187 3rd IEEE Inte

9

Performance EvaluBit Rate Traffic M

Using Dyn

Panos Bakalis*, Lawal Bello, ODept

E-mail :{P.

Abstract—In this paper, we describperformance of Vehicular Ad hoc netwtraffic models in a dynamic changing esimulation results showed that as delay anthe throughput of receiving bits decrstabilizes and the delay tends to drop at indo drop as the packet size increases. Keywords— Intelligent Transportation SAd hoc Networks, Contention Based RSource Routing.

I. INTRODUCTION

Wireless vehicular ad hoc network researchwithin the field of Intelligent Transportation recent developments in wireless technolVehicle-to-Vehicle communication (V2V) a(RSU) achievable in mobile ad hoc networkhas given birth and brought a new concept oknown as the vehicular ad hoc network (VANhoc Networks (VANETs) are self-organizinwheeled mobile units consisting of large numa small number of fixed infrastructure nodeaccess units within radio communication raThe initiative behind VANET is facilitating management and infotainment disseminatiopassengers. Internetworking over VANETs interest and importance for researchers by governmental organizations and the academgaining a great deal of momentum for the pVANET networks are identical to MANET nrapidly and dynamically change network topfast motion of vehicles but differ because of in vehicular density, relative high speed ocongestion on roads, traffic control mechanisof vehicles are constrained by predefined roadVANET is to improve the safety of motor velives have been lost and much more injuries due to car crashes. Accident prevention caalert drivers about conditions that could causethe event on an accident, communication wilother vehicles preventing further accidentRescue vehicles could immediately receive ethe location of an accident to reach the scenefaster. The use of VANETs could enhance tdrivers with its safety system features whichbroadcast road information. Information sucincidents and real-time traffic congestion, higso on. VANET should, upon implementdistributes a fety information to massively red

ernational Conference on Adaptive Science and Techn

978-1-4673-0759-8/11/$26.00©2011 IEEE

uation of Constant Bit Rate Models on Vehicular Ad Honamic Source Routing Proto

OlamideJagun, KwashieAnang, Titus Eneh & t of Wireless & Mobile Communication Engr,

University of Greenwich, UK .bakalis, L.Bello, et14, K.Anang}@greenwich.ac.uk

be a simulation work on different environment. The nd jitter increases, reases, the nodes nterval but packets

System, Vehicular Routing, Dynamic

h plays a vital role System (ITS). The ogies have made and Roadside Unit

ks (MANETs). This f MANET network

NET). Vehicular Ad ng communities of

mber of vehicles and es such as roadside ange to each other.

road safety, traffic on for drivers and

has been of great car manufacturers,

mic sector and it is ast few years now.

network in that they pologies due to the f the regular change of vehicular nodes, m and the mobility ds. The idea behind ehicles where many have been incurred

autions can quickly e a collision. And in ll be transmitted to ts from occurring. exact coordinates of e of the emergency the convenience of h may intelligently

ch as road hazards, gh-speed tolling and ation, collect and duce the number of

accidents by cautioning drivers actually face it. Such networks inUnits (OBU) installed in vehicles collected from the sensors could bsystem to provide alternative drivavoid platoon vehicles, improve rosafety systems in place, mainly accidents. A pictorial example of a vehicularshown in figure 1.

Figure 1. Vehicular ad hoc netCommunication Consortium 20 New applications are proposed by [that include Electronic Toll Collcommunications, travel and tourismmultimedia and game applications.need reliable and unfailing commucapable of achieving high data rbetween the transmitter and recconditions and different surrounding In [5], an analysis of network trafficthe Destination Sequenced Distanwith an emphasis on mobility and cmobile nodes is presented. The gowas to measure the ability of DSDmulti-hop ad-hoc network topologsize, mobile nodes movement, numobile nodes, and also the amountransmits. To measure this, the basi

nology (ICAST 2011)

and Variable oc Network ocol

Aminu Muhammad

about the risk before they nvolve sensors and On Board

as well as RSU. These data be fed into vehicle navigation ving routes and thus helps to oad capacity and with active

reduce the number of car

r ad hoc network scenario is

work scenario (Car to Car 10 [1].

[2,3,4] for vehicular networks lection (ETC), car to home

m information distribution and . However, these applications unication equipment which is rates and stable connectivity ceiver under high mobility gs.

c in ad hoc networks based on nce Vector (DSDV) protocol communication patterns of the al of the author’s simulations V routing protocol to react to

gy changes in terms of scene umber of connections among nt of data each mobile node c methodology was defined to

188 3rd IEEE International Conference on Adaptive Science and Technology (ICAST 2011)

a set of movement scenarios and communication patterns and applied them to an ad hoc network. Different simulations were examined by changing the parameters for mobile nodes movement scenarios and their connection patterns. The number of forwarded packets increased as the size of the ad hoc network scene area increased. Fewer packets needed to be forwarded when there was larger number of mobile nodes in a scene. Conversely, ratio of lost packets decreased with an increase in numbers of mobile nodes. Increasing the number of connections among fixed number of nodes enhanced the routing overhead and the packet delivery rate. Increasing the transmission rate in an ad hoc network with fixed size and number of mobile node increased the number of transmitted packets in different groups. Interestingly, this increase did not affect the packet delivery rate or the routing overhead. It was observed in [6] that despite the popularity of the most common routing protocols such as Ad Hoc on Demand Distance Vector (AODV), Destination Sequenced Distance Vector (DSDV), Dynamic Source Routing (DSR) and Optimized Link State Routing Protocol (OLSR), research efforts had not focused much in evaluating their performance when applied to variable bit rate (VBR). But these were implemented in a mobile ad hoc network scenario [7]. Ns-2 network simulator was used to evaluate the performance comparison of these protocols for VBR in MANETs. Proactive protocols failed to respond fast enough to changing topology. The authors observed that routing overhead in proactive protocols remained almost constant and OLSR being winner irrespective of mobility while AODV increased with increase in mobility. AODV and DSR use reactive approach to route discovery, but with different operation mechanism. DSR used source routing and route cache and did not depend on their timer base activity. On other hand AODV used routing tables, one route per destination, sequence number to maintain route. DSR however generated lower overhead than AODV while OLSR and DSDV generated almost constant overhead due proactive nature. The studies showed that reactive protocols perform better than proactive protocols. The author finally concluded that DSR performed well in terms of packet delivery ratio and less routing overload while AODV performed better in terms of less average end to end delay. The need to improve AODV routing protocol performance throughput was addressed in [8]. The AODV protocol always exchange control packets between neighbour nodes for routing which increases the bandwidth consumption. To make it more usable for VANET, elimination of route discovery phase by restricting neighbour’s distance and number of discovered routes was proposed. There were two methods used: restricting route request packets and restricting routes based on distance. In the ‘restricting route request packets, number of routes was reduced by limiting number of discovered routes based on a route boundary. While in ‘restricting routes based on distance was based on distance in reducing the number of hops, finding the shortest route between any source and destination and therefore broken links along a route would be reduced. This new improved AODV was termed Prior AODV (PAODV). Performance evaluation of routing protocols of AODV, DSR and Swarm routing protocols was conducted by [9], this is to verify a suitable protocol for VANET. Each simulation scenario was repeated 10 times to achieve a high confident level in results. Four typical performance measures for VANETs were considered and finally concluded that AODV and DSR might not be suitable for vehicular environments but SWARM showed promising results. Routing protocols have always been a challenge in vehicular ad hoc networks since the position of vehicular nodes change in high speed and time. Proposed routing protocols intended for VANET could play a big role and change the face of vehicular

environments. A routing protocol that would enhance the stability of Inter-vehicular Communications (IVC) and Road-Vehicle Communications (RVC) in VANET networks is proposed in [10]. This was divided into three parts: Grouping of vehicles, Receive on Most Stable Group-Path (ROMSGP) packet format and the calculation of link expiration time (LET). The idea behind the scheme was to group vehicles according to their velocity headings that would ensure that vehicles belong to the same group and would generally move together. Routes involving vehicles from the same group thus exhibit high level of stability and among these possible routes, communication was set up on the most stable route using the (ROMSGP) scheme. Decision on the most stable link was made based on the computation of the (LET) of each part and the path with the longest LET was considered the most stable link. Simulation results showed the effectiveness of the protocol compared to DSR and Associativity-Based Routing (ABR) and concluded that the proposed protocol should be able to provide good stability and maintain high throughput in VANET environment. A contention based routing protocol (CBRP) for VANETs in urban environments is proposed in [11]. CBRP’s main idea was to forward the packet through the wireless channel as much as possible, and adopt the idea of “carry and forward” if there is no suitable neighbour for packet forwarding. The protocol worked in two modes: street mode and junction mode. When a packet is carried by a vehicle in a street, CBRP operates in street mode; using contention based forwarding to deliver the packet greedily to the next junction. And when a packet is in the junction area, CBRP operates in junction mode; it first performs junction selection in order to determine the next junction, and then uses the contention based forwarding to forward the packet to the new next junction. CBRP performed better than the position based type in terms of packet delivery ratio as well as average delay transmission cost. One of the major worries of vehicular ad hoc networks is about its traffic and mobility models. Traffic and mobility models designed for Mobile Ad Hoc Networks (MANET) needs to be experimented on VANET to evaluate its performance in vehicular scenarios. However, conducting real experiments on roads for this kind of network are both dangerous and expensive. A real experiment might require the need of renting many vehicles (cars, Lorries, trucks, vans and so on), purchase communication gadgets and employ experimenters. At times, vehicles need to move on a high speed scenario which poses a possible danger such as collisions with other vehicles and even pedestrians. For this reason simulation model is used to carry out the research using Ns-2 simulator. Therefore, the contribution of this paper is to evaluate and compare the performance of Constant Bit Rate (CBR) over Variable Bit Rate (VBR) traffic models on vehicular ad hoc network using on demand Dynamic Source Routing protocol. The rest of the paper is organized as follows. Section II; focus on the Dynamic Source Routing (DSR) protocol for ad hoc wireless network. In Section III we describe the simulations model, results and interpretations. Section IV, presents the conclusions

II. DYNAMIC SOURCE ROUTING PROTOCOL (DSR)

DSR is a simple and efficient routing protocol designed specifically for use in multi-hop wireless ad hoc networks of mobile nodes which operate entirely on demand, allowing the

189 3rd IEEE International Conference on Adaptive Science and Technology (ICAST 2011)

routing packet overhead of DSR to scale automatically to only what is needed to react to changes in the routes currently in use [12]. Performance evaluation conducted on both proactive and reactive protocols [13-16], showed that DSR performed better than AODV and other proactive protocols in terms of throughput, end-to-end delay, and packets drop. The DSR performance is attributed to its characteristics of having multiple routes to other destination. In case of link failure, it does not require a new route discovery processes. Because of this, end-to-end delay is reduced, t less packet drops and less energy consumption. Hence, the DSR protocol was chosen as genial candidate for carrying out this work.

III. SIMULATION MODEL We use Ns-2 simulator (version 2.29.2) developed in [17]. Details about the simulation model and environment are presented in the rest of this section.

A. SIMULATION PARAMETERS In order to evaluate the performance of Vehicular ad hoc network on two different traffic models (CBR and VBR), simulations were carried out using Ns-2 simulator [17]. The topology consists of 1000 m X 1000 m grid with 50 mobile nodes moving around using the random way point mobility model. Constant bit rate (CBR) as well as Variable bit rate agents was used for generating traffic in the network. Each simulation scenario was repeated 6 times to achieve a high confidence level in results over a period of 500 seconds real time, which enabled the simulation to converge for accurate result. The basic parameters used for the simulations are summarized in Table I.

Table I. Simulation Parameters Simulation parameters

Parameters Values Network Simulator NS2-2.29.2 Simulation Area 1000 x 1000 metres Simulation Time 500 seconds Number of vehicles 50 Number of trials 6 Speed 70 miles per hour Traffic Model CBR,VBR Mac Protocol IEEE 802.11 Propagation Model Two-ray Ground reflection model Packet Size 532 bytes Channel Type Wireless Channel Antenna Model Omni directional

B. SIMULATION RESULTS

In this section, we present simulation results for the performance evaluation. Figure 2 and 3shows the average end to end time delay versus throughput of receiving bits. This illustrates what happens to the delay as the throughput of receiving bits is being received. At the beginning of the route discovery, the network with VBR traffic model experienced an average delay of 0.11 seconds as compared to5.0 X 10 average delay of the network with CBR traffic model. When the route is discovered, the throughput broadcasted increases to 2.5 x 105 bits for VBR and 1.0 x 104 bits for CBR traffic model and the delay fell drastically to 0.01 and 0.001 seconds respectively. When VBR generated data traffic of 5.0 x 105 bits was received, there was a broken link and an alternative route needs to be taken. Instead of starting all the process afresh, the route had to re-initiate another route discovery process in which a delay was triggered to about 0.1

second. This shows that as throughput of receiving bits of CBR generated traffic increases, the nodes stabilises and the delay tends to drop at interval. Packet jitter is usually expressed as an absolute value of delay variation. The delay is specified from the start of the packet being transmitted at the source to the end of the packet being received at the destination. The sequence numbers here refer to the packets. Different sequence number is generated for every new packet created as shown in figure 4& 5. In the early stages of the route request process of the network with VBR traffic model, sequence numbers from 1150 to 1375 experiences very less amount of packet to be received by the destination as compared to CBR traffic model which remain the same for the whole different packet sequence number. As the sequence number increases and more packets sent. The rapid change of jitter is attributed to the frequent change of network topology and the mechanism of inherent routing update. Figure 6 & 7 shows that, as the packet size increases, the throughput decreases. This means that there are some packets dropped during transmission. Packets dropped are as a result of the DSR route maintenance mechanism. Despite the fact that DSR does not locally repair a broken link CBR traffic model achieves a higher average performance throughput as compared to VBR traffic model.

Figure 2. (VBR) Average End to End Delay vs.

throughput of receiving bits.

190 3rd IEEE International Conference on Adaptive Science and Technology (ICAST 2011)

Figure 3. (CBR) Average End to End Delay vs.

throughput of receiving bits.

Figure4. (VBR) Jitter of Received Packet vs. Sequence Number.

Figure5. (CBR) Jitter of Received Packet vs. Sequence Number.

Figure 6. (VBR)Throughput of receiving bits vs.

Packet Size.

191 3rd IEEE International Conference on Adaptive Science and Technology (ICAST 2011)

Figure 7. (CBR)Throughput of receiving bits vs. Packet Size.

IV. CONCLUSION

Due to the importance of traffic and mobility models in Vehicular Ad hoc wireless network. We evaluated the performance of Constant Bit Rate (CBR) and Variable Bit Rate (VBR) traffic models on vehicular ad hoc network. The simulation result showed that as throughput of receiving bits increased, the nodes stabilised and the average end to end delay tends to drop at interval. As more packets are broadcasted and then discovered, the network was stabilised and network topology was steady. The rapid change of jitter is attributed to the frequent movement of wheeled mobile units and the mechanism of inherent routing update. Packets are dropped as the packet size increased which is not suitable for a high vehicle mobility environment.

REFERENCES

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[17] The Network Simulator - ns-2 [Online] available at http://www.isi.edu/nsnam/ns/ns-build.html#allinone