CN109168183B - Opportunistic network multicast routing method based on mobile features and social relations - Google Patents

Opportunistic network multicast routing method based on mobile features and social relations Download PDF

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CN109168183B
CN109168183B CN201810862398.8A CN201810862398A CN109168183B CN 109168183 B CN109168183 B CN 109168183B CN 201810862398 A CN201810862398 A CN 201810862398A CN 109168183 B CN109168183 B CN 109168183B
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CN109168183A (en
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陶军
徐晓星
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Southeast University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/20—Communication route or path selection, e.g. power-based or shortest path routing based on geographic position or location
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/14—Routing performance; Theoretical aspects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/16—Multipoint routing

Abstract

The invention discloses an opportunistic network multicast routing method based on mobile features and social relations, which comprises the following steps: dividing a target area into a plurality of geographical areas according to geographical positions, numbering the geographical areas one by one to obtain geographical labels, and acquiring a log record file of an access device (AP) to construct a Trace data set; calculating the probability of different geographical labels of each node in the network, selecting K geographical labels to form a geographical label set of the nodes, and combining to construct a geographical label table; constructing an encounter relation table of the nodes according to the constructed Trace data set and the geographical tag table; when two nodes meet, updating the meeting relation table; and according to the constructed geographic label table P and the encounter relation table, the multicast routing algorithm is adopted to carry out split forwarding on each multicast message in the nodes. The invention comprehensively considers the relationship between the mobile characteristics of the nodes and the social attributes, obviously improves the delivery success rate of the multicast messages in the opportunity network and reduces the delivery time delay.

Description

Opportunistic network multicast routing method based on mobile features and social relations
Technical Field
The invention relates to an opportunistic network multicast routing method based on mobile features and social relations, and belongs to the technical field of wireless communication technologies.
Background
Compared with the traditional wireless self-organizing network, the opportunity network emphasizes the meeting opportunity brought by the node mobility, provides data communication service for the non-completely connected network region, can realize data communication under harsh network conditions, and is more suitable for the requirements of self-organizing network in actual scenes. In general, nodes in the opportunistic network are not uniformly deployed, the initial positions of the nodes and the network scale are unknown, and a predicted communication path does not exist between a source node and a destination node. The connection between networks is mainly established by moving nodes into mutual communication range, and information exchange is carried out by adopting a mode of 'storage-carrying-forwarding' asynchronous routing.
The current multicast routing method in the opportunistic network mainly comprises the following schemes: 1) flooding, the message can be copied and forwarded indefinitely throughout the network, eventually reaching all destination nodes. 2) In the multicast routing method based on the mobile characteristics, the algorithm mainly utilizes the distribution information of the nodes to estimate the meeting probability and completes the processes of route discovery and data forwarding on the basis. 3) The multicast routing method based on the social information is characterized in that the algorithm extracts social characteristics of nodes in real time by analyzing the encounter history of users, and completes the processes of route discovery and data forwarding according to the social characteristics.
The inventor finds that the above schemes have disadvantages in the research process: in the first scheme, each encounter opportunity brings about message replication and forwarding, and excessive message redundancy causes large routing overhead of the algorithm. The second scheme and the third scheme are both concerned only with two single attributes of the mobile characteristics or the social relations of the nodes, and the relations between the mobile characteristics and the social relations of the nodes are not comprehensively considered, so that the mobile and social behaviors of the nodes cannot be comprehensively described.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art, provide an opportunistic network multicast routing method based on mobile characteristics and social relations, and solve the problems that the multicast routing method in the prior opportunistic network needs larger routing overhead, does not comprehensively consider the relations between the mobile characteristics of nodes and the social relations, and cannot comprehensively describe the mobile and social behaviors of the nodes. The invention comprehensively considers the mobile characteristics and social attributes of the nodes, improves the delivery success rate of the multicast messages in the opportunity network and reduces the delivery time delay.
The invention specifically adopts the following technical scheme to solve the technical problems:
an opportunistic network multicast routing method based on mobile features and social relations, comprising the following steps:
step 1, performing area division on a target area according to geographical positions, dividing the target area into a plurality of geographical areas, numbering the geographical areas one by one to obtain each geographical label, and acquiring a log record file of an access device AP in each geographical area to construct a Trace data set;
step 2, calculating the probability of different geographic labels of each node in the network according to the constructed Trace data set, selecting K geographic labels to form a geographic label set TL of the node, and combining the geographic label sets TL of all the nodes to construct a geographic label table P;
step 3, constructing an encounter relation table of the nodes according to the constructed Trace data set and the geographic tag table P;
step 4, when two nodes meet, updating the meeting relation table; and according to the constructed geographic label table P and the encounter relation table, the multicast routing algorithm is adopted to carry out split forwarding on each multicast message in the nodes.
Further, as a preferred technical solution of the present invention, the Trace data set in step 1 includes a node number, a node encounter time, an access device AP number, and a geographic tag.
Further, as a preferred technical solution of the present invention, in the step 2, the probability that each node appears in different geographical labels in the network is calculated, and the node miAppear in the geotag ljProbability p ofijThe formula is adopted:
Figure BDA0001750026010000021
wherein T is node miTotal time of occurrence in the network, njIs node miAppear in the geotag ljTotal number of times of (ct)jsIs node miOccurrence at geographic tag l for the s-th timejTime of (d).
Further, as a preferred technical solution of the present invention, the encounter relationship table of the nodes in step 3 includes node numbers, geographical labels, node sets, and encounter time intervals.
Further, as a preferred technical solution of the present invention, the splitting and forwarding each multicast message in the nodes in step 4 by using a multicast routing algorithm includes:
step 41, if there are two nodes maAnd mbMeet, judge meeting node mbWhether there is a multicast message to proceedForwarding, if yes, entering step 42, otherwise ending the message split forwarding;
step 42, extracting node mbIntegrating a target node set D of the extracted multicast message to construct a geographic label set MTL corresponding to the multicast message;
step 43, judge node maAnd mbGeographic tag l of where the encounter iscWhether it belongs to the geographical label set MTL: if the geographic label lcIf not, respectively calculating the nodes m according to the constructed geographic label table PaNode mbGeographic utility GU with all destination nodes in multicast messageaAnd GUb(ii) a If the geographic label lcIf the node belongs to the geographic label set MTL, the node m is respectively calculateda、mbSocial utility SU with all destination nodes in a multicast messageaAnd SUb；
If calculated geographic utility GUa≤GUbOr social utility SUa≤SUbStep 44 is entered, otherwise, the multicast message is not forwarded;
step 44, respectively node maAnd node mbConstructing a set DaAnd DbFor any one destination node m in the destination node set DiObtain its geotag set TLi；
And judging node maAnd mbGeographic tag l of where the encounter iscWhether or not to belong to the geotag set TLi: if the geographic label lcNot belonging to the set of geotags TLiThen respectively calculate the node ma、mbWith destination node miGeographical similarity between GSa、GSb(ii) a If the geographic label lcBelong to a set of geotags TLiThen respectively calculate the node ma、mbWith destination node miSocial affinity SC ofa、SCb；
If calculated geographical similarity GSa≥GSbOr social affinity SCa≥SCbThen add the destination node to the set DaPerforming the following steps; otherwise, adding the destination node into the set DbPerforming the following steps;
according to set DaGenerating a new multicast message to join node maIn the cache of (2); and according to set DbGenerating a new multicast message to join node mbIn the cache of (2).
Further, as a preferred technical solution of the present invention, the step 42 further includes a node mbCheck if its own cache contains node maThe extracted multicast message is merged into a node m if the multicast message contains the multicast messagebThe multicast message and node maThe destination node of the extracted multicast message generates a target node set, otherwise, the node m is directly usedaThe destination node in the extracted multicast message generates a set of destination nodes.
By adopting the technical scheme, the invention can produce the following technical effects:
the method of the invention establishes a Trace data set by collecting the log record files of APs of the access equipment, evaluates the forwarding capability of the node by integrating the mobile characteristics and the social attributes, and takes the forwarding capability as the basis for selecting the next hop node. The present invention is based on a single copy model, where only one copy is kept for each destination node, but multiple nodes are allowed to own multicast messages. The invention is based on a comparison-splitting mechanism, which mainly comprises two parts, wherein the comparison part determines whether a destination node set needs to be split into subsets to be respectively distributed to two mobile nodes according to the overall mobile characteristics and social attributes, and the splitting part splits the node set according to the mobile characteristics and social attributes of a meeting node and the destination node.
Therefore, compared with the prior art, the invention has the following advantages:
1) according to the invention, a Trace data set is established by utilizing the log record file of the APs, the geographic utility, the geographic similarity, the social utility and the social affinity are calculated through the Trace data set, and the mobile characteristics and the social relationship of the nodes can be well quantified.
2) The invention optimizes the contents of geographic information and social relationship by selecting the first K popular geographic labels, and can effectively reduce the maintenance and updating cost and provide data support for a data forwarding algorithm.
3) The method comprehensively considers the mobile characteristics and the social relationship of the nodes, determines whether to compare and split the multicast messages for forwarding by comparing the geographic utility with the social utility, determines the nodes for forwarding by comparing the geographic similarity with the social affinity, and can effectively split the multicast messages into different sets for forwarding. The method comprehensively considers the relationship between the mobile characteristics of the nodes and the social attributes, obviously improves the delivery success rate of the multicast messages in the opportunity network, and reduces the delivery delay.
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Fig. 1 is a diagram of an application scenario of the embodiment of the present invention.
FIG. 2 is a message type of the log file of the present invention.
FIG. 3 is a visualization of the encounter relationship of the present invention.
Fig. 4 is a flow chart of a multicast routing algorithm of the present invention.
Detailed Description
The following describes embodiments of the present invention with reference to the drawings.
The invention provides an opportunistic network multicast routing method based on mobile characteristics and social relations. Specifically, the method comprises the following steps:
step 1, carrying out regional division on a target region according to geographic positions to divide the target region into a plurality of geographic regions
Figure BDA0001750026010000041
Numbering one by one to obtain the geographic labels l of all geographic areasjAnd collecting log record files of access equipment APs in each geographic area to construct a Trace data set.
As shown in fig. 1, an application scenario-campus of an embodiment of the present invention is described, where the campus is divided into a plurality of areas and then geographic tags of the areas are obtained, for example, 20 represents a teaching building, 7 represents a library, 16 represents a dining room, and 24 represents a computer building. Each building is full of access devices AP, the message types of the access devices AP are shown in fig. 2, and the log record files of APs mainly include 5 message types. Firstly, when a new wireless device is accessed into a campus network, an AP records information (APMG-6-STA-ADD) containing a device MAC address and access time; secondly, when a wireless device is switched from one AP to another AP, the current AP records a message (ROAMING-6-ROAM _ EVENT) containing a ROAMING EVENT; in addition, when the wireless device disconnects the network, the last connected AP also records a message (APMG-6-STA _ DEL) of leaving the network. In addition, when the mobile device is connected to an AP as a node for a long time, the AP records the hotspot switching information through the APMG-6-STA _ CHANGE message, and re-acquires the access state of the node through the APMG-6-STA _ UPDT message. By analyzing the contents of the log files, node meeting records containing geographic information are extracted from the log files, and a Trace data set in a real scene is constructed on the basis of the node meeting records, wherein the format of the data set is as follows:
Figure BDA0001750026010000051
the specific content of the data set mainly comprises a node number, an encounter time, an AP number and a geographic tag.
Step 2, aiming at the node set according to the constructed Trace data set
Figure BDA0001750026010000054
Calculating the probability of each node appearing in a different geotag in the network, i.e. using a formula
Figure BDA0001750026010000052
To calculate the probability that each node appears at a different geotag, where T is node miTotal time of occurrence in the network, njIs node miAppear in the geotag ljTotal number of times of (ct)jsIs node miOccurrence at geographic tag l for the s-th timejTime of (d). And selecting K most frequently visited geographical labels to form a geographical label set TL of the nodes, and combining the geographical label sets TL of all the nodes to construct a geographical label table P. The constructed geotag table P is as follows:
Figure BDA0001750026010000053
the geotag table includes the first K popular geotags selected by each node and the probability of the occurrence of the geotags, and the value of K is 3 in this embodiment.
And 3, constructing an encountering relation table of the nodes according to the constructed Trace data set and the geographical tag table P.
In order to conveniently establish an encounter relationship graph of nodes, the Trace data set is visualized in the invention, as shown in the graph at the left half part of fig. 3, the encounter history of the node a is visualized, and the encounter relationship graph of the node a is established through the encounter history as follows:
Figure BDA0001750026010000061
the information contained in the encounter relationship graph includes node number, geotag, node set, and encounter time interval. When two nodes meet, the meeting relations corresponding to their common geographic labels need to be exchanged, as shown in the right half-view of fig. 3, the node a and the node B meet in the computer building, the node a can obtain more meeting relation information from the node B to expand the social relations between the teaching building and the laboratory, and finally the meeting relation table of the node a is as follows:
Figure BDA0001750026010000062
step 4, at two nodes maAnd mbWhen meeting, namely two nodes can use the device-to-device mode to communicate, updating a meeting relation table; and according to the constructed geographic label table P and the encounter relation table, the node m is matchedaAnd mbEach multicast message in the cache is compared and split by the multicast routing algorithm, as shown in fig. 4, node maMulticast routing message msg injThe multicast routing steps of (1) are as follows:
step 41, if there are two nodes maAnd mbMeet, judge meeting node maIf there is multicast message to transmit, if yes, go to step 42, otherwise, end the message split transmission;
step 42, if maTo forward a message msgjThen, m needs to be determinedbWhether there is this multicast message, i.e. node mbChecking if its buffer contains multicast routing message msgjIf the multicast message msg is already containedjThen merge node mbThe multicast message and node maThe destination node of the extracted multicast message generates a set of destination nodes
Figure BDA0001750026010000073
Otherwise directly using multicast message msgjThe target node in (2) generates a target node set D, and a geographic label set MTL corresponding to the message and a weight corresponding to each label are constructed according to the target node set D. The geographic label set MTL specifically comprises:
Figure BDA0001750026010000074
and the weight value corresponding to each label is
Figure BDA0001750026010000071
Wherein
Figure BDA0001750026010000075
For the destination node dsAppear in the geotag lsProbability of (A), NDRefers to the number of target nodes.
In particular, assume that the destination node includes d1、d2And d3Destination node d1、d2And d3Are {7(0.5),20(0.2),24(0.2) }, {1(0.3),6(0.4),19(0.1) } and {16(0.1),20(0.5),24(0.2) }, so that the set of geotags corresponding to the one multicast message is MTL {1(0.3),6(0.4),7(0.5),16(0.1),19(0.1),20(0.7),24(0.4) }.
And step 43, judging whether the message is split or not. First, a node m is judgedaAnd mbGeographic tag l of where the encounter iscWhether it belongs to the geographical label set MTL:
if the geographic label lcNot belonging to the set of geotags MTL, i.e.
Figure BDA0001750026010000076
Respectively calculating nodes m according to the constructed geographic label table PaNode mbGeographic utility GU with all destination nodes in multicast messageaAnd GUb(ii) a If the geographic label lcIf the node belongs to the geographic label set MTL, the node m is respectively calculateda、mbSocial utility SU with all destination nodes in a multicast messageaAnd SUb. If calculated geographic utility GUa≤GUbOr social utility SUa≤SUbStep 44 is entered, otherwise the multicast message is not forwarded.
Specifically, assume node maAnd mbMeeting in the geographic label 2, the MTL is the geographic label set constructed in the step 43, the geographic label 2 does not belong to the MTL, and the formula is used
Figure BDA0001750026010000072
Calculate node m separatelyaGeographic utility of GUaAnd node mbGeographic utility of GUbWhere K is the destination node miNumber of selected geotags, pisFor destination node miAppear in the geotag lsProbability of (MTL)jFor multicast messages msgjCorresponding toA set of geo-tags is provided,
Figure BDA0001750026010000085
a weight for each geotag. If the calculated GUa≤GUbThen step 44 is performed, otherwise the message is not forwarded.
If node maAnd mbWhen the geographic labels 16 meet, the geographic labels 16 belong to a geographic label set MTL, and the nodes m are respectively calculatedaSocial utility SU with all destination nodes in a multicast messageaAnd node mbSocial utility SU with all destination nodesb. When calculating the social effect, firstly, the meeting relation table is used for constructing a social affinity table between nodes. In particular, the encounter relationship table is used to find the miTo mjHaving n paths, hkIs the hop count of the kth path, schIs the direct social affinity between two nodes corresponding to the h-th hop, which is determined by a formula
Figure BDA0001750026010000081
Calculated to obtain, ICTijIs the encounter interval time recorded in the encounter relationship table,
Figure BDA0001750026010000086
if the calculated weight of k-route is adopted, the social affinity of the two nodes is
Figure BDA0001750026010000082
Node maThe social affinity table is as follows:
Figure BDA0001750026010000083
using the formula
Figure BDA0001750026010000084
Calculate node m separatelya、mbSocial utility with all destination nodes in a multicast message, where NDjIn multicast messagesThe number of the destination nodes is compared with the social utility of the destination nodes, and if the social utility is calculated, the SU is obtaineda≤SUbThen step 44 is performed, otherwise the message is not forwarded.
And step 44, splitting and recombining the multicast message. First, respectively, node maAnd node mbConstructing a set DaAnd DbFor storing the drop node maAnd mbTo form a new multicast message. Aiming at any one destination node m in the destination node set DiObtain its geotag set TLi。
Then, the node m is judgedaAnd mbGeographic tag l of where the encounter iscWhether or not to belong to the geotag set TLi: if the geographic label lcNot belonging to the set of geotags TLiThen respectively calculate the node ma、mbWith destination node miGeographical similarity between GSa、GSb(ii) a If the geographic label lcBelong to a set of geotags TLiThen respectively calculate the node ma、mbWith destination node miSocial affinity SC ofa、SCb(ii) a If calculated geographical similarity GSa≥GSbOr social affinity SCa≥SCbThen add the destination node to the set DaPerforming the following steps; otherwise, adding the destination node into the set DbPerforming the following steps; according to set DaGenerating a new multicast message to join node maIn the cache of (2); and according to set DbGenerating a new multicast message to join node mbIn the cache of (2).
In particular, destination node miOf a set of geotags TLiIs {7(0.5),20(0.2),24(0.2) }, if node maAnd mbUpon encounter with geotag 2, the formula is used
Figure BDA0001750026010000091
Calculate node m separatelyaAnd mbWith destination node miGeographic similarity GS ofaAnd GSb，pilAnd pjlAre respectively node miAnd mjProbability of appearing at a certain common geotag i. If GSa≥GSbThen add the destination node to the set DaPerforming the following steps; otherwise, adding the destination node into the set DbIn (1). If node maAnd mbWhen the geographic tags 7 meet, the node m is calculatedaAnd mbWith destination node miSocial affinity SC at geo-tag 7aAnd SCbThe calculation is carried out in the same manner as described in 2), if SCa≥SCbThen add the destination node to the set DaPerforming the following steps; otherwise, adding the destination node into the set DbIn (1). After all destination node splits are completed, according to set DaGenerating a new multicast message to join node maIn the cache of (2); according to set DbGenerating a new multicast message to join node mbAnd (4) caching, and ending the operation of the round.
In conclusion, the invention comprehensively considers the relationship between the mobile characteristics of the nodes and the social attributes, obviously improves the delivery success rate of the multicast messages in the opportunity network and reduces the delivery delay.
The embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.

Claims (5)

1. An opportunistic network multicast routing method based on mobile features and social relations is characterized by comprising the following steps:
step 1, performing area division on a target area according to geographical positions, dividing the target area into a plurality of geographical areas, numbering the geographical areas one by one to obtain each geographical label, and acquiring a log record file of an access device AP in each geographical area to construct a Trace data set;
step 2, calculating the probability of different geographic labels of each node in the network according to the constructed Trace data set, selecting K geographic labels to form a geographic label set TL of the node, and combining the geographic label sets TL of all the nodes to construct a geographic label table P;
step 3, constructing an encounter relation table of the nodes according to the constructed Trace data set and the geographic tag table P;
step 4, when two nodes meet, updating the meeting relation table; and according to the constructed geographic label table P and the encounter relation table, the multicast routing algorithm is adopted to carry out split forwarding on each multicast message in the nodes, and the method comprises the following steps:
step 41, if there are two nodes maAnd mbMeet, judge meeting node maIf there is multicast message to transmit, if yes, go to step 42, otherwise, end the message split transmission;
step 42, extracting node maIntegrating a target node set D of the extracted multicast message to construct a geographic label set MTL corresponding to the multicast message;
step 43, judge node maAnd mbGeographic tag l of where the encounter iscWhether it belongs to the geographical label set MTL: if the geographic label lcIf not, respectively calculating the nodes m according to the constructed geographic label table PaNode mbGeographic utility GU with all destination nodes in multicast messageaAnd GUb(ii) a If the geographic label lcIf the node belongs to the geographic label set MTL, the node m is respectively calculateda、mbSocial utility SU with all destination nodes in a multicast messageaAnd SUb；
The geographic utility of the computing node and all destination nodes in the multicast message adopts a formula:
Figure FDA0003069314340000011
Figure FDA0003069314340000012
in the formula, K is the destination node miNumber of selected geotags, pisFor destination node miAppear in the geotag lsProbability of (MTL)iFor multicast messages msgjA set of corresponding geo-tags that are,
Figure FDA0003069314340000013
for geographical labels lsThe weight of (c);
wherein the social utility SU of the computing node and all destination nodes in the multicast messageijThe formula is adopted:
Figure FDA0003069314340000014
in the formula, NDjRefers to the number of destination nodes in the multicast message,
Figure FDA0003069314340000015
is node miAnd node msSocial affinity between;
if calculated geographic utility GUa≤GUbOr social utility SUa≤SUbStep 44 is entered, otherwise, the multicast message is not forwarded;
step 44, respectively node maAnd node mbConstructing a set DaAnd DbFor any one destination node m in the destination node set DiObtain its geotag set TLi；
And judging node maAnd mbGeographic tag l of where the encounter iscWhether or not to belong to the geotag set TLi: if the geographic label lcNot belonging to the set of geotags TLiThen respectively calculate the node ma、mbWith destination node miGeographical similarity between GSa、GSb(ii) a If the geographic label lcBelong to a set of geotags TLiThen calculate the section respectivelyPoint ma、mbWith destination node miSocial affinity SC ofa、SCb(ii) a Wherein, the computing node and the destination node miThe geographical similarity between the two is determined by the following formula:
Figure FDA0003069314340000021
in the formula, pilAnd pjlRespectively a destination node miAnd node mjProbability of occurrence in the same geographic label L, LijIs node miAnd node mjA common set of geotags;
wherein, the computing node and the destination node miThe social affinity between the two people is determined by the following formula:
Figure FDA0003069314340000022
in the formula, n is the destination node miTo node mjNumber of paths of, hkIs the hop count of the kth path, schIs the direct social affinity between two nodes corresponding to the h-th hop; beta is ahkIs the calculated weight of k-route;
if calculated geographical similarity GSa≥GSbOr social affinity SCa≥SCbThen add the destination node to the set DaPerforming the following steps; otherwise, adding the destination node into the set DbPerforming the following steps;
according to set DaGenerating a new multicast message to join node maIn the cache of (2); and according to set DbGenerating a new multicast message to join node mbIn the cache of (2).
2. The opportunistic network multicast routing method based on mobile features and social relations according to claim 1, wherein the Trace data set in step 1 comprises a node number, a node encounter time, an access device (AP) number and a geographical label.
3. The opportunistic network multicast routing method based on mobile features and social relations according to claim 1, wherein the probability p that each node appears in different geographical labels in the network is calculated in step 2ijThe formula is adopted:
Figure FDA0003069314340000031
wherein T is node miTotal time of occurrence in the network, njIs node miAppear in the geotag ljTotal number of times of (ct)jsIs node miOccurrence at geographic tag l for the s-th timejTime of (d).
4. The opportunistic network multicast routing method based on mobile features and social relationships according to claim 1, wherein the encounter relationship table of nodes in step 3 comprises node numbers, geographical labels, node sets and encounter time intervals.
5. The mobile feature and social relationship based opportunistic network multicast routing method of claim 1 wherein the step 42 further comprises node mbCheck if its own cache contains node maThe extracted multicast message is merged into a node m if the multicast message contains the multicast messagebThe multicast message and node maThe destination node of the extracted multicast message generates a target node set D, otherwise, the node m is directly usedaThe destination node in the extracted multicast message generates a set of destination nodes D.
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