CN114007249B - Real-time routing method based on unbalanced tree for intelligent power distribution network - Google Patents
Real-time routing method based on unbalanced tree for intelligent power distribution network Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
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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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- 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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- 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
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Abstract
The invention discloses an unbalanced tree-based real-time routing method for an intelligent power distribution network, which relates to a real-time routing method. Through analysis, the selection speed of the cluster head nodes in the inter-cluster routing of an unbalanced tree is greatly improved, and the instantaneity of the routing protocol of the intelligent power distribution network is further improved.
Description
Technical Field
The invention relates to a real-time routing method, in particular to a real-time routing method based on an unbalanced tree for an intelligent power distribution network.
Background
The real-time transmission efficiency of data in the intelligent power distribution network is improved, and the real-time performance of a routing method is required to be improved. The invention provides a real-time routing method based on an unbalanced tree based on a ZigBee routing method. The basic idea of the routing method is that the area is divided by using the GAF geographic protocol, then the cluster heads are selected by using the mixed cluster head election method, and analysis discovers that the selection speed of cluster head nodes in the inter-cluster routing based on an unbalanced tree is greatly improved, and the ZigBee technology is a short-distance and low-power consumption wireless communication technology in the wireless sensor network. The real-time routing method based on the unbalanced tree is provided on the basis of the ZigBee routing method, and the real-time performance of the real-time routing method is further improved.
Disclosure of Invention
The invention aims to provide an unbalanced tree-based real-time routing method for an intelligent power distribution network.
The invention aims at realizing the following technical scheme:
an unbalanced tree-based real-time routing method for an intelligent power distribution network, which comprises the following steps:
1. network monitoring area division
The first step of the routing method is to divide the area into virtual cells (53) with a side length of a by using the idea of GAF protocol, all nodes in each cell form a cluster, the cells are not overlapped with each other, and only the nodes in adjacent cells can communicate with each other; the geographical position information of each node is obtained by setting partial nodes of the wireless sensor network as anchor nodes; then, by means of the GPS module, all surrounding nodes can acquire the position information of all nodes by using the current latest positioning method;
2. cluster head selection
After the area is divided, the number of nodes in each cell is different, and a mixed cluster head election method is adopted when the cluster heads are elected because the number of the nodes is considered;
3. inter-cluster routing
In the inter-cluster routing, cluster head nodes are connected to the left side as much as possible, so that the number of the cluster head nodes on the right side is sparse, and the cluster head nodes are more likely to be connected to the left side by an unbalanced tree, so that the method is fixed, and the connection mode of the inter-cluster routing is unique; an unbalanced tree method in data transmission is employed.
The intelligent distribution network-oriented real-time routing method based on the unbalanced tree has the advantages that in the inter-cluster routing, the importance of one cluster head node has a direct relation with the number of cluster head nodes connected with the cluster head node; this relationship of nodes is called degree; the greater the degree of a cluster head node, the more important the cluster head node is in routing.
The method comprises the steps of firstly placing root nodes into a 0 th layer before starting circulation, selecting leaf cluster head nodes of the zeroth layer, wherein the larger the degree of one cluster head node is, the larger the effect of the leaf cluster head node on a spanning tree is, so that the cluster head nodes are arranged according to the sum of the degrees of sub cluster head nodes of the leaf cluster head nodes of the first layer, the minimum degree of the left cluster head node and the maximum degree of the right cluster head node are sequentially arranged, and the cluster head nodes become child cluster head nodes after the arrangement; and finally, the child cluster head nodes can be calculated by putting the child cluster head nodes into L (m), and the child nodes under each child cluster head node are sequentially arranged in the descending order until the inter-cluster routing connection is completed.
The invention has the advantages and positive effects that:
the invention provides a real-time routing method based on an unbalanced tree based on a ZigBee routing method, and the ZigBee technology is a short-distance and low-power-consumption wireless communication technology in a wireless sensor network. The basic idea of the method is that the areas are divided by using the GAF geographic protocol, then the cluster heads are selected by using the mixed cluster head election method, and the analysis finds that an unbalanced tree has great improvement on the selection speed of the cluster head nodes in the inter-cluster routing, thereby improving the real-time performance of the routing protocol of the intelligent distribution network.
Detailed Description
The present invention will be described in detail with reference to examples.
The invention comprises the following steps:
1. network monitoring area division
The first step of the routing method is to divide the area into virtual cells (53) with a side length of a by using the idea of the GAF protocol, all nodes in each cell form a cluster, the cells are not overlapped, and only the nodes in adjacent cells can communicate with each other.
The geographical location information of each node may then be obtained by setting a part of the nodes of the wireless sensor network as anchor nodes. Then by means of the GPS module, all surrounding nodes can acquire the position information of all nodes by using the latest positioning method.
Furthermore, due to the above region division, the formula is necessary:
(1)
(2)
wherein a is the side length of the virtual square unit cell, and r is the communication radius of the nodes in the network monitoring area, so that adjacent nodes can communicate with each other after division.
Therefore, the formula (1) ensures that the wireless communication distance between two adjacent cells is larger than the distance between all the nodes of the two adjacent cells, and when the cluster head node is replaced by other nodes in the same cell, the connectivity of the network can be ensured in the communication process.
2. Cluster head selection
After the area is divided, the number of nodes in each cell is different, and a mixed cluster head election method is adopted in the cluster head election because of the consideration of the number of the selected nodes.
The centroid of the cluster is calculated by:
（3）
（4）
（5）
in the node point of the network, the node point,for its remaining energy,/>For it->Axis coordinates->For it->Axis coordinates->For it->Axis coordinates->Is the number of nodes in the cluster.
Assume that data volume transmission in real-time routing method isThe transmission distance between the nodes is +.>The energy lost by the node at transmission can be determined by equation (3-6).
（6）
The energy consumed by the nodes in the routing protocol in receiving the data is known from equation (7).
（7）
The circuit power consumption of the device for transmitting and receiving depends on various conditions such as a filter, and it is known from researches that the value is preferably 50 nJ/bit. />Is determined by the spacing between the two points and the bit error rate at reception,as in the former, for ease of calculation, < > for convenience of calculation>The value is 10 p J/bit/m2,/L>The value of 0.0013 p J/bit/m4 is selected. Threshold->Can be obtained by (8).
（8）
Wherein,is the antenna length of the transmitting device, < >>Is the wavelength of the signal, ">Is the antenna length of the receiving device.
2. Inter-cluster routing
In inter-cluster routing, the importance of a cluster head node has a direct relationship with the number of cluster head nodes to which it is connected. This relationship of nodes is called degree. The greater the degree of a cluster head node, the more important the cluster head node is in routing. If the cluster head nodes are connected to the left side as much as possible, so that the number of the cluster head nodes on the right side is sparse, and the cluster head nodes are more likely to be connected to the left side by using an unbalanced tree, the method can be fixed, and the connection mode of the routing among clusters is unique.
The maximum independent set is selected by the current method, and the shortest path method is abandoned, so that the most common shortest path method in the inter-cluster routing is adopted, and an unbalanced tree method in data transmission is adopted due to the fact that the shortest path method is easy to generate node confusion, high in time delay and low in fault tolerance rate, and the maximum independent set method is poor in adaptability in a complex sensor network environment due to the fact that the number of nodes is large.
TABLE 1 definition of spanning tree construction method variables
1) Input： G(M,R)
2) Output：T(M,d)
3) L(m) ← ,T(M,d)← ;
4) layer=0,d.layer=layer;
5) L(m) ←d;
6) T(M,d) ←d;
7) M=M-d;
8) for L(m)≠M
9) layer++;
10) (N(m)\Lm)).layer=layer;
11) St ←sorted with ASC according the sum of children node;
12)L(m) ←St；
13) T(M,d) ←St;
14)end for。
Before the method starts to circulate, firstly placing the root node into the 0 th layer, selecting the leaf cluster head node of the zeroth layer, and the larger the degree of one cluster head node is, the larger the effect of the cluster head node on the spanning tree is, so that the cluster head nodes are arranged according to the sum of the degrees of the sub cluster head nodes of the leaf cluster head nodes of the first layer, the minimum degree of the left cluster head node, the maximum degree of the right cluster head node are sequentially arranged, and after the arrangement, the cluster head nodes become child cluster head nodes. And finally, the child cluster head nodes can be calculated by putting the child cluster head nodes into L (m), and the child nodes under each child cluster head node are sequentially arranged in the descending order until the inter-cluster routing connection is completed. In theory, the greedy method can generate an uncertain error condition of the selected nodes, and the shortest path method is adopted for the inter-cluster routing, so that although the early real-time performance is good, the time delay is low, as the data flow is continuously increased, the cluster head nodes can be interfered by the adjacent cluster head nodes during the selection, the condition of node transmission errors can be generated, the node selection is disordered, the average delay is continuously increased, and the time delay fluctuation is also large.
Claims (1)
1. An unbalanced tree-based real-time routing method for an intelligent power distribution network is characterized by comprising the following steps of:
(1) Network monitoring area division
Dividing the area into virtual cells with a side length of a by using a geographic position routing protocol GAF, wherein all nodes in each cell form a cluster, the cells are not overlapped, and only the nodes in adjacent cells can communicate with each other; the geographical position information of each node is obtained by setting partial nodes in the network as anchor nodes;
(2) Cluster head selection
After the areas are divided, the number of nodes in each cell is different; adopting a mixed cluster head election method when the cluster head is elected;
(3) Inter-cluster routing:
adopting a routing method based on an unbalanced tree to connect cluster head nodes to the left as much as possible, so that the number of the cluster head nodes on the right is sparse, and the connection mode of the inter-cluster routing is unique; the importance of a cluster head node has a direct relationship with the number of cluster head nodes connected to the cluster head node, and the relationship of the nodes is called degree; the greater the degree of a cluster head node, the more important the cluster head node is in routing;
before starting circulation, firstly placing a root node into a zeroth layer, selecting leaf cluster head nodes of the zeroth layer, arranging according to the sum of the degrees of sub cluster head nodes of the leaf cluster head nodes of the first layer, wherein the degree of a left cluster head node is minimum, the degree of a right cluster head node is maximum, and after the cluster head nodes are orderly arranged, forming child cluster head nodes; finally, putting child cluster head nodes into L (m), calculating child nodes under each child cluster head node, and arranging the child nodes in sequence from small to large until the inter-cluster routing connection is completed; where L (m) represents the set of leaf nodes for each traversal.
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