CN102118884A - Data transmission method for opportunistic mobile sensor network based on closeness centrality - Google Patents

Data transmission method for opportunistic mobile sensor network based on closeness centrality Download PDF

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CN102118884A
CN102118884A CN2011100737086A CN201110073708A CN102118884A CN 102118884 A CN102118884 A CN 102118884A CN 2011100737086 A CN2011100737086 A CN 2011100737086A CN 201110073708 A CN201110073708 A CN 201110073708A CN 102118884 A CN102118884 A CN 102118884A
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CN102118884B (en
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牛建伟
郭锦铠
童超
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Beihang University
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Abstract

The invention relates to a data transmission method for an opportunistic mobile sensor network based on closeness centrality. An opportunistic mobile sensor network consisting of a plurality of sink nodes and sparsely distributed sensor nodes is taken as an application scene, wherein the sensor nodes are used for periodically collecting data during movement, the same time period is set for each sensor node, the interval time when each sensor node meets the sink nodes at the previous time and within the current time period is recorded, then the expected transmission delay and the closeness centrality for each sensor node are calculated, and the data transmission is determined by judging the closeness centrality when the sensor node meets the sink nodes. By adopting the method, the success ratio of data transmission is improved, and the transmission delay is remarkably shortened.

Description

A kind of based on chance mobile sensor network data transmission method near centrad
Technical field
The invention belongs to the communications field, be specifically related to a kind of based on chance mobile sensor network data transmission method near centrad.
Background technology
The chance mobile sensor network is development on the basis of wireless sensor network and time-delay tolerance network, and common between the source node that is characterized in data communication and sink (converging) node do not have a communication path end to end.Therefore, the pattern based on setting up sensor node transmission data after the route of sink node earlier of traditional wireless sensor networks can't be moved.In the chance mobile sensor network, transfer of data adopts the pattern of " storing-carry-transmit ", utilizes sensor node to move the chance forwarded hop-by-hop data of meeting of formation, until running into the sink node.Described sink node is the aggregation node that is positioned at the fixed position, can analyze, handle the data of receiving from sensor node.
The chance mobile sensor network has many typical application scenes, detects network ZebraNet as wild animal, organizes In-vehicle networking CarTel certainly, mobile device self-organizing network etc.The ZebraNet project is proposed by the Princeton University, collects them migrate characteristic information on wide prairie by being deployed in sensor node on the zebra neck.Transfer of data adopts the forwarding mechanism based on history, and each sensor node is safeguarded a collision probability to the sink node, the cell on wheels that sink node described herein regularly passes through for the researcher.When zebra and sink node met and successfully transmit data, the collision probability of the sensor node that this zebra is entrained just increased, otherwise collision probability can constantly reduce as time passes.When the two sensors node met, the sensor node that collision probability is lower was given the higher sensor node of collision probability with data forwarding.CarTel is the information gathering and the delivery system based on vehicle sensors of the MIT of Massachusetts Institute of Technology exploitation, can be used in environmental monitoring, road conditions collection, vehicle diagnostics and route guidance etc.By using wireless communication technologys such as Wi-Fi or BlueTooth, CarTel node direct swap data when vehicle meets.Simultaneously, the CarTel node also can send to server on the Internet by the wireless access in the roadside data of naming a person for a particular job.
Wang Yu etc. have proposed a kind of based on the data forwarding mechanism of improving ZebraNet at abstract chance mobile sensor network model DFT-MSN (delay/fault tolerant mobile sensor network).The collision probability of each sensor node not only increases when meeting with the sink node, and also increases when meeting with high other sensor nodes of collision probability, but this mechanism is easy to produce a large amount of redundancy messages.Other has the scholar to propose a kind of new chance data collection mechanism SCAR (sensor context-aware routing).The collision probability of each node association comprises the definition of node neighbours rate of change, energy etc. in the SCAR mechanism based on the node contextual information, and utilize Kalman filtering to predict the variation of node contextual information, estimate its collision probability based on multiple attribute utility theory, as the foundation of node forwarding.
Scholars such as Shah have proposed Data Mule method and have collected sparse static sensor netting index certificate, and Mule mobile agent agent moves in the observation area, collect the sensing data of near zone, and upload data when running into the sink node.But this method only proposes a transmission architecture, does not study how to transmit message between the node in great detail.
But said method mostly suppose sensor node when generating message known and specify message go to specific sink node, do not consider to exist in the practical application scene situation of a plurality of sink nodes.For example in the aware application of city, handheld device can be uploaded to a plurality of servers with perception data by being deployed in a plurality of AP in incity, city (Access Point, access point).So said method can not well be applied in the actual chance mobile sensor network.
Summary of the invention
The present invention is directed to the problem of present shortage, propose a kind of based on chance mobile sensor network data transmission method near centrad at the transfer of data of the chance mobile sensor network of many sink node scene.
A kind of based on chance mobile sensor network data transmission method near centrad, the chance mobile sensor network of forming with the sensor node of a plurality of sink of converging nodes and some sparse distribution is an application scenarios, sensor node is regular image data in moving process, specifically carries out transfer of data by following step:
Step 1: for each sensor node is all set a same time cycle.
Step 2: upgrade the sink node that run in each cycle sensor node current time and with the sink node record of all previous blanking time of meeting, if sensor node i once met n time with sink node j in current period, be respectively each blanking time of meeting: T 1, T 2..., T n
Step 3: when each time cycle finishes, upgrade the expectation transmission delay of each sensor node, the expectation transmission delay D of sensor node i and sink node j with respect to each sink node that meets i(j) be:
D i ( j ) = α × D i old ( j ) + ( 1 - α ) × D i cur ( j ) , D i cur ( j ) = Σ i = 1 n T i n
Wherein, The expectation transmission delay in cycle current time of expression sensor node i and sink node j, Be the expectation transmission delay that sensor node i and sink node j upgraded in last cycle time, parameter alpha ∈ [0,1] is used for regulating With
Figure BDA0000052079320000026
Weight.
Step 4: after having upgraded the expectation transmission delay of each sensor node, obtain each sensor node near centrad, sensor node i near centrad C (i) is:
C ( i ) = k - 1 Σ j - 1 k D i 2 ( j )
Wherein, k is the number of the sink node that runs into of node i.
Step 5: when sensor node i meets with node l in moving process, whether sensor node i decision node l is the sink node, if, execution in step 6; If not, change step 7 and carry out.
Step 6: sensor node i sends to sink node l successively with the data in self buffer area, changes step 2 and carries out.
Step 7: the size that compares sensor node i near centrad C (l) near centrad C (i) and sensor node l, if C (i)＞C (l), then sensor node l sends to sensor node i with the data on self buffer area, if C (l)＞C (i), then sensor node i sends to sensor node l with the data on self buffer area, if C (l)=C (i) does not then transmit mutually; Changeing step 2 then carries out.
The advantage and the good effect of chance mobile sensor network data transmission method of the present invention are: (1) introduces the expectation transmission delay model of movable sensor node and a plurality of sink nodes, propose the calculating and the update strategy of expectation transmission delay, make the inventive method can be applied to real opportunities mobile sensor network scene; (2) adopt community network near the theoretical average degree of closeness of investigating movable sensor node and all sink nodes of centrad, sensor node big more near centrad, the blanking time of on average meeting that shows this node and sink node is more little, when meeting in the two sensors node motion way, near the node that centrad is little data forwarding on its buffer area is given near the big node of centrad, up to running into the sink node, by the simulation comparison experiment under the different random scene, the inventive method has higher transmission success rate and lower transmission delay, and has good robustness.
Description of drawings
Fig. 1 is the application scenarios schematic diagram of data transmission method of the present invention;
Fig. 2 is the schematic flow sheet of chance mobile sensor network data transmission method of the present invention;
Fig. 3 be data transmission method of the present invention and Random and Zebra method in scene one unlike signal transmission radius to the influence contrast schematic diagram of transmission success rate;
Fig. 4 be data transmission method of the present invention and Random and Zebra method in scene one unlike signal transmission radius to the influence contrast schematic diagram of transmission delay;
Fig. 5 be data transmission method of the present invention and Random and Zebra method in scene one the different messages ttl value to the influence contrast schematic diagram of transmission success rate;
Fig. 6 be data transmission method of the present invention and Random and Zebra method in scene one the different messages ttl value to the influence contrast schematic diagram of transmission delay;
Fig. 7 be data transmission method of the present invention in scene one the different sensors interstitial content to the influence of transmission success rate contrast schematic diagram;
Fig. 8 be data transmission method of the present invention in scene one the different sensors interstitial content to the influence of transmission delay contrast schematic diagram;
Fig. 9 is that data transmission method of the present invention and Random, Zebra method unlike signal in scene two transmit the influence contrast schematic diagram of radius to the transmission success rate;
Figure 10 is that data transmission method of the present invention and Random, Zebra method unlike signal in scene two transmit the influence contrast schematic diagram of radius to transmission delay;
Figure 11 contrasts schematic diagram for data transmission method of the present invention and Random, Zebra method different messages ttl value in scene two to the influence of transmission success rate;
Figure 12 contrasts schematic diagram for data transmission method of the present invention and Random, Zebra method different messages ttl value in scene two to the influence of transmission delay;
Figure 13 for data transmission method of the present invention in scene two the different sensors interstitial content to the influence of transmission success rate contrast schematic diagram;
Figure 14 for data transmission method of the present invention in scene two the different sensors interstitial content to the influence of transmission delay contrast schematic diagram.
Embodiment
The present invention is described in further detail below in conjunction with accompanying drawing and example.
The application scenarios based near the chance mobile sensor network data transmission method of centrad that the present invention proposes is made up of sensor node and some sink nodes of sparse distribution, as shown in Figure 1, the black round dot is represented the sink node, and white round dot is represented the movable sensor node.Various data such as temperature around sensor node is regularly gathered in moving the way, humidity, air pollutants etc. are given the sink node with these data upload when running into the sink node.The sink node location is fixed, and the mobility of sensor node in network is inconsistent, and what have is more active, and moving area is bigger; On the contrary, there have some sensor nodes to move to be not frequent.Because node is sparse, and is disconnected when network is most of.The mostly effective property of data that sensor node is gathered, as not sending to the sink node processing for a long time, it is nonsensical that these data can become.When the two sensors node meets, node A and the Node B among Fig. 1 for example, one of them gives another and the bigger node of sink node collision probability with self-contained data forwarding, makes in the time of lacking as far as possible data upload.The key of problem is to each sensor node definition probability function f (x), when the two sensors node meets, the sensor node that carries message determines according to the size of both sides' probability function value whether needs are given the sensor node that meets with forwards, give the sink node up to transmission of messages.Because the intermittence communication of network node, the main target of the inventive method are to improve the transmission success rate, and reduce transmission delay.Described transmission success rate is the ratio of the message number summation that collects of the message number summation of uploading from sensor node received of all sink nodes and all the sensors node.Described transmission delay is meant that data-message finishes the average time that begins to being uploaded to the sink node from the sensor node collection.
In the chance mobile sensor network data transmission method of the present invention, according to the node of community network near the centrad theory, the expectation transmission delay of modeling movable sensor node and a plurality of sink nodes, and judge that with this this node is at present and the average degree of closeness of all sink nodes.Sensor node big more near centrad, the blanking time of on average meeting that shows this node and sink node is more little, show this sensor node can within a short period of time and the probability that meets of sink node big more, promptly mean by this sensor node transmission and can realize littler transmission delay, lower transmission cost.
It is a kind of based on the chance mobile sensor network data transmission method near centrad that the present invention proposes, and as shown in Figure 2, specifically comprises the steps:
Step 1: each sensor node is all set a same time cycle P.The length of time cycle determines that according to the practical application scene such as time cycle P is set at 1 hour, the time cycle of all the sensors node is all the same.
Step 2: upgrade the sink node that run in each cycle sensor node current time and with the sink node record of all previous blanking time of meeting.All sink nodes that run in each sensor node record current period, and record and each sink node all previous blanking time of meeting.If sensor node i once met n time with sink node j in current period, be respectively each blanking time of meeting: T 1, T 2..., T n
Step 3: when sensor node finished in each time cycle, upgrade expectation transmission delay D i(j).If
Figure BDA0000052079320000051
The expectation transmission delay of the current period of expression sensor node i and sink node j, Be the expectation transmission delay of renewal of last one-period, then D i(j) obtain according to following formula:
D i cur ( j ) = Σ i = 1 n T i n , D i ( j ) = α × D i old ( j ) + ( 1 - α ) × D i cur ( j )
Wherein, parameter alpha ∈ [0,1] is used for regulating
Figure BDA0000052079320000055
With Weight, determine occurrence according to the practical application scene.
Step 4: each sensor node after having upgraded the expectation transmission delay of self, obtain self near centrad.Sensor node i near centrad C (i) is:
C ( i ) = k - 1 Σ j = 1 k D i 2 ( j )
Wherein, the number of the sink node that runs into for sensor node i of k.
Step 5: when sensor node i meets with a certain node in moving process, establishing this node is l, and whether sensor node i decision node l is the sink node, if, execution in step six; If not, change step 7 and carry out.
Step 6: if node l is the sink node, sensor node i sends to this sink node l successively with the data in self buffer area, changes step 2 then and carries out.
Step 7: as if node l is not the sink node, then is exactly the sensor node that moves, and needs the relatively size near centrad C (l) near centrad C (i) and sensor node l of sensor node i this moment.If C (i)＞C (l), then sensor node l sends to sensor node i with the data on himself buffer area, if C (i)＜C (l), then sensor node i sends to sensor node l with the data on himself buffer area, if both equate, does not then transmit mutually.Changeing step 2 then carries out.
Compare the improvement effect of additive method with the chance mobile sensor network data transmission method that example explanation the present invention proposes below in conjunction with accompanying drawing.What example adopted is the transmission performance that ONE (opportunistic network environment) network simulation software verification is analyzed the method for the present invention's proposition.Simulation time is 12 hours (an ONE internal timing), and the simulating area area is 4500 * 3400m 2, 15 sink nodes and 300 sensor nodes are set altogether.The sensor node buffer memory is 5Mb, and each data-message size is 50bit, and the maximum rate travel of node is 6m/s, minimum is 0.5m/s, and internodal message transmission rate is 250b/s, in an embodiment of the present invention, time cycle, P was set at 1 hour, and parameter alpha is made as 0.4.
Embodiment is provided with the mobile scene of two kinds of different random.In the scene one, sensor node mobile has tangible locality, shows as to move near its peripheral region most of the time, and randomness is little.Data transmission method of the present invention can be predicted the meet characteristic of sensor node to the sink node exactly.In the scene two, the moving area scope of sensor node is bigger, and it is big that randomness becomes, and makes the characteristic accuracy for predicting of meeting of sensor node and sink node descend.Scene two is intended to investigate the robustness of the data transmission method that the present invention proposes.
Embodiment investigates them separately to the influence of transmission performance from the life span TTL of the transmission radius of node wireless signal, message and these three factors of sensor node number respectively.Transmission performance indicators is weighed from the transmission success rate and average transmission delay two aspects of message, moves 5 respectively and take turns under different random seed conditions, averages as end product.The intact data of sensor node collection just generate a new information, and determine the life span TTL of this message.The control methods of the inventive method is for the method for routing based on history (hereinafter to be referred as the Zebra method) of ZebraNet project use with based on the method for routing of selecting at random (hereinafter to be referred as the Random method).Described based on the method for routing of selecting at random, the sensor node that carries message is transmitted to the node that meets with message with a random chance.Fig. 3 is illustrated in the scene one, and the transmission radius of node signal is to the influence of transmission success rate, and the different signal of abscissa representative transmits radius, and unit is a rice, and ordinate is represented the transmission success rate.As can be seen from Figure 3, the transmission success rate of the method for the present invention's proposition improves a lot than these two kinds of methods of Random, Zebra.If node is with Wi-Fi transmission data, under the outdoor conditions of spaciousness, about 100 meters of can arrive of the transmission radius of general Wi-Fi signal.As shown in Figure 3, when the transmission radius reached 100 meters, the transmission success rate of the inventive method can reach about 90%.
Fig. 4 is illustrated in the scene one, and the transmission radius of node signal is to the influence of transmission delay, and abscissa is represented signal transmission radius, and unit is a rice, and ordinate is represented transmission delay, and unit is second.As can be seen from Figure 4, the transmission radius of node signal is big more, and the transmission delay of each method is more little.Because signal transmission radius is big more, the connectedness of expression network is good more, and the chance of meeting of node and other nodes is many more, and data reduced from the average time that sensor node is transferred to the sink node.It can also be seen that from Fig. 4 the transmission delay of data transmission method of the present invention is little more a lot of than the transmission delay of other two methods.
Fig. 5 is illustrated in the scene one, and the life span TTL of message (Time To Live) is to the influence of transmission success rate, and the ttl value that the abscissa representative is different, unit are hour that ordinate is represented the transmission success rate.Fig. 6 is illustrated in the scene one, and message TTL is to the influence of transmission delay, and the ttl value that the abscissa representative is different, unit be hour, and ordinate is represented transmission delay, and unit is hour.From Fig. 5 and Fig. 6 as can be seen, in scene one, no matter be in the transmission success rate or at transmission delay, the inventive method all is significantly improved than Random, Zebra method.
Fig. 7 represents in the scene one that the sensor node number is to the influence of transmission success rate, and it is 50,100,300 that the sensor node number N is set respectively, carries out three groups of contrast experiments, the signal transmission radius that the abscissa representative is different, and ordinate is represented the transmission success rate.As can be seen from Figure 7, there is obvious positive correlation in the transmission success rate of sensor node number and the inventive method, and interstitial content is many more, and the transmission success rate of the inventive method is high more.
Fig. 8 represents in the scene one, and the sensor node number is to the influence of transmission delay, the message TTL that the abscissa representative is different, and ordinate is represented transmission delay, and unit is hour, establishes three groups of control experiments, and the sensor node number N is respectively 50,100,300.As can be seen from Figure 8, the sensor node number is many in the network, and the transmission delay of the inventive method is little.
Fig. 9 is illustrated in the scene two, and the transmission radius of node signal is to the influence of transmission success rate, and the different signal of abscissa representative transmits radius, and unit is a rice, and ordinate is represented the transmission success rate.As can be seen from Figure 9, in the big scene of node motion randomness, the transmission success rate of the inventive method still improves a lot than these two kinds of methods of Random, Zebra.
Figure 10 is illustrated in the scene two, and the transmission radius of node signal is to the influence of transmission delay, and abscissa is represented signal transmission radius, and unit is a rice, and ordinate is represented transmission delay, and unit is second.It can also be seen that from Figure 10 the transmission delay of the inventive method is little more a lot of than the transmission delay of Random method, the transmission radius nearly 40m begin, also little more a lot of than the transmission delay of Zebra method.
Figure 11 is illustrated in the scene two, and the life span TTL of message (Time To Live) is to the influence of transmission success rate, and the ttl value that the abscissa representative is different, unit are hour that ordinate is represented the transmission success rate.Figure 12 is illustrated in the scene two, and message TTL is to the influence of transmission delay, and the ttl value that the abscissa representative is different, unit be hour, and ordinate is represented transmission delay, and unit is hour.From Figure 11 and Figure 12 as can be seen, in the very big scene two of node motion randomness, no matter be in the transmission success rate or at transmission delay, the inventive method still all is significantly improved than Random, Zebra method, shows that the inventive method has good robustness.
Figure 13 represents in the scene two that the sensor node number is to the influence of transmission success rate, and it is 50,100,300 3 groups of control experiments that the sensor node number N is set respectively, the signal transmission radius that the abscissa representative is different, and ordinate is represented the transmission success rate.As can be seen from Figure 13, the sensor node number is many more, and the transmission success rate of the inventive method is high more.
Figure 14 represents in the scene two, and the sensor node number is to the influence of transmission delay, the message TTL that the abscissa representative is different, and ordinate is represented transmission delay, and unit is hour, establishes three groups of control experiments, and the sensor node number N is respectively 50,100,300.As shown in Figure 14, the sensor node number is many more in the network, and the transmission delay of the inventive method is more little.
By the simulation comparison experiment under the different random scene, the inventive method has higher transmission success rate and lower transmission delay as can be seen, and have good robustness, can well be applicable to the transfer of data and the collection of the chance mobile sensor network of many sink node scene.

Claims (3)

1. one kind based on the chance mobile sensor network data transmission method near centrad, it is characterized in that, and the regular image data in moving process of the sensor node in the chance mobile sensor network, and carry out transfer of data by following step:
Step 1: each sensor node is all set a same time cycle;
Step 2: upgrade the sink node that run in each cycle sensor node current time and with the sink node record of all previous blanking time of meeting, if sensor node i once met n time with sink node j in current period, be respectively each blanking time of meeting: T 1, T 2..., T n
Step 3: when each time cycle finishes, upgrade the expectation transmission delay of each sensor node, the expectation transmission delay D of sensor node i and sink node j with respect to each sink node that meets i(j) be:
D i ( j ) = α × D i old ( j ) + ( 1 - α ) × D i cur ( j ) , D i cur ( j ) = Σ i = 1 n T i n
Wherein,
Figure FDA0000052079310000013
The expectation transmission delay in cycle current time of expression sensor node i and sink node j, Be the expectation transmission delay that sensor node i and sink node j upgraded in last cycle time, parameter alpha ∈ [0,1] is used for regulating With
Figure FDA0000052079310000016
Weight;
Step 4: after having upgraded the expectation transmission delay of each sensor node, obtain each sensor node near centrad, sensor node i near centrad C (i) is:
C ( i ) = k - 1 Σ j = 1 k D i 2 ( j )
Wherein, k is the number of the sink node that runs into of node i;
Step 5: when sensor node i meets with node l in moving process, whether sensor node i decision node l is the sink node, if, execution in step 6; If not, change step 7 and carry out;
Step 6: sensor node i sends to sink node l successively with the data in self buffer area, changes step 2 and carries out;
Step 7: the size that compares sensor node i near centrad C (l) near centrad C (i) and sensor node l, if C (i)＞C (l), then sensor node l sends to sensor node i with the data on self buffer area, if C (l)＞C (i), then sensor node i sends to sensor node l with the data on self buffer area, if C (l)=C (i) does not then transmit mutually; Changeing step 2 then carries out.
2. according to claim 1ly a kind ofly it is characterized in that based on chance mobile sensor network data transmission method the described time cycle of step 1 is set at 1 hour near centrad.
3. according to claim 1ly a kind ofly it is characterized in that based on chance mobile sensor network data transmission method parameter alpha is 0.4 near centrad.
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CN103607749A (en) * 2013-11-13 2014-02-26 福建工程学院 A direction perception guided data collection method in an opportunity mobile sensor network
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CN106211259A (en) * 2016-07-29 2016-12-07 北京智芯微电子科技有限公司 The route implementation method of a kind of time delay tolerant network and realize device
CN106211259B (en) * 2016-07-29 2019-07-16 北京智芯微电子科技有限公司 A kind of route implementation method and realization device of time delay tolerant network
CN108834093A (en) * 2017-04-26 2018-11-16 北京邮电大学 A kind of wireless mobile sensing network data method for congregating

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