CN116133082A - Multi-hop clustering method for improving topology duration of aviation ad hoc network - Google Patents
Multi-hop clustering method for improving topology duration of aviation ad hoc network Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
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- H04B7/00—Radio transmission systems, i.e. using radiation field
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- H04W—WIRELESS COMMUNICATION NETWORKS
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- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
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Abstract
A multi-hop clustering method for improving the topology duration of an aviation ad hoc network. Which includes a cluster formation phase and a cluster maintenance phase. The cluster formation stage includes: preprocessing flight trajectory data; broadcasting data; generating a neighbor attribute table; calculating a link duration; counting the number of links greater than a link duration threshold; when the number of links greater than the threshold of the link duration exceeds the set minimum value of connectivity, the node then makes a link establishment request to the neighbor node to form a network cluster. The cluster maintenance phase includes: updating track information in the neighbor attribute table; calculating the link duration time of the existing link and the link duration time between the existing link and the new neighbor node according to the track attribute of the neighbor node in the neighbor attribute table; maintaining the existing connection and creating a new connection to maintain clustering based on the calculated link duration. The invention has the advantages that: establishing clusters in a distributed manner; the link duration can be effectively increased.
Description
Technical Field
The invention belongs to the technical field of aviation communication, and particularly relates to a multi-hop clustering method for improving the topology duration of an aviation ad hoc network.
Background
The aviation communication system is a core infrastructure for guaranteeing the high-efficiency operation of the aviation transport system, so that the stability and timeliness of data transmission are required to be guaranteed. Aeronautical ad hoc networks are one of the effective schemes for aeronautical communication systems, which rely on aircraft nodes as relays for transmitting data over multi-hop air-to-air communication links. However, the high-speed movement of the nodes of the aviation ad hoc network can cause high dynamic change of the network topology of the aviation ad hoc network, and the high dynamic network topology can cause frequent failure of the routing information of the network nodes, so that the data transmission efficiency is reduced and even the transmission fails.
Currently, the aeronautical ad hoc network routing protocol is improved on the traditional mobile ad hoc network routing protocol, however, there are a plurality of problems in these methods: 1) These routing protocols require a significant amount of network resources to update routing information frequently to accommodate highly dynamic network topologies; 2) These flat routing protocols can lead to an exponential increase in the resource cost of maintaining routing information as the network scale increases. Therefore, there is a need to develop a network topology sustainability method.
The aviation ad hoc network clustering refers to that aviation ad hoc network nodes are placed in the same cluster according to the position and movement attribute of the aviation ad hoc network nodes, and the nodes with relatively stable movement form a subnet. At present, few students use K-means, DBSCAN, learning vector quantization and other methods in the aviation ad hoc network clustering to improve the aviation ad hoc network topology sustainability, but because the methods only simply weight and combine the position attribute and the movement attribute of the network node, the improvement of the network topology sustainability by the methods is limited.
Disclosure of Invention
In order to solve the problem of low network topology sustainability caused by high dynamic change of aviation ad hoc network topology, the invention aims to provide a method capable of fully utilizing the position attribute and the movement attribute of aviation ad hoc network nodes to form a stable network clustering structure, namely: a multi-hop clustering method for improving the topology duration of an aviation ad hoc network. The method aims at establishing stable air-to-air links between nodes by using the link duration as a clustering index so as to improve the aviation ad hoc network topology duration.
In order to achieve the above objective, the multi-hop clustering method for improving the topology duration of the aviation ad hoc network provided by the present invention comprises the following steps sequentially performed:
(1) Stage of cluster formation
1.1 Preprocessing the original data of the flight track of the aviation node to obtain preprocessed track attributes;
1.2 Each node sends the preprocessed track attribute to the neighbor node in a broadcasting mode;
1.3 Each node obtains the track attribute of all the neighbor nodes and generates a neighbor attribute table;
1.4 Calculating the link duration between the node and the neighbor node according to the track attribute in the neighbor attribute table;
1.5 Counting the number m of links larger than the threshold value of the duration time of the links;
1.6 When the number m of links larger than the threshold value of the duration time of the links exceeds the set minimum value n of the connectivity, the node sends a link establishment request to the neighbor node to form a network cluster;
(2) Cluster maintenance phase
2.1 Acquiring the track attribute of the neighbor node and updating the track information of the neighbor node in the neighbor attribute table;
2.2 Calculating the link duration of the existing link and the link duration between the existing link and the new neighbor node according to the track attribute of the neighbor node in the neighbor attribute table;
2.3 Maintaining existing connections and creating new connections to maintain clustering based on the calculated link durations in step 2.2);
2.4 Repeating the steps 2.1) to 2.3), and carrying out network clustering on the dynamic network according to the track information of the nodes in real time.
In step 1.1), the method for preprocessing the flight trajectory original data of the aviation node to obtain the preprocessed trajectory attribute is as follows:
converting the aviation node flight trajectory original data from a WGS-84 coordinate system (World Geodetic System-1984 Coordinate System) to a geocentric Fixed coordinate system (ECEF), wherein the conversion formula is shown in formula (1):
wherein B, L and H represent latitude, longitude and altitude in the WGS-84 coordinate system, respectively; x, y, z respectively represent ECEF coordinate positions; a represents the semi-major axis of the earth, which is 6,378,137m; b represents the semi-minor axis of the earth, 6,356,752m; n (N) R Representing the principal vertical radius of curvature; e denotes a first eccentricity of the ellipsoid.
In step 1.2), the method for each node to send the preprocessed track attribute to the neighboring node in a broadcast manner is as follows:
and placing the preprocessed track attribute into the data packet according to a fixed format, taking the current node as a source node, and sending the data packet to all the one-hop neighbor nodes in a broadcast mode.
In step 1.3), each node acquires track attributes of all neighboring nodes, and the method for generating the neighboring attribute table is as follows:
the node receives the track attribute data packet from the neighbor node while broadcasting the attribute of the node, and the node collects the track attributes of all the neighbor nodes to generate a neighbor attribute table.
In step 1.4), the method for calculating the link duration between the node and its neighbor according to the track attribute of the neighbor node is as follows:
calculating the link duration time between the nodes according to the position attribute of the nodes and the movement attribute of the nodes; the link duration refers to the duration that two nodes can communicate with each other, and the calculation formula is shown in formula (2):
wherein, stime ij Representing the duration of nodes i and j within their transmission range; d (D) ij Representing the relative positions of node i and node j; v (V) ij Representing the relative speeds of node i and node j; r represents the communication radius of node i and node j.
In step 1.5), the method for counting the number m of links greater than the threshold of the link duration is as follows:
the link duration threshold is an over-parameter in the method, and needs to be set in advance, which means that the minimum value of the link duration between the established nodes is met. The number of links counted to be greater than the link duration threshold is the number of neighbors satisfying the link condition between the established nodes in the statistical neighbor attribute table.
In step 1.6), when the number of links greater than the threshold of the link duration exceeds the set minimum value n of connectivity, the node sends a link establishment request to the neighbor node to form a network cluster, which is as follows:
the connectivity minimum value n here is another super parameter in the method, and needs to be set in advance. The number of neighbors meeting the link condition between the established nodes can be obtained from the step 1.5). When the node meets the condition that the number m of neighbors of the link from the node to the node is greater than the minimum value n of the connectivity, sending a connection establishment request to the neighbor node so as to establish the link from the node to the node; otherwise, the node waits for connection requests of other nodes.
In step 2.1), the method for updating the track information of the neighbor node in the neighbor attribute table is as follows:
the procedure is the same as steps 1.1) to 1.3) of the cluster formation stage. Firstly, each node preprocesses the flight track original data to obtain preprocessed track attributes, then broadcasts the preprocessed track attributes, receives the track attributes of neighbors at the same time, and then updates the neighbor attribute table according to the received track attributes.
In step 2.2), the method for calculating the link duration of the existing link and the link duration between the existing link and the new neighbor node according to the track attribute of the neighbor node in the neighbor attribute table is as follows:
the procedure is the same as step 1.4) of the cluster formation stage. And calculating the link duration time between the nodes by using a formula (2) according to the position attribute of the nodes and the movement attribute of the nodes.
In step 2.3), the method for maintaining the existing connection and creating the new connection to maintain the cluster according to the link duration calculated in step 2.2) is as follows:
first, the number n of connections with existing connections greater than the link duration threshold is counted separately 1 The number of connections n for which the existing connection is less than the link duration threshold 2 And the number of new connections being greater than the link duration threshold; when n is 1 >0 and n 1 +n 3 When the connection is not less than n, the existing connection is kept unchanged, and a new connection is established; when n is 1 >0 and n 1 +n 3 <When n, only the existing connection is kept unchanged; when n is 1＝ 0 and n 2 +n 3 When the connection is not less than n, the existing connection is kept unchanged, and a new connection is established; when n is 1 =0 and n 2 +n 3 <And when n, disconnecting all the connections and waiting for the requests of other nodes for establishing links.
In step 2.4), the method for performing network clustering on the dynamic network according to the node track information in real time by repeating steps 2.1) to 2.3) is as follows:
each time period passes, steps 2.1), 2.2) and 2.3) are sequentially performed to form a real-time efficient network cluster, thereby improving network topology persistence.
Compared with the existing clustering algorithm, the multi-hop clustering method for improving the topology duration of the aviation ad hoc network has the following advantages: 1) Establishing clusters in a distributed manner; 2) The link duration can be effectively increased.
Drawings
Fig. 1 is a flowchart of a clustering stage in a multi-hop clustering method for improving the topology duration of an aviation ad hoc network.
Fig. 2 is a flowchart of a clustering maintenance stage in a multi-hop clustering method for improving the topology duration of an aviation ad hoc network.
Fig. 3 is a node distribution diagram of a certain time slice.
Fig. 4 is a movement trace diagram of all nodes.
Detailed Description
The multi-hop clustering method for improving the topology duration of the aviation ad hoc network provided by the invention is described in detail below with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1 and fig. 2, the multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network provided by the invention comprises the following steps sequentially:
(1) Stage of cluster formation
1.1 Preprocessing the original data of the flight track of the aviation node to obtain preprocessed track attributes;
converting the aviation node flight trajectory original data from a WGS-84 coordinate system (World Geodetic System-1984 Coordinate System) to a geocentric Fixed coordinate system (ECEF), wherein the conversion formula is shown in formula (1):
wherein B, L and H represent latitude, longitude and altitude, respectively, in the WGS-84 coordinate system. x, y, z denote ECEF coordinate positions, respectively. A represents the semi-major axis of the earth, which is 6,378,137m. b denotes the semi-minor axis of the earth, 6,356,752m. N (N) R Representing the principal vertical radius of curvature. e denotes a first eccentricity of the ellipsoid.
1.2 Each node sends the preprocessed track attribute to the neighbor node in a broadcasting mode;
and placing the preprocessed track attribute into the data packet according to a fixed format, taking the current node as a source node, and sending the data packet to all the one-hop neighbor nodes in a broadcast mode.
1.3 Each node obtains the track attribute of all the neighbor nodes and generates a neighbor attribute table;
the node receives the track attribute data packet from the neighbor node while broadcasting the attribute of the node, and the node collects the track attributes of all the neighbor nodes to generate a neighbor attribute table.
1.4 Calculating the link duration between the node and the neighbor node according to the track attribute of the neighbor node in the neighbor attribute table;
and calculating the link duration time between the nodes according to the position attribute of the nodes and the movement attribute of the nodes. The link duration refers to the duration that two nodes can communicate with each other. The calculation formula is shown as formula (2):
wherein, stime ij Representing the duration of nodes i and j within their transmission range; d (D) ij Representing the relative positions of node i and node j, V ij Representing the relative speeds of node i and node j, and R represents the radius of communication of node i and node j.
1.5 Counting the number m of links larger than the threshold value of the duration time of the links;
the link duration threshold is a super parameter of the method (according to experiments, the invention sets the link duration threshold to 600 s) that needs to be set in advance, indicating that the minimum value of link duration between nodes is met. Counting the number m of links greater than the link duration threshold refers to counting the number of neighbors in the neighbor attribute table that meet the link condition between the established nodes.
1.6 When the number m of links larger than the threshold value of the link duration exceeds the set minimum value n of the connectivity, the node sends a link establishment request to the neighbor node to form a network cluster.
The connectivity minimum value n here is another super parameter in the method (experiments show that the connectivity minimum value n is set to 2) and needs to be set in advance. The number of neighbors meeting the link condition between the established nodes can be obtained from the step 1.5). When the node meets the condition that the number of neighbors is larger than the minimum value n of the connectivity, sending a connection establishment request to the neighbor node so as to establish a link between the nodes; otherwise, the node waits for connection requests of other nodes.
(2) Cluster maintenance phase
2.1 Acquiring the track attribute of the neighbor node and updating the track information of the neighbor node in the neighbor attribute table;
the procedure is the same as steps 1.1) to 1.3) of the cluster formation stage. Firstly, each node preprocesses the flight track original data, then broadcasts the preprocessed track attribute, receives the track attribute of the neighbor, and updates the neighbor attribute table according to the received track attribute.
2.2 Calculating the link duration of the existing link and the link duration between the existing link and the new neighbor node according to the track attribute of the neighbor node in the neighbor attribute table;
the procedure is the same as step 1.4) of the cluster formation stage. And calculating the link duration time between the nodes by using a formula (2) according to the position attribute of the nodes and the movement attribute of the nodes.
2.3 Maintaining existing connections and creating new connections to maintain clustering based on the calculated link durations in step 2.2);
first, the number n of connections with existing connections greater than the link duration threshold is counted separately 1 The number of connections n for which the existing connection is less than the link duration threshold 2 And the number of new connections being greater than the link duration threshold. When n is 1 >0 and n 1 +n 3 When the connection is not less than n, the existing connection is kept unchanged, and a new connection is established; when n is 1 >0 and n 1 +n 3 <When n, only the existing connection is kept unchanged; when n is 1 =0 and n 2 +n 3 When the connection is not less than n, the existing connection is kept unchanged, and a new connection is established; when n is 1 =0 and n 2 +n 3 <And when n, disconnecting all the connections and waiting for the requests of other nodes for establishing links.
2.4 Repeating the steps 2.1) to 2.3), and clustering the dynamic network according to the node track information in real time.
Each time period passes, steps 2.1), 2.2) and 2.3) are sequentially performed to form a real-time efficient network cluster, thereby improving network topology persistence.
The effect of the multi-hop clustering method for improving the topology duration of the aviation ad hoc network provided by the invention can be further illustrated through the following experimental results.
Evaluation index description: for quantitative evaluation of the method according to the invention, the following three evaluation indices are used: average link duration (average sustained time of link, avgStime) link ) Number of link changes (Number of link changes, num) Clink ) Average number of isolated nodes (Average number of orphaned nodes, avgNumO) node )。
Wherein n represents the total number of connections established from node to node, stime i Representing the duration of the ith connection, the timer represents the number of time slices of the experimental procedure, clink j Indicating the number of connection breaks in time slice j, numO j Indicating the number of orphaned nodes for which no connection has been established within time slice j.
To illustrate the effectiveness of the method of the present invention, the method of the present invention is compared to the DBSCAN algorithm. The DBSCAN algorithm simply weights the track attributes of the nodes to perform network clustering. The method is inspired by a DBSCAN algorithm, and the clustering is established by introducing the concept of link duration, so that the effectiveness of the method can be verified compared with the DBSCAN algorithm.
DBSCAN algorithm description:
DBSCAN algorithm. Classical clustering algorithms, reference is made to: shahbazi, M.imsek and B.Kantarci, "Density-Based Clustering and Performance Enhancement of eronautical Ad Hoc Networks,"2022International Balkan Conference on Communications and Networking (Balkanecom), 2022, pp.51-56, doi:10.1109/Balkanecom 55633.2022.9900681.
In order to illustrate the effectiveness of the method for clustering the aviation ad hoc Network nodes, aviation historical flight data of the U.S. sky of 2022, 6 months, 27 days, 14:00-15:00 are obtained from the OpenSky Network, and 571 nodes are extracted from the original data. The node distribution diagram of a certain time slice is shown in fig. 3. The movement trajectories of all nodes throughout the period are shown in fig. 4.
As can be seen from Table 1, the method of the present invention is significantly better than the DBSCAN algorithm in terms of the average number of isolated nodes, the number of link changes, and the average link duration.
Table 1 comparison of experimental results
Claims (10)
1. A multi-hop clustering method for improving the topology duration of an aviation ad hoc network is characterized by comprising the following steps of: the multi-hop clustering method for improving the topology duration of the aviation ad hoc network comprises the following steps in sequence:
(1) Stage of cluster formation
1.1 Preprocessing the original data of the flight track of the aviation node to obtain preprocessed track attributes;
1.2 Each node sends the preprocessed track attribute to the neighbor node in a broadcasting mode;
1.3 Each node obtains the track attribute of all the neighbor nodes and generates a neighbor attribute table;
1.4 Calculating the link duration between the node and the neighbor node according to the track attribute in the neighbor attribute table;
1.5 Counting the number m of links larger than the threshold value of the duration time of the links;
1.6 When the number m of links larger than the threshold value of the duration time of the links exceeds the set minimum value n of the connectivity, the node sends a link establishment request to the neighbor node to form a network cluster;
(2) Cluster maintenance phase
2.1 Acquiring the track attribute of the neighbor node and updating the track information of the neighbor node in the neighbor attribute table;
2.2 Calculating the link duration of the existing link and the link duration between the existing link and the new neighbor node according to the track attribute of the neighbor node in the neighbor attribute table;
2.3 Maintaining existing connections and creating new connections to maintain clustering based on the calculated link durations in step 2.2);
2.4 Repeating the steps 2.1) to 2.3), and carrying out network clustering on the dynamic network according to the track information of the nodes in real time.
2. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 1.1), the method for preprocessing the flight trajectory original data of the aviation node to obtain the preprocessed trajectory attribute is as follows:
converting the aviation node flight trajectory original data from a WGS-84 coordinate system (World Geodetic System-1984 Coordinate System) to a geocentric Fixed coordinate system (ECEF), wherein the conversion formula is shown in formula (1):
x＝(N R +H)·osB·osL
y＝(N R +H)·cosB·sinL
z＝[N R ·1 2 )+H]·sinB(1)
e 2 ＝(a 2 -b 2 )/ 2
wherein B, L and H represent latitude, longitude and altitude in the WGS-84 coordinate system, respectively; x, y, z respectively represent ECEF coordinate positions; a represents the semi-major axis of the earth, which is 6,378,137m; b represents the semi-minor axis of the earth, 6,356,752m; n (N) R Representing the principal vertical radius of curvature; e denotes a first eccentricity of the ellipsoid.
3. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 1.2), the method for each node to send the preprocessed track attribute to the neighboring node in a broadcast manner is as follows:
and placing the preprocessed track attribute into the data packet according to a fixed format, taking the current node as a source node, and sending the data packet to all the one-hop neighbor nodes in a broadcast mode.
4. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 1.3), each node acquires track attributes of all neighboring nodes, and the method for generating the neighboring attribute table is as follows:
the node receives the track attribute data packet from the neighbor node while broadcasting the attribute of the node, and the node collects the track attributes of all the neighbor nodes to generate a neighbor attribute table.
5. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 1.4), the method for calculating the link duration between the node and its neighbor according to the track attribute of the neighbor node is as follows:
calculating the link duration time between the nodes according to the position attribute of the nodes and the movement attribute of the nodes; the link duration refers to the duration that two nodes can communicate with each other, and the calculation formula is shown in formula (2):
wherein, stime ij Representing the duration of nodes i and j within their transmission range; d (D) ij Representing node i and node jA relative position; v (V) ij Representing the relative speeds of node i and node j; r represents the communication radius of node i and node j.
6. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 1.5), the method for counting the number m of links greater than the threshold of the link duration is as follows:
counting the number of links greater than the link duration threshold refers to counting the number of neighbors in the neighbor attribute table that meet the link condition between the established nodes.
7. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 1.6), when the number of links greater than the threshold of the link duration exceeds the set minimum value n of connectivity, the node sends a link establishment request to the neighbor node to form a network cluster, which is as follows:
when the node meets the condition that the number m of neighbors of the link from the node to the node is greater than the minimum value n of the connectivity, sending a connection establishment request to the neighbor node so as to establish the link from the node to the node; otherwise, the node waits for connection requests of other nodes.
8. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 2.1), the method for updating the track information of the neighbor node in the neighbor attribute table is as follows:
firstly, each node preprocesses the flight track original data to obtain preprocessed track attributes, then broadcasts the preprocessed track attributes and receives the track attributes of neighbors at the same time, and then updates a neighbor attribute table according to the received track attributes;
in step 2.2), the method for calculating the link duration of the existing link and the link duration between the existing link and the new neighbor node according to the track attribute of the neighbor node in the neighbor attribute table is as follows:
and calculating the link duration time between the nodes by using a formula (2) according to the position attribute of the nodes and the movement attribute of the nodes.
9. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 2.3), the method for maintaining the existing connection and creating the new connection to maintain the cluster according to the link duration calculated in step 2.2) is as follows:
first, the number n of connections with existing connections greater than the link duration threshold is counted separately 1 The number of connections n for which the existing connection is less than the link duration threshold 2 And the number of new connections being greater than the link duration threshold; when n is 1 >0 and n 1 +n 3 When the connection is not less than n, the existing connection is kept unchanged, and a new connection is established; when n is 1 >0 and n 1 +n 3 <When n, only the existing connection is kept unchanged; when n is 1 =0 and n 2 +n 3 When the connection is not less than n, the existing connection is kept unchanged, and a new connection is established; when n is 1 =0 and n 2 +n 3 <And when n, disconnecting all the connections and waiting for the requests of other nodes for establishing links.
10. The multi-hop clustering method for improving the topology duration of an aeronautical ad hoc network according to claim 1, wherein: in step 2.4), the method for clustering the dynamic network according to the node track information in real time by repeating steps 2.1) to 2.3) is as follows:
each time period passes, steps 2.1), 2.2) and 2.3) are sequentially performed to form a real-time efficient network cluster, thereby improving network topology persistence.
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