CN111683377A - Real-time reliable relay deployment method for power distribution network - Google Patents

Real-time reliable relay deployment method for power distribution network Download PDF

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CN111683377A
CN111683377A CN202010506714.5A CN202010506714A CN111683377A CN 111683377 A CN111683377 A CN 111683377A CN 202010506714 A CN202010506714 A CN 202010506714A CN 111683377 A CN111683377 A CN 111683377A
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communication node
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CN111683377B (en
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郭夫然
张清峰
宋文卓
马超凡
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State Grid Corp of China SGCC
Economic and Technological Research Institute of State Grid Henan Electric Power Co Ltd
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State Grid Corp of China SGCC
Economic and Technological Research Institute of State Grid Henan Electric Power Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22—Traffic simulation tools or models
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • 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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
    • H04W88/02—Terminal devices
    • H04W88/04—Terminal devices adapted for relaying to or from another terminal or user

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Abstract

A real-time reliable relay deployment method facing to a power distribution network is characterized in that communication radiuses of deployment positions are re-estimated according to measured channel quality, a communication topological graph is re-constructed for guiding deployment, a deployment position meeting real-time requirements is selected each time for attempted deployment, and the method for estimating the communication radiuses of the deployment positions comprises a communication node classifying step; the communication nodes capable of measuring the packet receiving rate are obtained through the correlation relationship between the path loss factor and the signal to noise ratio; the communication radius of the communication node which can not measure the packet receiving rate is equal to the communication radius of the communication node which is nearest to the communication node and can measure the packet receiving rate. Therefore, the defect of poor accuracy of the traditional offline deployment method is effectively overcome, and the network reliability is ensured.

Description

Real-time reliable relay deployment method for power distribution network
Technical Field
The invention relates to a wireless communication network construction method, in particular to a real-time reliable relay deployment method for a power distribution network.
Background
Wireless sensor networks have been widely adopted in various applications, and generally comprise large-scale wireless sensor nodes and a small number of sink nodes, and communicate by means of single/multi-hop paths. Due to the limitations of communication, calculation, energy consumption and the like, a network formed by only sensor nodes has many defects, such as unbalanced energy consumption, short service life of the network, short communication distance, poor expandability and the like. Therefore, scholars at home and abroad advocate to build a connected topological structure for the whole network by deploying additional relay nodes so as to enhance the network performance. The deployment of the relay node directly constructs network topology connectivity, and the performance of each layer of protocol of the wireless sensor network is deeply influenced, so that the relay node is widely and deeply researched.
Wireless sensor networks are being applied to a variety of industrial scenarios with their advantages of low cost, ease of installation, and ease of maintenance. The power distribution network detection is an important application scene of a wireless sensor network in the industrial field, and the main purpose of the power distribution network detection is to realize functions of real-time monitoring, fault prediction and the like for power distribution network lines and equipment. The coverage area of the power distribution network is large, so that the terrain of the area where the power distribution network is located is complex, if the traditional wired communication system is adopted, the network deployment cost is greatly increased, and even the communication network is difficult to deploy in severe cases. The wireless sensor network does not need to lay lines, so that the wireless sensor network can be well adapted to various complex environments of a power distribution network, and the network deployment cost is effectively reduced.
However, the distribution network deployment site terrain is complex, and especially various switching stations in the distribution network have the characteristics of severe radio frequency environment, serious metal shielding and the like, so that low-power-consumption lossy channels in the distribution network have high dynamics and uncertainty, and the off-line static channel model loses use value. Therefore, the static channel model cannot be used to accurately obtain the channel quality between any two points in the deployment area in advance. In addition, the coverage area of the power distribution network is large, and channel quality detection cannot be performed on all positions in the deployment area, so that global channel information is lost. Unfortunately, the basic assumption of research is that the global channel quality information is known and accurate prior to relay deployment. This means that the existing research results and experience are no longer applicable to wireless sensor networks oriented to power distribution networks.
Disclosure of Invention
The first object of the present invention is to provide a method for estimating a communication radius of a communication node in a communication network, so as to solve the technical problem that the communication radius of the communication node in a specific application situation is not easy to obtain due to physical barrier effect.
The second purpose of the present invention is to provide a real-time reliable relay deployment method for a power distribution network, so as to solve the technical problem that effective relay nodes are not easily added in a wireless communication network due to physical barrier.
The third invention aims to provide a real-time reliable relay deployment method for a power distribution network, so as to solve the technical problem that a wireless communication network which can meet communication requirements is not easy to rapidly deploy due to physical barrier influence.
In order to solve the technical problems, the following technical scheme can be selected according to the needs:
a method for estimating communication radius of a communication node in a communication network is provided, the communication node is composed of gateway nodes, sensor nodes and candidate nodes, the positions for deploying the communication node comprise gateway node deployment positions, n sensor node deployment positions and m candidate node deployment positions, the set of gateway nodes is { g }, the set of sensor nodes is S = S { (S })1,s2,…,snThe candidate node set is C = C1,c2,…,cmThe method comprises the following steps:
step 1, acquiring an initial communication radius r of the communication node, a sensor node hop count constraint and a channel quality constraint theta; all communication nodes capable of measuring packet receiving rate form set
Figure BDA0002526787850000021
All communication nodes incapable of measuring packet receiving rate form set
Figure BDA0002526787850000022
Step 2, obtaining the communication radius corresponding to the communication node capable of measuring the packet receiving rate, comprising the following sub-steps,
step 2a, collecting the collection
Figure BDA0002526787850000023
One communication node in the communication network is marked as communication node u, and a maximum communication radius set corresponding to the communication node u is generated
Figure BDA0002526787850000024
Step 2b, collecting the collection
Figure BDA0002526787850000025
Recording the other communication node as a communication node v, and obtaining a path loss factor a between the communication node u and the communication node v according to the actually measured packet receiving rate Ψ (u, v) between the communication node u and the communication node v, the position information of the communication node u and the position information of the communication node v;
calculating the minimum signal-to-noise ratio
Figure BDA0002526787850000026
Where ρ is the data rate, BNFor noise bandwidth, l is datagram length, function Q-1(x) Is the inverse of function q (x), θ is the channel quality constraint;
calculating the maximum communication radius of the communication node u after passing through the communication node v
Figure BDA0002526787850000027
Where P is the transmit power, PL is the reference range average path loss, PnIn order to be the basis of the noise,d0as a reference distance, γmin(u, v) is the minimum signal-to-noise ratio between the communication node u and the communication node v, and a is the path loss factor between the communication node u and the communication node v;
updating Ru＝Ru∪{dmax(u,v)}；
Substep 2c, repeatedly executing substep 2b to obtain communication node u and set
Figure BDA0002526787850000031
Set of maximum communication radii R between all other communication nodes within the clusteruThen the communication radius r of the communication node uu＝min Ru；
Step 3, repeatedly executing the step 2 to obtain a set
Figure BDA0002526787850000032
Any element corresponding communication node
Figure BDA0002526787850000033
A communication radius of (a);
step 4, assembling
Figure BDA0002526787850000034
Any element corresponding communication node
Figure BDA0002526787850000035
Is set as the communication node
Figure BDA0002526787850000036
Set of distances
Figure BDA0002526787850000037
The communication radius corresponding to the nearest communication node.
Preferably, in said step 2, according to sets
Figure BDA0002526787850000038
And communication node u, and a measured packet reception rate Ψ (u, v) between communication node u and communication node vThe method for obtaining the path loss factor a between the communication node u and the communication node v comprises the following steps:
signal-to-noise ratio between communication node u and communication node v
Figure BDA0002526787850000039
Where ρ is the data rate, BNFor noise bandwidth, l is datagram length, function Q-1(x) Is the inverse of function q (x);
pathloss factor between communication node u and communication node v
Figure BDA00025267878500000310
Where P is the transmit power, PL is the reference range average path loss, PnD is the distance between communication node u and communication node v, d is the noise floor0Is a reference distance.
A real-time reliable relay deployment method facing a power distribution network is characterized in that a communication node is composed of gateway nodes, sensor nodes and candidate nodes, the positions for deploying the communication node comprise gateway node deployment positions, n sensor node deployment positions and m candidate node deployment positions, the set of the gateway nodes is { g }, and the set of the sensor nodes is S = S { (S) }1,s2,…,snThe candidate node set is C = C1,c2,…,cm}; the method is characterized by comprising the following steps:
step A, setting a deployed communication node of an upper wheel as w, recording the parent node of the communication node w as p (w), setting the hop count from a gateway node to the deployed communication node w as kappa (w), setting a deployed relay node set as R, and recording a reduction point A; estimating the communication radius of all communication nodes by using the method for estimating the communication radius of the communication nodes in the communication network, and constructing a communication topological graph G (V, E), wherein V is a communication node set, and E is an edge set;
step B, updating the upper first wheel deployment communication nodes w to deploy the relay nodes, and constructing all neighbor communication nodes of the upper first wheel deployment communication nodes w in the communication topological graph G to form a set NG(w), actually measuring the communication nodes w and the set N arranged in the previous wheel one by oneG(w) ∩ S, setting the channel quality constraint as theta, and taking the sensor nodes with the packet receiving rate psi (S, w) being greater than or equal to theta with the last wheel deployment communication node as the first sensor nodes, deleting the first sensor nodes from the set S and updating the set S;
traversing set omega is NGEach communication node u in (w) \ (R ∪ S) to obtain a set y (u) of sensor nodes to which each communication node u can operatively connect
{Υ(u)|s∈S,h(pG(s,u))+κ(w)+1≤} (5)
In the formula, pG(s, u) represents the shortest path from the sensor node s to the communication node u in the communication topology G;
recording a reduction point B;
step C, if
Figure BDA0002526787850000041
Or any communication node u in the set omega can be effectively connected with the sensor node set
Figure BDA0002526787850000042
Reducing to a reduction point A and executing the step B again; if it is
Figure BDA0002526787850000043
And all communication nodes u in the set omega can be effectively connected with the sensor node set
Figure BDA0002526787850000044
The weight of each non-empty communication node u in the weighted y (u) is
Figure BDA0002526787850000045
In the formula, TG(u, γ (u)) means communication topologyA shortest path tree from the communication node u to all sensor nodes in y (u) corresponding to the communication node u in the flapping graph G, wherein | x represents the number of the communication nodes on the path tree x;
in the weights ω (u) corresponding to all the communication nodes in the set Ω, setting the communication node with the smallest weight ω (u) to correspond to the deployment position of the relay node t, actually measuring Ψ (t, w) between the relay node t and the last wheel deployment communication node w, and re-estimating the communication radii of all the communication nodes by using the method for estimating the communication radii of the communication nodes in the communication network;
if Ψ (t, w) ≧ θ, a new relay node t is successfully deployed in the communication network, and w = t, p (t) = w, k (t) = k (w) +1, R = R { (t }; if Ψ (t, w) < θ, Ω \ t }, and reverts to the reduction point B, and step C is performed anew.
Preferably, in the step a, if the last-wheel deployment communication node w is the gateway node g, the first-wheel deployment communication node w is a gateway node g
Figure BDA0002526787850000051
p(w)＝-1，κ(w)＝0。
Preferably, in the step a, the method for constructing the edge element in the edge set E includes the following steps: traversing any two communication nodes u and V in the communication node set V, if | | | u-V | | | < min (r | |)v,ru) If the communication node u is located in the communication topology G, then there is an edge connecting two points of the communication node u and the communication node v, where | | u-v | | is the distance between the communication node u and the communication node v, and ruIs the communication radius of the communication node u, rvIs the communication radius of the communication node v.
Preferably, the method further comprises a step D provided after the step C, wherein the step D comprises: in the collection
Figure BDA0002526787850000052
And repeatedly executing the processes from the step B to the step C until the set is obtained after one relay node is deployed successfully each time
Figure BDA0002526787850000053
The method is provided under the condition that the characteristics of complex terrain, serious radio frequency interference and the like in the coverage area of the power distribution network are fully considered, and the requirements of the power distribution network on deployment cost, network reliability, instantaneity and the like are met.
Compared with the prior art, the invention has the beneficial effects that:
(1) the method for estimating the communication radius of the communication node in the communication network can estimate the communication radius of all the deployment positions in the deployment area again according to the measured channel quality during deployment, and is used for guiding the deployment process. The online real-time channel estimation method can effectively avoid the defects of poor channel quality prediction accuracy and incapability of ensuring network reliability caused by the adoption of an offline static model in the conventional deployment method.
(2) The real-time reliable relay deployment method for the power distribution network is different from an online relay deployment method of an existing offline deployment strategy, and the method utilizes the communication radius estimation method to re-estimate the deployment position communication radius according to the measured channel quality after each wheel is deployed, and re-constructs a communication topological graph for guiding deployment, so that the defect of poor accuracy of the traditional offline deployment method is effectively overcome, and the reliability of the network is ensured. On the other hand, the method adopts a depth-first deployment strategy, and selects a deployment position meeting the real-time requirement each time to try deployment so as to meet the real-time requirement of the power distribution network. In addition, the depth-first strategy facilitates field deployment implementation.
Drawings
Fig. 1 is a flow chart of a method of estimating a communication radius of a communication node in a communication network according to the present invention.
Fig. 2 is a flowchart of a real-time reliable relay deployment method for a power distribution network according to the present invention.
Fig. 3 is a flowchart of a method for deploying relay nodes in a power distribution network-oriented real-time reliable relay deployment method according to the present invention.
Fig. 4 is a schematic diagram illustrating an estimation method for estimating a communication radius of a communication node in a communication network according to the present invention.
Fig. 5 is a schematic diagram of asymptotic deployment of a power distribution network-oriented real-time reliable relay deployment method according to the present invention.
Fig. 6 is a schematic diagram of asymptotic deployment of a real-time reliable relay deployment method for a power distribution network according to the present invention.
Fig. 7 is a schematic diagram of asymptotic deployment of a real-time reliable relay deployment method for a power distribution network according to the present invention.
Fig. 8 is a schematic diagram of asymptotic deployment of the real-time reliable relay deployment method for the power distribution network according to the present invention.
Fig. 9 is a schematic diagram of asymptotic deployment of the real-time reliable relay deployment method for the power distribution network according to the present invention.
Fig. 10 is a schematic diagram six of asymptotic deployment of the real-time reliable relay deployment method for the power distribution network according to the present invention.
Fig. 11 is a schematic diagram seven of asymptotic deployment of the real-time reliable relay deployment method for the power distribution network according to the present invention.
Fig. 12 is an asymptotic deployment schematic diagram eight of the real-time reliable relay deployment method for the power distribution network according to the present invention.
Fig. 13 is a schematic diagram of a deployment process of a real-time reliable relay deployment method for a power distribution network according to the present invention.
Detailed Description
The present invention is described below in terms of embodiments in conjunction with the accompanying drawings to assist those skilled in the art in understanding and implementing the present invention. Unless otherwise indicated, the following embodiments and technical terms therein should not be understood to depart from the background of the technical knowledge in the technical field.
The expression in the present invention is defined as follows:
the algebraic expression { A } \ { B } represents the deletion of all elements contained in the set { B } in the set { A } and the updating of the set { A }.
The equation x +1 indicates that x is updated after x +1, that is, x on the left side of the equation is updated x, and x on the right side of the equation is x before update, which is similar to pointer update in a computer program.
The equation a = u ∪ B indicates that the original set a is updated after union operation with the set B, that is, the set a on the left side of the equation is updated, and the set a on the right side of the equation is set a before update, which is similar to pointer update in a computer program.
First part of the invention
Referring to fig. 1, the communication node is composed of gateway nodes, sensor nodes and candidate nodes, the positions for deploying the communication node include gateway node deployment positions, n sensor node deployment positions and m candidate node deployment positions, the gateway node set is { g }, and the sensor node set is S = S }, where1,s2,…,snThe candidate node set is C = C1,c2,…,cmThe method comprises the following steps:
step 1, acquiring an initial communication radius r of the communication node, a sensor node hop count constraint and a channel quality constraint theta; the hop constraint is used for controlling the time delay and the reliability from the sensor node to the gateway node; all communication nodes capable of measuring packet receiving rate form set
Figure BDA0002526787850000071
All communication nodes incapable of measuring packet receiving rate form set
Figure BDA0002526787850000072
Step 2, obtaining the communication radius corresponding to the communication node capable of measuring the packet receiving rate, comprising the following sub-steps,
step 2a, collecting the collection
Figure BDA0002526787850000073
One communication node in the communication network is marked as communication node u, and a maximum communication radius set corresponding to the communication node u is generated
Figure BDA0002526787850000074
Step 2b, collecting the collection
Figure BDA0002526787850000075
And the other communication node, which is marked as the communication node v, obtains a path loss factor a between the communication node u and the communication node v according to the measured packet receiving rate Ψ (u, v) between the communication node u and the communication node v, the location information of the communication node u, and the location information of the communication node v, and specifically as follows:
signal-to-noise ratio between communication node u and communication node v
Figure BDA0002526787850000081
Where ρ is the data rate, BNFor noise bandwidth,. l.is the datagram length (in bits), function Q-1(x) Is the inverse of function q (x);
pathloss factor between communication node u and communication node v
Figure BDA0002526787850000082
Where P is the transmit power, PL is the reference range average path loss, PnD is the distance between communication node u and communication node v, d is the noise floor0Is a reference distance;
calculating the minimum signal-to-noise ratio gamma according to the following formulamin(u,v)
Figure BDA0002526787850000083
Where ρ is the data rate, BNFor noise bandwidth, l is datagram length, function Q-1(x) Is the inverse of function q (x), θ is the channel quality constraint;
calculating the maximum communication radius of the communication node u after passing through the communication node v
Figure BDA0002526787850000084
Where P is the transmit power, PL is the reference range average path loss, PnBeing a noise floor, d0Is a reference distance;
updating Ru＝Ru∪{dmax(u,v)}；
Substep 2c, repeating substep 2b to obtain a set
Figure BDA0002526787850000085
Intra-communication node u and set
Figure BDA0002526787850000086
Set of maximum communication radii R between all other communication nodes within the clusteruThen the communication radius r of the communication node uu＝min Ru；
Step 3, repeatedly executing the step 2 to obtain a set
Figure BDA0002526787850000091
Any element corresponding communication node
Figure BDA0002526787850000092
A communication radius of (a);
step 4, assembling
Figure BDA0002526787850000093
Any element corresponding communication node
Figure BDA0002526787850000094
Is set as the communication node
Figure BDA0002526787850000095
Set of distances
Figure BDA0002526787850000096
The communication radius corresponding to the nearest communication node.
It should be understood that the two-dot chain line box in fig. 1 corresponds to step 2.
It should be understood that the candidate node deployment location may be deployed with a communication device or may be in a reserved state without a communication device deployed. All communication nodes corresponding to the deployment positions where the communication equipment is deployed can measure the packet receiving rate, and the communication nodes form a set
Figure BDA0002526787850000097
All communication nodes corresponding to the deployment positions of the undeployed communication equipment cannot measure the packet receiving rate, and the communication nodes form a set
Figure BDA0002526787850000098
Example 1: fig. 4 is a diagram illustrating a communication distance estimation of a logarithmic distance path loss model. The packet receiving rates among the communication nodes tested in the graph are psi (c)4,c13)＝0.93，Ψ(c12,c13)＝0.76，Ψ(c15,c13)＝0.87，Ψ(c11,c16)＝0.95，Ψ(c11,s2)＝0.96，Ψ(c11,c10)＝0.91，Ψ(c11,c9)＝0.78，Ψ(c6,c7) 0.76. Inputting transmission power p, reference distance average path loss PL and reference distance d at user0Noise floor PnNoise bandwidth BNAfter parameters such as data rate rho and datagram length lbit, the maximum communication radius d along each measured direction can be calculated according to equations (9) - (12)max(c4,c13)，dmax(c12,c13)，dmax(c15,c13)，dmax(c11,c16)，dmax(c11,s2)，dmax(c11,c10)，dmax(c11,c9)，dmax(c6,c7). Thereafter, the maximum communication radius of all communication nodes can be estimated based on these measured values. E.g. to estimate c13Due to the communication radius of c13For a tested communication node, firstFirst, find out the maximum estimated radius d of all the measured directionsmax(c4,c13)，dmax(c12,c13)，dmax(c15,c13) It can be seen that dmax(c12,c13) Is a minimum value, so c13Has a communication radius of dmax(c12,c13). And for example to estimate c2Radius of communication, because of c2For a communication node to be tested, first the distance c is found2The nearest measured communication node, known as c6. Then calculate c6Radius of communication, c6Testing only one direction, i.e. Ψ (c)6,c7) D can be calculated from the values of equations (9) to (12) as 0.76max(c6,c7) Thus c is6And (4) calculating the radius. From step 2, c2Communication radius dmax(c6,c7)。
Second part of the invention
Referring to fig. 3, the communication node is composed of a gateway node, sensor nodes and candidate nodes, the positions for deploying the communication node include a gateway node deployment position, n sensor node deployment positions and m candidate node deployment positions, the gateway node set is { g }, and the sensor node set is S = S { (S) }1,s2,…,snThe candidate node set is C = C1,c2,…,cmThe method comprises the following steps:
step A, setting a deployed communication node of an upper wheel as w, recording the parent node of the communication node w as p (w), setting the hop count from a gateway node to the deployed communication node w as kappa (w), setting a deployed relay node set as R, and recording a reduction point A; generally, a gateway node g is deployed at a gateway node deployment position, and a relay node is deployed at a candidate node deployment position;
estimating communication radii of all communication nodes by using the method for estimating the communication radii of the communication nodes in the communication network disclosed in the first part of the invention, and constructing a communication topological graph G as (V, E), wherein V is a communication node set, and E is an edge set;
the construction method of the edge is as follows: traversing any two communication nodes u and V in the communication node set V, if | | | u-V | | | < min (r | |)v,ru) If the communication node u is located in the communication topology G, then there is an edge connecting two points of the communication node u and the communication node v, where | | u-v | | is the distance between the communication node u and the communication node v, and ruIs the communication radius of the communication node u, rvIs the communication radius of the communication node v.
Step B, updating the communication nodes w deployed in the first wheel to deploy the relay nodes, generally deploying the relay nodes in the candidate node deployment positions, and constructing a set N formed by all neighbor communication nodes of the communication nodes w deployed in the first wheel in the communication topological graph GG(w), actually measuring the communication nodes w and the set N arranged in the previous wheel one by oneG(w) ∩ S, setting the channel quality constraint as theta, and taking the sensor nodes with the packet receiving rate psi (S, w) being greater than or equal to theta with the last wheel deployment communication node as the first sensor nodes, deleting the first sensor nodes from the set S and updating the set S;
traversing set omega is NGEach communication node u in (w) \ (R ∪ S) to obtain a set y (u) of sensor nodes to which each communication node u can operatively connect
{Υ(u)|s∈S,h(pG(s,u))+κ(w)+1≤} (13)
In the formula, pG(s, u) represents the shortest path from the sensor node s to the communication node u in the communication topology G;
recording a reduction point B;
step C, if
Figure BDA0002526787850000101
Or any communication node u in the set omega can be effectively connected with the sensor node set
Figure BDA0002526787850000102
Reducing to a reduction point A and executing the step B again; if it is
Figure BDA0002526787850000103
And all communication nodes u in the set omega can be effectively connected with the sensor node set
Figure BDA0002526787850000111
The weight of each non-empty communication node u in the weighted y (u) is
Figure BDA0002526787850000112
In the formula, TG(u, y (u)) represents the shortest path tree from communication node u to all sensor nodes in y (u) corresponding to communication node u in the communication topology map G, | x | represents the number of communication nodes on path tree x;
in the weights ω (u) corresponding to all the communication nodes in the set Ω, setting the communication node with the smallest weight ω (u) to correspond to the deployment position t, actually measuring Ψ (t, w) between the deployment position t and the last wheel deployment communication node w, and re-estimating the communication radii of all the communication nodes by using the method for estimating the communication radii of the communication nodes in the communication network disclosed in the first part of the invention;
if Ψ (t, w) ≧ θ, a new relay node t is successfully deployed in the communication network, where w = t, p (t) = w, k (t) = κ (w) +1, R = R { (t }; if Ψ (t, w) < θ, Ω \ t }, and reverts to the reduction point B, and step C is performed anew.
It should be understood that, in fig. 3, the first wheel deployment communication node w in step a may be a gateway node or a relay node. The two-dot chain line block in fig. 3 corresponds to step C. If the communication node w deployed in the first wheel in the step A is the gateway node g, the communication node is the gateway node g
Figure BDA0002526787850000113
p(w)＝-1，κ(w)＝0。
Third part of the invention
According to the real-time reliable relay deployment method facing the power distribution network, disclosed by the invention, referring to fig. 2-3, the communication node is composed of a gateway node, a sensor node and a candidate node and is used for deploying the communicationThe positions of the nodes comprise gateway node deployment positions, n sensor node deployment positions and m candidate node deployment positions, the gateway node set is { g }, and the sensor node set is S = S { (S })1,s2,…,snThe candidate node set is C = C1,c2,…,cmThe method comprises the following steps:
step A, setting a deployed communication node of an upper wheel as w, setting a parent node of the communication node w as p (w), setting the hop number from a gateway node to the deployed communication node w as kappa (w), setting a deployed relay node set as R, and recording a reduction point A; generally, a gateway node g is deployed at a gateway node deployment position;
estimating communication radii of all communication nodes by using the method for estimating the communication radii of the communication nodes in the communication network disclosed in the first part of the invention, and constructing a communication topological graph G as (V, E), wherein V is a communication node set, and E is an edge set;
the construction method of the edge is as follows: traversing any two communication nodes u and V in the communication node set V, if | | | u-V | | | < min (r | |)v,ru) If the communication node u is located in the communication topology G, then there is an edge connecting two points of the communication node u and the communication node v, where | | u-v | | is the distance between the communication node u and the communication node v, and ruIs the communication radius of the communication node u, rvIs the communication radius of the communication node v.
Step B, updating the communication nodes w deployed in the first wheel to deploy the relay nodes, generally deploying the relay nodes in the candidate node deployment positions, and constructing a set N formed by all neighbor communication nodes of the communication nodes w deployed in the first wheel in the communication topological graph GG(w), actually measuring the communication nodes w and the set N arranged in the previous wheel one by oneG(w) ∩ S, setting the channel quality constraint as theta, and taking the sensor nodes with the packet receiving rate psi (S, w) being greater than or equal to theta with the last wheel deployment communication node as the first sensor nodes, deleting the first sensor nodes from the set S and updating the set S;
traversing set omega is NGEach communication node u in (w) \ (R ∪ S) to acquire each communicationThe sensor node set y (u) to which the node u can be effectively connected is
{Υ(u)|s∈S,h(pG(s,u))+κ(w)+1≤} (15)
In the formula, pG(s, u) represents the shortest path from the sensor node s to the communication node u in the communication topology G;
recording a reduction point B;
step C, if
Figure BDA0002526787850000121
Or any communication node u in the set omega can be effectively connected with the sensor node set
Figure BDA0002526787850000122
Reducing to a reduction point A and executing the step B again; if it is
Figure BDA0002526787850000123
And all communication nodes u in the set omega can be effectively connected with the sensor node set
Figure BDA0002526787850000124
The weight of each non-empty communication node u in the weighted y (u) is
Figure BDA0002526787850000125
In the formula, TG(u, y (u)) represents the shortest path tree from communication node u to all sensor nodes in y (u) corresponding to communication node u in the communication topology map G, | x | represents the number of communication nodes on path tree x;
in the weights ω (u) corresponding to all the communication nodes in the set Ω, setting the communication node with the smallest weight ω (u) to correspond to the deployment position t, actually measuring Ψ (t, w) between the deployment position t and the last wheel deployment communication node w, and re-estimating the communication radii of all the communication nodes by using the method for estimating the communication radii of the communication nodes in the communication network disclosed in the first part of the invention;
if Ψ (t, w) ≧ θ, a new relay node t is successfully deployed in the communication network, where w = t, p (t) = w, k (t) = κ (w) +1, R = R { (t }; if Ψ (t, w) < θ, Ω \ t }, and reducing to a reduction point B, and re-executing step C;
step D, in the set
Figure BDA0002526787850000131
And repeatedly executing the processes from the step B to the step C until the set is obtained after one relay node is deployed successfully each time
Figure BDA0002526787850000132
It should be understood that, in fig. 3, the communication node deployed in step a may be a gateway node or a relay node. The two-dot chain line block in fig. 3 corresponds to step C. If the communication node w deployed in the first wheel in the step A is the gateway node g, the communication node is the gateway node g
Figure BDA0002526787850000133
p(w)＝-1，κ(w)＝0。
Example 2: fig. 5-12 are schematic diagrams of a weighted depth-first based progressive relay deployment method. Deployment starts with the gateway node, i.e., v = g, p (g) = 1, h (g) = 0. Firstly, the communication radius of all nodes is estimated by using the communication distance of the logarithmic distance path loss model, and a communication topological graph is constructed according to the step A, which is shown in FIG. 5. Then step B is entered to search all the neighbor nodes of v, i.e. all the neighbor nodes of g in the round, and N is known from FIG. 5G(g)＝{c1,c2,c3}. Then, c is found out according to the formula (15)1、c2And c3A set of sensor nodes that can be operatively connected, and c is calculated according to equation (16)1、c2And c3The weight of (2). First from c1、c2And c3C with the smallest weight is selected1Then test c1And v (g) the bag receiving rate psi (c)1G) due to Ψ (c)1G) is not less than θ, so that in c1Deploy a relay and c1And recording U. Then, let p (c1) = v, k (c1) = k (v) +1, and v = c1. Then enter intoAnd C, repeating the steps B to C in the next round. And in the second round at c6One relay node is deployed. After the third pass, attempt to place the relay at c11Location, but tested to find Ψ (c)11,c6) The reliability constraint theta cannot be satisfied and a change in the communication topology is found after the next round of estimation of the communication distance, as shown in fig. 6. In the next round of step C, C is found6The neighbors which can be effectively connected with the sensor nodes can not be found in the topological graph any more, so that the current deployment position v returns to the parent node c of the current deployment position v1The deployment is reattempted. Then at c1Also, neighbors that can effectively connect sensor nodes cannot be found, so roll back to c1The parent node g is deployed from g again.
Repeating steps B through C during subsequent deployment, wherein FIG. 7 shows the method continuing along C2、c9、c7、c12Successfully deployed and sensor nodes s are connected1Connecting to a gateway node; FIG. 8 shows that the method has been unable to find neighbors that can effectively connect the remaining sensor nodes, along c12、c7、c9Go back all the way to c2(ii) a FIG. 9 shows the method from c2There is a successful finding of neighbors that effectively connect the remaining sensor nodes, all the way along c2、c8、c13To c16And connecting the sensor node s2Connecting to a gateway node; FIG. 10 shows that at c16 no more neighbors can be found to effectively connect the remaining sensor nodes, and the process returns to c13(ii) a FIG. 11 is a view taken at c13With the neighbor c found again to be effectively connected with the rest of the sensor nodes17And effectively connecting the last sensor node s by the node3Is connected to the gateway node. To this end, all sensor nodes are operatively connected to the gateway node. Finally, a shortest path tree which takes the network management node as a root node to connect all the sensor nodes is generated, and the relay nodes which are not on the tree (namely c) are eliminated1And c6) The final output result is shown in fig. 12.
The invention is described in detail above with reference to the figures and examples. It should be understood that in practice it is not intended to be exhaustive of all possible embodiments, and the inventive concepts of the present invention are presented herein by way of illustration. Without departing from the inventive concept of the present invention and without any creative work, a person skilled in the art should, in all of the embodiments, make optional combinations of technical features and experimental changes of specific parameters, or make a routine replacement of the disclosed technical means by using the prior art in the technical field to form specific embodiments, which belong to the content implicitly disclosed by the present invention.

Claims (5)

1. A real-time reliable relay deployment method facing a power distribution network is characterized in that a communication node is composed of gateway nodes, sensor nodes and candidate nodes, the positions for deploying the communication node comprise gateway node deployment positions, n sensor node deployment positions and m candidate node deployment positions, the set of the gateway nodes is { g }, and the set of the sensor nodes is S = S { (S) }1,s2,…,snThe candidate node set is C = C1,c2,…,cm}; the method is characterized by comprising the following steps:
step A, setting a deployed communication node of an upper wheel as w, recording the parent node of the communication node w as p (w), setting the hop count from a gateway node to the deployed communication node w as kappa (w), setting a deployed relay node set as R, and recording a reduction point A; estimating the communication radius of all communication nodes by using a method for estimating the communication radius of the communication nodes in the communication network, and constructing a communication topological graph G (V, E), wherein V is a communication node set, and E is an edge set;
step B, updating the upper first wheel deployment communication nodes w to deploy the relay nodes, and constructing all neighbor communication nodes of the upper first wheel deployment communication nodes w in the communication topological graph G to form a set NG(w), actually measuring the communication nodes w and the set N arranged in the previous wheel one by oneG(w) ∩ S, setting the channel quality constraint as theta, and the sensor nodes with the packet receiving rate phi (S, w) being more than or equal to theta with the last wheel deployment communication node w as the first sensor nodes, and deleting the first sensor nodes from the set SSensor nodes and update the set S;
traversing set omega is NGEach communication node u in (w) \ (R ∪ S) to obtain the sensor node set y (u) to which each communication node u can be operatively connected as { y (u) | S ∈ S, h (p) y (p)G(s,u))+κ(w)+1≤} (1)
In the formula, pG(s, u) represents the shortest path from the sensor node s to the communication node u in the communication topology G;
recording a reduction point B;
step C, if
Figure FDA0002526787840000012
Or any communication node u in the set omega can be effectively connected with the sensor node set
Figure FDA0002526787840000013
Reducing to a reduction point A and executing the step B again; if it is
Figure FDA0002526787840000014
And all communication nodes u in the set omega can be effectively connected with the sensor node set
Figure FDA0002526787840000015
The weight of each non-empty communication node u in the weighted y (u) is
Figure FDA0002526787840000011
In the formula, TG(u, y (u)) represents the shortest path tree from communication node u to all sensor nodes in y (u) corresponding to communication node u in the communication topology map G, | x | represents the number of communication nodes on path tree x;
in the weights omega (u) corresponding to all the communication nodes in the set omega, setting the communication node with the minimum weight omega (u) to correspond to the deployment position of the relay node t, actually measuring psi (t, w) between the relay node t and the last wheel deployment communication node w, and re-estimating the communication radius of all the communication nodes by using a method for estimating the communication radius of the communication nodes in the communication network;
if Ψ (t, w) ≧ θ, a new relay node t is successfully deployed in the communication network, and w = t, p (t) = w, k (t) = k (w) +1, R = R { (t }; if Ψ (t, w) < θ, Ω \ t }, and reducing to a reduction point B, and re-executing step C;
the method for estimating the communication radius of the communication nodes in the communication network comprises the following steps:
step 1, acquiring an initial communication radius r of the communication node, a sensor node hop count constraint and a channel quality constraint theta; all communication nodes capable of measuring packet receiving rate form set
Figure FDA0002526787840000021
All communication nodes incapable of measuring packet receiving rate form set
Figure FDA0002526787840000022
Step 2, obtaining the communication radius corresponding to the communication node capable of measuring the packet receiving rate, comprising the following sub-steps,
step 2a, collecting the collection
Figure FDA0002526787840000023
One communication node in the communication network is marked as communication node u, and a maximum communication radius set corresponding to the communication node u is generated
Figure FDA0002526787840000024
Step 2b, collecting the collection
Figure FDA0002526787840000025
Recording the other communication node as a communication node v, and obtaining a path loss factor a between the communication node u and the communication node v according to the actually measured packet receiving rate Ψ (u, v) between the communication node u and the communication node v, the position information of the communication node u and the position information of the communication node v;
calculating the minimum signal-to-noise ratio
Figure FDA0002526787840000026
Where ρ is the data rate, BNFor noise bandwidth, l is datagram length, function Q-1(x) Is the inverse of function q (x), θ is the channel quality constraint;
calculating the maximum communication radius of the communication node u after passing through the communication node v
Figure FDA0002526787840000031
Where P is the transmit power, PL is the reference range average path loss, PnBeing a noise floor, d0As a reference distance, γmin(u, v) is the minimum signal-to-noise ratio between the communication node u and the communication node v, and a is the path loss factor between the communication node u and the communication node v;
updating Ru＝Ru∪{dmax(u,v)}；
Substep 2c, repeatedly executing substep 2b to obtain communication node u and set
Figure FDA0002526787840000032
Set of maximum communication radii R between all other communication nodes within the clusteruThen the communication radius r of the communication node uu＝min Ru；
Step 3, repeatedly executing the step 2 to obtain a set
Figure FDA0002526787840000033
Any element corresponding communication node
Figure FDA0002526787840000034
A communication radius of (a);
step 4, assembling
Figure FDA0002526787840000035
Any element corresponding communication node
Figure FDA0002526787840000036
Is set as the communication node
Figure FDA0002526787840000037
Set of distances
Figure FDA0002526787840000038
The communication radius corresponding to the nearest communication node.
2. The distribution network-oriented real-time reliable relay deployment method according to claim 1, wherein in the step 2, the real-time reliable relay deployment method is based on aggregation
Figure FDA0002526787840000039
The method for obtaining the path loss factor a between the communication node u and the communication node v by the measured packet reception rate Ψ (u, v) between the communication node u and the communication node v and the position information of the communication node u and the position information of the communication node v comprises the following steps:
signal-to-noise ratio between communication node u and communication node v
Figure FDA00025267878400000310
Where ρ is the data rate, BNFor noise bandwidth, l is datagram length, function Q-1(x) Is the inverse of function q (x);
pathloss factor between communication node u and communication node v
Figure FDA0002526787840000041
Where P is the transmit power, PL is the reference range average path loss, PnD is the distance between communication node u and communication node vFrom, d0Is a reference distance.
3. The real-time reliable relay deployment method for the power distribution network as claimed in claim 1, wherein in the step a, if the last wheel deployment communication node w is a gateway node g, then the last wheel deployment communication node w is a gateway node g
Figure FDA0002526787840000042
p(w)＝-1，κ(w)＝0。
4. The distribution network-oriented real-time reliable relay deployment method according to claim 1, wherein in the step a, the method for constructing the edge element in the edge set E comprises the following steps: traversing any two communication nodes u and V in the communication node set V, if | | | u-V | | | < min (r | |)v,ru) If the communication node u is located in the communication topology G, then there is an edge connecting two points of the communication node u and the communication node v, where | | u-v | | is the distance between the communication node u and the communication node v, and ruIs the communication radius of the communication node u, rvIs the communication radius of the communication node v.
5. The real-time reliable relay deployment method for the power distribution network according to claim 1, further comprising a step D after the step C, wherein the step D comprises: in the collection
Figure FDA0002526787840000043
And repeatedly executing the processes from the step B to the step C until the set is obtained after one relay node is deployed successfully each time
Figure FDA0002526787840000044
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