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Bilal Munir Mughal1, Asif Ali Wagan

2, Halabi Hasbullah

3

Safety Messaging

Department of Computer and Information Sciences,Universiti Teknologi PETRONAS,

Bandar Sri Iskandar, 31750 Tronoh, Perak Malaysia1bilalmunirmughal@gmail.com, 2asifwaggan@gmail.com, 3halabi@petronas.com.my

Abstract The prime goal of Vehicular Ad hoc Network(VANET) is to provide life safety on the road. To achieve this,

vehicles make use of two types of safety messages i) Periodic

safety messages (beacons): to exchange status information e.g.

position, speed etc. ii) Event-driven messages: broadcast in case of

an emergency situations e.g. accidents, hard-braking etc. As both

type of messages use same Control Channel, in dense traffic

periodic beacons may consume the entire channel bandwidth

resulting in a saturated/congested channel. In a congested channel

event-driven messages may not be able to access the channel at

all, thus providing no safety. Researchers have proposed different

strategies to overcome this problem. Most of these strategies rely

on the concept of a limiting beacon bandwidth usage level below a

specific threshold and thus implicitly reserving a chunk of

bandwidth for high priority even-driven messages. In the

proposed strategies either transmission rate or power control

techniques are used to control congestion. In this paper we

evaluate such techniques and highlight following major

drawbacks first: using only power control techniques do not

satisfy requirements of envisioned beacon-dependent safety

applications, second: methods used for measuring channel usage

level in transmission rate control technique may not be as

effective under real world conditions. We also present a

conceptual view of a congestion control scheme using

transmission rate and transmission power simultaneously for

optimal results.

Keywords-VANET; safety messaging; congestion control;

beacon rate control; transmit power control; bandwidth reservation

I. INTRODUCTION

Vehicular ad hoc network (VANET) is envisaged from the

Intelligent Transportation System (ITS). Technically speaking

VANET is a form of Mobile Ad hoc Network (MANET), in

which vehicles form a decentralized network bycommunicating via On-board units (OBUs). One major

difference between MANET and VANET is that in MANETs

nodes move randomly and in VANETs nodes primarily follow

a predefined path such as roads making their movement more

predictable. As shown in Figure-1, in VANET environment

vehicles communicate with roadside infrastructure (V2R) and

with nearby vehicles (V2V) generally described as V2X

communication. VANET applications can be divided into two

major categories safety and non-safety applications.

Applications that are critical to human life safety are placed

under safety application category e.g. pre-crash sensing, post-

crash warning, pedestrian/children warning etc. and non-safety

applications include toll collection, mobile internet,

infotainment and many more.

Figure 1. VANET Communication: Vehicle-to-Vehicle (V2V) and

Vehicle-to-Roadside Infrastructure (V2R)

A. Standards

A lot of work and research around the globe is beingconducted to help define the standards for VANET i.e.

frequency allocation, PHY & Link layer standards, routing

algorithms as well as security issues and new application [1].

Effort to finalize VANET communication standards such as

Wireless Access in Vehicular Environment (WAVE), IEEE

1609.x and 802.11p is in progress by standardization

organizations. WAVE is a trial layered architecture used by

IEEE 802.11 devices to operate in the DSRC band for V2X

communication. In USA, FCC has allocated DSRC spectrum

at 5.9 GHz, which is structured into seven of 10 MHz wide

channels. Channel 178 (5.885-5.895GHz) is the control

channel (CCH), that is primarily used for safetycommunications. The two extreme channels are reserved for

future safety applications, e.g. advanced accident avoidance

applications. The other service channels (SCH) can be used for

both safety and non-safety applications. At PHY level, the

philosophy of IEEE 802.11p design is to make minimum

necessary changes to IEEE PHY so that WAVE devices can

communicate effectively among fast moving vehicles in the

roadway environment [2].

978-1-4244-6716-7/10/$26.00 2010 IEEE

Efficient Congestion Control in VANET for

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B. Safety Applications & Messaging

Safety can be achieved in VANET via safety applications

that depend upon message exchange among neighboring

vehicles and roadside infrastructure. A comprehensive set of

DSRC-enabled safety applications have been identified in

Vehicle Safety Communications Project report [3].

VANET safety messages can be divided into two types,

periodic messages (aka beacons) and event-driven safety

messages. Periodic messages are exchanged among

neighboring vehicles several times per second and contain

information (position, speed; direction etc) that is useful for

drivers awareness of the surrounding situation. Efficiency of

many envisioned safety applications e.g. Intersection Collision

Warning, Low Bridge Warning, Cooperative Collision

Warning (CCW) depend upon the information received from

beaconing. Even-driven messages are broadcast when a

hazardous situation is detected on the road e.g. accident.

Examples of applications that can use event-driven messages

are Post Crash Warning, Emergency Electronic Break Lights

(EEBL) etc.

C. Research spotlight

Providing efficient messaging schemes is a challenging task

because of particular characteristics of VANET i.e. high

mobility, limited channel bandwidth, very short

communication duration, highly dynamic topology etc.

Furthermore due to the broadcast nature of the communication

in VANET, IEEE 802.11 RTS/CTS mechanism is expected to

perform poorly under high speed dense node population [1].

This could potentially lead to saturated/congested channel,

which has been identified as a major concern in [4-5] forefficient safety communication. Because of the fact that

beacons dominate control channel load and have a relatively

long useful life of a few seconds, it is natural to devise a

congestion control scheme around adjusting their generation

rate and transmission power [4]. Furthermore according to [6]

transmission powers and transmission rate are suitable

methods for periodic message congestion control. However to

the best of our knowledge no effort has been done to so far to

use both methods simultaneously.

In this paper we provide an analysis of previously proposed

schemes that are based on beacon generation rate and

transmission power control. We carefully select two of themost promising techniques from each method for a detailed

analysis. Based on our analysis we identify drawbacks of the

existing techniques. To tackle these drawbacks we also

propose a conceptual view of conditional hybrid approach that

controls transmission rate and power concurrently.

The rest of the paper is organized as follows. Section II

related work, Section III information analysis, Section IV

problem formulation and technical challenges, proposed

research methodology is given in Section V, finally we

conclude our paper in section VI followed by

acknowledgement and references.

II. R ELATED WORK

Lars Wischhof and Hermann Rohling provide a Utility-based

packet forwarding and congestion control scheme (UBPFCC)

scheme [7] that works on top of IEEE 802.11 MAC protocol

and is focused on non-safety applications which is out of thescope of this study. Furthermore authors in [8] argue that this

approach needs the road to be segmented into sections for

calculating the message utility metric, thus it cannot be used

directly in the context of safety applications.

Authors of [9] present a power control scheme based on

estimation of surrounding traffic density concerning a

particular node. However like many other power control

schemes, the main focus is to maintain connectivity using

dynamic transmission range assignment.

A power control technique is introduce in [10] that is based

upon a Delay-Bounded Dynamic Interactive Power Controlmodule that shows prompt 1-hop neighbor connectivity but

makes use of eight directional antennas thus not readily

suitable for VANET environment.

In [11], Marc Torrent-Moreno, Paolo Santi and Hannes

Hartenstein present Fair Power adjustment for Vehicular

environment (FPAV) algorithm. Conceptually in FPAV

vehicles have to adjust their transmission power using power

control techniques in such a way that bandwidth utilized by

periodic messaging does not exceed a predefined threshold

known as MBL (maximum beaconing load). The idea behind

defining MBL is to reserve a chunk of bandwidth for event-

driven message so that communication of safety applications is

not hindered by channel saturation. In addition an approach to

attain max-min fairness transmit power is given that relies on

global knowledge assumption. The centralized nature of the

scheme makes it unrealistic in VANET environment due to

lack of central entity presence at all locations.

Considering the drawbacks of FPAV same researchers

designed an enhanced and fully distributed version called D-

FPAV (Distributed Fair Power adjustment for Vehicular

Networks) in [12]. D-FPAV was also formally proven to

follow the max-min fairness criterion. Its effectiveness was

proved through simulations under different radio propagationmodels such as two Ray Ground, Nakagami and log normal

shadowing. The enhancements in D-FPAV come at the cost of

reduced beaconing range and control message overhead.

Moreover like its predecessor D-FAV also requires global

knowledge which is not easy to obtain in VANET.

To reduce communication overhead generated by D-FPAV,

Jens Mittag et al. introduce Distributed vehicle Density

Estimation (DVDE) and Segment-based Power Adjustment for

Vehicular environments (SPAV) strategies in [6]. Simulation

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results of DVDE/SPAV also confirm less control overhead as

compared to D-FPAV. It is also shown that in order to

guarantee a network-wide beaconing threshold, precise

information is necessary up to three times a nodes maximum

communication range, regardless of the propagation model or

of traffic density distribution. Nevertheless presented scheme

does not strictly follow the MBL threshold and beaconing

range remains limited.

A contention-based forwarding scheme namely EMDV

(Emergency Message Dissemination for Vehicular

environment) [13] works along customized D-FPAV and is

used to improve propagation of event-driven messages in the

network. Simulations results show that with D-FPAV on

beacon reception rate drops significantly after the distance of

160 meters. We further discuss these results in section III.

One congestion detection and two beacon rate control

algorithms are presented in [8]. However we only concentrate

on second beacon rate control approach called adaptive QoS

which is already proven to outperform first approach known asqueue freezing. We further discuss this in following section.

III. INFORMATION ANALYSIS

Research studies that focus on CCH saturation from safety

communication point of view are presented in previous

section. Most of the proposed congestion control schemes are

based on one fundamental concept, i.e. limiting resource

allocation (e.g. bandwidth, channel access) to periodic

messages in such a way that sufficient resources are always

available for efficient event-driven safety messaging.

Furthermore these schemes either use adjustment of

transmission range (using power control) or transmission rate(packet generation rate) to achieve their goal. However

researchers have used different metric for congestion detection

(e.g. channel busy time, carrier sensing) and efficiency

assessment (e.g. message reception probability, warning

delay). Therefore, as per information provided in referenced

literature, it is not convenient to present a comprehensive

comparison of the proposed solutions.

We carefully choose two promising approaches for detailed

analysis one each from power control and transmission rate

control techniques. From power control techniques we select

D-FPAV protocol as it has been well studied in literature and

its effectiveness in achieving certain objectives has beenestablished through extensive simulations [6][13]. We also

analyze and discuss only available transmission rate control

technique so far that is presented in [8].

A. Transmission Range/Power Control Technique: Distribute

Fair Power Assignment for Vehicular Networks (D-FPAV)

D-FPAV [12] is extension of FPAV [11] which was based

on a centralized approach (thus not suitable for VANET). The

main concept of the scheme is to keep the transmission power

thus transmission range of periodic safety messages (beacons)

in check by keeping network load below a specified threshold

called maximum beaconing load (MBL) measured in Mbps.

By restricting data rate of beacons below desired threshold, the

remaining bandwidth is implicitly reserved for high priority

event-driven messages. D-FPAV is based on strict fairness

criterion; according to this criterion no sender should increase

its transmission power if it affects the transmission/receptionability of another node. Effectiveness of fairness is possible

only if each node has complete knowledge of the network with

no exceptions. Algorithm Pseudo code is depicted in Figure-2.

Figure 2. Distribute Fair Power Assignment for Vehicular Networks (D-

FPAV) as given in [12]

In step 1 algorithm initializes as each node ui computes

optimal power level Pi in such a way that MBL threshold is

not exceeded. As the power computed is based upon eachnodes local view so in step 2a computed powerPi is broadcast

to all nodes in maximum carrier sense range CSMAX(i).

According to [13] piggybacking the power information every

10th

beacon is a suitable tradeoff between message overhead

and outdated information. In step 2b node receives Pi from

other nodes in CSMAX(i) and stores the received values. Finally

node ui sets its Pi as minimum power computed among

received power levels. For detailed description please consult

[12].

At first sight limiting transmission power seems

counterproductive in a sense that having maximum

transmission power at each node guarantees maximum

receivers thus ensuring higher level of safety. Nevertheless

more nodes in transmission range also mean higher collision

rate, increased channel load and more interference. Authors in

[8] argue that per packet transmit power control is very hard to

implement. However simulations results in [6][13] indicate

that actual rate of change in traffic load conditions is expected

to be lower than the rate of information update used, which

supports computation of power/transmission range assignment

on per packet basis. Another question that can be raised is the

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efficiency in achieving fairness, as complete knowledge of the

network may not be available always. Conversely the

simulation results support the accurate MBL control of D-

FPAV under changing traffic load condition. Moreover a

message dissemination strategy EMDV is proposed in [13]

that work well along D-FPAV for increasing message

reception probability over longer distances.

Discussion: Authors have performed extensive simulations

with realistic propagation models (i.e. Nakagami) and prove

the effectiveness of the protocol for achieving certain

objectives i.e. fairness, control over MBL threshold, efficient

event-driven message dissemination. However as per

simulation results, in D-FPAV-ON mode, beacon reception

rate drops significantly after 160 meters. According to Vehicle

Safety Communications Project Task 3 Final Report [3] most

of the safety applications that rely on periodic messaging

require a maximum message propagation area of between 200

to 300 meters and a maximum of up to 400m. As a conclusion

using simple power control techniques alone i.e. D-FPAV may

severely degrade performance of such applications.Furthermore efficient bandwidth usage with D-PAV is not

always possible as event-driven messages are suppose to be

rare thus reserved bandwidth is not utilized at all most of the

time.

B. Packet Transmission Rate Technique: Detecting

Congestion through channel usage measurement and

controlling it using prioritized queuing

In [8] authors use packet transmission rate in order to

maintain background traffic (beacons) load below a specified

threshold. The idea is based on technique called measurement-

based congestion detection. Two congestion controlalgorithms are proposed, however we only contemplate second

approach called adaptive QoS which is already proven to

outperform first approach known as queue freezing. For

demonstration purpose Emergency Electric Brake Light with

Forwarding (EEBL-F) safety application is used which is also

recognized as cooperative forward collision warning (CCW).

Proposed scheme consists of two parts Congestion Detection

and Congestion Control. In congestion detection approach

node continuously measures channel usage level according to

following formula, for detailed information please consult

paper itself.

Measuring channel usage level is difficult to achieve under

realistic environment due to various reasons such as varying

traffic densities, hidden/exposed terminal problem etc.

However simulation results show that approximation of

channel usage as per given formula is well estimated. For

congestion control authors use simple but effective approach

called adapting the channel access probability. This approach

exploits dynamic contention window (CW) size to control the

message transmission rate. Larger CW size means lower

channel access thus lower transmission rate and vice versa. If

the channel usage level exceeds set value of 95% all output

queues are blocked except for event-driven safety messages. In

case of 70% channel usage or higher, CW size is doubled, and

30% or lower channel usage results in reduction of CW size to

half till it reaches predefined minimum CW size.

Discussion: Simulations using Wireless Access Radio Protocol

II (WARP2) have shown that proposed scheme can bound the

warning delay of event driven messages below 500ms, which

is an acceptable human response time. However to further

establish the results of both proposed schemes (congestion

detection & control) further investigation is required under

realistic propagation models i.e. Nakagami, Two-ray ground

(TRG).

IV. PROBLEM FORMULATION AND TECHNICAL CHALLLENGES

A. Problem Formulation

In the light of discussions in section III we conclude that

existing power control schemes do not ensure efficient

functionality of safety applications that depend upon periodic

messaging, while it is very intricate to measure channel busy

time under real world scenarios thus channel busy time

estimation technique discussed in previous section may not

provide a solid base for congestion control. Thus finding right

channel congestion detection method for efficient transmission

rate control remains an open issue.

As of [13] power and rate control should jointly be treated

for optimum performance of vehicle-to-vehicle

communication system in traffic scenario with very high trafficdensity e.g. traffic-jam situation. We support use of

transmission rate control along with transmission power

adjustment to increase the beaconing range to an optimal

maximum level so that even under dense traffic conditions

driver awareness of surrounding is increased by providing

beacon-dependent safety applications sufficient propagation

region. However, to the best of our knowledge no such

solution exists that can take advantage of both power and rate

control methods in tandem.

B. Technical Challenges

Combining transmission rate and transmission power

techniques inevitably gives rise to technical challenges. Some

of the key challenges are highlighted below:

x Finding suitable metric for congestion detection before

dynamically choosing suitable congestion control

method.

x Ensuring simultaneous execution as well as efficient

and successful transition between both techniques

without violating predefined channel load threshold

metric i.e. MBL.

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x Efficient bandwidth utilization in absence of event-

driven safety messages.

x Maintaining fare use of resources among nodes

(fairness) within a specific region.

x Tradeoff between accurate neighbor information and

communication overhead.

V. RESEARCH METHODOLOGY

As a general concept higher transmission power results in

higher transmission range which in turn means more number

of nodes in contention for same channel e.g. CCH in a wireless

802.11 network. Given that sufficient numbers of nodes are

present within a certain transmission range of each other e.g.

traffic jams there is always a chance that a bandwidth

constraint channel may not be able to serve all the nodes

beyond a saturation point. For example as of [13] 100

neighboring nodes sending 500bytes packet at ten packets per

second can generate load more than higher to saturate CCH

with available bandwidth of 3Mb/s (with most robustmodulation/coding scheme) in VANET. Similarly transmitting

500 byte packets in shorter communication range and with half

of the above neighboring nodes at a rate of 20 packets per

second can result in the same situation.

So efficiently managing transmission range and

transmission rate is a natural choice to keep channel

congestion in check while satisfying beacon-based safety

application requirements. Though altering message size may

be another possible way to achieve the congestion control but

considering the dynamic VANET environment it is not

recommended to synthetically regulate message sizes.

Based on the technical challenges highlighted in previous

section we propose an approach shown in Figure-3 which

basically depicts flow of our scheme as conceptualized at

present.

In this scheme all nodes need to be informed about their

channel status all the time. Whenever a channel reaches its

saturation level a node is able to sense congestion

immediately. A suitable congestion detection method e.g.

beaconing load, vehicle density, channel access time etc. is

required. As soon as a node faces a saturated channel it

initiates congestion mitigation process. Based on the current

transmission power and/or transmission rate, congestion

mitigation process decides appropriate technique to be used

i.e. adjusting transmission power or message transmission rate.

A complete set of instructions is required to execute the

process. Special consideration is needed for handling smooth

transition between both techniques as increasing/decreasing

power level by one step may have different effect on channel

load as compared to adjusting transmission rate by one level.

This step is repeated if required until channel load gets below

congestion level. In the meantime event driven messages can

easily be propagated via the remaining bandwidth withmaximum penetration.

VI. CONCLUSION AND FUTURE WORK

In this paper we analyzed congestion control problem and

some of the previously proposed solutions. Specifically we

focused on transmission rate and transmission power control

methods. We presented a detailed analysis on two of the most

promising techniques one from both methods. Based on issues

highlighted in our analysis and discussions we advocate a

hybrid solution that can use both techniques dynamically and

adaptively. To achieve this we also presented a conceptual

view of a congestion control scheme. As of our future work

we intend to develop suitable algorithms along with

congestion metric that best fit in our conceptualized scheme.

This is a preliminary study for comprehensive congestion

control solutions for VANET and the technical challenges

highlighted in this study are to be dealt in future work.

ACKNOWLEDGMENT

Figure 2. Flow chart for conceptualized congestion control scheme

We would like to thank Department of Computer and

Information Sciences of Universiti Teknologi PETRONAS

(UTP) for providing grant and facility for the research.

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