aodvlsr: aodv limited source routing protocol for vanets in city scenarios

7/30/2019 AODVLSR: AODV LIMITED SOURCE ROUTING PROTOCOL FOR VANETS IN CITY SCENARIOS

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International Journal of Computer Networking,

Wireless and Mobile Communications (IJCNWMC)

ISSN 2250-1568Vol. 2 Issue 4 Dec - 2012 7-16

TJPRC Pvt. Ltd.,

AODVLSR: AODV LIMITED SOURCE ROUTING PROTOCOL FOR VANETS IN CITY

SCENARIOS

1DHARMENDRA SUTARIYA, 2RONAK SOLANKI & 3PRATIK MEWADA

1,2,3Assistant Professor, CE Department, B. S. Patel Polytechnic, Kherva, Mehsana, Gujarat, India

ABSTRACT

Vehicular Ad hoc Network (VANET) is a new communication paradigm in the field of intelligent transport

system that enables the communication between vehicles on the road network which falls in two categories: 1) Vehicle to

Vehicle (V2V) and 2) Vehicle to Infrastructure (V2I). Various approaches of data dissemination in vehicular Network are

used to inform vehicles about dynamic road traffic condition for achieving safe and efficient transportation system. Types

of VANET applications and inherent characteristics such as unpredictable node density, high speed and constrained

mobility of vehicles make data dissemination quite challenging and general purpose ad hoc network routing protocols

cannot work efficiently with it. In this paper, we propose a routing protocol AODVLSR (AODV Limited Source Routing)

that ensures giving timely and accurate information to drivers in V2V communication compare to AODV protocols in city

scenarios of vehicular ad hoc networks. Proposed AODVLSR is defined as limited source routing up to two hops for

network nodes. The performance of the proposed AODVLSR protocol is compared with basic AODV protocol in terms of

Packet Delivery Ratio, Avg. End-to-End Delay, Dropped TCP Packets and Normalized Routing Load. Simulation results

show that AODVLSR performs better than AODV protocol in given city scenarios of VANETs.

KEYWORDS:AODV, City Scenarios, Routing Protocols, Vehicular Ad hoc Network (VANET)

INTRODUCTION

Numerous local incidents occur on road networks daily, many of which may lead to congestion and safety

hazards. If vehicles can be provided with information about such incidents or traffic conditions in advance, the

quality of driving and transportation can be improved significantly with respect to safety, time, distance and fuel

consumption. VANET applications include traffic engineering, traffic management, environmental protection, information

services like dissemination of emergency information to avoid hazardous situations and other user applications. Various

approaches of data dissemination in vehicular Network are to inform vehicles about dynamic road traffic condition for

achieving safe and efficient transportation. VANETs are self organizing networks established among vehicles equipped

with communication facilities like wireless transceivers and computerized control modules.

The equipped vehicles are network nodes so that each node can act as the source of data, destination for data and a

network router. VANET is a special application of MANETs and have some similar characteristics such as short range of

transmission low bandwidth, high mobility, omni-directional broadcast and low storage capacity. Fast changing network

topology and varying communication conditions pose a great challenge for routing protocols being used in VANETs. For

using routing protocols in VANET they should be robust, reliable, minimize latency and network load.

Various ad hoc network routing protocols have been proposed in recent years, whereas two main classes of

protocols can be distinguished as: location-based (position-based) and topology-based protocols. These protocols enable

the exchange of data between distinct pairs of nodes, using intermediate network participants for forwarding packets on


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8 Dharmendra Sutariya, Ronak Solanki & Pratik Mewada

their way to the destination. Topology-based routing protocols can be further classified as proactive, reactive and hybrid

approaches.

AODV routing protocol is preferable for Packet Delivery Ratio and Normalized Routing Load but higher Avg.

End-to-End delay and Dropped packets compare to other topology based routing protocols, While DSR has lower End-to-

End delay and AOMDV has lower number of dropped packets [1]. To make AODV a better choice for effective data

dissemination in VANET scenarios it is required to improve Avg. End-to-End delay and Dropped packets without effecting

packet delivery ratio and normalized routing load. AODVLSR is proposed for the same by integrating routing mechanism

of DSR protocol with AODV.The paper is organized as follows. Section II describes working of AODV routing protocols

and related work on it to improve performance in ad hoc networks. Section III describes proposed AODVLSR with

algorithm and packet structure. Section IV describes city mobility model. Section V contains details about network

simulation model, section VI discussed result evaluation and section VII concludes the paper.

AODV AND RELATED WORK

AODV

Ad hoc On demand Distance Vector (AODV) is a reactive protocol consists of two main phases: Route Discovery

and Route Maintenance. AODV uses traditional routing tables, one entry per destination and sequence numbers to verify

freshness of routing information in route tables and prevents routing loops. AODV has the advantage of minimizing

routing table size and broadcast process as routes are created on demand. AODV specifies three types of control packets

for discovering and maintaining routes: Route Request (RREQ), Route Reply (RREP), Route Error (RERR) packets [2].

The Route discovery process starts when a source node desires to send a message to a destination node and does

not have a valid route. The source node broadcasts a route request packet (RREQ) to its neighbor nodes, which then

forward the request to their neighbor nodes, and so on. The process continues until either the destination node, or an

intermediate node with an updated (fresh enough) route to the destination, is reached by this request. Then, the node

responds with a route reply packet (RREP) back to the neighbor from which it first received the RREQ.

The reply packets are routed back along the reverse path established by the request packets. The reply packets that

travel along the intermediate nodes setup forwarding entries in the routing tables. These table entries point to the node from

which the RREP was received. There is a timer associated with each route entry. The entries expire if not used by data

packets. Destination sequence numbers are used by AODV to ensure loop-free routes and up to date routing information.

Due to nature of mobile node in ad hoc network, links in the network can go down and a route repair procedure

may be necessary. If a node moves out of the radio range of its neighbor, the upstream neighbor propagates a link failure

notification (routing error packet - RERR) to each of its upstream neighbors to inform the failure of part of the route. The

failure notification is propagated until the source node is reached. When the source node is reached by the routing error

packet it initiates a new route discovery process. Connectivity information can be obtained using hello messages. Hello

messages are routing reply packets which are periodically broadcasted by a node to inform its existence to its neighbors.

Related Work on AODV

Baozhu Li. et al. [3] ,in 2010 proposed a routing protocol AODV_BD for vehicular Adhoc networks that

improves the AODV routing protocol by making it reduce the packet delay. AODV_BD establishes a routing to the

destination node by broadcasting data packets when local repair is going on. Means data packets broadcasted is not only

the request packets, but also the data packets.


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AODVLSR: AODV Limited Source Routing Protocol for Vanets in City Scenarios 9

This will not only setup the routing but also reduce the delay. Baozhu Li. et al. [4], in 2010 proposed a routing

protocol AODV_OBD that induces the packet delay to a certain extent compare to AODV. Mechanism was based on

reference [3] with limited hop count for RREQ, so when the RREQ cannot find the destination node, it can only go through

very small count.

Also new method is used by replying a reply packet which can tell the node that the next node is active and

decided whether the node gets a RREP or not. Yongjun Hu. et al. [5], in 2010 proposed an improvement of the route

discovery process in AODV (IMAODV) to decrease the delay and routing overload. IMAODV combines the route

discovery process of AODV and DSR with append second node's address on RREQ. Noor Azlam Ahmad et al. [6], in 2008

proposed lifetime ratio (LR) to reduce unnecessary packets in the rebroadcast of AODV.

The formula for LR is lifetime of an intermediate node divided by the time to live of the route. Fei Jiang and

JianJun Hao [7], in 2010 proposed an improved routing protocol based on AODV for adhoc network, which optimize Hello

mechanism, Local repair mechanism and provide multi-backup pathway for the source node. Abdulsalam Alammari et al.

[8], in 2009 utilized multiple paths in Intermediate nodes in AODV protocol (MIAODV) and multiple paths at source and

destination nodes in AODV (NMIAODV). The performance was evaluated in terms of routing packet overhead, Avg. end-

to-end delay and packet delivery fraction.

THE PROPOSED AODVLSR PROTOCOL

Proposed AODVLSR is defined as "Limited Source Routing up to two hops for network nodes". AODVLSR

protocol combines routing mechanism of DSR protocol in to basic AODV protocol. AODVLSR is inspired from

methodology proposed by Yongjun Hu. et al. [5] which is given for the Ad hoc network with random mobility model. The

proposed AODVLSR (AODV Limited Source Routing) protocol can ensures giving timely and accurate information to

driver in V2V data dissemination compare to AODV protocol in city scenario. In proposed method route discovery

mechanism of AODV protocol is modified for limited source routing up to two hops.

Route Request Procedure

AODV can gather only a limited amount of routing information, route learning is limited only to source node.

This usually causes AODV to rely on a route discovery flood more often, which may carry significant network overhead

[5]. Combination of route discovery process of AODV and DSR routing protocol has lower delay and lower routing load

than original AODV.

However, it has set up too many reverse routes, this would bring in DSR's disadvantage and results in limited

performance so only append second node's address on RREQ. Design a new packet structure of RREQ packet by addition

of two field as shown in Figure 1.

Fig. 1: RREQ Packet Structure


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Modification in Route Request Procedure of AODV protocol is as shown Algorithm 7.1.

Algorithm 1. Modification in Route Request Procedure

1. Node i receives a RREQ packet2. If node i is the destination node then3. Reply RREP Packet4. Else5. If node i is second node then6. Building a reverse link in routing table for source node7. Append its node ID and sequence number and rebroadcast the Packets8. Else9. If exists a route in table then10. If check for better route then11. Update existing route in table12. End If13. Discard Packet14. Else15. Build a reverse link in routing table for source node16. Build a reverse link in routing table for second node17. Rebroadcast the Packets18. End If19. End If20. End If

CITYMOBILITYMODEL

A realistic vehicular mobility scenario for a City is generated using MOVE. MOVE is built on top of an open

source microtraffic simulator SUMO [9]. A vehicular mobility pattern defines vehicle motions within the road segmentduring a simulation time, which reflects, as close as possible, the real behavior of vehicular traffic such as traffic jams and

stop at intersections.

As shown in Fig. 2 City Scene consists of eight vertically and horizontally oriented streets as well as 12 crossings.

Fig. 3 defines view of crossing in road network. Each modeled street has a total length of 1500 m, where as parallel streets

are separated by a distance of 500 m with bidirection two lanes in each side. Vehicles can move with maximum speed of

40 km/h and vehicle flow is determined from upper left corner to bottom right corner and upper right to bottom left of the

city map. Traffic lights to be placed at each crossing and vehicles randomly make a turn at each crossing. To make

comparative study of selected routing behavior in their respective scenes, an approach of density formulation among traffic


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flow is reused. The city model is further sub-classified on the basis of their participating vehicles, maximum speed of

vehicles and number of TCP connection used for established path.

Fig. 2: Manhattan Like City Roadways

Fig. 3: Intersection Structure

SIMULATION

In This Study, Network Simulation Tool, Ns2.34 [10] Has Been Used As A Simulation Platform. Ns2 Is Open

Source, Object-Oriented, Discrete Event-Driven Network Simulation Software Which Was Developed In Both Languages

Including The Otcl And C++. It Is Excellent Simulation Software Which Can Study Network Topology And Analyze

Network Transmission.

Network Performance Indicators

Following performance metrics are used to analyze the simulation results.

1. Packet Delivery Ratio (PDR): This metric gives the ratio of the total data packets successfully received at thedestination and total number of data packets generated at source.

2. Average End-to-End Delay (E2E Delay): It is the calculation of typical time taken by packet (in average packets)to cover its journey from the source end to the destination end. In other words, it covers all of the potential delays

such as route discovery, buffering processes, various in-between queuing stays, etc. during the entire trip of

transmission of the packet.


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3. Dropped TCP packets: It defines a total number of TCP packets dropped during transmission of packet fromsource end to destination end.

4. Normalized Routing Load (NRL): Normalized Routing load is the numbers of routing packets transmitted per datapacket send to the destination. This metric is also highly correlated with the number of route changes occurred in

the simulation.

Routing protocol is more privileged for lower value of E2E Delay, Dropped TCP Packets and NRL metrics while

higher value of PDR metric.

Network and Simulation Parameters

The experiments were carried out using the network simulator (ns-2). For all scenarios mobility of vehicle is

generated with MOVE which work on SUMO, which is open source software. Traffic patterns are based on TCP

connections which are generated with the help of cbrgen.tcl script of NS-2. Fifteen different traffic files are generated with

use of cbrgen.tcl with varying number of traffic connection and then integrate with TCL script for scenarios. The randomly

chosen source-destination pairs are spread in the network. We had integrated AODV protocol as new name AODVLSR in

NS-2.34 and implementing proposed improvement on it. Simulation parameters for test cases are carried out on the NS-2

for varying Vehicle Density and traffic concentration in the network. Table 1 shows simulation parameters used in the city

scene for varying Vehicle Density with network parameters.

Table 1: Simulation Parameters

Parameter Simulated Value

Simulator NS 2.34

Simulation Time 400 Second

Antenna Model Omni directional antenna

Radio Propagation

Model

Two Ray Ground

Transmission Range 250 m

MAC Type IEEE 802.11

Interface Queue Type Priority Queue (50 Packets)

Routing Protocols AODV, AODVLSR

Simulation Area 1500 m X 1500 m

No. of vehicles 24, 48, 120, 280

No. of TCP

Connections

10, 20

Mobility of Vehicles 40 m/h

ANALYSISOFSIMULATIONRESULTS

The performance of the proposed AODVLSR is compared with basic AODV protocol in terms of Packet Delivery

Ratio, Average End-to-End delay, Dropped TCP Packets and Normalized Routing Load. All experiment results presented

in this section are average of fifteen simulation runs for all the cases. The performance metrics measurements are with

respect to Vehicle Density with varying No. of Active Connections.

Performance Metrics with 10 TCP Connections

Fig. 4 shows the simulation results for varying vehicle density with 10 TCP communication pair with maximum

speed of 40 km/h.


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(a) Packet Delivery Ratio

(b) Avg. End-To-End Delay

(c) Dropped TCP Packets


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(d) Normalized Routing Load

Fig. 4: Performance Metrics with 10 TCP Connection

By analyzing results of city scene for 10 TCP connections with varying vehicle density as shown in Fig. 4

performance improvement in Avg. End-to-End delay is 5.81% and Dropped TCP Packet is 7.84% without affecting

Normalized Routing Load or decreasing Packet Delivery Ratio. As number of vehicle increases beyond 120 NRL is

increases for AODVLSR.

Performance Metrics with 20 TCP Connections

Fig. 5 shows the simulation results for varying vehicle density with 20 TCP communication pair with maximum

speed of 40 km/h.

(a) Packet Delivery Ratio

(b) Avg. End-to-End Delay


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(c) Dropped TCP Packets

(d) Normalized Routing Load

Fig. 5: Performance Metrics with 20 TCP Connection

By analyzing results of city scene for 20 TCP connections with varying vehicle density as shown in Fig. 5

performance improvement in Avg. End-to-End delay is 6.27% and Dropped TCP Packet is 7.62% without affecting

Normalized Routing Load or decreasing Packet Delivery Ratio.

CONCLUSIONS

Limited Source Routing up two hop approach reduces Average End-to-End delay and Dropped TCP Packet

without degrading the network performance in terms of Packet Delivery Ratio and Normalized Routing Load compared to

the existing data dissemination approach of AODV protocol. AODVLSR reduces Avg. End-to-End delay by around 6%

and Dropped TCP Packet around 8% with respect to Vehicle Density with 10 and 20 TCP communication pair. ProposedAODVLSR protocol provides timely and accurate information in V2V data dissemination to achieve safe and efficient

transportation compare to AODV protocol in manhattan city scene.

Future task is to verify AODVLSR improvement for other type of road topologies because in real world road

topology is different for different areas of city and highways. The DSRC standard is adopted by ASTM and IEEE to

provide a secure, reliable, and timely wireless communication component as an integral part for the intelligent

transportation system (ITS) by supporting multichannel communication. The next improvement possible is at the MAC

layer assumptions. We have considered 802.11 for communication requirements which can be replaced with 802.11p

(DSRC) communication standard.


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REFERENCES

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2. C. Perkins, E. Belding-Royer, S. Das, Ad hoc On- Demand Distance Vector (AODV) Routing, RFC 3561, July2003.

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4. Baozhu Li,Yue Liu and Guoxin Chu, Optimized AODV routing protocol for vehicular Ad hoc networks, GlobalMobile Congress (GMC),pp.1-4, Oct.2010.

5. Yongjun Hu,Tao Lu and Junliang ShenD, An Improvement of the Route Discovery Process in AODV for AdHoc Network, International Conference on Communications and Mobile Computing (CMC), pp. 458-461,

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7. Fei Jiang and JianJun Hao, Simulation of an improved AODV algorithm for ad hoc network, InternationalConference on Computer and Automation Engineering (ICCAE), Vol. 1, pp. 540-543, Feb. 2010.

8. Alammari A.,Zahary A. and Ayesh A., Multipath contribution of intermediate nodes in AODV extensions,International Conference on Computer Engineering & Systems (ICCES), pp. 347-352, Dec. 2009.

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aodvlsr: aodv limited source routing protocol for vanets in city scenarios

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