Once the cluster head CH is generated, the member nodes in the cluster send q bit control information to the cluster head CH, and the assumption is made that the data transmission from the member nodes in the cluster to the cluster head CH is based on a free space channel model; the energy E consumed by each cluster member node to send the q-bit control message to the cluster head node normal-CH Comprises the following steps:
d in formula (6) CH The average distance from the cluster member node to the cluster head CH;
when the cluster head is far away from the base station, the message transmission model is a multipath fading channel model; cluster head CH slave
Receiving the q bit control message by each cluster member node, carrying out data fusion, and transmitting the total consumed energy E of the message to the base station CH Comprises the following steps:
the first term in formula (7) is selected from
Energy consumed by the cluster member nodes for receiving the q bit control message, wherein the second item is energy consumed by fusing data, and the last item is energy consumed by transmitting the data to the base station; wherein E is data Presentation blendEnergy consumed by the synthesis of a single bit message, d BS The average distance between the cluster head CH and the base station; thus, the total energy E of a cluster message in a round of communication cluster Comprises the following steps:
then the total energy E consumed in the r-th network round Comprises the following steps:
in order to minimize the energy consumed by the network in each round, the cluster number C is offset to 0 by equation (9), and the optimal cluster number C is obtained opt (ii) a Accordingly, the optimal cluster head ratio p opt Comprises the following steps:
preferably, the step S2 specifically includes the following steps:
s2.1 node coverage: assuming that the monitoring area is a rectangular area with a length of h m and a width of w m, the area is h × wm 2 (ii) a Establishing a two-dimensional coordinate system by taking h as a vertical coordinate w as a horizontal coordinate, and obtaining the coordinates of N sensor nodes thrown in the area in the two-dimensional coordinate system; assuming that the sensing radiuses of all the sensors are R and the communication radiuses are R; in order to ensure network connectivity and give consideration to wireless interference, a communication radius R is set to be twice of a sensing radius R, namely R is 2R; by c i ＝{x i ,y i And r represents the node coordinate { x } i ,y i Taking the circle as the center of the circle and monitoring the circle with the radius r; assuming that the coordinates of the monitored target are (x, y), the distance between the target and the sensing node is
Defining the event of the monitoring target covered by the sensing node as e i Then the probability of the event occurring P { e } i I.e. target (x, y) sensor node c i The covered probability considers monitoring environment and noise interference, and the sensing node measurement model is in probability distribution with certain characteristics in practical application, namely:
in the formula (11), r e (0<r e <r) is a sensing node measurement reliability parameter, α 1 、α 2 、β 1 、β 2 Is a measurement parameter, λ, related to the characteristics of the sensing node 1 And λ 2 For the input parameters:
λ 1 ＝r e -r+d(c i ) (12)
λ 2 ＝r e +r-d(c i ) (13)
in order to improve the target measurement probability, a plurality of sensing nodes are used to measure the target simultaneously, and the joint measurement probability is shown as the following formula (14):
s2.2 area coverage rate: the area of the monitoring region is h x wm 2 The rectangle is discretized into pixel points, and the size of the pixel points is determined according to an actual application scene; node set joint measurement probability P for whether each pixel point is covered cov (Cov); the area coverage rate R of the node set C area (C) Defined as the ratio of the coverage area of the node assembly C to the total area of the monitored area, namely:
preferably, the step S3 specifically includes the following steps:
s3.1 cluster head selection algorithm: numbering N sensors in a monitoring area from 1 to N, randomly selecting a node as a cluster head, and if the number of the selected node is K, selecting C from the rest N-1 nodes according to the previously calculated optimal cluster head number opt -1 node as cluster head; c opt -1 cluster head selection principle is to calculate the node coverage rate according to the above steps in sequence to maximize the area coverage rate of formula (15); recording energy consumption of all cluster heads in the data communication process of the current round
And remaining energy per cluster head
Introducing cluster head vitality parameter eta i ，η i Is defined as follows:
the more energy remains, η, with the same energy consumption i The larger the size, the higher the activity of the cluster head, and the longer the life cycle; under the condition of the same residual energy, the more energy consumed by the wheel is, eta i The smaller the size, the smaller the vitality of the cluster head is, and the shorter the life cycle is; after one round of communication is finished, C is added opt Eta of individual cluster head i Sorting from small to large; the algorithm is a round of cluster head selection algorithm, and the cluster head selection of the next round is carried out again after one round of data communication is finished; the cluster heads of the current round need to be replaced when the cluster heads of the next round are selected, the cluster heads with strong activity are kept as much as possible during replacement, and the replacement proportion rho (rho is in the range of (0, 1)]) Is a (0, 1)]Pure decimal of interval, ρ ═ 1 denotes C of the current wheel opt All cluster heads are replaced, and all cluster heads in the next round are selected from the non-cluster-head set G; rho is 0, all cluster heads of the next round use the cluster head of the current round, and the cluster heads do not exist in the model, so rho is not equal to 0; the number of cluster heads to be replaced is C rep ＝C opt X rho, press the wheel by eta i Top C in order from small to large rep Replacing cluster heads, and selecting C from non-cluster head set G rep The cluster heads enable the area coverage rate of the formula (15) to be maximum, and the next round of cluster head selection process is completed;
s3.2 clustering process: c in one-round communication opt After the cluster head nodes are selected, the cluster head broadcasts a request joining message, and after the non-cluster head nodes receive the message, the nearest cluster is selected to join until the number of the cluster head nodes reaches the number
The clustering process is terminated. The number of nodes in the last cluster may be less than
A plurality of;
s3.3, working stage: the cluster head broadcasts a TDMA data stream to inform member nodes of the TDMA data stream to start a data acquisition process, the member nodes in the cluster send sensed data to the cluster head according to a TDMA time slot, and the cluster head CH collects data of the nodes in the cluster, then performs fusion and finally transmits the data to the base station; after the data transmission is finished, re-entering the cluster head selection work of the next round, and re-selecting clusters; the working phase data acquisition is started after the cluster head sends a TDMA (time division multiple access) broadcast to the member nodes, the member nodes in the cluster send the acquired data to the respective cluster heads in the TDMA process, and the cluster heads integrate the data to reduce the noise in the signals after receiving all the data; the cluster head sends the integrated data to the base station in a single-hop or multi-hop mode, and then the network starts the process of circularly selecting the cluster head and clustering the next time; when all nodes become over-cluster heads, the next cycle is started.
The invention has the beneficial effects that: according to the invention, through a protocol based on energy consumption and cluster head coverage rate, an energy model is firstly designed, the optimal cluster number is determined based on the minimum system energy consumption principle, and then cluster head selection is carried out based on the area coverage rate maximization principle. In order to balance the network load as much as possible, the cluster heads with low residual energy and high energy consumption in the current round are replaced by the cluster heads in the next round of cluster head election according to a certain proportion, so that the purpose of prolonging the service life of the network is achieved.
The features and advantages of the present invention will be described in detail by embodiments in conjunction with the accompanying drawings.
[ description of the drawings ]
Fig. 1 is a system timing diagram of an implementation method of an energy heterogeneous wireless sensor network clustering protocol according to the present invention;
FIG. 2 is a radio energy consumption model of an implementation method of an energy heterogeneous wireless sensor network clustering protocol according to the present invention;
fig. 3 is a schematic diagram of random distribution of sensing nodes in a monitoring area 20 × 20 in an embodiment of a method for implementing an energy heterogeneous wireless sensing network clustering protocol according to the present invention;
FIG. 4 is a flow chart of a cluster head selection algorithm of an implementation method of an energy heterogeneous wireless sensor network clustering protocol according to the present invention;
FIG. 5 shows the influence of a cluster head replacement ratio ρ on the life cycle of a network according to an implementation method of an energy heterogeneous wireless sensor network clustering protocol;
fig. 6 shows the influence of the number of active nodes on the service life of the network in the system of the method for implementing the energy heterogeneous wireless sensor network clustering protocol.
[ detailed description ] embodiments
The invention discloses a method for realizing an energy heterogeneous wireless sensor network clustering protocol, which comprises the following steps:
s1, firstly, establishing a system energy consumption model, and determining the optimal cluster number of a system under the condition of considering the minimum energy consumption, so as to determine the number of nodes in each cluster; to simplify the problem model, the present invention makes the following assumptions for the study problem features: (1) the wireless sensing network is composed of a large number of fixed sensing nodes, namely once the sensing nodes are arranged in a certain monitoring area, the positions of the sensing nodes are not changed any more, and the number of the sensing nodes is assumed to be N; (2) after the nodes are arranged in the monitoring area, the position information of the nodes can be acquired by some means (such as GPS); (3) all nodes are basically synchronous in the precision of second level; (4) only one base station exists in the monitoring area, and the position of the base station is fixed in the right center of the area A; (5) the N sensing nodes are heterogeneous, wherein the heterogeneous mainly refers to the fact that the initial energies of the sensors are different; (6) the system routing model is a hierarchical routing protocol based on clusters, one cluster is composed of a cluster head node CH and a plurality of non-cluster head nodes, the non-cluster head nodes firstly transmit data sensed by the non-cluster head nodes to the respective cluster head CH, and the CH node heads are responsible for fusing the data of the non-cluster head nodes and forwarding the data to a base station BS (base station).
Step S1 specifically includes the following steps:
s1.1, system time sequence division: the system timing is divided into a plurality of periods, and one period is counted as one round, as shown in fig. 1. Each round is internally provided with an initial stage and a working stage, the initial stage is used for selecting a cluster head and forming a cluster, and the working stage is used for finishing data transmission; in order to avoid the interference of data transmission among nodes, a time slot is allocated to each node in the transmission process, and the nodes transmit data in the time slot;
s1.2, establishing an energy model: considering the radio energy consumption model as shown in fig. 2, the transmitting end consumes energy when operating the transmitter element, the power amplifier, and the receiving end consumes energy when operating the transmitter element; the distance between the receiving end and the transmitting end is d m, if d is smaller, a free space transmission model is adopted, and if d is larger, a multipath fading channel model is adopted;
the energy consumed to transmit the qbit message between the transmitting end and the receiving end at distance d m is:
in formula (3): e el Representing the energy consumed per bit when operating the transmitter element; e frs 、E tworay Represents the energy consumption of the transmitter in the free space and the unit power amplifier of the dual path propagation model, respectively, and d 0 Comprises the following steps:
h in the formula (4) t 、h r Respectively is the ground clearance between the sending end and the receiving end, and lambda is the wavelength;the energy consumed to receive the q-bit message is:
E re (q)＝q×E el (5)；
s1.3, determining the optimal cluster number: the cluster hierarchical routing protocol firstly divides the sensing nodes in the network into different clusters. How to cluster and how to select cluster head nodes are all problems to be solved, and the optimal probability p of one node becoming a cluster head opt Is an important embodiment of the clustering result. If the cluster is not optimally constructed, i.e., the number of clusters is slightly larger or smaller than the optimal number of clusters, the total power consumption of the system also increases exponentially. To this end, the present invention first calculates the optimal cluster number from the viewpoint of minimum energy consumption.
The number of nodes in the network is N, and the initial energy of each node is different; assuming that C cluster heads CH are generated in the r-th round, there is an average in each cluster
Once a cluster head CH is generated, the member nodes in the cluster send q-bit control messages to the cluster head CH, the basis of clustering is that the communication cost of all the nodes in the cluster is as low as possible, the cluster head is generally used as the center, and clustering is carried out according to the distance from other nodes to the cluster head, so the member nodes are generally close to the cluster head CH, and the assumption is made that the data transmission from the member nodes in the cluster to the cluster head CH is based on a free space channel model; the energy E consumed by each cluster member node to send the q-bit control message to the cluster head node normal-CH Comprises the following steps:
d in formula (6) CH The average distance from the cluster member node to the cluster head CH;
considering the general situation, the cluster head is far away from the base station, and the message transmission model is a multipath fading channel model; cluster head CH slave
Individual cluster member node receptionq bit control message and data fusion, and the total energy E consumed by transmitting the message to the base station CH Comprises the following steps:
the first term in formula (7) is selected from
The energy consumed by the q bit control message received by the member nodes of each cluster is energy consumed by fusing data, and the last item is energy consumed by transmitting the data to the base station; wherein E is data Representing the energy consumed by fusing single-bit messages, d BS The average distance between the cluster head CH and the base station; thus, the total energy E of a cluster message in a round of communication cluster Comprises the following steps:
then the total energy E consumed in the r-th round of the network round Comprises the following steps:
in order to minimize the energy consumed by the network in each round, the cluster number C is offset to 0 by equation (9), and the optimal cluster number C is obtained opt (ii) a Accordingly, the optimal cluster head ratio p opt Comprises the following steps:
s2, selecting cluster head nodes under the condition of ensuring the maximum cluster head coverage rate, replacing the cluster head nodes with higher energy consumption in the current communication according to a certain proportion, and preparing for the next communication; although the implementation of the LEACH algorithm is simple, the completely random manner may cause a large density of cluster heads in a local area, and the cluster heads in other areas are sparsely distributed even without cluster heads, so that the distribution of the cluster heads in the whole system is uneven. The coverage rate is considered in the selection process of the cluster heads so as to solve the problem of uneven distribution of the cluster heads. Coverage generally refers to area coverage, although it is difficult to ensure random coverage of the target area to 100% assuming all sensors are operational. In practical applications, the overall impact of a small monitoring vulnerability on the system is small and acceptable. The overlay mechanism is used to ensure that the planning node remains active while meeting the coverage expectations. Therefore, applying the overlay mechanism to the interior of a cluster, called intra-cluster overlay, based on the previous work, the selection calculation process of the minimum cluster head number is as follows:
s2.1 node coverage: assuming that the monitoring area is a rectangular area with a length of h meters and a width of w meters, the area is h × wm 2 (ii) a Establishing a two-dimensional coordinate system by taking h as a vertical coordinate w as a horizontal coordinate, and obtaining the coordinates of N sensor nodes thrown in the area in the two-dimensional coordinate system; assuming that the sensing radiuses of all the sensors are R and the communication radiuses are R; in order to ensure network connectivity and give consideration to wireless interference, a communication radius R is set to be twice of a sensing radius R, namely R is 2R; by c i ＝{x i ,y i R represents the node coordinate x i ,y i Taking the circle as the center of the circle and monitoring the circle with the radius r; assuming that the coordinates of the monitored target are (x, y), the distance between the target and the sensing node is
Defining the event of the monitoring target covered by the sensing node as e i Then the probability of the event occurring P { e } i I.e. target (x, y) sensor node c i The covered probability considers monitoring environment and noise interference, and the sensing node measurement model is in probability distribution with certain characteristics in practical application, namely:
in the formula (11), r e (0<r e <r) is a sensing node measurement reliability parameter, α 1 、α 2 、β 1 、β 2 Is a measurement parameter, λ, related to the characteristics of the sensing node 1 And λ 2 For the input parameters:
λ 1 ＝r e -r+d(c i ) (12)
λ 2 ＝r e +r-d(c i ) (13)
in order to improve the target measurement probability, a plurality of sensing nodes are used to measure the target simultaneously, and the joint measurement probability is shown as the following formula (14):
s2.2 area coverage rate: the area of the monitoring region is h × wm 2 The rectangle is discretized into pixel points, and the size of the pixel points is determined according to an actual application scene; node set joint measurement probability P for whether each pixel point is covered cov (Cov) as measured; the area coverage rate R of the node set C area (C) Defined as the ratio of the coverage area of the node assembly C to the total area of the monitored area, i.e.:
description of coverage problem:
assuming that a monitoring area is a square of 20m × 20m, which is divided into 100 pixels with equal size, and 20 sensing nodes are put into the area, a schematic diagram of the monitoring area is shown in fig. 3. The position of the sensing node in the region is denoted by x in the figure, and the coverage problem is described as follows: 1) calculating the coverage rate of each pixel point by using the formula (11) to the formula (13); 2) calculating the joint coverage rate of each pixel point by the sensing node by using the formula (14); 3) repeating the steps (1) to (2) to calculate the joint coverage rate of each pixel point by the sensing node; 4) the area coverage of the area is calculated by using the formula (15), and the formula (15) is taken as an optimization objective function of the coverage control algorithm.
And S3, adding the rest member nodes of each cluster into the cluster in a nearby clustering mode, sending the data of the rest member nodes to the cluster head node, fusing the data of all the member nodes by the cluster head node, and then sending the data to the base station, thereby completing one round of communication. The method specifically comprises the following steps:
s3.1 cluster head selection algorithm: numbering N sensors in a monitoring area from 1 to N, randomly selecting a node as a cluster head, and if the number of the selected node is K, selecting C from the rest N-1 nodes according to the previously calculated optimal cluster head number opt -1 node as cluster head; c opt -1 cluster head selection principle is to calculate the node coverage rate according to the above steps in sequence to maximize the area coverage rate of formula (15); recording energy consumption of all cluster heads in the data communication process of the current round
And remaining energy per cluster head
Introducing cluster head vitality parameter eta i ，η i Is defined as follows:
the more energy remains, η, with the same energy consumption i The larger the cluster head, the higher the activity of the cluster head, and the longer the life cycle; under the condition of the same residual energy, the more energy consumed by the wheel is, eta i The smaller the size, the smaller the vitality of the cluster head is, and the shorter the life cycle is; after one round of communication is finished, C is added opt Eta of individual cluster head i Sorting from small to large; in order to prolong the life cycle of the system as much as possible, the more active the node as a cluster head is, the better; the algorithm is a round of cluster head selection algorithm and is carried out again after one round of data communication is finishedOne round of cluster head selection; because the cluster head needs to collect the data of the common nodes for fusion at first and then pack and send the fused data to the base station, the energy consumption of the cluster head is far larger than that of the common nodes; in order to balance the energy load of the whole system, all nodes should have an opportunity to become cluster heads as much as possible; therefore, the cluster heads of the current round need to be replaced when the cluster heads of the next round are selected, the cluster heads with strong activity are kept as much as possible during replacement, and the replacement proportion rho (rho is equal to (0, 1)]) Is a (0, 1)]Pure decimal of interval, ρ ═ 1 denotes C of the current wheel opt All cluster heads are replaced, and all cluster heads in the next round are selected from the non-cluster-head set G; ρ ≠ 0, which means that all cluster heads of the next round use the cluster head of the current round, but does not exist in the current model; the number of cluster heads to be replaced is C rep ＝C opt X rho, the principal round is pressed by eta i Top C in order from small to large rep Replacing cluster heads, and selecting C from non-cluster head set G rep The cluster heads enable the area coverage rate of the formula (15) to be maximum, and the next round of cluster head selection process is completed; a flow chart of the cluster head election algorithm is shown in fig. 4.
S3.2 clustering process: c in one-round communication opt After the cluster head nodes are selected, the cluster head broadcasts a request joining message, and after the non-cluster head nodes receive the message, the nearest cluster is selected to join until the number of the cluster head nodes reaches the number
The clustering process is terminated. The number of nodes in the last cluster may be less than
A plurality of;
s3.3, working stage: the cluster head broadcasts a TDMA data stream to inform member nodes of the TDMA data stream to start a data acquisition process, the member nodes in the cluster send sensed data to the cluster head according to a TDMA time slot, and the cluster head CH collects data of the nodes in the cluster, then performs fusion and finally transmits the data to the base station; after the data transmission is finished, re-entering the cluster head selection work of the next round and re-selecting clusters; the working phase data acquisition is started after the cluster head sends a TDMA broadcast to the member nodes, the member nodes in the cluster send the acquired data to the respective cluster heads in the TDMA process, and the cluster heads integrate the data to reduce the noise in the signals after receiving all the data; the cluster head sends the integrated data to the base station in a single-hop or multi-hop mode, and then the network starts the process of circularly selecting the cluster head and clustering the next time; when all nodes become over-cluster heads, the next cycle is started.
The performance of the clustering protocol provided by the invention is simulated and analyzed as follows:
the simulation environment was built using MATLABR2016b and compared to the LEACH, DDEEC, SEP protocols. Specific simulation parameters are shown in table 1.
TABLE 1 simulation parameters
The cluster head replacement ratio rho has an influence on the network life cycle:
the introduction of the cluster head replacement proportion rho is to leave part of cluster heads with low energy consumption in each round of cluster heads on the premise of balancing the energy load of the whole system so as to achieve the purpose of prolonging the life cycle of the network. The life cycle of the network, i.e. the life of the network, is expressed in terms of the number of rounds, the value of which is equal to the round in which the last node in the network failed. The influence of the value of ρ on the life cycle of the system network is shown in fig. 5:
as can be seen from fig. 5, the cluster head replacement ratio ρ has a large influence on the network life cycle. ρ ═ 0 represents that all cluster heads in the next round use the cluster heads in the current round, in this case, the network life is ended only when the number of rounds is more than 3000, and is smaller than 8000 rounds of the highest point by half, which indicates that the life cycle of the cluster head nodes determines the life cycle of the system if no cluster head replacement is performed in the network, and once the life of all cluster head nodes is ended, the network will not work any more. It can be seen that networks that do not take load and power balancing into account are not suitable. From fig. 5, the number of network rounds reaches the highest point near ρ ═ 0.65, which illustrates that under the current assumed parameters, the replacement ratio of the cluster head in each round of the network is 0.65, which will prolong the life cycle of the network. And p is 1, all cluster heads of the current round are replaced, and the algorithm is converted into a LEACH algorithm. The change curve of rho to the number of wheels rises first and then falls, which shows that the condition that the rho value is too large or too small has no positive influence on the prolonging of the life cycle of the network, and the life cycle of the network can be prolonged only by proper rho value.
Several algorithms compare network life cycles:
the performance of the cluster head selection protocol provided by the invention is analyzed from two aspects of stable duration and network service life. And the stable time duration is represented by the number of rounds and is equal to the round of calculating the failure time of the first node from the initial start of the network. The protocol provided by the invention is designed as an E-CRCP protocol, and the stability duration and the network life of four protocols of LEACH, DDEEC, SEP and E-CRCP are firstly analyzed. Table 2 lists the experimental data of 10 tests. As calculated from the data in Table 2, the mean values of the stable periods of LEACH, DDEEC, SEP and E-CRCP are 950.2, 1256.8, 1398.5 and 1690.7, respectively. And the average network life values are 5535.7, 5863.6, 8626.5 and 8652.3, respectively. The data show that the E-CRCP protocol provided by the invention can effectively prolong the stable period and prolong the service life of the network.
TABLE 2 comparison of settling duration and network lifetime for several algorithms
From the above table, the E-CRCP protocol can effectively prolong the stable duration and the network lifetime, and is superior to the LEACH, DDEEC and SEP protocols. The reason is that: the LEACH protocol does not consider the residual energy of the nodes, but gives each node the same opportunity; DDEEC only considers the remaining energy of the node, while SEP considers the node energy level. However, these considerations do not favor the preferential generation of cluster heads CH. The E-CRCP protocol dynamically adjusts the replacement proportion of the cluster heads, and the measure prompts the E-CRCP protocol to select the optimal cluster head CH, reduces energy consumption, and further prolongs the stability time and the service life of the network. The extension of the network life means that more nodes can collect data, which is beneficial for the base station to receive more data packets.
The impact of the number of active nodes in the network on the lifetime of the network:
the active node is the node which is working, and once the energy of the node is exhausted, the node is dead and does not work any more. As time progresses, there are fewer and fewer active nodes in the system. Several different protocols are compared for differences in network lifetime when the number of active nodes in the network is the same. FIG. 6 reflects the effect of the number of active nodes on the lifetime of the network.
Fig. 6 illustrates the relationship between the number of active nodes and the lifetime of the network. As can be seen from the graph, the extended lifetime fails as the number of nodes increases in LEACH, DDEEC and SEP, whereas the E-CRCP protocol of the present invention (shown in delta in FIG. 6) can maintain extended lifetime as the number of nodes increases. This is because LEACH, DDEEC, and SEP do not consider the intra-cluster coverage mechanism, and each node needs to send all collected environment information, including redundant information, to its cluster head node, thereby increasing energy consumption. The E-CRCP protocol considers the energy load balance of the network and the maximum coverage rate in the cluster, so that the service life of the network can be prolonged along with the increase of the number of nodes.
The invention discloses a method for realizing an energy heterogeneous wireless sensor network clustering protocol. And then selecting cluster head nodes under the condition of ensuring the maximum cluster head coverage rate, replacing the cluster head nodes with larger energy consumption in the current round of communication according to a certain proportion, and preparing for the next round of communication. The rest member nodes of each cluster are added into the cluster in a nearby clustering mode, the data of the rest member nodes are firstly sent to the cluster head node, and the cluster head node fuses the data of all the member nodes and then sends the data to the base station, so that one round of communication is completed. Simulation results show that the algorithm provided by the invention has obvious advantages compared with the network life of LEACH, DDEEC and SEP protocols in energy heterogeneous network application. In the process of selecting the cluster heads, the cluster heads with larger energy consumption in the current round are replaced according to a certain proportion based on the energy consumption condition of the cluster head nodes, so that the whole energy consumption of the network is favorably reduced, the network load is balanced, and the service life of the network is prolonged.
The above embodiments are illustrative of the present invention, and are not intended to limit the present invention, and any simple modifications of the present invention are within the scope of the present invention.
Claims (2)
1. A method for realizing an energy heterogeneous wireless sensor network clustering protocol is characterized by comprising the following steps: the method comprises the following steps:
s1, firstly, establishing a system energy consumption model, and determining the optimal cluster number of a system under the condition of considering the minimum energy consumption, so as to determine the number of nodes in each cluster;
s2, selecting cluster head nodes under the condition of ensuring the maximum cluster head coverage rate, replacing the cluster head nodes with higher energy consumption in the current communication according to a certain proportion, and preparing for the next communication;
s3, adding the rest member nodes of each cluster into the cluster in a nearby clustering mode, sending own data to a cluster head node, fusing the data of all the member nodes by the cluster head node, and then sending the data to a base station, thereby completing one round of communication;
the step S1 specifically includes the following steps:
s1.1, system time sequence division: dividing a system time sequence into a plurality of periods, wherein one period is designed into one round, an initial stage and a working stage are arranged in each round, the initial stage is used for selecting a cluster head and forming a cluster, and the working stage is used for completing data transmission;
s1.2, establishing an energy model: the transmitting end of the wireless energy consumption model consumes energy when operating the transmitter element and the power amplifier, and the receiving end consumes energy when operating the transmitter element; the distance between the receiving end and the transmitting end is dm, if d is less than d 0 Adopting a free space transmission model, d is more than or equal to d 0 Then a multi-path fading channel model is adopted;
the energy consumed for transmitting the qbit message between the transmitting end and the receiving end at a distance dm is:
e in the formula (3) el Representing the energy consumed per bit when operating the transmitter element; e frs 、E tworay Represents the energy consumption of the transmitter in the free space and the unit power amplifier of the dual path propagation model, respectively, and d 0 Comprises the following steps:
h in the formula (4) t 、h r Respectively is the ground clearance between the sending end and the receiving end, and lambda is the wavelength; the energy consumed to receive the q-bit message is:
E re (q)＝q×E el (5)；
s1.3, determining the optimal cluster number: the number of nodes in the network is N, and the initial energy of each node is different; assuming that C cluster heads CH are generated in the r-th round, there is an average in each cluster
Once a cluster head CH is generated, the member nodes in the cluster send a control message of qbit to the cluster head CH, and the assumption is made that the member nodes in the cluster transmit data to the cluster head CH according to a free space channel model; the energy E consumed by sending the qbit control message to the cluster head node by each member node in the cluster normal-CH Comprises the following steps:
d in formula (6) CH The average distance from the cluster member node to the cluster head CH;
when the cluster head is far away from the base station, the message transmission model is a multipath fading channel model; cluster head CH slave
Receiving the control message of the qbit by the member nodes of each cluster, carrying out data fusion, and transmitting the total consumed energy E of the message to the base station CH Comprises the following steps:
the first term in formula (7) is selected from
Energy consumed by the cluster member nodes for receiving the q bit control message, wherein the second item is energy consumed by fusing data, and the last item is energy consumed by transmitting the data to the base station; wherein, E data Representing the energy consumed by fusing single-bit messages, d BS The average distance between the cluster head CH and the base station; thus, the total energy E of a cluster message in a round of communication cluster Comprises the following steps:
then the total energy E consumed in the r-th network round Comprises the following steps:
in order to minimize the energy consumed by the network in each round, the cluster number C is offset to 0 by equation (9), and the optimal cluster number C is obtained opt (ii) a Accordingly, the optimal cluster head ratio p opt Comprises the following steps:
the step S2 specifically includes the following steps:
s2.1 node coverage: assuming that the monitoring area is a rectangular area with a length of h meters and a width of w meters, the area is h × wm 2 (ii) a Establishing a two-dimensional coordinate system by taking h as a vertical coordinate w as a horizontal coordinate, and obtaining the coordinates of N sensor nodes thrown in the area in the two-dimensional coordinate system; assuming that the sensing radiuses of all the sensors are R and the communication radiuses are R; in order to ensure network connectivity and give consideration to wireless interference, a communication radius R is set to be twice of a sensing radius R, namely R is 2R; by c i ＝{x i ，y i And r represents the node coordinate { x } i ，y i Taking the circle as the center of the circle and monitoring the circle with the radius r; assuming that the coordinates of the monitored target are (x, y), the distance between the target and the sensing node is
Defining the event of the monitoring target covered by the sensing node as e i Then the probability of the event occurring P { e } i I.e. target (x, y) sensor node c i The covered probability considers monitoring environment and noise interference, and the sensing node measurement model is in probability distribution with certain characteristics in practical application, namely:
in the formula (11), r e (0＜r e < r) is a sensing node measurement reliability parameter, α 1 、α 2 、β 1 、β 2 Is a measurement parameter, λ, related to the characteristics of the sensing node 1 And λ 2 For the input parameters:
λ 1 ＝r e -r+d(c i ) (12)
λ 2 ＝r e +r-d(c i ) (13)
in order to improve the target measurement probability, a plurality of sensing nodes are used to measure the target simultaneously, and the joint measurement probability is shown as the following formula (14):
s2.2 area coverage rate: the area of the monitoring region is h × wm 2 The rectangle is discretized into pixel points, and the size of the pixel points is determined according to an actual application scene; node set joint measurement probability P for whether each pixel point is covered cov (Cov) as measured; the area coverage rate R of the node set C area (C) Defined as the ratio of the coverage area of the node assembly C to the total area of the monitored area, i.e.:
2. the method for implementing the energy heterogeneous wireless sensor network clustering protocol according to claim 1, wherein: the step S3 specifically includes the following steps:
s3.1 cluster head selection algorithm: numbering N sensors in a monitoring area as 1-N, randomly selecting a node as a cluster head, and if the number of the selected node is K, selecting C from the rest N-1 nodes according to the previously calculated optimal cluster head number opt -1 node as cluster head; c opt -1 cluster head selection principle is to calculate the node coverage rate according to the above steps in sequence to maximize the area coverage rate of formula (15); recording energy consumption of all cluster heads in the data communication process of the current round
And remaining energy per cluster head
Introducing cluster head vitality parameter eta i ，η i Is defined as follows:
the more energy remains, η, with the same energy consumption i The larger the size, the higher the activity of the cluster head, and the longer the life cycle; under the condition of the same residual energy, the more energy consumed by the wheel is, eta i The smaller the size, the smaller the vitality of the cluster head is, and the shorter the life cycle is; after one round of communication is finished, C is added opt Eta of individual cluster head i Sorting from small to large; the algorithm is a round of cluster head selection algorithm, and the cluster head selection of the next round is carried out again after one round of data communication is finished; the cluster heads of the current round need to be replaced when the cluster heads of the next round are selected, the cluster heads with strong activity are kept as much as possible during replacement, and the replacement proportion rho (rho is in the range of (0, 1)]) Is one (0, 1)]Pure decimal of interval, ρ ═ 1 denotes C of the current wheel opt Replacing all cluster heads, and selecting all cluster heads in the next round from the non-cluster-head set G; ρ ≠ 0, which means that all cluster heads of the next round use the cluster head of the current round, but does not exist in the current model; the number of cluster heads to be replaced is C rep ＝C opt X rho, press the wheel by eta i Top C in order from small to large rep Replacing cluster heads, and selecting C from non-cluster head set G rep The cluster heads enable the area coverage rate of the formula (15) to be maximum, and the next round of cluster head selection process is completed;
s3.2 clustering process: c in one-round communication opt After the cluster head nodes are selected, the cluster head broadcasts a request joining message, and after the non-cluster head nodes receive the message, the nearest cluster is selected to join until the number of the cluster head nodes reaches the number
The time-clustering process is terminated and the number of nodes in the last cluster may be less than
A plurality of;
s3.3, working stage: the cluster head broadcasts a TDMA data stream to inform member nodes of the TDMA data stream to start a data acquisition process, the member nodes in the cluster send sensed data to the cluster head according to a TDMA time slot, and the cluster head CH collects data of the nodes in the cluster, then performs fusion and finally transmits the data to the base station; after the data transmission is finished, re-entering the cluster head selection work of the next round and re-selecting clusters; the working phase data acquisition is started after the cluster head sends a TDMA broadcast to the member nodes, the member nodes in the cluster send the acquired data to the respective cluster heads in the TDMA process, and the cluster heads integrate the data to reduce the noise in the signals after receiving all the data; the cluster head sends the integrated data to the base station in a single-hop or multi-hop mode, and then the network starts the process of circularly selecting the cluster head and clustering next time; when all nodes become over-cluster heads, the next cycle is started.
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