CN105872957A - Chance type data uploading method for crowd sensing - Google Patents

Abstract

The invention discloses a chance type data uploading method for crowd sensing. The method comprises the steps that firstly, a node completing a crowd sensing task needs to actively drive sample data to a nearby bus station and forward the sample data to any waiting passenger node mu a, wherein mu a is a data carrier; the data carrier mu a will set up an LAN and maintain existence of the LAN, passenger nodes having access to the LAN through other connections at a bus station or inside a bus calculate the data carrying effect of themselves and send the data carrying effect to the data carrier mu a; the data carrier mu a selects the best node mu b according to a corresponding algorithm and forwards data, and the mu a does not carry the data and does not maintain existence of the LAN anymore, and mu b becomes a new data carrier; if the mu b takes off a bus at the bus station with a WIFI access point, data uploading is completed, and the forwarding process is ended, and if not, the forwarding process is repeatedly executed. According to the chance type data uploading method, the comprehensive efficiency of data loading in a crowd sensing network can be effectively improved.

Description

A kind of opportunistic data uploading method towards intelligent perception

[technical field]

The present invention relates to a kind of opportunistic data uploading method towards intelligent perception.

[background technology]

Along with constantly increasing and the embedding of more multisensor of Intelligent mobile equipment number, intelligent perception is just becoming solution urban area A kind of effective means of interior extensive perception task, task requester can be by corresponding intelligent perception platform by numerous for perception tasks The mobile node being distributed in city has gone, and is no longer necessary to arrange that fixing sensor carries out data collection in a large number.Sensing node After completing task, upload if directly carrying out data by cellular network, then can cause the generation too much moving campus network, as Fruit uploads data by the way of chance is uploaded indirectly, then can face bigger uploading and postpone and repeatedly forward to cause node too much Energy expenditure.In order to improve the participation enthusiasm of user, need to design suitable method for uploading, data upload process can either be reduced In expense, energy consumption minimize the interference to user, that can reduce again data uploads delay to improve transfer efficiency in data.

[summary of the invention]

It is an object of the invention to provide a kind of opportunistic data uploading method towards intelligent perception, to solve above-mentioned technical problem. First this data uploading method selects a small amount of bus station to arrange WIFI access according to the public bus network number through bus station Point, in intelligent perception network, perception data uploads；The forwarder selection mechanism that the method is reasonable in design, according to node Data are carried in effectiveness passenger's node cluster in bus station and bus and are selected suitable node to carry out the forwarding of perception data, By passenger's node of a certain WIFI of going to website, data taken to WIFI website eventually and upload to data center S, thus eliminating number According to uploading expense.This data uploading method utilizes bus passenger internodal stably contact duration to forward to meet the complete of data, Utilize the quickly mobile delay of uploading reducing data of bus carrier, at utmost reduce simultaneously and passenger's node is normally gone on a journey Interference, improves the participation enthusiasm of node.

To achieve these goals, the present invention adopts the following technical scheme that

A kind of modem towards intelligent perception network can quick method for uploading, comprise the following steps:

Step one: the new structure connecting collection: data carrier (bus passenger) u_aAutomatically constructing local network, data carrier place Other passenger's nodes at the L of position, bus station connect this network of entrance and constitute new connection collection Q (u_a,L)；

Step 2: the trip stable factor of most probable destination calculates: Q (u_a, L) in each passenger's node according to time limit HT Interior history trip record, a this time position x that gets on the bus for trip^*And departure time section h^*Automatically most probable destination y is calculated_max's Trip probit P_u(y_max|x^*h^*)；

Subsequently according to calculating the line stabilization factor；

Step 3: node carries effectiveness and calculates: the new each passenger node u concentrated that connects carries effectiveness from the node of host computer oneself, And it is sent to data carrier by LAN；

Step 4: the selection of forward node: if data carrier is waited at website or ridden in car, then data carrier u_a? Q(u_a,L)∪u_aNode set in select to carry the maximum passenger's node of effectiveness to carry data；If data carrier is being got off At website, then data are handed to Q (u_a, L) in carry passenger's node that effectiveness is maximum；

Step 5: repeat repeating process: data carrier repetition step one, to four, maintains the existence of LAN, in new site position Q (the u of L_a, L) in carry out the selection of forward node, until data carrier arrives WIFI website, complete uploading of perception data.

Further, in step 2,

P_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to website y_maxProbability；x^*: This time bus trip originate website；h^*: this time time period of trip, h^*∈ { morning, afternoon, evening }；y_max: Cheng Kejie Point u is at period h^*From x^*Under conditions of website is got on the bus, most probable trip purpose ground；Passenger node u is at period h^* From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；R: all of public bus network set；BSQ (r): Public bus network r the website sequence of process；REM(r,x^*): public bus network r is at x^*Set of sites after website；

Trip stable factor calculates according to equation below:

$S_u\left(y_{max}\right|x^{*}{h}^{*})=P_u\left(y_{max}\right|x^{*}{h}^{*})*\frac{e_{x^{*}{y}_{\max }{h}^{*}}\left(u\right)}{{\mathrm{\Σ}}_{x\∈B}{\mathrm{\Σ}}_{y\∈B}{\mathrm{\Σ}}_{h\∈H}{e}_{xyh}\left(u\right)}$

S_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Website goes to y_maxThe trip stable factor of website； Passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；

∑_x∈B∑_y∈B∑_h∈He_xyh(u): all history trip number of times of passenger node u.

Further, in step 3, the node of passenger node u is carried effectiveness and is calculated by following formula:

$Utility\left(u\right)=(aF+b(1-F\left)SE\right(y_{max}\left)\right)*S_u\left(y_{max}\right|x^{*}{h}^{*})+\frac{c}{D}$

Utility (u): passenger node u carries the effectiveness of data；F: passenger node u most probable destination y_maxType, if It is WIFI website, then F=1, if common website, then F=0；D: current location L and y of passenger node u_maxAway from From；A, b, c: be respectively described WIFI website, common website, the weight factor of distance.

Further, it is assumed that effectiveness calculates the possible maximum of first factor and second factor in function right half part and is set as M and n, then a, the establishing method of tri-weight factors of b, c is as follows:

$a=\frac{m}{0.5},b=\frac{m}{0.5*{\mathrm{SE}}_{max}\left(b\right)},c=n$

Weight a set the stable trip factor maximum that take into account passenger's node as 0.5 (the most only coming and going a circuit)；Weight The setting of b considered not only the stable trip factor, it is also contemplated that the WIFI of most probable destination connects entropy, SE_max(b) table Show the maximum connecting entropy in all bus stations；The maximum occurrences of distance is 1, so c weight factor is set as n.According to reality Test effect, recommend the ratio of m Yu n to be respectively set as 0.9 and 0.1. here

Further, current location L and y of passenger's node u_maxDistance be specially station number.

The invention discloses a kind of opportunistic data uploading method towards intelligent perception, first, complete the node of intelligent perception task Need sampled data is actively taken to neighbouring bus station and is transmitted to arbitrary passenger node μ that waits_a, μ_aBecome data carrier； Data carrier μ_aMeeting constructing local network also maintains LAN to exist, and in bus station or bus, other connects this local of entrance Passenger's node of net calculates the data of oneself and carries effectiveness, and is sent to data carrier μ_a；Data carrier μ_aCalculate according to corresponding Method selects optimum node μ_bAnd forward data, and μ_aNo longer hold data and no longer maintain LAN to exist, and μ_bBecome new Data carrier；If μ_bGet off in the bus station being provided with WIFI access point, then complete uploading of data, terminate forwarded over Journey, otherwise μ_bRepeat this repeating process.

Compared with prior art, the invention has the beneficial effects as follows:

Data upload process is limited in public transit system by the inventive method, by the moving contact of passenger's node, carries data and arrives WIFI website completes to upload, thus saves and upload expense；The method utilizes meet time of contact stable between bus passenger node The complete forwarding of relatively large data；The method take into account the kinestate participating in node, utilizes the most mobile of public transport carrier to subtract Minority evidence upload delay；The method devises the redundancy that rational forwarder selection mechanism effectively prevent in data forwarding process Problem；The method reduces the impact on passenger's node normal activity to the full extent, only needs data carrier to complete data after getting off Forwarding or upload, other parts are all that system is automatically performed, it is not necessary to node participates in, thus improves the participation enthusiasm of node.

[accompanying drawing explanation]

Fig. 1 is the present invention block flow diagram towards the opportunistic data uploading method of intelligent perception.

[detailed description of the invention]

The present invention is described in further details by explanation and detailed description of the invention below in conjunction with the accompanying drawings:

A kind of system being based on towards the opportunistic data uploading method of intelligent perception of the present invention, including DCC S, public affairs Hand over website b (b ∈ B), public bus network r (r ∈ R) and passenger node u (u ∈ U)；Wherein, B is the set of bus station, and R is public The set on intersection road, U is the set of passenger's node.

This system selects a small amount of bus station to arrange WIFI access point conduct firstly the need of the institute's via line number according to bus station WIFI website wb (wb ∈ WB) (suggestion choose bus station set in circuit most 1%～2% bus station be set to WIFI website), residue website exists as common website gb (gb ∈ GB)；WB is WIFI Website Hosting, and GB is ormal station Point set；Data are uploaded platform and are calculated the connection entropy of each common website and WIFI set of sites WB, and computing formula is as follows:

$SE\left(b\right)=\underset{r\∈R}{\Σ}(X_{br}+1)log(X_{br}+1)$

SE (b): arrived the entropy of WIFI website by all routes of common website b (b ∈ GB)；X_br: bus routes r from Website b start after the number (up-downgoing separately consider) of WIFI website of process；

The node completing intelligent perception task in whole urban area needs sampled data is actively taken to neighbouring bus station and turns Issue arbitrary passenger node μ that waits_a, μ_aBecome data carrier；

Data carrier u_aThe automatic constructing local network of meeting, if u_aOther passenger's joint of waiting at a certain bus station, this website Point can be newly added this LAN；If u_aGetting on the bus in a certain bus station, other the existing passenger's node being ridden in a bus interior can newly add Enter this LAN；If u_aBeing ridden in a bus and stop at a certain website, the passenger's node got on the bus at this website can be newly added this local Net；

It is newly added u at website L_aAll passenger node Q (u of the LAN set up_a, L) all can be according in time limit certain time TH History ride record, a this time position x that gets on the bus for trip^*And departure time section h^*Calculate most probable destination y_maxTrip general Rate value P_u(y_max|x^*h^*):

$P_u\left(y_{max}\right|x^{*}{h}^{*})=\frac{e_{x^{*}{y}_{\max }{h}^{*}}\left(u\right)}{{\mathrm{\Σ}}_{y\∈{\mathrm{\Σ}}_{r\∈R,x^{*}\∈BSQ\left(r\right)}REM(r,x^{*})}{e}_{x^{*}{\mathrm{yh}}^{*}}\left(u\right)}$

P_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to website y_maxProbability；y_max: Passenger node u is at period h^*From x^*Under conditions of website is got on the bus, most probable trip purpose ground；Passenger node u exists Period h^*From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；R: all of public bus network set； BSQ (r): public bus network r the website sequence of process；REM(r,x^*): public bus network r is at x^*Set of sites after website；

Obtain y_maxTrip probability after, then calculate the factor of stably going on a journey:

$S_u\left(y_{max}\right|x^{*}{h}^{*})=P_u\left(y_{max}\right|x^{*}{h}^{*})*\frac{e_{x^{*}{y}_{\max }{h}^{*}}\left(u\right)}{{\mathrm{\Σ}}_{x\∈B}{\mathrm{\Σ}}_{y\∈B}{\mathrm{\Σ}}_{h\∈H}{e}_{xyh}\left(u\right)}$

S_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Website goes to y_maxThe trip stable factor of website； Passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；

∑_x∈B∑_y∈B∑_h∈He_xyh(u): all history trip number of times of passenger node u.

Q(u_a, L) in each passenger node u can be in conjunction with the station number between oneself current location and destination from master computing node Carry effectiveness:

$Utility\left(u\right)=(aF+b(1-F\left)SE\right(y_{max}\left)\right)*S_u\left(y_{max}\right|x^{*}{h}^{*})+\frac{c}{D}$

Utility (u): passenger node u carries the effectiveness of data；F: passenger node u most probable destination y_maxType, if It is WIFI website, then F=1, if common website, then F=0；D: current location L and y of passenger node u_maxAway from From (station number)；A, b, c: be respectively described WIFI website, common website, the weight factor of distance；

Assume that effectiveness calculates the ratio of first factor and second factor in function right half part and is set as m:n, then a, b, c tri- The establishing method of weight factor is as follows:

$a=\frac{m}{0.5},b=\frac{m}{0.5*{\mathrm{SE}}_{max}\left(b\right)},c=n$

Weight a set the stable trip factor maximum that take into account passenger's node as 0.5 (the most only coming and going a circuit)；Weight b Setting considered not only the stable trip factor, it is also contemplated that the WIFI of most probable destination connects entropy, SE_maxB () represents institute There is in bus station the maximum connecting entropy；The maximum occurrences of distance is 1, so c weight factor is set as n.According to experiment effect Really, the ratio of m Yu n is recommended to be set as 0.9 and 0.1 here；

Q(u_a, L) in each passenger's node the effectiveness of carrying calculated can be sent to data carrier by LAN；If Data carrier is waited at website or is ridden in car, then data carrier u_aCan be at Q (u_a,L)∪u_aNode set in select to take The node maximum with effectiveness carries data；If data carrier u_aAt get-off stop, then data are handed to Q (u_a, L) in Carry passenger's node that effectiveness is maximum；

Data carrier all the time can be at the Q (u of various location_a, L) and node connects concentration and carries out the selection of forward node, until data Carrier arrives WIFI website, upload the data to DCC by WIFI, then this data upload process completes.

Refer to shown in Fig. 1, a kind of opportunistic data uploading method towards intelligent perception of the present invention, comprise the following steps:

First data carrier u_aMeeting constructing local network, other and u_aPassenger's node at same site location L can connect this office of entrance Territory net becomes forward node Candidate Set Q (u_a,L)；Q(u_a, L) in each node can infer most probable according to history record by bus Trip purpose ground, and calculate the trip stable factor of this destination；Later in conjunction with this destination type and be presently in position The distance put, what each node can calculate oneself carries effectiveness Utility (u), and is sent to data carrier u_a；Data carrier u_a According in oneself status and Q (u, L) each passenger's node carry effectiveness, decide whether to forward data and whom is transmitted to； Data carrier, along with the movement of bus carrier, carries out the selection of optimum forward node at new website, until data carrier Arriving WIFI website, upload data to data center S by WIFI, this data upload process terminates.

The inventive method detailed process comprises the steps:

Step one: the new structure connecting collection: data carrier u_aConstructing local network, other nodes at the site location L of place are even Tap into constitute into this network and new connection collect Q (u_a,L)；

Step 2: the trip stable factor of most probable destination calculates: Q (u_a, L) in each passenger's node according to phase certain time History trip record in limit HT, a this time position x that gets on the bus for trip^*And departure time section h^*Calculate most probable destination y_max Trip probit P_u(y_max|x^*h^*):

$P_u\left(y_{max}\right|x^{*}{h}^{*})=\frac{e_{x^{*}{y}_{\max }{h}^{*}}\left(u\right)}{{\mathrm{\Σ}}_{y\∈{\mathrm{\Σ}}_{r\∈R,x^{*}\∈BSQ\left(r\right)}REM(r,x^{*})}{e}_{x^{*}{\mathrm{yh}}^{*}}\left(u\right)}$

P_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to website y_maxProbability；x^*: This time bus trip originate website；h^*: this time time period of trip, h^*∈ { morning, afternoon, evening }；y_max: Cheng Kejie Point u is at period h^*From x^*Under conditions of website is got on the bus, most probable trip purpose ground；Passenger node u is at period h^* From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；R: all of public bus network set；BSQ (r): Public bus network r the website sequence of process；REM(r,x^*): public bus network r is at x^*Set of sites after website；

The line stabilization factor is calculated subsequently according to equation below:

$S_u\left(y_{max}\right|x^{*}{h}^{*})=P_u\left(y_{max}\right|x^{*}{h}^{*})*\frac{e_{x^{*}{y}_{\max }{h}^{*}}\left(u\right)}{{\mathrm{\Σ}}_{x\∈B}{\mathrm{\Σ}}_{y\∈B}{\mathrm{\Σ}}_{h\∈H}{e}_{xyh}\left(u\right)}$

S_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Website goes to y_maxThe trip stable factor of website； Passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；

∑_x∈B∑_y∈B∑_h∈He_xyh(u): all history trip number of times of passenger node u；

Step 3: node carries effectiveness and calculates: the new each passenger node u that concentrates of connecting carries effectiveness from the node of host computer oneself:

$Utility\left(u\right)=(aF+b(1-F\left)SE\right(y_{max}\left)\right)*S_u\left(y_{max}\right|x^{*}{h}^{*})+\frac{c}{D}$

Utility (u): passenger node u carries the effectiveness of data；F: passenger node u most probable destination y_maxType, if It is WIFI website, then F=1, if common website, then F=0；D: current location L and y of passenger node u_maxAway from From (station number)；A, b, c: be respectively described WIFI website, common website, the weight factor of distance；

After calculating completes, the effectiveness of carrying of oneself is sent to data carrier by LAN；

Step 4: the selection of forward node: Q (u_a, L) in each passenger's node the effectiveness of carrying calculated is passed through LAN It is sent to data carrier；If data carrier is waited at website or is ridden in car, then data carrier u_aMeeting exists Q(u_a,L)∪u_aNode set in select to carry the maximum node of effectiveness to carry data；If data carrier is at get-off stop Place, then hand to Q (u by data_a, L) in carry passenger's node that effectiveness is maximum；

Step 5: repeat repeating process: data carrier maintains the existence of LAN, newly connects collection at new site position L Q(u_a, L) in carry out the selection of forward node, until data carrier arrives WIFI website, complete uploading of perception data；

Step 6: this data upload process terminates.

For verifying further the effectiveness of the inventive method, by Beijing part public transport follow-up investigation and based on Beijing The data that the true trip data of bus passenger is carried out upload simulation experiment, and feasibility and effect to this invention are assessed. On-site inspection is the most stable in order to verify the LAN set up between bus passenger under real scene, and whether time of contact can meet greatly The forwarding duration of most perception datas, it has been observed that either in bus station or bus, the LAN of establishment all compares Stable, it is possible to meet the stable forwarding of data, the go on a journey running time of a stop of bus passenger is about two minutes simultaneously, and 100M is big Little data can intactly be transmitted complete by LAN, can be with gratification primary data as transmission medium hence with bus passenger Upload some required characteristics.This data uploading method is mainly estimated by simulation experiment from three below performance indications: (1) Biography success rate: the ratio that data are successfully uploaded；(2) delay is averagely uploaded: data upload required average duration；(3) averagely turn Send out number of times: required in data forwarding process averagely participate in interstitial content.Test 50000 different time not coordinatioies of stochastic generation Put the data upload requests at place, be divided into ten groups to verify.By to experimental analysis, the data of each group upload success rate Can reach more than 90%, the especially success in morning peak and evening peak period data is uploaded rate and has been reached 99% especially；Data Averagely upload delay be only 67.23 minutes, this be far superior to some other institute propose method；Forward each time During, forward the number of participant the most only to need 2.13, owing to hop count is greatly reduced, then the energy in repeating process Consumption reduces the most accordingly.By the above experimental verification to this inventive method, it can be seen that this inventive method can be effectively improved data The combination property uploaded.

Claims (6)

1. the opportunistic data uploading method towards intelligent perception, it is characterised in that comprise the following steps:

Step one: the new structure connecting collection: is carried the bus passenger needing to upload data as data carrier u_aAutomatically set up LAN, other passenger's nodes at the L of position, bus station, data carrier place connect entrance this network composition and newly connect collection Q(u_a,L)；

Step 2: the trip stable factor of most probable destination calculates: Q (u_a, L) in each passenger's node according to time limit HT Interior history trip record, a this time position x that gets on the bus for trip^*And departure time section h^*Automatically most probable destination y is calculated_max's Trip probit P_u(y_max|x^*h^*)；

Subsequently according to calculating the line stabilization factor；

Step 3: node carries effectiveness and calculates: the new each passenger node u concentrated that connects carries effectiveness from the node of host computer oneself, And it is sent to data carrier by LAN；

Step 4: the selection of forward node: if data carrier is waited at website or ridden in car, then data carrier u_a? Q(u_a,L)∪u_aNode set in select to carry the maximum passenger's node of effectiveness to carry data；If data carrier is being got off At website, then data are handed to Q (u_a, L) in carry passenger's node that effectiveness is maximum；

Step 5: repeat repeating process: data carrier repetition step one, to four, maintains the existence of LAN, in new site position Q (the u of L_a, L) in carry out the selection of forward node, until data carrier arrives WIFI website, complete uploading of perception data.

A kind of opportunistic data uploading method towards intelligent perception the most according to claim 1, it is characterised in that step In two,

P_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to website y_maxProbability；x^*: This time bus trip originate website；h^*: this time time period of trip, h^*∈ { morning, afternoon, evening }；y_max: Cheng Kejie Point u is at period h^*From x^*Under conditions of website is got on the bus, most probable trip purpose ground；Passenger node u is at period h^* From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；R: all of public bus network set；BSQ (r): Public bus network r the website sequence of process；REM(r,x^*): public bus network r is at x^*Set of sites after website；

Trip stable factor calculates according to equation below:

$S_u\left(y_{max}\right|x^{*}{h}^{*})=P_u\left(y_{max}\right|x^{*}{h}^{*})*\frac{e_{x^{*}{y}_{\max }{h}^{*}}\left(u\right)}{{\mathrm{\Σ}}_{x\∈B}{\mathrm{\Σ}}_{y\∈B}{\mathrm{\Σ}}_{h\∈H}{e}_{xyh}\left(u\right)}$

S_u(y_max|x^*h^*): passenger node u is at period h^*From x^*Website goes to y_maxThe trip stable factor of website； Passenger node u is at period h^*From x^*Under conditions of website is got on the bus, go to y_maxThe history trip number of times of website；

∑_x∈B∑_y∈B∑_h∈He_xyh(u): all history trip number of times of passenger node u.

A kind of opportunistic data uploading method towards intelligent perception the most according to claim 1, it is characterised in that step In three, the node of passenger node u is carried effectiveness and is calculated by following formula:

$Utility\left(u\right)=(aF+b(1-F\left)SE\right(y_{max}\left)\right)*S_u\left(y_{max}\right|x^{*}{h}^{*})+\frac{c}{D}$

Utility (u): passenger node u carries the effectiveness of data, Utinity (u) ∈ (0,1]；F: passenger node u most probable destination y_maxType, if WIFI website, then F=1, if common website, then F=0；SE(y_max): website y_maxWith The connection entropy of WIFI set of sites WB；D: current location L and y of passenger node u_maxDistance；A, b, c: retouch respectively State WIFI website, common website, the weight factor of distance.

A kind of opportunistic data uploading method towards intelligent perception the most according to claim 3, it is characterised in that passenger The node of node u carries in the right-hand component of effectiveness formula, and maximum possible to first factor and second factor is set as m And n, then a, the establishing method of tri-weight factors of b, c is as follows:

$a=\frac{m}{0.5},b=\frac{m}{0.5*{\mathrm{SE}}_{max}\left(b\right)},c=n$

Setting of weight a take into account the stable trip factor maximum of passenger's node as 0.5；The setting of weight b considers not only The stable trip factor, it is also contemplated that the WIFI of most probable destination connects entropy, SE_maxB () represents in all bus stations and connects Connect the maximum of entropy；The maximum occurrences of distance is 1, so c weight factor is set as n；The value of m Yu n is set as 0.9 and 0.1.

A kind of opportunistic data uploading method towards intelligent perception the most according to claim 3, it is characterised in that passenger Current location L and y of node u_maxDistance be specially station number.

A kind of opportunistic data uploading method towards intelligent perception the most according to claim 1, it is characterised in that choose The bus station of 1%～2% that in the set of bus station, circuit is most is set to WIFI website.