CN107371188B - Energy consumption balanced routing method capable of controlling cluster scale - Google Patents
Energy consumption balanced routing method capable of controlling cluster scale Download PDFInfo
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- H—ELECTRICITY
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- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
- H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
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- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/08—Load balancing or load distribution
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
- H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
A cluster-scale controllable energy consumption balanced routing method comprises the following steps: step 1, electing a cluster head through the residual energy of the cluster head candidate node, the Link Quality (LQI) between the cluster head candidate node and the cluster member node of the cluster head candidate node and the degree of the cluster head candidate node; step 2, adding common sensor nodes into a cluster head by using a virtual gravity method to form a cluster, and controlling the scale of the cluster; and 3, designing a cluster head next hop cost selection function to balance the energy consumption of cluster head nodes in the network, wherein the routing between the cluster heads adopts a link type routing protocol. The invention provides an energy balance routing protocol capable of controlling cluster scale, which fully considers load balance in cluster head election, cluster scale control and inter-cluster routing. Therefore, the method has important significance for the problem of node load imbalance which is the main difficulty of wireless sensor network routing research.
Description
Technical Field
The invention relates to a routing method of a wireless sensor network, in particular to an energy consumption balance routing method capable of controlling cluster scale.
Background
The Wireless Sensor Network (WSN) is a multi-hop self-organizing network formed by a large number of cheap micro sensor nodes deployed in a monitoring area in a wireless communication mode, has the main functions of data acquisition and monitoring, and is widely applied to various fields. Generally, the deployment area environment of the sensor network is complex, batteries of the sensor nodes are difficult to replace, the sensor nodes are easy to die under the condition of limited power supply of the nodes, and particularly, a large amount of data needs to be collected and forwarded by a large-scale sensor network. In the process of forwarding data, the load of some sensor nodes is too large, the energy consumption is too fast, and the wireless sensor network is dead early, so that the research on the routing protocol with balanced energy consumption is of great significance. At present, there are two main aspects of research on WSN routing protocols, one is a link-type routing protocol, and the other is a hierarchical routing protocol. But these protocols lack research on election of cluster heads, cluster size control, inter-cluster-head routing.
Disclosure of Invention
In order to overcome the defects of unbalanced node load and short network service life of the existing routing method of the wireless sensor network, the invention provides the energy consumption balanced routing method of controllable cluster scale, which fully considers load balance and prolongs the service life of the network.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a controllable cluster-scale energy consumption balancing routing method comprises the following steps:
step 1: and (3) electing a cluster head, wherein the process is as follows:
considering the residual energy of the cluster head candidate node, the link quality LQI between the cluster head candidate node and the cluster member nodes thereof, and the degree of the cluster head candidate node, cluster head election is performed, and a neighbor node table is established and stored for each sensor node, as shown in table 1:
| ID | Ej | RSSIij | LQIij |
TABLE 1
Where ID is the only representation of the neighbor node, EjAs residual energy of neighboring nodes, RSSIijIs the signal strength, LQI, between a node and its neighbor nodesijFor the link quality between the node and the neighboring node, the W value of each cluster head candidate node is calculated according to the related information in table 1, and as shown in formula (1), the W value comprehensively considers the remainder of the cluster head candidate nodesEnergy, link quality of a cluster head candidate node and cluster member nodes and cluster head candidate node degree, and when the W value of the cluster head candidate node is larger than the W values of other sensor nodes within the competition radius, the cluster head candidate node goes out of any cluster head;
in the formula (1), α, β and χ are constants and are set empirically, and α + β + χ is 1, EiResidual energy of candidate nodes as a cluster head, EjCompeting the residual energy of the point j in the radius for the cluster head candidate node i0Is the initial energy of the sensor node, LQIijThe link quality between the cluster head candidate node i and the neighbor node j within the competition radius is obtained. LQImaxIs a constant, i.e. the maximum value within the link quality range, DaThe average degree of the sensor network is D, and the degree of the cluster head candidate node is D;
step 2: the cluster scale control comprises the following processes:
step 2.1: selecting a cluster head, namely judging whether the candidate node is out of the cluster head or not in a range of taking the candidate cluster head node as the center of a circle and taking the competition radius as the radius;
the shortest hop count of the node from the Sink node is used for representing the distance between the node and the Sink node, and the shortest hop count of the sensor node can be obtained by a sensor network flood norm method; adopting signal strength as the competition radius, and when the signal strength between the node and the cluster head candidate node is greater than cr which is an RSSI value corresponding to the competition radius, considering that the node is positioned in the competition radius of the cluster head candidate node; cr is shown in equation (2):
in equation (2), RSSIrRepresenting the signal strength value, hop, at the node communication radius rminThe shortest hop count from the Sink node is represented, and h is a constant;
step 2.2: after the node i goes out of the head of the random cluster, the beacon frame is broadcasted to the surrounding sensor nodes,informing the neighbor nodes of the nodes; including the remaining energy E of the cluster head in the broadcasted beacon frameiAnd signal strength RSSI of cluster head to neighbor node jijThe same neighbor node j may receive beacon frames sent by multiple cluster heads, the gravitation F (i, j) of the node j and each neighbor cluster head is calculated according to information in the beacon frames, and finally the node j joins the cluster head with the largest gravitation, and the gravitation calculation is shown as a formula (3):
in the formula (3), Ej is the residual energy of the common node;
and step 3: the inter-cluster routing comprises the following steps:
step 3.1: amplifying the power of the cluster head node, regularly collecting data by the cluster member nodes, sending the data to the cluster head node through a one-hop route, fusing the data by the cluster head node, forwarding the data to the next-hop cluster head node, and finally transmitting the data to the Sink node; the cluster head node actively amplifies the transmitting power, and the communication radius R is adjusted to be R ═ gamma × R, wherein gamma is a constant and is larger than 1;
step 3.2: designing inter-cluster-head routing, wherein a link type routing protocol is adopted for inter-cluster-head routing, and a cluster-head next-hop cost selection function is designed, as shown in a formula (4):
in formula (4), ci is the cluster head node number that needs to send a data packet, cj is the cluster head node number adjacent to the cluster head ci, EcjIs the residual energy of the clusterhead cj, HcjThe shortest hop count H from the cluster head cj to the Sink nodemaxIs the maximum value of the shortest hop count of the cluster head node from the Sink node within the communication radius R of the cluster head ci, D is the degree of the cluster head ci, DaIs the network average degree;
when the cluster head node ci collects the data of the cluster member nodes, the cost of forwarding the data packet of the cluster head node cj adjacent to the cluster head node ci is calculated according to the cost selection function, and the cluster head with the minimum forwarding cost is selected as the next hop forwarding node.
The technical conception of the invention is as follows: the main difficulty of the existing wireless sensor network routing research is that the load of nodes is unbalanced, which easily causes the energy of some nodes to be exhausted in advance, so that the sensor network is dead early. Aiming at the difficulty, the invention provides an energy balance routing protocol (CCEBP) with controllable cluster size. Firstly, the remaining energy of the nodes, the link quality of the nodes and the neighbor nodes and the node degree are comprehensively considered, then the cluster head node is selected, the cluster head competition radius is controlled according to the shortest hop count of the nodes from the Sink node, the cluster scale is controlled, then the common nodes are clustered by utilizing a virtual force model, and finally the cluster head sends the collected data to the Sink node through a multi-hop route. The protocol fully considers load balance in cluster head election, cluster scale control and inter-cluster-head routing, so that the protocol has good energy consumption balance and has important significance for the problem of unbalanced node load of the main difficulty of wireless sensor network routing research.
The invention has the following beneficial effects: 1. the energy consumption balance routing protocol provided by the invention can be used for sensor nodes with unknown positions, so that the limitation is smaller; 2. the energy consumption balancing routing protocol provided by the invention fully considers the load balancing property, and has important significance for the problem of unbalanced node load which is the main difficulty of wireless sensor network routing research.
Drawings
Fig. 1 is a cluster head distribution diagram of the present invention.
FIG. 2 is a graph of the clustering results of the present invention.
Fig. 3 is a flow chart of a controllable cluster size energy consumption balancing routing method.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Referring to fig. 1 to 3, a cluster-scale controllable energy consumption balancing routing method includes the following steps:
step 1: electing a cluster head;
step 1.1: the significance of cluster head election is that the influence of the selection of the cluster head on a clustering routing protocol is great, and the network energy consumption can be well balanced and the network survival time can be prolonged by selecting a proper node to go out of the arbitrary cluster head. The task of the cluster head is to receive the message of the cluster member node and forward the message to the cluster head of the next hop, so the cluster head needs to consider the residual energy, and then the cluster member node can send a large amount of data packets to the cluster head node, so the Link Quality (LQI) between the cluster member node and the cluster head node is good. Finally, the communication radius needs to be enlarged for communication between the cluster head and the cluster head, and a larger amount of energy needs to be consumed when the cluster head becomes the cluster head, so that the cluster head degree (the number of sensor nodes in the competition radius of the cluster head candidate nodes) is not too small, otherwise, energy waste is caused.
Step 1.2: and (3) electing the cluster head by considering the residual energy of the cluster head candidate node, the Link Quality (LQI) between the cluster head candidate node and the cluster member node thereof and the degree of the cluster head candidate node. A neighbor node table is created and stored for each sensor node as shown in table 1.
Table 1 neighbor node table
| ID | Ej | RSSIij | LQIij |
ID in Table 1 is a unique representation of a neighbor node, EjAs residual energy of neighboring nodes, RSSIijIs the signal strength, LQI, between a node and its neighbor nodesijIs the link quality between the node and the neighboring node. Calculating the W value of each cluster head candidate node according to the related information in the table 1, wherein the W value comprehensively considers the rest of the cluster head candidate nodes as shown in the formula (1)The residual energy, the link quality of the cluster head candidate node and the cluster member nodes and the cluster head candidate node degree. And when the W value of the cluster head candidate node is larger than the W values of other sensor nodes within the competition radius, the cluster head candidate node goes out of the arbitrary cluster head.
α, β and χ in the formula (1) are constants which can be set according to experience, and α + β + χ is 1, EiResidual energy of candidate nodes as a cluster head, EjCompete for cluster head candidate node i within Radius (RSSI)ij>cr) residual energy of point j, E0Is the initial energy of the sensor node, LQIijThe link quality between the cluster head candidate node i and the neighbor node j within the competition radius is obtained. LQImaxIs a constant, i.e. the maximum value within the link quality range, DaAnd D is the average degree of the sensor network, and the degree of the cluster head candidate node.
800 sensor nodes are deployed in a rectangular area with the length of 500 and the width of 300, the communication radius r of the sensor nodes is 30, and the cluster head node selected according to the cluster head selection method is shown in fig. 1. From the graph, the closer to the Sink node, the higher the cluster head density, and the farther away from the Sink node, the lower the cluster head density.
Step 2: controlling the cluster scale;
step 2.1: and (3) cluster head competition radius, wherein the cluster head is selected by taking the candidate cluster head node as a circle center and judging whether the candidate node is out of the cluster head within the range taking the competition radius as the radius. The competition radius of the candidate cluster head nodes is related to the number of the finally selected cluster heads, and as the data packets collected by the sensor network are forwarded to the Sink nodes through the plurality of cluster heads, the cluster heads closer to the Sink nodes not only need to receive and forward the data packets of the cluster members of the cluster, but also need to forward a large number of data packets sent by the cluster head nodes farther away from the Sink nodes, and the energy consumed by the cluster head nodes farther away from the Sink nodes in the aspect of forwarding the data packets for other cluster head nodes is relatively less. In summary, the energy consumed by the cluster heads closer to the Sink node in the same round of data acquisition and forwarding process is far more than that consumed by the cluster heads farther from the Sink node, in order to balance the overall energy consumption of the sensor network, more sensor nodes should be selected to become the cluster heads in the area closer to the Sink node to share the load of the sensor network, and less cluster heads should be selected in the area farther from the Sink node.
The research of the invention aims at the sensor nodes with unknown positions, so that the shortest hop count of the nodes from the Sink node is used for representing the distance between the nodes and the Sink node, and the shortest hop count of the sensor nodes can be obtained by a sensor network flood norm method. And the competition radius of the invention does not adopt Euclidean distance, but adopts signal strength (RSSI <0), when the signal strength between the node and the cluster head candidate node is greater than cr (RSSI value corresponding to the competition radius), the node is considered to be positioned in the competition radius of the cluster head candidate node. The competition radius is shown in equation (2).
RSSI in equation (2)rRepresenting the signal strength value, hop, at the node communication radius rminRepresents the shortest hop count from the Sink node, and h is a constant. When the signal strength between the node and the cluster head candidate node is greater than cr, the node is considered to be located within the competition radius of the cluster head candidate node.
Step 2.2: and adding the common sensor nodes into the cluster head by using a virtual gravitation method to form a cluster. When the residual energy and the communication quality of the cluster head node are high, the cluster head node has the capacity of constructing a cluster with a large scale, and the cluster head with low residual energy constructs a cluster with a small scale, so that the energy consumption balance among the cluster heads is facilitated.
In the routing protocol, after a node i goes out of a head of a random cluster, a beacon frame is broadcasted to surrounding sensor nodes to inform the neighboring nodes of the beacon frame. Including the remaining energy E of the cluster head in the broadcasted beacon frameiAnd signal strength RSSI of cluster head to neighbor node jijThe same neighbor node j may receive beacon frames sent by a plurality of cluster heads according to the beacon framesThe gravitation F (i, j) of the node j and each neighbor cluster head of the node j is calculated, the cluster head with the largest gravitation is added to the node j, and the calculation of the gravitation is shown as a formula (3).
Ej in the formula is the residual energy of the common node.
The distance between nodes can be expressed in terms of signal strength, as signal strength RSSIijThe larger the absolute value of (3), the longer the distance between the node and the cluster head is, the more energy is consumed for communication, and the communication quality between the nodes is also influenced, so that when a common node is selected to join the cluster head, the cluster head relatively close to the node is selected, namely the signal strength RSSIijIs relatively large. When the rest energy E of the cluster head nodeiThe larger the gravity F (i, j) of the common nodes around the cluster is, the easier the cluster with larger scale is to be constructed, and the large-scale cluster enables the energy consumption of the cluster head to be faster and finally to be balanced with the residual energy of other cluster heads. And the cluster head with relatively less residual energy constructs a cluster with smaller scale, so that the energy consumption is reduced.
The final clustering result using this chapter of clustering method is shown in fig. 2. The general trend is that the closer to the Sink node the smaller the cluster size, the larger the cluster size away from the Sink node.
And step 3: routing between cluster heads;
step 3.1: amplifying the power of the cluster head node, regularly collecting data by the cluster member nodes, sending the data to the cluster head node through a one-hop route, fusing the data by the cluster head node, forwarding the data to the next-hop cluster head node, and finally transmitting the data to the Sink node. Because the distance between the cluster heads is large, in order to ensure the communication quality of the sensor network, the cluster head node actively amplifies the transmitting power, and the communication radius R is adjusted to be R ═ gamma multiplied by R, wherein gamma is a constant and is larger than 1. The routing protocol provided by the invention not only fully considers the energy consumption balance in the aspect of network clustering, but also needs to consider the energy consumption balance in the aspect of routing forwarding among cluster heads.
Step 3.2: the inter-cluster-head routing is designed, a link type routing protocol is adopted for the inter-cluster-head routing, and in order to balance the energy consumption of cluster head nodes in the network, a cluster head next hop cost selection function is designed, as shown in a formula (4):
ci in the formula (4) is the serial number of the cluster head node which needs to send the data packet, cj is the serial number of the cluster head node adjacent to the cluster head ci, EcjIs the residual energy of the clusterhead cj, HcjThe shortest hop count H from the cluster head cj to the Sink nodemaxIs the maximum value of the shortest hop count of the cluster head node from the Sink node within the communication radius R of the cluster head ci, D is the degree of the cluster head ci, DaIs the network average.
As can be seen from the formula (4), when the cluster head node ci collects the data of the cluster member nodes, the cost of forwarding the data packet by the adjacent cluster head node cj is calculated according to the cost selection function, and the cluster head with the minimum forwarding cost is selected as the next hop forwarding node. When the rest energy E of the cluster head nodecjAnd lower, the lower the probability of being selected as the next hop forwarding node. Shortest hop count H from Sink nodecjThe larger the cluster head node is, the lower the probability that the cluster head node is selected as a next hop transmitting node is, and when the cluster head degree is too large, it consumes a large amount of energy for intra-cluster communication, and thus the lower the probability that the cluster head node is selected as a next hop node is. Therefore, the cost selection function can well balance the communication energy consumption between the cluster heads.
Claims (1)
1. A controllable cluster-scale energy consumption balanced routing method is characterized in that: the routing method comprises the following steps:
step 1: and (3) electing a cluster head, wherein the process is as follows:
considering the residual energy of the cluster head candidate node, the link quality LQI between the cluster head candidate node and the cluster member nodes thereof, and the degree of the cluster head candidate node, cluster head election is performed, and a neighbor node table is established and stored for each sensor node, as shown in table 1:
TABLE 1
Where ID is the only representation of the neighbor node, EjIs the residual energy, RSSI, of the neighbor node jijIs the signal strength, LQI, between a node and its neighbor nodesijCalculating the W value of each cluster head candidate node according to the related information in the table 1 for the link quality between the node and the neighbor node, wherein the W value comprehensively considers the residual energy of the cluster head candidate node, the link quality of the cluster head candidate node and the cluster member nodes and the cluster head candidate node degree as shown in the formula (1), and when the W value of the cluster head candidate node is greater than the W values of other sensor nodes within the competition radius, the cluster head candidate node goes out of the cluster head;
in the formula (1), α, β and χ are constants and are set empirically, and α + β + χ is 1, EiResidual energy of candidate nodes as a cluster head, EjIs the residual energy of the neighbor node j, E0Is the initial energy of the sensor node, LQIijIs the link quality, LQI, between the cluster head candidate node i and the neighbor node j within the competition radiusmaxIs a constant, i.e. the maximum value within the link quality range, DaThe average degree of the sensor network is D, and the degree of the cluster head candidate node is D;
step 2: the cluster scale control comprises the following processes:
step 2.1: selecting a cluster head, namely judging whether the candidate node is out of the cluster head or not in a range of taking the candidate cluster head node as the center of a circle and taking the competition radius as the radius;
the shortest hop count of the node from the Sink node is used for representing the distance between the node and the Sink node, and the shortest hop count of the sensor node can be obtained by a sensor network flooding method; adopting signal strength as the competition radius, and when the signal strength between the node and the cluster head candidate node is greater than cr which is an RSSI value corresponding to the competition radius, considering that the node is positioned in the competition radius of the cluster head candidate node; cr is shown in equation (2):
in equation (2), RSSIrRepresenting the signal strength value, hop, at the node communication radius rminThe shortest hop count from the Sink node is represented, and h is a constant;
step 2.2: after the node i goes out of the head of the random cluster, a beacon frame is broadcasted to surrounding sensor nodes to inform the neighboring nodes of the beacon frame; including the remaining energy E of the cluster head in the broadcasted beacon frameiAnd signal strength RSSI of cluster head to neighbor node jijThe same neighbor node j may receive beacon frames sent by multiple cluster heads, the gravitation F (i, j) of the node j and each neighbor cluster head is calculated according to information in the beacon frames, and finally the node j joins the cluster head with the largest gravitation, and the gravitation calculation is shown as a formula (3):
in the formula (3), EjIs the residual energy of the neighbor node j;
and step 3: the inter-cluster routing comprises the following steps:
step 3.1: amplifying the power of the cluster head node, regularly collecting data by the cluster member nodes, sending the data to the cluster head node through a one-hop route, fusing the data by the cluster head node, forwarding the data to the next-hop cluster head node, and finally transmitting the data to the Sink node; the cluster head node actively amplifies the transmitting power, and the communication radius R is adjusted to be R ═ gamma × R, wherein gamma is a constant and is larger than 1;
step 3.2: designing inter-cluster-head routing, wherein a link type routing protocol is adopted for inter-cluster-head routing, and a cluster-head next-hop cost selection function is designed, as shown in a formula (4):
in formula (4), ci is the cluster head node number that needs to send a data packet, cj is the cluster head node number adjacent to the cluster head ci, EcjIs the residual energy of the clusterhead cj, HcjThe shortest hop count H from the cluster head cj to the Sink nodemaxIs the maximum value of the shortest hop count of the cluster head node within the communication radius R of the cluster head ci from the Sink node, D is the degree of the cluster head candidate node, DaIs the network average degree;
when the cluster head node ci collects the data of the cluster member nodes, the cost of forwarding the data packet of the cluster head node cj adjacent to the cluster head node ci is calculated according to the cost selection function, and the cluster head with the minimum forwarding cost is selected as the next hop forwarding node.
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