基于预测性竞争窗口的VANET广播冲突缓解策略
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Predictive Contention Window-based Broadcast
Collision Mitigation Strategy for VANET
Yanfei Lu
1
, Jianmin Ren
1
, Jin Qian
1
, Meng Han
2
, Yan Huo
1
, Tao Jing
1
1
School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China
2
Department of Computer Science, Georgia State University, USA
E-mail: {yflu,14120113,qianjin}@bjtu.edu.cn, mhan7@student.gsu.edu, {yhuo,tjing}@bjtu.edu.cn
Abstract—In vehicular ad-hoc network (VANET), safety ap-
plications require the dissemination of safety information and
vehicular states to all nearby vehicles through broadcasting.
However, due to the tremendous information, broadcast channel
will be confronted with great pressure. Therefore, vehicles should
adjust their contention window to avoid intense competition on
channel. In this paper, we propose a new contention window
adjustment mechanism based on classification strategy and pre-
diction scheme. The classification strategy availably classifies
vehicular states into attribute sets by taking account of mul-
tiple factors. With this processing, we can obtain contention
window corresponding to the attribute sets by BPR (Bayesian
Personalized Ranking) algorithm. Subsequently, we adopt the
prediction scheme to obtain vehicular states at next moment
which map directly to the attribute sets. Finally, the prediction
result is employed to explore the contention window at next
moment according to retrieving attribute sets. The simulation and
analysis show that our scheme provides outstanding performance
compared with other classical single factor schemes in term of
reducing collision probability and transmission delay.
Keywords—VANET, Broadcast, Contention Window, Hidden
Markov model
I. INTRODUCTION
Because of the various diversity of networks, VANET,
an exclusive form of mobile ad-hoc network (MANET), is
widely employed in vehicular area, such as vehicle to vehi-
cle (V2V) or vehicle to infrastructure (V2I). For smoothly
conducting studies on VANET, FCC (Federal Communica-
tions Commission) has allocated 75MHz bandwidth which
is between 5.850GHz and 5.925GHz for DSRC in traffic
filed [1]. Within the designated spectrum, 6 service channels
(SCHs) are divided for exchanging non-safety related data.
Conversely, system management related to security appli-
cations is implemented only by a control channel (CCH)
[2], [3]. Essentially, the increasing demand in VANET is
security applications. The reliability of this demand is mostly
based on the inter-vehicle communications, in which a large
portion of the communicated messages are delivered through
broadcasting. Periodic broadcasting of the safety messages
is the most frequently used message delivery mode on the
CCH in VANET for safety applications [4]. For example, the
warning messages need to be broadcasted to nearby vehicles
if there is an emergency event occurring (e.g. accident or lane-
changing) and the vehicular status messages (beacon) [5], [6]
also need to be exchanged periodically among vehicles. As we
know, the beacon contains useful vehicular information (e.g.
vehicle location, velocity and direction) to achieve significant
security applications, especially in collision avoidance and
driver assistance [6]. However, due to the huge amount of
information to exchange, CCH suffers a great deal of broadcast
pressure which prominently reflects in high message collision
ratio and long transmission delay.
Focusing on the broadcast performance improvement in
VANET, the previous optimized work was in IEEE 802.11p
[4], [7] which was an approved amendment to IEEE 802.11
standard to provide wireless access to support Intelligent
Transportation System (ITS) [8]–[10] applications in VANET.
Unlike the unicast communications, the significant charac-
teristics of broadcast were lack of RTS/CTS handshake and
acknowledgment (ACK) which would lead to an ACK storm
during transmission procedure. Therefore, when each node
sensed the CCH before transmission, contention window be-
came the decisive measure for coordination of information
transmission. If the channel was sensed to be idle for a period
time equal to DIFS (distributed interframe space) [11], [12],
the node generated a random backoff time which was drawn
from a uniform distribution over the interval [0,CW], where
CW is the value of contention window. However, the window
in IEEE 802.11p was determined by fixed value and only
when the message collision occurred, it would double its value
[9]. Obviously, the distinctive characteristics that the VANET
possessed include variability in node density and higher speeds
of vehicular nodes which had an great effect on broadcast
capacity by changing congestion level [10]. So the window
should be intelligent enough to dynamically adjust its size
with the characteristics in VANET. Previously, there had been
automatic adjustment in [13] for VANET. The existing work
provided contention window adjustment formulas which are
respectively on the basis of only one kind of influence factor.
This limitation restricted the comprehensive utility of vehicular
information, accordingly resulting in inaccurate window size.
In this paper, we propose predictive contention window
(PCW) strategy to dynamically adjust the window size by
comprehensively considering multiple factors which directly
represent traffic density. The basis of new method is to
establish classification strategy for preprocessing vehicular in-
formation. Subsequently, we implement estimation mechanism
to achieve the adjustment so as to solve the problem of poor
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2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking
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2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking
(SocialCom), Sustainable Computing and Communications (SustainCom)
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DOI 10.1109/BDCloud-SocialCom-SustainCom.2016.41
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2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking
(SocialCom), Sustainable Computing and Communications (SustainCom)
978-1-5090-3936-4/16 $31.00 © 2016 IEEE
DOI 10.1109/BDCloud-SocialCom-SustainCom.2016.41
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