CN113692031A - Routing algorithm based on multidimensional community in ship self-organizing network - Google Patents
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Abstract
The invention discloses a routing algorithm based on multidimensional communities in a ship self-organizing network, which comprises a multidimensional community division algorithm based on ship social attributes and a distributed data transmission routing algorithm of the ship self-organizing network, wherein the multidimensional community is defined through a ship real track to describe the social relationship among ships; and according to the condition of the multidimensional community to which the ship belongs, the capability of the ship to reach a target port more quickly is quantified, and quick data transmission is realized.
Description
Technical Field
The invention belongs to the technical field of data transmission, relates to a data transmission technology in a marine ship self-organizing network, and particularly relates to a multi-dimensional community-based routing algorithm in the marine ship self-organizing network.
Background
The ship self-organizing network is a temporary multi-hop dynamic network which can carry out mutual communication among ships without the help of fixed basic communication equipment, spontaneously carry out networking according to a self mechanism and spontaneously manage the network, and has certain autonomy and flexibility. In the process of ocean navigation, the ship transmits messages through the ship-mounted equipment, so that the defect that no network communication infrastructure can not be used is overcome, and communication resources of satellites and the like are saved. The exploration of the ship self-organizing network can support various practical applications, and mainly aims at a data transmission scene with large ocean data volume and low real-time requirement in the field of ocean Internet of things. Such as fishery resource detection, water quality monitoring, etc.
The ship self-organization network is different from self-organization networks in other fields and has unique characteristics. First, the signal coverage of the shore-based base station is limited, and when a ship sails in a wide sea area, the ship carrying data may exceed the communication range of the shore-based base station, which makes direct data transmission difficult. Secondly, the ocean area is wide, the limitation of roads is avoided, the mobility of ships is strong, the number of the ships in a certain range is limited, the density of nodes is low, the distribution is uneven, and a fully-connected network is difficult to form. Third, the marine environment is complex, and the ship communication is greatly affected by the environment in actual navigation. The satellite is expensive in data transmission, small in bandwidth and slow in transmission rate, is commonly used for communication in emergency, and occupies too much satellite resources for data transmission with large data volume.
In the ship self-organizing network, the transmission of data packets needs to be carried out by an effective protocol, but a routing protocol specially aiming at the ship self-organizing network is few. In recent years, importance has been placed on ad hoc networks by virtue of the social property between ships. Some researchers design routes by utilizing the affinity and sparseness of social relations among ships, but the influence factors of the social relations among the ships considered by the algorithms are single, and the familiarity among the ships cannot be objectively described. Some researchers use community attributes of ships to carry out routing design, but most of the researchers are based on the existing community algorithm, the community factor is single, the community formed by the factors of the ships in the navigation process is only considered, and the navigation characteristics of the ships cannot be combined with the destination port. In the ship self-organizing network, many-to-many data transmission still lacks a reliable routing strategy for controlling the timeliness of data.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a routing algorithm based on a multi-dimensional community in a ship self-organization network, which is used for analyzing ship navigation behaviors based on historical track records of ships, constructing a ship communication abstract model, increasing the communication probability between ship self-organization network nodes by considering the ship behaviors and community division and reducing the data transmission cost, and is a routing algorithm for forwarding data from ocean-going ships to shore bases. If a certain model collects information of nearby sea areas for a plurality of message sources and transmits a large amount of data messages to a plurality of corresponding ports, data packets are forwarded by meeting ships meeting conditions, and finally the data are transmitted to target ports.
In order to solve the technical problems, the invention adopts the technical scheme that: the routing algorithm based on the multidimensional community in the ship self-organizing network comprises two parts:
defining a multi-dimensional community through a real ship track based on a multi-dimensional community division algorithm of ship social attributes, and describing a social relationship among ships; and a distributed data transfer routing algorithm of the ship self-organizing network quantifies the capability of a ship to reach a target port more quickly according to the condition of the multidimensional community to which the ship belongs, and realizes quick data transmission.
Further, the multidimensional community division algorithm based on the ship social attributes comprises the following steps:
s11, discovery of social attributes:
designing a port discovery algorithm, and determining the position of a port formed by the existing track by using the social attributes of the ship;
s12, coarse-grained port community division:
the ports explored by the port discovery algorithm of the step S11 have N small ports, and the ports are clustered according to the communication radius of the shore base station as the judgment distance of the K-means algorithm to form M port clusters, wherein M is less than N;
s13, based on different social attributes of the ship, dividing the multidimensional community:
dividing ship port communities according to the number of times of meeting between a ship and a port within a certain time, and defining that the number of times of meeting between the ship and a port is the most in all the meeting ports for a port community to which a certain ship belongs;
the ship navigation community is defined as two ships enter the communication radius range of each other in the navigation process and accompany navigation within a period of time, which is called the meeting of one ship; defining the weight between two ships by counting the number of times of meeting between all the ships; according to the relation, the ship sailing overseas is divided into different sailing communities by using a community division algorithm.
Further, the distributed data transfer routing algorithm of the ship self-organizing network comprises the following steps:
s21, identifying ship social contact areas, and finding out community formation leading factors in each social contact area in multiple dimensions;
s22, obtaining the ship relay of the next hop of the data packet according to the leading social factors of the communities with different dimensions;
selecting ships which can reach a target community more quickly in the ship communities with the same dimensionality; under the condition of cross-social area, quantifying the cross-community connectivity of ships, and selecting ships with higher connectivity for communicating communities with different dimensions;
s23, maintaining and updating a neighbor table in the ship navigation chart, and quantizing transmission capacity according to community information of the ships in the neighbor table;
s24, the ship updates the neighbor table once every a period of time and updates the capacity value of the ship transmission data in the neighbor table;
and S25, the data carrying ship starts to judge whether to forward the program.
Further, in step S22, when the social area in step S21 is divided into two dimensional social areas, the specific method is:
firstly, constructing a ship social relationship graph: the ship and the port cluster are abstracted into nodes in a relational graph, and all ships are divided into two dimensional communities, namely a port community and a navigation community, from the conditions of ship return and ship ocean operation encounter by means of a multi-dimensional community division algorithm; connecting ship nodes belonging to the same navigation community according to the navigation community relation of the ship; according to the port community relation of the ship, clustering ship nodes belonging to the same port community with port nodes; in the node cluster, the average ship return port period is used as the weight among the nodes, so that a ship social relation graph is constructed;
secondly, quantifying community dimensions according to the ship social relationship graph: based on the community attributes of the neighboring ships in the neighbor table, the onboard computing platform calculates the ability of each neighboring ship to quickly transfer data to the target port
The specific calculation formula is shown as (1):
wherein the content of the first and second substances,
representing the ability of ship a to reach the target port cluster through ship b; in the social relationship graph, quantifying the capacity by the number of shortest paths from a to the destination port community through b node;
representing the speed of returning the ship in the target port community to the target port; in the social relationship graph, the average return port period is used as the edge weight between nodes,
and the value is the maximum path product from the current node to the port node.
Further, in step S23, each ship maintains a dynamic neighbor table, including all neighboring ships around the ship at the current time; the ship sends a detection frame in a communication range to confirm a neighbor ship and sends community information of the ship to the neighbor ship; and when a new neighbor ship arrives in the communication range, updating the information of the neighbor ship in the neighbor table.
Furthermore, in step S25, when the neighbor list of the data carrying ship is not newly added, no process is performed; when a data carrying ship meets a newly-added neighbor ship, judging whether to forward a program or not;
the process of judging whether the ship forwards the ship is as follows: firstly, checking the quick transmission capacities of all neighboring ships in a neighbor table, and selecting a ship with the maximum transmission capacity value to a target port as a candidate ship; and comparing the transmission capability value of the alternative ship to the target port with the transmission capability value which is transmitted historically, if the transmission capability value of the alternative ship is greater than the recorded historical transmission maximum value, transmitting, otherwise, not transmitting.
Compared with the prior art, the invention has the advantages that:
the invention is different from the traditional route design idea, does not need to design a route path in advance, can deal with the problem of uncertain ship routes, and can ensure the transmission time and reduce the transmission cost. Respectively as follows:
(1) the invention defines the multidimensional community, fully excavates the community attribute of the ship and more objectively describes the social relationship between the ships. Compared with other routing schemes based on social attributes, the scheme is specially aimed at the ship self-organizing network, is based on the long-term stable social relationship of ships, and fully considers the unique characteristics of the ship self-organizing network; compared with other routing schemes for exploring community attributes, the method has the advantages that the community division is unreasonable and the effectiveness is insufficient due to the fact that a single community dimension is influenced by a certain dominant factor, ship community attributes are mined from multiple dimensions, corresponding social activities are excavated in different social regions by identifying different social ranges, and the routing is ensured to be effectively guided by the social attributes through the combination of time, space and activities.
The two-dimensional social relationship is taken as an example, the navigation community is divided according to the overseas navigation behavior of the ship, the ship port community is defined according to the ship return port characteristic, the ship navigation community and the ship port community are jointly considered, and the defect that the single community factor is considered in the existing community scheme is overcome. For example: according to the traditional method, only the navigation communities of the ships are divided, and under the scene of the method, the navigation community where the ship in the target port is located cannot be determined, so that an obstacle is caused to the routing between communities.
(2) The invention provides a new routing algorithm, which realizes rapid data transmission through the ship multi-dimensional community attributes, and greatly improves the performance of ship data transmission. The routing algorithm of the invention also considers the factor of the time required by the ship in transmitting the data packet on the basis of fully mining the community attribute, so that the single value of the data packet transmitted by the ship is extremely high. Compared with other routing algorithms, the scheme can ensure the high-standard data transmission success rate through the community attribute, greatly shortens the data packet transmission time and ensures the timeliness of data.
(3) The invention increases the success rate of data transmission and reduces the cost of data transmission on the premise of ensuring the timeliness of data, namely, the invention greatly reduces the cost of a routing algorithm and realizes the performance equivalent to that of a flooding-based routing. The design and implementation of the scheme are based on the really collected ship track data, and the long-term stable and regular social attributes among the ships contained in the ship track are excavated by analyzing the long-term stable and regular sailing behaviors of the ships, so that the scheme is stable and long in timeliness, the social attributes of the ships are introduced into the routing scheme, the long-term stable routing relation of the ships can be better reflected, and the cost for maintaining the network topology is reduced. Meanwhile, the invention does not need to reform the original ship infrastructure, thereby saving the routing cost.
(4) The invention is designed based on the distributed mode and has strong robustness. Different from a uniformly-scheduled routing scheme, the scheme greatly overcomes the defects of poor stability and adaptability of a centralized routing strategy by using a distributed design idea, and can well cope with the situations of a complex and changeable environment of the ocean and an unfixed ship navigation route.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a two-dimensional community-based ship social relationship diagram according to embodiment 1 of the present invention;
FIG. 2 is a diagram of social relationships among ships within the same harbor cluster according to embodiment 1 of the present invention;
fig. 3 is a flowchart of a routing algorithm based on a multidimensional community in a ship ad hoc network according to embodiment 2 of the present invention.
Detailed Description
The invention is further described with reference to the following figures and specific embodiments.
Example 1
The embodiment provides a routing algorithm based on a multi-dimensional community in a ship self-organizing network, which comprises two parts, wherein the first part is as follows: a multidimensional community division algorithm based on ship social attributes defines multidimensional communities through ship real tracks and describes social relations among ships.
The second part is: according to the distributed data transfer routing algorithm of the ship self-organizing network, the capacity of a ship to reach a target port more quickly is quantified according to the condition of the multidimensional community of the first part of the ship, and quick data transmission is realized.
The following are detailed separately:
the multidimensional community division algorithm based on the ship social attributes comprises the following steps:
s11, discovery of social attributes:
designing a port discovery algorithm, and determining the position of a port formed by the existing track by using the social attributes of the ship.
During the navigation of the ship, similar to the behaviors of human society, a long-term stable relationship exists, and the behaviors are called as the social attributes of the ship. Since the social attributes of the ship are stable for a long time, the relationship can reflect the sailing behavior of the ship in turn, and can be used for guiding the design of the routing scheme of the ship. Such relationships can be explored through data mining, mathematical statistics, and the like.
For example, the position of the port formed by the existing track is determined by utilizing the behavior characteristics of the ship near the port, such as the social attributes of the navigation speed, the stop time and the like. By observing the characteristics of the ship track on the map, the record of the ship track at the port is relatively dense, and the navigation speed of the ship at the port approaches 0 sea. From the above features, it is determined whether or not a point near the coastline having the above features is a harbor, which is called a harbor finding algorithm.
S12, coarse-grained port community division:
the ports explored by the port discovery algorithm of the step S11 are a plurality of ports, the number of the ports is large, and the positions of a plurality of ports are close to each other. When the data arrives at the port, the data can be completely transferred through a cellular network of a shore base station and the like. Therefore, in order to reduce the later-stage calculation cost, the ports are clustered by taking the communication radius of the shore base station as the judgment distance of the K-means algorithm for N small ports, and M (M < N) port clusters are formed.
S13, based on different social attributes of the ship, dividing the multidimensional community:
if the navigation behavior of the ship at the offshore location is greatly influenced by port factors, the number of times the ship goes to the port can reflect the relationship between the ship and the port within a certain time, and the number of times the ship returns to the port is more, so that the port communities of the ship are divided according to the number of times the ship meets the port within a certain time, and the number of times the ship meets the port is defined as the number of times the ship meets the port is the most in all the meeting ports for the port community to which the ship belongs; if the formation of a ship navigation community mainly depends on the meeting times of ships when the ships navigate overseas, two ships enter the communication radius range of each other during the navigation process and accompany the navigation within a period of time, which is called the meeting of one ship. The weight between two ships is defined by counting the number of times of meeting between all the ships. According to the above relationship, the ship sailing overseas is divided into different communities by using the existing community division algorithm, such as Infomap.
The distributed data transfer routing algorithm of the ship self-organizing network comprises the following steps:
s21, identifying ship social areas, and finding community forming dominant factors in each social area in multiple dimensions.
Take two-dimensional community attributes as an example: according to the maximum communication range of the shore base, the sea is divided into two parts by taking a plurality of seas away from a coastline as a dividing boundary. The division of the community at one side close to the land is greatly influenced by port berthing factors, and the formation of the ship community at one side far away from the land is greatly influenced by ship sailing behaviors.
And S22, obtaining the ship relay of the next hop of the data packet according to the leading social factors of the communities with different dimensions. Selecting ships which can reach a target community more quickly in the ship communities with the same dimensionality; further, in the case of cross-social areas, connectivity of ships among communities is quantified, and ships with higher connectivity and with different dimensionality communities are selected.
If the ship and the port cluster are abstracted into nodes in the relation graph, the two-dimensional community attributes of the ship are divided into the ship social relation graph by depending on the social area division in the step S21, the ship social relation graph is divided into communities with different dimensions according to different behaviors in different space ranges, the ship nodes are clustered according to the attribute of which port community the ship returns, and the ship nodes are connected with different ships according to the ocean fishing factor, wherein the connection degrees between different port communities are represented by the number of the sides. Fig. 2 shows a social relationship diagram of ships within the same port cluster, wherein the average meeting period of two nodes is used as a weight for nodes within the same port, and if the nodes are the ship and port nodes, the average return period of the ship is represented.
With reference to fig. 1 and 2, the ship community division in two dimensions is taken as an example to describe the process in detail:
firstly, a shipborne platform is constructed, and a ship social relationship graph is constructed. The ship and the port cluster are abstracted into nodes in a relational graph, and all ships are divided into two dimensional communities, namely a port community and a navigation community, from the conditions of ship return and ship ocean operation encounter by means of a multi-dimensional community division algorithm. Connecting ship nodes belonging to the same navigation community according to the navigation community relation of the ship; according to the port community relation of the ship, ship nodes belonging to the same port community are clustered with port nodes. And in the node cluster, the average ship return port period is used as the weight among the nodes, so that a ship social relation graph is constructed.
Secondly, quantifying community dimensions according to the ship social relationship graph. Based on the community attributes of the neighboring ships in the neighbor table, the onboard computing platform calculates the ability of each neighboring ship to quickly transfer data to the target port
The specific calculation formula is shown as (1):
wherein the content of the first and second substances,
representing the ability of ship a to reach the target port cluster via ship b. In the social relationship graph, the capacity is quantified by the number of shortest paths from a through node b to the destination port community.
Indicating how fast the ships in the target port community are returning to the target port. In the social relationship graph, the average return port period is used as the edge weight between nodes,
and the value is the maximum path product from the current node to the port node.
And S23, maintaining and updating the neighbor table in the ship navigation chart, and quantizing transmission capacity according to the community information of the ships in the neighbor table.
The ship confirms the neighbor ship by sending a detection frame in a communication range during navigation. Each ship maintains a dynamic neighbor table, including all neighbor ships around the ship at the current moment; the ship sends a detection frame in a communication range to confirm a neighbor ship and sends community information of the ship to the neighbor ship; and when a new neighbor ship arrives in the communication range, updating the information of the neighbor ship in the neighbor table.
And S24, the ship updates the neighbor table once every period of time and updates the capacity value of the ship for transmitting data in the neighbor table.
And S25, the data carrying ship starts to judge whether to forward the program.
When the neighbor table of the data carrying ship is not newly added with a neighbor ship, no process is carried out; when the data carrying ship meets a newly added neighbor ship, whether the program is forwarded or not is judged.
The process of judging whether the ship forwards the ship is as follows: the quick transmission capacities of all the neighboring ships are checked in a neighbor table, and the ship with the maximum transmission capacity value to the target port is selected as a candidate ship. And comparing the transmission capability value of the alternative ship to the target port with the transmission capability value forwarded historically, if the transmission capability value of the alternative ship is greater than the recorded historical forwarding maximum value, forwarding, otherwise, not forwarding.
Example 2
Based on the routing algorithm based on the multidimensional community in the ship ad hoc network described in embodiment 1, the present embodiment, with reference to fig. 2, describes a flow of the routing algorithm based on the ship ad hoc network based on the social attributes of the multidimensional community.
Firstly, main social attributes of ships in different areas are identified (namely social attribute discovery), reasonable social range division is selected, and main social activities in corresponding social ranges are identified.
Then, carrying out multi-dimensional community division on the ship according to the social attributes.
And finally, based on the division result of the ship multi-dimensional community, applying a routing strategy to select a relay ship until the data packet is transmitted to a target port. The routing policy may refer to the content of the distributed data collection routing algorithm of the ship ad hoc network described in embodiment 1, and details are not described here.
In conclusion, the ship navigation behavior analysis method based on the historical track record of the ship defines the multidimensional community, fully excavates the community attribute of the ship, and more objectively describes the social relationship among the ships. The invention provides a new routing algorithm, which realizes rapid data transmission through the ship multi-dimensional community attribute and greatly improves the performance of ship data transmission. The invention increases the success rate of data transmission and reduces the cost of data transmission on the premise of ensuring the timeliness of data, and is a routing algorithm for forwarding data to shore base by ocean vessels.
The same or similar parts among the various embodiments of the present description may be referred to each other, and each embodiment is described with emphasis on differences from the other embodiments. Moreover, the structure of the system embodiment is only schematic, wherein the program modules described by the separable components may or may not be physically separated, and in actual application, some or all of the modules may be selected as needed to achieve the purpose of the solution of the embodiment.
It is understood that the above description is not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art should understand that they can make various changes, modifications, additions and substitutions within the spirit and scope of the present invention.
Claims (6)
1. The routing algorithm based on the multidimensional community in the ship self-organizing network is characterized by comprising two parts: defining a multi-dimensional community through a real ship track based on a multi-dimensional community division algorithm of ship social attributes, and describing a social relationship among ships; and a distributed data transfer routing algorithm of the ship self-organizing network quantifies the capability of a ship to reach a target port more quickly according to the condition of the multidimensional community to which the ship belongs, and realizes quick data transmission.
2. The multi-dimensional community-based routing algorithm in the ship self-organizing network according to claim 1, wherein the multi-dimensional community division algorithm based on the ship social attributes comprises the following steps:
s11, discovery of social attributes:
designing a port discovery algorithm, and determining the position of a port formed by the existing track by using the social attributes of the ship;
s12, coarse-grained port community division:
the ports explored by the port discovery algorithm of the step S11 have N small ports, and the ports are clustered according to the communication radius of the shore base station as the judgment distance of the K-means algorithm to form M port clusters, wherein M is less than N;
s13, based on different social attributes of the ship, dividing the multidimensional community:
dividing ship port communities according to the number of times of meeting between a ship and a port within a certain time, and defining that the number of times of meeting between the ship and a port is the most in all the meeting ports for a port community to which a certain ship belongs;
the ship navigation community is defined as two ships enter the communication radius range of each other in the navigation process and accompany navigation within a period of time, which is called the meeting of one ship; defining the weight between two ships by counting the number of times of meeting between all the ships; according to the relation, the ship sailing overseas is divided into different sailing communities by using a community division algorithm.
3. The multi-dimensional community based routing algorithm in the ship ad hoc network according to claim 2, wherein the distributed data transfer routing algorithm of the ship ad hoc network comprises the following steps:
s21, identifying ship social contact areas, and finding out community formation leading factors in each social contact area in multiple dimensions;
s22, obtaining the ship relay of the next hop of the data packet according to the leading social factors of the communities with different dimensions;
selecting ships which can reach a target community more quickly in the ship communities with the same dimensionality; under the condition of cross-social area, quantifying the cross-community connectivity of ships, and selecting ships with higher connectivity for communicating communities with different dimensions;
s23, maintaining and updating a neighbor table in the ship navigation chart, and quantizing transmission capacity according to community information of the ships in the neighbor table;
s24, the ship updates the neighbor table once every a period of time and updates the capacity value of the ship transmission data in the neighbor table;
and S25, the data carrying ship starts to judge whether to forward the program.
4. The multi-dimensional community based routing algorithm in the ship ad hoc network according to claim 3, wherein in the step S22, the social area in the step S21 is divided into two-dimensional social areas by the following specific method:
firstly, constructing a ship social relationship graph: the ship and the port cluster are abstracted into nodes in a relational graph, and all ships are divided into two dimensional communities, namely a port community and a navigation community, from the conditions of ship return and ship ocean operation encounter by means of a multi-dimensional community division algorithm; connecting ship nodes belonging to the same navigation community according to the navigation community relation of the ship; according to the port community relation of the ship, clustering ship nodes belonging to the same port community with port nodes; in the node cluster, the average ship return port period is used as the weight among the nodes, so that a ship social relation graph is constructed;
secondly, quantifying community dimensions according to the ship social relationship graph: based on the community attributes of the neighboring ships in the neighbor table, the onboard computing platform calculates the ability of each neighboring ship to quickly transfer data to the target port
The specific calculation formula is shown as (1):
wherein the content of the first and second substances,
representing the ability of ship a to reach the target port cluster through ship b; in the social relationship graph, quantifying the capacity by the number of shortest paths from a to the destination port community through b node;
representing the speed of returning the ship in the target port community to the target port; in the social relationship graph, the average return port period is used as the edge weight between nodes,
and the value is the maximum path product from the current node to the port node.
5. The multi-dimensional community based routing algorithm in the ship self-organizing network according to claim 4, wherein in step S23, each ship maintains a dynamic neighbor table including all neighbor ships around the ship at the current time; the ship sends a detection frame in a communication range to confirm a neighbor ship and sends community information of the ship to the neighbor ship; and when a new neighbor ship arrives in the communication range, updating the information of the neighbor ship in the neighbor table.
6. The multi-dimensional community based routing algorithm in the ship self-organizing network according to claim 4, wherein in step S25, no process is performed when no neighbor ship is added to the neighbor list of the data carrying ship; when a data carrying ship meets a newly-added neighbor ship, judging whether to forward a program or not;
the process of judging whether the ship forwards the ship is as follows: firstly, checking the quick transmission capacities of all neighboring ships in a neighbor table, and selecting a ship with the maximum transmission capacity value to a target port as a candidate ship; and comparing the transmission capability value of the alternative ship to the target port with the transmission capability value which is transmitted historically, if the transmission capability value of the alternative ship is greater than the recorded historical transmission maximum value, transmitting, otherwise, not transmitting.
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