CN103312535B - Community-based layering opportunistic network and method for building up thereof and communication means - Google Patents

Abstract

The present invention discloses a kind of community-based layering opportunistic network and method for building up thereof and communication means, for solving existing opportunistic network, has that node administration is loose, connectivity is poor, data and inquiry rely on the problems such as flooding to design.Described community-based laminating machine network packet can contain some communities；In each described community all include ordinary node and in order to identify community and management ordinary node communication super node；It is in communication with each other by the free node between community that moves between described community.Community-based layering opportunistic network of the present invention and method for building up thereof and communication means, have the multiple advantages such as network management is orderly, connectivity good, data sharing high, and storage pressure is little.

Description

Community-Based Hierarchical Opportunity Network and Its Establishment Method and Communication Method

technical field

The invention relates to the communication field, in particular to a community-based layered opportunity network, a community-based layered opportunity network establishment method and a communication method.

Background technique

Opportunistic networks are evolved on the basis of DTN (Delay Tolerant Networks) delay-tolerant networks. They are self-organizing networks that do not require a complete path between the source node and the destination node, and use the encounter of node movement to realize network communication.

The communication mode of opportunistic networks is "store-carry-forward". The source node transmits the information to be forwarded to the node where it meets, forwards and carries it continuously, and finally reaches the destination node.

Opportunistic networks are suitable for network environments where sound connectivity cannot be established, such as interstellar network communications, network transmission in remote areas, portable device networking, vehicle communication networks, wild animal tracking networks, etc.

However, the existing opportunistic network has the following problems because all nodes are equal in function and level, and the nodes have greater mobility and frequent physical location changes:

1: The nodes in the network lack management and the network connectivity is poor;

2: It may cause a problem of repeated flooding of data in the whole network, wasting the storage resources of nodes;

3: The scope of data query is the whole network, which is easy to cause flood search, and the selected data forwarding path is improper, which will lead to large amount of information forwarded by nodes, high storage pressure, and increased delay.

4: The departure or failure of a node may cause some data that only exists on this node to disappear from the network, and the sharing and effectiveness of data are poor.

Contents of the invention

(1) Purpose of the invention

The invention provides a community-based layered opportunity network with orderly node management, good connectivity, and increased data reliability and effectiveness, as well as its establishment method and communication method.

(2) Technical solutions

To achieve the above-mentioned purpose, the present invention is based on a community-based hierarchical opportunity network, which includes several communities; each of the communities includes ordinary nodes and a super node;

The inter-communities communicate with each other by moving free nodes among the communities.

Further, the community is established in a communication hotspot.

In order to achieve the above-mentioned purpose, the method for establishing a community-based hierarchical opportunity network of the present invention, the method for establishing a community-based hierarchical opportunity network includes the following steps:

Step S1: The super node detects the communication nodes within its communication range in real time and reads the attribute information carried by the communication nodes;

Step S2: The super node calculates the encounter probability with each communication node according to a preset method;

Step S3: The super node compares whether its encounter probability with the communication node is greater than the encounter probability of the communication node with other super nodes,

If it is greater than, enter step S3.1; if it is not greater, enter step S3.2;

Step S3.1: The super node sets the communication node as an ordinary node managed by it to form a community identified by it, and returns the probability of encountering the communication node to the communication node;

Step S3.2: The super node returns the probability of encountering the communication node to the communication node, wherein the communication node is an ordinary node or a free node outside the community identified by the super node.

Preferably, the preset method calculates the encounter probability between the super node and the communication node through the following formula;

$<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; init</span>}}& \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ <span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; )</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; contact</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; contact</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; noncontact</span>}}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\frac{{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; init</span>}}}{{\mathrm{<span\; class="notranslate">\; e</span>}}^{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>}}<span\; class="notranslate">\; )</span>& \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&Greater\; Equal;</span>\mathrm{<span\; class="notranslate">\; 2</span>}\end{array}\right.$

P(S,M _n ) is the encounter probability between super node S and communication node M _n ;

f is the total number of encounters between super node S and communication node _Mn .

P _Init is the initial value of the encounter probability;

λ is a constant with a value between 0 and 1;

T _contact is the accumulative duration of encounter between super node S and communication node M _n within the previous preset time; T _noncontact is the accumulative duration of non-encounter between super node S and communication node M _n within the previous preset time;

γ is the adjustment factor.

Preferably, the attribute information includes encounter probabilities between the communication node and all super nodes and the communities they belong to.

In order to achieve the above-mentioned purpose, the present invention is based on a community-based layered opportunity network communication method, and the community-based layered opportunity network communication method includes the following steps:

Step A: The super node establishes a data index table for the data stored by the common nodes in the identified community, establishes a temporary data index table for the data stored by the free node, and copies the data index table of other communities carried by the free node To build inter-community data index tables;

Step B: The ordinary node M submits the retrieval information of the data to be queried to the super node;

Step C: The super node queries in the data index table,

If there is a record in the data index table, the super node will send the identification information of the ordinary node N that stores the data to be queried to the ordinary node M, and the ordinary node M realizes the communication with the ordinary node N through the encounter between the ordinary nodes in its community ;

If there is no record in the data index table, the super node will query whether there is a record in the temporary data index table,

If yes, the super node returns the identification information of the free node O to the ordinary node M, and the ordinary node M communicates with the free node O through the encounter of the communication nodes;

None, the super node queries whether there is a record in the inter-community data index table,

If yes, the free node P accesses the ordinary nodes of other communities that store the data to be queried, and the free node P returns the data to the ordinary node M;

If none, the communication fails;

Wherein, the community-based hierarchical opportunity network includes several communities; each of the communities includes common nodes and super nodes used to identify the community and manage the communication of common nodes.

especially,

In the step C, the super node also monitors the popularity of each data being queried, and judges according to a predetermined method whether to establish a copy of the queried data in a common node managed by it or itself.

In particular, the predetermined method includes the following steps:

Step C1.1: Calculate P _f and α _i respectively according to the following formulas;

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Pi;</span>}}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; \&delta;e</span>}}^{{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&theta;\; HD</span>}}_{\mathrm{<span\; class="notranslate">\; I</span>}}}$

P _f is the failure probability of the corresponding data;

C is the number of copies of data in the corresponding community;

P(S,M _n ) is the encounter probability between the super node S and the communication node M _n storing the data to be queried;

Heat HD _I is the number of times the corresponding data is queried per unit time;

The dynamic factor α _i characterizes the maximum failure probability allowed by the corresponding data;

δ is the data reliability assurance parameter; θ is the adjustment factor;

Step C1.2, the super node judges the size of P _f and α _i , and when P _f > α _i , the super node creates a copy of the queried data in the ordinary node managed by it or itself.

In particular, the predetermined method is a hotness threshold determination method, if the hotness of the queried data is greater than the threshold, a copy of the queried data will be established on the common node managed by it or itself.

In particular, the step A also includes that the super node monitors the connection status of each node communicating with it in real time, and updates the data index table, the temporary data index table and the sub-community data index table in real time according to the operating status of each communication node. step.

(3) Beneficial effects of the present invention

The present invention is based on the community-based layered opportunistic network and its establishment method and communication method, through the establishment of communities and the management of ordinary nodes by super nodes, the connectivity is improved; the query of data is prioritized in the community, and the flood query is suppressed It prevents problems such as high pressure on data storage and occupation of storage resources caused by the macro-spreading of data in the entire network.

Description of drawings

FIG. 1 is a schematic structural diagram of a community-based hierarchical opportunity network according to Embodiment 1 of the present invention;

FIG. 2 is a flowchart of a method for establishing a community-based hierarchical opportunity network according to Embodiment 2 of the present invention;

FIG. 3 is a flow chart of a community-based hierarchical opportunistic network communication method according to Embodiment 4 of the present invention.

detailed description

The community-based hierarchical opportunity network and its establishment method and communication method of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

Embodiment one:

This embodiment is based on a community-based hierarchical opportunity network, including several communities; each of the communities includes ordinary nodes and super nodes used to identify the community and manage the communication of ordinary nodes;

The inter-communities communicate with each other by moving free nodes among the communities.

In this embodiment, the layering of the opportunistic network is reflected in the asymmetry between nodes, and super nodes have more powerful authority and functions than ordinary nodes and free nodes.

As shown in Figure 1, the community-based hierarchical opportunity network shown in the figure includes three communities, namely community S1, community S2, and community S3, where each of communities S1, S2, and S3 includes a super node and Three ordinary nodes managed by supernodes. The identification of the community is realized by the super node, so usually the identification of the community is consistent with the ID of the corresponding super node, so the super node in the community S1 is S1, the super node in the community S2 is S2, and the super node in the community S3 for S3.

Communities communicate through free nodes, as shown in Figure 1, including free node M1 moving between community S1 and community S3, free nodes M2 and M3 moving between community S1 and community S2, and between community S2 and community S3 The free node M4 between

The selection of the super node is usually a slow-moving or non-moving communication node in the community with high stability, high radiant energy, wide wireless coverage, computing power and information processing energy, which can ensure that the communication range covered by it It performs signaling interaction and data transmission with most nodes within the network. Super nodes have a unique representation S in the entire network.

Ordinary nodes include human-carried and vehicle-mounted mobile devices with low storage capacity. They are producers, transmitters, and users of data and have stable communication with super nodes. They communicate with ordinary nodes through Bluetooth, IEEE802.11X, etc. To achieve short-distance wireless communication, the probability of ordinary nodes moving within the community is relatively high, and the probability of roaming outside the community is small. Therefore, the density of nodes in the community is large, the number of encounters between nodes is large, the data transmission is frequent, the data transmission delay is small, and it is stable and reliable. Each common node has a unique representation ID for the entire network.

As a further improvement of this embodiment, the community is established in a communication hotspot. The communication hotspots are areas with high node density, frequent encounters between nodes, and frequent data interactions. Usually, areas such as office buildings, shopping malls, laboratories and other areas will form communication hotspots. Building communities in communication hotspots effectively utilizes The community feature realizes the efficient transfer and sharing of data.

Embodiment two:

As shown in FIG. 2 , in this embodiment, a method for establishing a community-based hierarchical opportunity network, the method for establishing a community-based hierarchical opportunity network includes the following steps:

Step S1: The supernode detects the communication nodes within its communication range in real time and reads the attribute information carried by the communication nodes; it can be seen from the first embodiment that the supernode is a communication node with strong computing power and information processing ability, and the supernode is in Detect and search communication nodes within the communication range covered by it, and copy the attribute information carried by the communication nodes, including at least the probability of encountering any super node;

Step S2: The super node calculates the encounter probability with each communication node according to a preset method;

Step S3: The super node compares whether its encounter probability with the communication node is greater than the encounter probability of the communication node with other super nodes,

If it is greater than, enter step S3.1; if it is not greater, enter step S3.2;

Step S3.1: The super node sets the communication node as an ordinary node managed by it to form a community identified by it, and returns the probability of encountering the communication node to the communication node; since the super node calculates Its encounter probability with this communication node is greater than any other super node, which means that the reliability of data transmission between the super node and this communication node is high, the data sharing is high, and the connectivity between nodes is high, and it can be seen from this Communication nodes in the same community have high encounter frequency, high data sharing, and high data reliability. Under the management of super nodes, efficient data interaction is realized to avoid query flooding and data flooding.

Step S3.2: The super node returns the probability of encountering the communication node to the communication node, wherein the communication node is an ordinary node or a free node outside the community identified by the super node.

As a further embodiment of this embodiment, the attribute information includes encounter probabilities between the communication node and all super nodes and the communities they belong to. A communication node can record the encounter probability between itself and other communication nodes by establishing an encounter probability table, which provides data reference or calculation parameters for super nodes to establish a community.

Usually, information such as the encounter time, disconnection time, connection status, encounter probability, and storage space of each communication node between the super node and all communication nodes that it meets can be recorded in the form of a data probability table and other records.

This embodiment is the layered opportunistic network based on the community described in Embodiment 1. It provides a specific establishment method, which is simple and quick to implement, and makes good use of the community nature of human-carried or vehicle-mounted mobile communication terminal equipment to establish a community A community-based hierarchical opportunity network with closer connection, better connectivity, and high data sharing capabilities between internal communication nodes. Communities communicate through free nodes, preventing data flooding and improving community-based stratification opportunities Efficiency of network distributed storage.

Embodiment three:

On the basis of the previous embodiment, this embodiment provides a preferred method for calculating the encounter probability; the preset method calculates the encounter probability between the super node and the communication node through the following formula;

Preferably, the preset method calculates the encounter probability between the super node and the communication node through the following formula;

$\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span>\left\{\begin{array}{cc}\mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}\\ {\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; init</span>}}& \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}\\ <span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; )</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; contact</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; contact</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; noncontact</span>}}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&lambda;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\frac{{\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; init</span>}}}{{\mathrm{<span\; class="notranslate">\; e</span>}}^{\mathrm{<span\; class="notranslate">\; \&gamma;</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>}}<span\; class="notranslate">\; )</span>& \mathrm{<span\; class="notranslate">\; f</span>}<span\; class="notranslate">\; \&Greater\; Equal;</span>\mathrm{<span\; class="notranslate">\; 2</span>}\end{array}\right.$

P(S,M _n ) is the encounter probability between super node S and communication node M _n ;

f is the total number of encounters between super node S and communication node _Mn .

P _Init is the initial value of the encounter probability;

λ is a constant with a value between 0 and 1;

T _contact is the accumulative duration of meeting between super node S and communication node M _n within the previous preset time; T _noncontact is the accumulative duration of no encounter between super node S and communication node M _n within the previous preset time; if the preset time is T, Then T=T _contact +T _noncontact ;

γ is the adjustment factor.

The preset method described in this embodiment is a special one proposed according to the community attributes of the community-based hierarchical opportunity network to be established in this embodiment, and has the advantages of simple calculation and accurate calculation results.

As a further improvement of this embodiment, this embodiment further provides a calculation method for inter-community connection probability, specifically as follows:

When the free node M _n moving between the community S _i and the community S _j moves to the community S _j managed by the super node S _j , the free node sends the encounter probability of the super node S _i it carries to the community S _j , S _j can calculate the indirect connection probability between S _j and S _i through node M _n through this table as follows:

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; P</span>}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}_{\mathrm{<span\; class="notranslate">\; old</span>}}<span\; class="notranslate">\; +</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; P</span>}{<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}_{\mathrm{<span\; class="notranslate">\; old</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; \&beta;</span>}<span\; class="notranslate">\; )</span>$

By counting the number of free nodes moving between the two communities (that is, between the super nodes S _j and S _i ), the average indirect connection probability between S _j and S _i can be calculated as:

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; Indirect</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; N</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}$

Among them, N(S _i , S _j ) is the total number of nodes between S1 and S2.

Through the above method, the connection and connection between communities can be well calculated, which further strengthens the super node's management of the community-based hierarchical opportunity network.

Embodiment four:

As shown in FIG. 3, the community-based layered opportunistic network communication method of this embodiment includes the following steps:

Step A: The super node establishes a data index table for the data stored by the common nodes in the identified community, establishes a temporary data index table for the data stored by the free node, and copies the data index table of other communities carried by the free node Build an inter-community data index table; in the specific implementation process, ordinary nodes, free nodes and super nodes name the data stored in them according to the preset unified naming rules or numbering rules, so as to facilitate the subsequent retrieval of data

Step B: The ordinary node M submits the search information of the data to be queried to the super node; the index information is index information such as keywords or data storage numbers

Step C: The super node queries in the data index table,

If there is a record in the data index table, the super node will send the identification information of the ordinary node N that stores the data to be queried to the ordinary node M, and the ordinary node M realizes the communication with the ordinary node N through the encounter between the ordinary nodes in its community ;Priority to query the data index table in the community, that is, to share data with the communication nodes in the community in priority. Since the nodes in the community meet frequently, it has the advantages of fast transmission and sharing efficiency, and compared with the traditional method in the whole network query , can provide more high-quality data forwarding and carrying paths faster, avoid unnecessary data forwarding of intermediate communication nodes, thereby reducing the storage pressure of each communication node and improving storage efficiency; wherein the common node N can be one or Multiple communication nodes located in the community;

If there is no record in the data index table, the super node will query whether there is a record in the temporary data index table,

If there is, the super node returns the identification information of the free node O to the ordinary node M, and the ordinary node M communicates with the free node O through the encounter of the communication nodes; if there is no, the super node queries whether there is a record in the inter-community data index table,

If yes, the free node P accesses the ordinary nodes of other communities that store the data to be queried, and the free node P returns the data to the ordinary node M;

If none, the communication fails.

If there is no communication node in the same community that can provide the required data, and then communicate through the free node, on the basis of ensuring the optimal query for data query, it ensures the method of communicating with other communities and nodes outside the community, and ensures the communication based on The data can be queried if it exists in the hierarchical opportunity network of the community, thus ensuring high query efficiency.

In the previous community-based hierarchical opportunistic network, when two communication nodes meet, they first read each other’s encounter probability with other communication nodes. , then transmit the information that needs to be forwarded to the second node; it is a node forwarding carrying transmission mode established between a source node and a destination node, and in the community-based hierarchical opportunistic network described in this embodiment, The node that stores the data can be obtained through the super node. When the data transfer between the nodes is passed, it is the data transfer from one node to multiple nodes. There are more transfer paths, so the stability and reliability of data interaction are higher. Latency is reduced.

Embodiment five:

In this embodiment, on the basis of the previous embodiment, in the step C, the super node also monitors the popularity of each data being queried, and judges whether to establish a copy of the queried data in the common node managed by it or itself according to a predetermined method .

In this embodiment, through the establishment of a data copy, it is prevented that only one source node saves the data, which causes the entire community-based hierarchical opportunity network to lose the data when the node fails or disappears, thereby improving the The community's layered opportunity network data reliability and security.

As a further improvement of this embodiment, this embodiment also provides at least two of the aforementioned preset methods;

First: the predetermined method includes the following steps:

Step C1.1: Calculate P _f and α _i respectively according to the following formulas;

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; f</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; C</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Pi;</span>}}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; m</span>}}_{\mathrm{<span\; class="notranslate">\; no</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>$

${\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; \&delta;\; e</span>}}^{{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; \&theta;\; HD</span>}}_{\mathrm{<span\; class="notranslate">\; I</span>}}}$

P _f is the failure probability of the corresponding data;

C is the number of copies of data in the corresponding community;

P(S,M _n ) is the encounter probability between super node S and communication and node M _n this time;

Heat HD _I is the number of times the corresponding data is queried per unit time;

The dynamic factor α _i characterizes the maximum failure probability allowed by the corresponding data;

δ is the data reliability assurance parameter; θ is the adjustment factor;

Step C1.2, the super node judges the size of P _f and α _i , and when P _f > α _i , then the super node creates a copy of the queried data in the ordinary node managed by it or itself, and finally can judge P Whether _f ≤ α _i holds true, decides whether to stop creating copies.

This default method is preferentially used for data copies during communication between ordinary nodes in the same community, and usually the data copies are established on ordinary nodes with sufficient remaining storage space, which not only ensures the reliability of the data, but also ensures that each communication node load balancing.

Second: the predetermined method is a hotness threshold determination method, if the hotness of the queried data is greater than the threshold, a copy of the queried data will be established on the common node managed by it or itself. The number of copies created can be determined according to the threshold value of the average popularity of each copy.

The threshold judgment method can also be used to judge whether it is necessary to establish a copy of the queried data, but it is usually used between communities, that is, if the number of times a node outside the community queries a data in the community reaches a certain upper limit, a copy will be established in the community , and the copy is usually established on the super node, and the nodes outside the community can realize the data interaction through the encounter between the free node and the super node, which further simplifies the transmission path and improves the effectiveness of data acquisition.

The above two methods can be used to establish a copy of the queried data. Supernodes can choose only one of the methods during specific operation, or apply both methods at the same time. For example, in the community, the first failure probability and The method of dynamic factor comparison, the second method of heat threshold judgment is used among communities.

Embodiment six:

In this embodiment, on the basis of any one of the above-mentioned communication methods for community-based hierarchical opportunistic networks, the step A also includes the super node monitoring the connection status of each node communicating with it in real time, and according to each communication node The sub-steps of updating the data index table, temporary data index table, and inter-community data index table in real time.

Ordinary nodes move in real time in the community. Free nodes may enter the community and become ordinary nodes, or they may enter a community and can no longer communicate with the super nodes of this community. Ordinary nodes may also move out of the community and become The free nodes connected by the community need to update the data index table, temporary data index table, and community see data index table in a timely manner to ensure that the references found are accurate and will not become free nodes because of ordinary nodes. Most of the time it is not possible to communicate with the nodes in the community, resulting in unreliable communication. The update includes actions such as adding an index, deleting an index, and rewriting an index.

The above embodiments are only used to illustrate the present invention, but not to limit the present invention. Those of ordinary skill in the relevant technical field can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, all Equivalent technical solutions also belong to the category of the present invention, and the scope of patent protection of the present invention should be defined by the claims.

Claims (4)

1. a community-based laminating machine meeting network creating method, it is characterised in that described community-based laminating machine can net Network method for building up comprises the following steps:

Step S1: communication node in its communication range of super node real-time detection also reads the attribute letter entrained by communication node Breath；

Step S2: super node is calculated and the collision probability of each described communication node by presetting method；

Step S3: it is super with other more than this communication node with the collision probability of this communication node that super node compares himself The collision probability of level node,

It is more than, then enters step S3.1, be not more than and then enter step S3.2；

Step S3.1: this communication node is set to the ordinary node managed by it by super node, is identified by it in order to set up Community, and its collision probability with this communication node is returned to this communication node；

Step S3.2: itself and this communication node collision probability are returned to this communication node, wherein, this communication node by super node Ordinary node outside by the identified community of described super node or free node；Wherein, described presetting method passes through equation below Calculate collision probability between super node and communication node；

$P(S,M_n)=\left\{\begin{array}{ccc}0& & f=0\\ P_{init}& & f=1\\ (1-\mathrm{\&lambda;})\frac{T_{contact}}{T_{contact}+T_{noncontact}}+\mathrm{\&lambda;}& (1-\frac{1-P_{init}}{e^{\mathrm{\&gamma;}(f-2)}})& f\&GreaterEqual;2\end{array}\right.$

P(S,M_n) it is super node S and communication node M_nCollision probability；

F is super node S and communication node M_nThe total degree that meets；

P_InitInitial value for collision probability；

λ is value constant between 0 to 1；

T_contactFor super node S in Preset Time before this and communication node M_nThe accumulative duration met；T_noncontactFor the most pre- If super node S and communication node M in the time_nUnmet accumulative duration；

γ is Dynamic gene；

Wherein, described attribute information includes the collision probability between this communication node and all super nodes and affiliated community thereof.

2. a community-based laminating machine meeting network communication method, it is characterised in that described community-based laminating machine can net Network communication means comprises the following steps:

Step A: the data stored by the ordinary node in its identified community are set up data directory, to trip by super node The data stored from node set up ephemeral data concordance list, and replicate the data directory of free other communities entrained by node Table builds data directory between community；

Step B: the retrieval information of data to be checked is submitted to super node by ordinary node M；

Step C: super node is inquired about in data directory,

If data directory has record, storage is had the identification information of the ordinary node N of these data to be checked to send by super node The communication with ordinary node N is realized by meeting between the ordinary node in its place community to ordinary node M, ordinary node M；

If data directory no record, super node inquires about whether have record in ephemeral data concordance list,

Have, then super node returns the identification information of free node O, the ordinary node M phase by communication node to ordinary node M Meet and communicate with free node O；

Nothing, super node inquires about whether have record between community in data directory,

Have, then access, by free node P, the ordinary node that storage has other communities of these data to be checked, and by free node P returns data to ordinary node M；

Nothing, then communication failure；

Wherein, described community-based laminating machine network packet can contain some communities；All including in each described community is commonly saved Put and in order to identify community and the super node of management ordinary node communication.

Community-based laminating machine the most according to claim 2 meeting network communication method, it is characterised in that

In described step C, super node also monitors the temperature that each data are queried, and judges whether by it according to preordering method The ordinary node of management or himself foundation are queried data trnascription；Described preordering method comprises the following steps:

Step C1.1: calculate P according to equation below respectively_fAnd α_i；

$P_f=\underset{n=1}{\overset{C+1}{\&Pi;}}(1-P(S,M_n\left)\right)$

${\mathrm{\&alpha;}}_i={\mathrm{\&delta;e}}^{-{\mathrm{\&theta;HD}}_I}$

P_fFailure probability for its corresponding data；

C is the number of copies of data in the community that it is corresponding；

P(S,M_n) it is super node S and storage has the communication node M of data to be checked_nCollision probability；

Temperature HD_IThe number of times being queried for its corresponding data in the unit time；

Dynamic factor α_iCharacterize the maximum failure probability that its corresponding data allow；

δ is that data reliability ensures parameter；θ is Dynamic gene；

Step C1.2, super node judges P_fWith α_iSize, and work as P_f>α_iTime, super node is at the ordinary node managed by it Or himself set up this copy being queried data.

4. according to the community-based laminating machine meeting network communication method described in Claims 2 or 3, it is characterised in that described step Rapid A also including, the real-time monitoring of super node communicates with the connection state of each node, and according to the operation of each communication node What situation was instant updates the sub-step of data directory between data directory, ephemeral data concordance list and community.