CFT: A Cluster-based File Transfer Scheme for Highway

0.8 MB·

by  Quyuan Luo

CFT: A Cluster-based File Transfer Scheme for
Highway VANETs
Quyuan Luo1, Changle Li1∗, Qiang Ye2, Tom H. Luan3, Lina Zhu1 and Xiaolei Han1
1State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, Shaanxi, 710071 China
2School of Mathematical and Computational Sciences, University of Prince Edward Island, Charlottetown, PE, C1A 4P3 Canada
3School of Information Technology, Deakin University, Melbourne, VIC 3125, Australia
∗E-mail: [email protected]
7 Abstract—Effectivefiletransferbetweenvehiclesisfundamen- Max-Rate First method, in which the roadside unit selects
1 tal to many emerging vehicular infotainment applications in the the node with the highest data rate as the receiver to serve.
0 highwayVehicularAdHocNetworks(VANETs),suchascontent
Liu et al. [5] proposed a cooperative downloading strategy
2 distributionandsocialnetworking.However,duetofastmobility,
that can provide mobile users with varied services to access
theconnectionbetweenvehiclestendstobeshort-livedandlossy,
n whichmakesintactfiletransferextremelychallenging.Totackle the Internet using WiFi according to user-defined classes in
a
this problem, we presents a novel Cluster-based File Transfer highway scenarios. T. Wang et al. [6] proposed a cooperative
J
(CFT) scheme for highway VANETs in this paper. With CFT, approach based on coalition formation games, in which on-
8
whenavehiclerequestsafile,thetransmissioncapacitybetween
board units download pieces from RSUs and then exchange

the resource vehicle and the destination vehicle is evaluated. If
] their possessed pieces by broadcasting to and receiving from
the requested file can be successfully transferred over the direct
I
N Vehicular-to-Vehicular (V2V) connection, the file transfer will their neighbors.
be completed by the resource and the destination themselves. Most of the existing file transfer schemes focus on the QoS
.
s Otherwise,aclusterwillbeformedtohelpthefiletransfer.Asa issues, such as packet delay and network throughput. Despite
c fully-distributedschemethatreliesonthecollaborationofcluster
the importance of the QoS issues, we believe that file transfer
[
members, CFT does not require any assistance from roadside
units or access points. Our experimental results indicate that integrity (i.e. whether a file can be completely transferred or
1
CFT outperforms the existing file transfer schemes for highway not)playsamoreimportantrolebecauseithasadirectimpact
v
VANETs. onthequalityofuserexperience.Normally,userscantolerate
1
3 some extra delay. However, if file transfer attempts often lead
9 I. INTRODUCTION to failures, users will be seriously upset. So far, only few
1 VehicularAdHocNetworks(VANETs)haveattractedmuch studiesonfiletransferinVANETshavepaidenoughattention
0
attention in both academia and industry. Among the problems to the integrity aspect. Luan et al. [9] proposed an integrity-
.
1 to be tackled in VANETs, effective vehicle-to-vehicle (V2V) oriented content transmission scheme, which focuses on the
0 file transfer is fundamental to many emerging infotainment performance of the entire file transfer process and is opti-
7
applications, such as content distribution and file sharing. mizedtowardsguaranteedintegrity.However,withthescheme
1
However,itremainstobeaverychallengingproblembecause presented in [9], the file that is unlikely to be completely
:
v inter-vehicle links tend to be short-lived and lossy thanks to transferred during the transient connection time will simply
i
X fast node mobility. With short-lived and lossy links, it is very be discarded, which is overly simple and leaves much room
likely that only part of a file, which often turns to be useless for improvement.
r
a intheend,canbetransferred.Thisleadstoasignificantwaste In this paper, we present a high-integrity Cluster-based File
of network resources and hurts user experience seriously. Transfer (CFT) scheme for highway VANETs. CFT adopts a
To enable efficient file transfer in VANETs, a variety cooperative approach and achieves high-integrity file transfer
of different schemes have been proposed. Deng et al. [1] between vehicles without the assistance of roadside units or
proposed a Prior-Response-Incentive-Mechanism to stimulate access points. With CFT, when the requested file cannot be
vehicles to take part in cooperative downloading in VANETs- successfullytransferredfromthesourcetothedestinationover
LTEheterogeneousnetworks.Huangetal.[2]proposedacell- asingledirectV2Vconnection,aclusterisformedandthefile
based clustering scheme and a strategy of inter-cluster Relay is collaboratively transmitted over multiple hops. To facilitate
Selection to construct a pear-to-pear (P2P) network of scale- the multi-hop file transfer, we developed a Connection Time
free property, which help to enhance the information spread. Prediction Model and a Content File Distribution Model to
Ota et al. [3] proposed a cooperative downloading algorithm evaluate the transmission capability of cluster members and
calledMax-throughputandMin-delayCooperativeDownload- optimally select the intermediate relay nodes.
ing, in which the RoadSide Units (RSUs) intelligently select The rest of the paper is organized as follows. Section II
vehicles to serve towards the minimal average delivery delay presents the models adopted in CFT and Section III describes
of file transfer. Yang et al. [4] proposed a Cooperation-aided the details of the proposed cluster-based file transfer scheme.
Section IV includes our experimental results and Section V vector of vehicle i at time t, ∆t is the time interval, d (t)
ij
concludes the paper with closing remarks. is the distance between vehicle i and vehicle j ∈Ω at time t,
SD denotes the safety distance between two vehicles.
II. SYSTEMMODEL
With these velocity equations, we can arrive at a highway
In this paper, we focus on the scenario in which vehicles mobility model in terms of both time and space. In our
travelonabi-directionalhighway.Weassumethatallvehicles research, we assume that the initial distance between any two
are equipped with the Global Positioning System (GPS) and vehicles is d (t ), and the initial speed of vehicles is set to
ij 0
are aware of their geographical locations. |V(cid:126)(t )|,andγ isarandomnumberbetween0and1.Thenwe
0
In our research, we adopted three models to study the file have the following equations:
transferprobleminVANETs:vehiclemobilitymodel,connec-
(cid:26) d (t )=(1+γ)∗SD,
tion time prediction model, and vehicle-to-vehicle communi- ij 0 (2)
|V(cid:126)(t )|=V +γ∗(V −V ).
cationmodel[7].The details ofthesemodelsarepresentedas 0 min max min
follows. B. Connection Time Prediction Model
A. Vehicle Mobility Model WeassumethatthecommunicationrangeofeachnodeisR.
The position, the velocity and the moving direction of vehicle
Consideringthemobilityfeaturesonpracticalhighways,we
i∈Ω at time t are (x (t),y (t)), V(cid:126) (t) and θ (t) respectively.
apply the free mobility model to represent the mobility of i i i i
Similarly, the position, the velocity and the moving direction
vehicles on highways [8].
of vehicle j ∈ Ω at time t are (x (t),y (t)), V(cid:126) (t) and θ (t)
The mobility features of vehicles are summarized as fol- j j j j
respectively. Fig. 2 illustrates how the connection time is
lows:
predicted in our research.
• The current moving speed is independent of the previous
In order to predict the connection time between two vehi-
moving speed. In addition, the speed range is specified
cles, we use the following equations to calculate the connec-
by a maximal speed and a minimal speed.
tion time ∆T [10]:
• A Safety Distance (SD) is defined. Namely, two adjacent ij
vehicles on the same lane should maintain the SD for  ∆v =|V(cid:126) (t)|cosθ (t)−|V(cid:126) (t)|cosθ (t),
safetypurposes.Whenthedistancebetweentwoadjacent  ∆vyx=|V(cid:126)ii(t)|sinθii(t)−|V(cid:126)jj(t)|sinθjj(t),
vehicles is less than SD, the rear vehicle should slow ∆d =x (t)−x (t), (3)
x i j
dreoqwunireumnetinlt.the distance between them meets at the SD  (∆∆ddyx=+y∆i(vt)x−∗∆yjT(itj)),2+(∆dy+∆vy∗∆Tij)2 =R2,
• A vehicle only travels along one lane of the highway. (cid:26) A=∆v ∗∆d +∆v ∗∆d ,
x x y y (4)
In the mobility model adopted in our research, both the B =∆vx2+∆vy2,
speed of all vehicles and the distance between two adjacent (cid:113)
−A+ B∗R2−(∆v ∗∆d −∆v ∗∆d )2
vehicles are specified. Fig. 1 illustrates the specifications for y x x y
∆T = . (5)
two adjacent vehicles. ij B
C. Vehicle-to-Vehicle Communication Model
Vqj(((tt))) In this section, we analyze the transmission capacity of
j
the physical layer in vehicle-to-vehicle communication [11].
Vjt j ConsideringthecharacteristicsofDSRCcommunication[12],
((t))
Vit dijt qiV(it) twhiethretcheeiviendcrseigansealopfowtheerodbisetyanscReicbeetDwiesternibutwtioonvienhitiicallelsy,,bthuet
received signal power obeys Rayleigh Distribution. In order
i
to better simulate the envelope of fading signal in highway
Fig.1:SpeedandDistance Fig.2:ConnectionTimePrediction
vehicular networking environment, we apply the Nakagami-m
distribution[13].Theprobabilitydensityfunctionofthesignal
Let Ω denote the set of vehicles. According to the mobility envelope f(x;µ,Ω) is formulated as
features mentioned previously, we can use the following
2µµ µ
velocity equations to represent the movement of two vehicles f(x;µ,Ω)= x2µ−1exp(− x2), (6)
Γ(µ)Ωµ Ω
and the relationship between the speed of two vehicles:
(cid:90) ∞
 (cid:12)(cid:12)(cid:12)V(cid:126)i(t+(cid:12)∆t)(cid:12)(cid:12)(cid:12)=(cid:12) (cid:12)(cid:12)(cid:12)V(cid:126)i(t)(cid:12)(cid:12)(cid:12)+γi(t)∗|(cid:126)ai(t)|∗∆t, Γ(µ)= 0 e−xxµ−1dx, (7)
Vmin ≤(cid:12)(cid:12)V(cid:126)i(t)(cid:12)(cid:12)≤Vmax, (1) where µ is the signal fading index related to the surroundings
 (cid:12)(cid:12)(cid:12)V(cid:126)j(t)(cid:12)(cid:12)(cid:12)≤(cid:12)(cid:12)(cid:12)V(cid:126)i(t)(cid:12)(cid:12)(cid:12),dij(t)≤SD. andthedistancebetweentwocommunicationvehicles[14].In
ourresearch,weadoptthefollowingreferencevalues:µ=0.74
where V(cid:126) (t) represents the velocity vector of vehicle i ∈ Ω when d ∈ [90.5,230.7]; µ=0.84 when d ∈ [230.7,588]. Ω
i ij ij
at time t, γ (t) is a random number,(cid:126)a (t) is the acceleration istheaveragereceivedpowerbeforeenvelopedetection.Itcan
i i
be defined as directly without establishing a cluster.
h2h2
Ω=P G G t r, (8) • If two vehicles cannot complete the file transfer within
t t rdαL
ij their connection time, the request vehicle establishes a
where P is the transmission power, G and G are the trans- linear cluster. Then the request vehicle cooperates with
t t r
missionandreceptionantennagainrespectively,h andh are the vehicles in the cluster to download the file.
t r
the transmission and reception antenna length respectively, L To evaluate the communication capacity between two ve-
is the loss coefficient of the system, and α represents the path hicles and establish a cluster when necessary, each vehicle
loss index [15]. Then we can calculate the probability density requires the position, the velocity and the moving direction
functionofthesignaltonoiseratio(SNR)usingthefollowing its neighbors. Therefore, we assume that all vehicles in the
equation: VANETs under investigation are equipped with GPS. In ad-
P ( S ≤x)=1− Γ(µ,ΩµNrx), (9) dition, each vehicle broadcasts Hello messages periodically
r N Γ(µ)
r in order to collect the position and velocity information of
where N is the thermal noise power, Γ(µ, µN x) is formu- its neighboring vehicles. The details of CFT are presented as
r Ω r
lated as follows.
µ (cid:90) ∞
Γ(µ, N x)= e−xxµ−1dx. (10)
Ω r ΩµNrx A. Transmission Capacity between Two Vehicles
In order to evaluate the transmission capacity between two
Here, we assume that the transmitter of each node in
vehicular environment supports K modulation rates, c is the vehicles,wedevelopedtheContentFileDistributionModelin
k
kth modulation rate (c < c < ··· < c , 1 ≤ k ≤ K), our research. This model can be illustrated using Fig. 3.
1 2 k
and v is the pre-set threshold. When v ≤ S ≤ v , the
modulke velocity is c . In addition, we setkv Nr=∞.k+C1onse- t t0
k K+1
quently, according to the equations mentioned previously, the
V V V0
i i i
transmission rate c is selected with the probability
Pr{C =c }=(cid:40) k Γ(1µ)(Γk−Γk+1), 1≤k≤K−1 (11) Li VjS Lj S Vj
k Γk , k=K,
Γ(µ)
K
(cid:88)
Pr{C =0}=1− Pr{C =c }, (12)
k
Fig. 3: Content File Distribution Model: S selects another vehicle (Vi)
1
to transfer fragments once the predicted amount of fragments have been
where Γk and Γk+1 are defined as transferredtothecurrentcooperativevehicle(Vj).
(cid:40) Γ = (cid:82)∞ yµ−1e−ydy,
Γk =(cid:82)∞ΩµNrvk yµ−1e−ydy. (13) If the request vehicle and resource vehicle cannot complete
k+1 ΩµNrvk+1 the file transfer within their connection time, cooperative
Thus,theaveragetransmissionratecanbeobtainedthrough vehicles are needed. The file content is equally divided into
the following equation: N fragments denoted by Γ = {γ1,γ2,...,γN} with the size
of each fragment s. During the whole connection time ∆T ,
i,S
K
(cid:88) vehicle i ∈ Ω can not exactly download n fragments since
E(c)=0·P (C =0)+ C ·P (C =C )
r i r i
vehicle i is out of the communication range of the resource
i=1 (14)
(cid:88)K vehicle S so that the link Li between i and S is disconnected
= Ci·Pr(C =Ci). when the nth fragment is transferring. And according the
i=1 predicted connection time ∆T , we can obtain the number
i,S
III. CFT:AHIGH-INTEGRITYFILETRANSFERSCHEME of fragments ni by
(cid:22) (cid:23)
In this section, we present the details of the proposed high- n = E(c)·∆Ti,S , (15)
integrity file transfer scheme, CFT. Based on the established i s
clusters,CFTleadstohighfiletransferintegrity.Anoverview
where (cid:98)·(cid:99) denote the floor function, E c) is the average
(
of CFT is presented as follows:
transmissionratewhichcanbeobtainedbyEq.14.Besides,in
• When a vehicle needs a file, it will broadcast a resource Fig.3,∆t0 isthetimespendingondownloadingni fragments
requestmessagetoitsneighboringvehicles.Ifaneighbor completely,∆t(cid:48)isthetime∆T minus∆t0andduringwhich
i,S
vehicle has the file, it will send a response message the nth fragment can not be downloaded completely. Their
back.Thereafter,therequestvehicleselectsaneighboring relationship is formulated as
vehicle as the downloading source according to the ve-
(cid:26) ∆t(cid:48)+∆t0 =∆T ,
locity,thedirectionofthevehicleandthecommunication ∆t0 = ni·s. i,S (16)
capacity. E(c)
• If two vehicles can complete the file transfer within their Inourproposedscheme,upontransferringthentihfragment,
connection time, the request vehicle downloads the file S selects another cooperative vehicle j ∈ Ω to transfer file
(cid:40) n (cid:41)
fragments and establishes the link Lj. Through this method, N = min{n}|(cid:88)Vi ≥V ,n=1,2,··· . (19)
c data file
suchdatalossD willnotoccuranditisofgreatimportance
loss i=1
for transfer time saving. Consequently, the communication
C. Cooperative Vehicles Transfer File Fragments to Request
capacity Cc between any vehicle i and resource vehicle S is
i,S Vehicle
calculated as
(cid:22) (cid:23)
Cc =s· E(c)·∆Ti,S . (17) After cluster members complete the file fragment transfer,
i,S s theyforwardtheirfragmentstotheresourcevehicle.Weadopt
In the cooperative phase, if several vehicles are in the the IEEE 802.11b DCF mechanism as the MAC protocol of
communication range of resource vehicle, as shown in Fig. the network and employ the RTS/CTS mechanism to avoid
4,theresourcevehicleS willtransferthefilefragmentstothe the hidden terminal problem. Furthermore, we calculate the
vehicle with the shortest distance from S. back-off time using a constant back-off window size so that
we can calculate the average transmission probability of each
vehicle as
V1 ζ = 2 . (20)
V2 V3 W +1
S
In order to calculate the success probability of packet
Resource vehicle communication transmission,weassumethatnnodescompeteforonechannel
coverage wherenobeysPoissonDistributionanditsprobabilitydensity
V,V,V:vehicles that are in the communi-
1 2 3 cation range of resource vehicle Travel direction（towards the left） function is formulated as
S: resource vehicle Travel direction（towards the right） (ρR )x
f (x)= cs exp(−ρR ), (21)
n x! cs
Fig. 4: Multiple Vehicles within Communication Range: the nearest vehicle
isselectedastheclustermember,thereafterStransfersfragmentstoit. where ρ is a traffic density parameter, R is the diameter of
cs
carrier sense range of a vehicle. Then the probability that a
B. Cluster Establishment
nodesuccessfullysendingpacketsinanyslotcanbecalculated
With CFT, if a vehicle cannot download the required file
as
completely from the resource vehicle within the connection nζ(1−ζ)n−1
P = . (22)
time between them, then the vehicle will establish a liner suc 1−(1−ζ)n
cluster and cooperate with other vehicles in the cluster to
Then the throughput of the MAC layer between two vehicles
download the file. There are many methods to establish a
can be formulated as
cluster in VANETs. The key problem is how to find the
E[V ] P L
vehicles that have similar characteristics as cluster members. R = payload = suc p[1−(1−ζ)n], (23)
thr E[length of a slot time] T
In the proposed scheme, the following steps are used to
establish a cluster. whereVpayload isthepayloadinformationtransmittedinaslot
Step 1: The request vehicle broadcasts a request packet for time, Lp is the average length of a packet, T is the average
cooperative file transfer, then a neighboring vehicle which is length of a slot which is formulated in [9].
within the communication range and willing to assist sends Consequently, the amount of data that can be transferred
back an ACK. When the request vehicle receives the ACK, between cooperative vehicle i and request vehicle R within
it will request the basic information, such as velocity and lo- their connection time can be calculated using the connection
cation, of the neighboring vehicle. Thereafter, the appropriate time ∆Ti,R, which can be obtained using Eq. 5, and the
neighboring vehicle will be invited to join the cluster. Note throughput Rthr, which can be obtained using Eq. 23.
that the neighboring vehicle is a cluster member while the
request vehicle is the cluster-head. D. Detailed File Transfer Process
Step 2: The neighboring vehicle that joins the cluster
The detailed file transfer process is summarized as Alg. 1,
continues to broadcast the request packet for cooperative file whereRistherequestvehicle,Sistheresourcevehicle,VRS
data
transfer and invites its neighbors to join the cluster. Then the
is the transmissioncapacity between R and S, and V is the
file
basic information about the newly-added cluster member is
size of the file to be transferred.
forwarded to the cluster-head vehicle. Step 2 is repeated until
enough cluster members have jointed the cluster. Algorithm 1 CFT: Cluster-based File Transfer
According to the V2V communication model mention pre-
1: if R requests resource from S then
viously, we are able to calculate the amount of data every 2: R evaluates the transmission capacity VRS ;
data
cluster member can download. Assuming that the size of the 3: if VdRaSta ≥Vfile then
filetobetransferredisVfile,thesizeofallfilefragmentsthat 4: R downloads files directly;
vehicle i in the cluster can download is Vi and the number 5: else
data
oftherequiredvehicles(i.e.thesizeofthecluster)isN ,then 6: R establishes a cluster and cooperates to download files
c with cluster members;
Vi and N are formulated as
data c 7: end if
Vi =Cc , (18) 8: end if
data i,S
TABLEI:SimulationParameters
Fig. 5 includes a file transfer example. If R can download
the file from S within the connection time, then R will Parameter Value
not establish a cluster. Otherwise, R will establish a cluster Lengthofperlane(km) 11
Widthofperlane(m) 5
for cooperative file transfer. We assume that three vehicles
Minimumspeed(km/h) 60
are needed to finish the file transfer in this example and
Maximumspeed(km/h) 120
each of them can finish the file fragment transfer within Trafficdensityρ(car/km) {5,6,...,10}
the connection time. After cluster members complete the file CommunicationrangeofvehicleR(m) {250,300,...,600}
fragment transfer, they forward their fragments to the cluster- SafetyDistanceSD (m) {75,100,150}
Sizeofback-offwindowW 32
head R, which is illustrated in Fig. 6.
LengthofAPacketLp (KB) 4.2
LengthofaslotTslot−time (us) 13
TransmissiontimeofRTSframe(us) 53
TransmissiontimeofCTSframe(us) 37
123 TransmissiontimeofDIFSframe(us) 32
R R TransmissiontimeofSIFSframe(us) 53
S S
TransmitpowerPt (W) 0.2
HotnoisepowerNr (dBm) −96
123456 123456
Pathlossindexα 4
(a) (b)
Gt,Gr,ht,hr,L 1
123 4 123 4
R R 56 B. Simulation Results
S S
1) Average Connection Time: Fig. 7 shows the average
123456 123456 connection time under different traffic densities and commu-
(c) (d)
nication ranges when SD = 150 m. Note that ρ denotes the
Fig.5:CooperativeDownloading numberofvehiclesperkilometer.Ouranalysisandsimulation
resultsindicatethattheaverageconnectiontimeincreaseswith
(cid:23) the communication range. When the communication range
(cid:20)(cid:21)(cid:22)(cid:23)(cid:24)(cid:25) (cid:24)(cid:25) is 250 m, the average connection time is 5.3 s. When the
(cid:39) communication range is 600 m, the average connection time
(cid:54)
is about 12.7 s. The average connection time does not vary
significantly with the densities under investigation.
(cid:20)(cid:21)(cid:22)(cid:23)(cid:24)(cid:25)
2) Average Throughput: Fig. 8 shows the average through-
Fig.6:ClusterMembersForwardFileFragmentstoCluster-Head
put between two vehicles under different traffic densities,
safety distances and communication ranges. Our experimental
results indicate that when ρ = 5 and the communication
IV. EXPERIMENTALRESULTS range varies from 250 m to 600 m, the average throughput
varies from 6.6 Mbps to 8.0 Mbps; when ρ = 6, the average
In our research, we studied the performance of CFT via throughput varies form 6.9 Mbps to 8.2 Mbps; when ρ = 7,
extensive theoretical analysis and Mablab-based simulations. the average throughput varies form 7.2 Mbps to 8.4 Mbps.
Ourdetailedexperimentalresultsarepresentedinthissection. In summary, the average throughput increases with the traffic
Specifically, the performance of CFT was investigated in density and communication range.
termsofaverageconnectiontime,averagethroughput,average 3) Average Transmission Capability: Fig. 9 shows the
transmission capability, maximum file transfer volume, and average transmission capability between two vehicles under
cluster size. We also compared CFT to one of the state-of- different communication ranges and traffic densities when
the-art scheme, IOCT [9], to understand the advantages and SD = 150 m. Our experimental results indicate that when
disadvantages of CFT. Our detailed experimental results are ρ = 5 and the communication range varies from 250m to
presented in this section. 600 m, the average transmission capability varies from 35.0
MB to 102.9MB; when ρ = 6, the average transmission
capability varies from 37.1 MB to 104.8 MB; when ρ = 7,
A. Simulation Settings
the average transmission capability varies from 38.1 MB
Inoursimulations,weuseafreewaymodel,wherevehicles to 107.9 MB Therefore, the average transmission capability
travelonabi-directionalhighwaywithtwolanesperdirection increases with the traffic density and linearly increases with
[16]. The major parameters are included in Table I. We use the communication range.
the IEEE 802.11b DCF mechanism as the MAC protocol and 4) MaximumFileTransferVolume: Fig.10showsthemax-
V2V communication protocol as the wireless communication imum file transfer volume of CFT and IOCT under different
protocol.Inaddition,theRTS/CTSmechanismisusedtoavoid traffic densities when R = 250m. Our experimental results
the hidden terminal problem. indicate that when ρ varies from 5 to 10, the maximum file
9.0
r=5 Analysis (cid:1)(cid:8)(cid:7)(cid:6)(cid:3)(cid:4)(cid:2)(cid:9)r=5 (cid:1)(cid:8)(cid:7)(cid:6)(cid:3)(cid:4)(cid:2)(cid:9)r=6 (cid:1)(cid:8)(cid:7)(cid:6)(cid:3)(cid:4)(cid:2)(cid:9)r=7
Average Connection Time (sec.)11246802 rrrrr=====56677 SASASininimmmaauuullyylllssaaaiitttssiiiooonnn Average Throughput Between Two Vehicles (Mbps)67788.....50505 (cid:1)(cid:1)(cid:8)(cid:8)(cid:7)(cid:7)(cid:6)(cid:6)(cid:3)(cid:5)(cid:2)(cid:4)(cid:2)(cid:9)(cid:9)(cid:1)(cid:1)rr==55 (cid:1)(cid:1)(cid:8)(cid:8)(cid:7)(cid:7)(cid:6)(cid:6)(cid:3)(cid:5)(cid:2)(cid:4)(cid:2)(cid:9)(cid:9)r=r=6 6 (cid:1)(cid:1)(cid:8)(cid:8)(cid:7)(cid:7)(cid:6)(cid:6)(cid:3)(cid:5)(cid:2)(cid:4)(cid:2)(cid:9)(cid:9)r=r=77
0
250 300 350 400 450 500 550 600 250 300 350 400 450 500 550 600
Com m unication Range of Vehicles (m ) Com m unication Range of Vehicles (m )
Fig.7 :AverageConnectionTime Fig.8:AverageThroughput
120
B) r=5 C FT C FT
Average Transmission Capability between Two Vehicles (M12468000000 250 3 0rr0==67 350 400 450 500 550 600 Maximum File Transfer Volume (MB)1234000000000 5 IO C T6 7 8 9 10 Maximum File Transfer Volume (MB)1234000000000 5 IO C T6 7 8 9 10
Com m unication Range of Vehicles (m ) Traffic Density (vehicle/km) Traffic Density (vehicle/km)
Fig.9:AverageTransmissionCapability Fig.10:MaximumFileTransferVolume Fig.11:ClusterSize
transfer volume of IOCT varies from 35 MB to 45 MB, REFERENCES
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